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o.flags&256?(o.flags&=-257,c=mc(Error(s(422))),Ni(t,o,x,c)):o.memoizedState!==null?(o.child=t.child,o.flags|=128,null):(m=c.fallback,h=o.mode,c=zi({mode:"visible",children:c.children},h,0,null),m=wo(m,h,x,null),m.flags|=2,c.return=o,m.return=o,c.sibling=m,o.child=c,(o.mode&1)!==0&&Ko(o,t.child,null,x),o.child.memoizedState=xc(x),o.memoizedState=wc,m);if((o.mode&1)===0)return Ni(t,o,x,null);if(h.data==="$!"){if(c=h.nextSibling&&h.nextSibling.dataset,c)var S=c.dgst;return c=S,m=Error(s(419)),c=mc(m,c,void 0),Ni(t,o,x,c)}if(S=(x&t.childLanes)!==0,wt||S){if(c=tt,c!==null){switch(x&-x){case 4:h=2;break;case 16:h=8;break;case 64:case 128:case 256:case 512:case 1024:case 2048:case 4096:case 8192:case 16384:case 32768:case 65536:case 131072:case 262144:case 524288:case 1048576:case 2097152:case 4194304:case 8388608:case 16777216:case 33554432:case 67108864:h=32;break;case 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c=o.pendingProps,h=c.revealOrder,m=c.tail;if(pt(t,o,c.children,i),c=We.current,(c&2)!==0)c=c&1|2,o.flags|=128;else{if(t!==null&&(t.flags&128)!==0)e:for(t=o.child;t!==null;){if(t.tag===13)t.memoizedState!==null&&ym(t,i,o);

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Error(s(153));if(o.child!==null){for(t=o.child,i=Gn(t,t.pendingProps),o.child=i,i.return=o;t.sibling!==null;)t=t.sibling,i=i.sibling=Gn(t,t.pendingProps),i.return=o;i.sibling=null}return o.child}function Kb(t,o,i){switch(o.tag){case 3:mm(o),qo();break;case 5:Mp(o);break;case 1:yt(o.type)&&di(o);break;case 4:ec(o,o.stateNode.containerInfo);break;case 10:var c=o.type._context,h=o.memoizedProps.value;Ce(yi,c._currentValue),c._currentValue=h;break;case 13:if(c=o.memoizedState,c!==null)return c.dehydrated!==null?(Ce(We,We.current&1),o.flags|=128,null):(i&o.child.childLanes)!==0?gm(t,o,i):(Ce(We,We.current&1),t=yn(t,o,i),t!==null?t.sibling:null);Ce(We,We.current&1);break;case 19:if(c=(i&o.childLanes)!==0,(t.flags&128)!==0){if(c)return wm(t,o,i);o.flags|=128}if(h=o.memoizedState,h!==null&&(h.rendering=null,h.tail=null,h.lastEffect=null),Ce(We,We.current),c)break;return null;case 22:case 23:return o.lanes=0,dm(t,o,i)}return yn(t,o,i)}var xm,kc,bm,vm;xm=function(t,o){for(var i=o.child;i!==null;){if(i.tag===5||i.tag===6)t.appendChild(i.stateNode);else if(i.tag!==4&&i.child!==null){i.child.return=i,i=i.child;continue}if(i===o)break;for(;i.sibling===null;){if(i.return===null||i.return===o)return;i=i.return}i.sibling.return=i.return,i=i.sibling}},kc=function(){},bm=function(t,o,i,c){var h=t.memoizedProps;if(h!==c){t=o.stateNode,ho(Xt.current);var m=null;switch(i){case"input":h=Qa(t,h),c=Qa(t,c),m=[];break;case"select":h=K({},h,{value:void 0}),c=K({},c,{value:void 0}),m=[];break;case"textarea":h=el(t,h),c=el(t,c),m=[];break;default:typeof h.onClick!="function"&&typeof c.onClick=="function"&&(t.onclick=li)}nl(i,c);var x;i=null;for(D in h)if(!c.hasOwnProperty(D)&&h.hasOwnProperty(D)&&h[D]!=null)if(D==="style"){var S=h[D];for(x in S)S.hasOwnProperty(x)&&(i||(i={}),i[x]="")}else 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c=o.stateNode,Qo(),Ee(gt),Ee(it),oc(),c.pendingContext&&(c.context=c.pendingContext,c.pendingContext=null),(t===null||t.child===null)&&(fi(o)?o.flags|=4:t===null||t.memoizedState.isDehydrated&&(o.flags&256)===0||(o.flags|=1024,Ht!==null&&(Lc(Ht),Ht=null))),kc(t,o),lt(o),null;case 5:tc(o);var h=ho(Zs.current);if(i=o.type,t!==null&&o.stateNode!=null)bm(t,o,i,c,h),t.ref!==o.ref&&(o.flags|=512,o.flags|=2097152);else{if(!c){if(o.stateNode===null)throw Error(s(166));return lt(o),null}if(t=ho(Xt.current),fi(o)){c=o.stateNode,i=o.type;var m=o.memoizedProps;switch(c[Zt]=o,c[qs]=m,t=(o.mode&1)!==0,i){case"dialog":Pe("cancel",c),Pe("close",c);break;case"iframe":case"object":case"embed":Pe("load",c);break;case"video":case"audio":for(h=0;h<Us.length;h++)Pe(Us[h],c);break;case"source":Pe("error",c);break;case"img":case"image":case"link":Pe("error",c),Pe("load",c);break;case"details":Pe("toggle",c);break;case"input":th(c,m),Pe("invalid",c);break;case"select":c._wrapperState={wasMultiple:!!m.multiple},Pe("invalid",c);break;case"textarea":sh(c,m),Pe("invalid",c)}nl(i,m),h=null;for(var x in m)if(m.hasOwnProperty(x)){var S=m[x];x==="children"?typeof S=="string"?c.textContent!==S&&(m.suppressHydrationWarning!==!0&&ai(c.textContent,S,t),h=["children",S]):typeof S=="number"&&c.textContent!==""+S&&(m.suppressHydrationWarning!==!0&&ai(c.textContent,S,t),h=["children",""+S]):l.hasOwnProperty(x)&&S!=null&&x==="onScroll"&&Pe("scroll",c)}switch(i){case"input":Eo(c),oh(c,m,!0);break;case"textarea":Eo(c),ih(c);break;case"select":case"option":break;default:typeof m.onClick=="function"&&(c.onclick=li)}c=h,o.updateQueue=c,c!==null&&(o.flags|=4)}else{x=h.nodeType===9?h:h.ownerDocument,t==="http://www.w3.org/1999/xhtml"&&(t=ah(i)),t==="http://www.w3.org/1999/xhtml"?i==="script"?(t=x.createElement("div"),t.innerHTML="<script><\/script>

8",t=t.removeChild(t.firstChild)):typeof c.is=="string"?t=x.createElement(i,{is:c.is}):(t=x.createElement(i),i==="select"&&(x=t,c.multiple?x.multiple=!0:c.size&&(x.size=c.size))):t=x.createElementNS(t,i),t[Zt]=o,t[qs]=c,xm(t,o,!1,!1),o.stateNode=t;e:{switch(x=ol(i,c),i){case"dialog":Pe("cancel",t),Pe("close",t),h=c;break;case"iframe":case"object":case"embed":Pe("load",t),h=c;break;case"video":case"audio":for(h=0;h<Us.length;h++)Pe(Us[h],t);h=c;break;case"source":Pe("error",t),h=c;break;case"img":case"image":case"link":Pe("error",t),Pe("load",t),h=c;break;case"details":Pe("toggle",t),h=c;break;case"input":th(t,c),h=Qa(t,c),Pe("invalid",t);break;case"option":h=c;break;case"select":t._wrapperState={wasMultiple:!!c.multiple},h=K({},c,{value:void 0}),Pe("invalid",t);break;case"textarea":sh(t,c),h=el(t,c),Pe("invalid",t);break;default:h=c}nl(i,h),S=h;for(m in S)if(S.hasOwnProperty(m)){var T=S[m];m==="style"?uh(t,T):m==="dangerouslySetInnerHTML"?(T=T?T.__html:void 0,T!=null&&lh(t,T)):m==="children"?typeof T=="string"?(i!=="textarea"||T!=="")&&Ss(t,T):typeof T=="number"&&Ss(t,""+T):m!=="suppressContentEditableWarning"&&m!=="suppressHydrationWarning"&&m!=="autoFocus"&&(l.hasOwnProperty(m)?T!=null&&m==="onScroll"&&Pe("scroll",t):T!=null&&R(t,m,T,x))}switch(i){case"input":Eo(t),oh(t,c,!1);break;case"textarea":Eo(t),ih(t);break;case"option":c.value!=null&&t.setAttribute("value",""+Ae(c.value));break;case"select":t.multiple=!!c.multiple,m=c.value,m!=null?Mo(t,!!c.multiple,m,!1):c.defaultValue!=null&&Mo(t,!!c.multiple,c.defaultValue,!0);break;default:typeof h.onClick=="function"&&(t.onclick=li)}switch(i){case"button":case"input":case"select":case"textarea":c=!!c.autoFocus;break e;case"img":c=!0;break e;default:c=!1}}c&&(o.flags|=4)}o.ref!==null&&(o.flags|=512,o.flags|=2097152)}return lt(o),null;case 6:if(t&&o.stateNode!=null)vm(t,o,t.memoizedProps,c);else{if(typeof c!="string"&&o.stateNode===null)throw Error(s(166));if(i=ho(Zs.current),ho(Xt.current),fi(o)){if(c=o.stateNode,i=o.memoizedProps,c[Zt]=o,(m=c.nodeValue!==i)&&(t=It,t!==null))switch(t.tag){case 3:ai(c.nodeValue,i,(t.mode&1)!==0);break;case 5:t.memoizedProps.suppressHydrationWarning!==!0&&ai(c.nodeValue,i,(t.mode&1)!==0)}m&&(o.flags|=4)}else c=(i.nodeType===9?i:i.ownerDocument).createTextNode(c),c[Zt]=o,o.stateNode=c}return lt(o),null;case 13:if(Ee(We),c=o.memoizedState,t===null||t.memoizedState!==null&&t.memoizedState.dehydrated!==null){if(Re&&St!==null&&(o.mode&1)!==0&&(o.flags&128)===0)Ip(),qo(),o.flags|=98560,m=!1;else if(m=fi(o),c!==null&&c.dehydrated!==null){if(t===null){if(!m)throw Error(s(318));if(m=o.memoizedState,m=m!==null?m.dehydrated:null,!m)throw Error(s(317));m[Zt]=o}else qo(),(o.flags&128)===0&&(o.memoizedState=null),o.flags|=4;lt(o),m=!1}else Ht!==null&&(Lc(Ht),Ht=null),m=!0;if(!m)return o.flags&65536?o:null}return(o.flags&128)!==0?(o.lanes=i,o):(c=c!==null,c!==(t!==null&&t.memoizedState!==null)&&c&&(o.child.flags|=8192,(o.mode&1)!==0&&(t===null||(We.current&1)!==0?Qe===0&&(Qe=3):Wc())),o.updateQueue!==null&&(o.flags|=4),lt(o),null);case 4:return Qo(),kc(t,o),t===null&&Gs(o.stateNode.containerInfo),lt(o),null;case 10:return Yl(o.type._context),lt(o),null;case 17:return yt(o.type)&&ui(),lt(o),null;case 19:if(Ee(We),m=o.memoizedState,m===null)return lt(o),null;if(c=(o.flags&128)!==0,x=m.rendering,x===null)if(c)or(m,!1);else{if(Qe!==0||t!==null&&(t.flags&128)!==0)for(t=o.child;t!==null;){if(x=vi(t),x!==null){for(o.flags|=128,or(m,!1),c=x.updateQueue,c!==null&&(o.updateQueue=c,o.flags|=4),o.subtreeFlags=0,c=i,i=o.child;i!==null;)m=i,t=c,m.flags&=14680066,x=m.alternate,x===null?(m.childLanes=0,m.lanes=t,m.child=null,m.subtreeFlags=0,m.memoizedProps=null,m.memoizedState=null,m.updateQueue=null,m.dependencies=null,m.stateNode=null):(m.childLanes=x.childLanes,m.lanes=x.lanes,m.child=x.child,m.subtreeFlags=0,m.deletions=null,m.memoizedProps=x.memoizedProps,m.memoizedState=x.memoizedState,m.updateQueue=x.updateQueue,m.type=x.type,t=x.dependencies,m.dependencies=t===null?null:{lanes:t.lanes,firstContext:t.firstContext}),i=i.sibling;return Ce(We,We.current&1|2),o.child}t=t.sibling}m.tail!==null&&Ue()>ts&&(o.flags|=128,c=!0,or(m,!1),o.lanes=4194304)}else{if(!c)if(t=vi(x),t!==null){if(o.flags|=128,c=!0,i=t.updateQueue,i!==null&&(o.updateQueue=i,o.flags|=4),or(m,!0),m.tail===null&&m.tailMode==="hidden"&&!x.alternate&&!Re)return lt(o),null}else 2*Ue()-m.renderingStartTime>ts&&i!==1073741824&&(o.flags|=128,c=!0,or(m,!1),o.lanes=4194304);m.isBackwards?(x.sibling=o.child,o.child=x):(i=m.last,i!==null?i.sibling=x:o.child=x,m.last=x)}return m.tail!==null?(o=m.tail,m.rendering=o,m.tail=o.sibling,m.renderingStartTime=Ue(),o.sibling=null,i=We.current,Ce(We,c?i&1|2:i&1),o):(lt(o),null);case 22:case 23:return Dc(),c=o.memoizedState!==null,t!==null&&t.memoizedState!==null!==c&&(o.flags|=8192),c&&(o.mode&1)!==0?(jt&1073741824)!==0&&(lt(o),o.subtreeFlags&6&&(o.flags|=8192)):lt(o),null;case 24:return null;case 25:return null}throw Error(s(156,o.tag))}function Yb(t,o){switch(Ul(o),o.tag){case 1:return 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0)}sample(n){return this.startTime=0,this.tick(n,!0)}}const BS=new Set(["opacity","clipPath","filter","transform"]);function zS(e,n,s,{delay:a=0,duration:l=300,repeat:u=0,repeatType:d="loop",ease:p="easeInOut",times:f}={}){const g={[n]:s};f&&(g.offset=f);const y=ix(p,l);return Array.isArray(y)&&(g.easing=y),e.animate(g,{delay:a,duration:l,easing:Array.isArray(y)?"linear":y,fill:"both",iterations:u+1,direction:d==="reverse"?"alternate":"normal"})}const HS=Id(()=>Object.hasOwnProperty.call(Element.prototype,"animate")),va=10,VS=2e4;function US(e){return _d(e.type)||e.type==="spring"||!rx(e.ease)}function GS(e,n){const s=new Zd({...n,keyframes:e,repeat:0,delay:0,isGenerator:!0});let a={done:!1,value:e[0]};const l=[];let u=0;for(;!a.done&&u<VS;)a=s.sample(u),l.push(a.value),u+=va;return{times:void 0,keyframes:l,duration:u-va,ease:"linear"}}const zx={anticipate:wx,backInOut:yx,circInOut:bx};function $S(e){return e in zx}class Xf extends Dx{constructor(n){super(n);const{name:s,motionValue:a,element:l,keyframes:u}=this.options;this.resolver=new Rx(u,(d,p)=>this.onKeyframesResolved(d,p),s,a,l),this.resolver.scheduleResolve()}initPlayback(n,s){let{duration:a=300,times:l,ease:u,type:d,motionValue:p,name:f,startTime:g}=this.options;if(!p.owner||!p.owner.current)return!1;if(typeof u=="string"&&wa()&&$S(u)&&(u=zx[u]),US(this.options)){const{onComplete:w,onUpdate:b,motionValue:A,element:j,...k}=this.options,I=GS(n,k);n=I.keyframes,n.length===1&&(n[1]=n[0]),a=I.duration,l=I.times,u=I.ease,d="keyframes"}const y=zS(p.owner.current,f,n,{...this.options,duration:a,times:l,ease:u});return y.startTime=g??this.calcStartTime(),this.pendingTimeline?(Ff(y,this.pendingTimeline),this.pendingTimeline=void 0):y.onfinish=()=>{const{onComplete:w}=this.options;p.set(Ja(n,this.options,s)),w&&w(),this.cancel(),this.resolveFinishedPromise()},{animation:y,duration:a,times:l,type:d,ease:u,keyframes:n}}get duration(){const{resolved:n}=this;if(!n)return 0;const{duration:s}=n;return kn(s)}get time(){const{resolved:n}=this;if(!n)return 0;const{animation:s}=n;return kn(s.currentTime||0)}set time(n){const{resolved:s}=this;if(!s)return;const{animation:a}=s;a.currentTime=vn(n)}get speed(){const{resolved:n}=this;if(!n)return 1;const{animation:s}=n;return s.playbackRate}set speed(n){const{resolved:s}=this;if(!s)return;const{animation:a}=s;a.playbackRate=n}get state(){const{resolved:n}=this;if(!n)return"idle";const{animation:s}=n;return s.playState}get startTime(){const{resolved:n}=this;if(!n)return null;const{animation:s}=n;return s.startTime}attachTimeline(n){if(!this._resolved)this.pendingTimeline=n;else{const{resolved:s}=this;if(!s)return Ct;const{animation:a}=s;Ff(a,n)}return 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b=e.getValue(w,(u=e.latestValues[w])!==null&&u!==void 0?u:null),A=f[w];if(A===void 0||y&&XS(y,w))continue;const j={delay:s,...Od(d||{},w)};let k=!1;if(window.MotionHandoffAnimation){const N=hx(e);if(N){const E=window.MotionHandoffAnimation(N,w,Le);E!==null&&(j.startTime=E,k=!0)}}Ru(e,w),b.start(Xd(w,b,A,e.shouldReduceMotion&&ux.has(w)?{type:!1}:j,e,k));const I=b.animation;I&&g.push(I)}return p&&Promise.all(g).then(()=>{Le.update(()=>{p&&EI(e,p)})}),g}function zu(e,n,s={}){var a;const l=Ka(e,n,s.type==="exit"?(a=e.presenceContext)===null||a===void 0?void 0:a.custom:void 0);let{transition:u=e.getDefaultTransition()||{}}=l||{};s.transitionOverride&&(u=s.transitionOverride);const d=l?()=>Promise.all(Hx(e,l,s)):()=>Promise.resolve(),p=e.variantChildren&&e.variantChildren.size?(g=0)=>{const{delayChildren:y=0,staggerChildren:w,staggerDirection:b}=u;return ej(e,n,y+g,w,b,s)}:()=>Promise.resolve(),{when:f}=u;if(f){const[g,y]=f==="beforeChildren"?[d,p]:[p,d];return g().then(()=>y())}else return 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Zx=({current:e})=>e?e.ownerDocument.defaultView:null,Lj=new WeakMap;class Rj{constructor(n){this.openDragLock=null,this.isDragging=!1,this.currentDirection=null,this.originPoint={x:0,y:0},this.constraints=!1,this.hasMutatedConstraints=!1,this.elastic=$e(),this.visualElement=n}start(n,{snapToCursor:s=!1}={}){const{presenceContext:a}=this.visualElement;if(a&&a.isPresent===!1)return;const l=y=>{const{dragSnapToOrigin:w}=this.getProps();w?this.pauseAnimation():this.stopAnimation(),s&&this.snapToCursor(Fr(y).point)},u=(y,w)=>{const{drag:b,dragPropagation:A,onDragStart:j}=this.getProps();if(b&&!A&&(this.openDragLock&&this.openDragLock(),this.openDragLock=jI(b),!this.openDragLock))return;this.isDragging=!0,this.currentDirection=null,this.resolveConstraints(),this.visualElement.projection&&(this.visualElement.projection.isAnimationBlocked=!0,this.visualElement.projection.target=void 0),_t(I=>{let N=this.getAxisMotionValue(I).get()||0;if(on.test(N)){const{projection:E}=this.visualElement;if(E&&E.layout){const R=E.layout.layoutBox[I];R&&(N=Et(R)*(parseFloat(N)/100))}}this.originPoint[I]=N}),j&&Le.postRender(()=>j(y,w)),Ru(this.visualElement,"transform");const{animationState:k}=this.visualElement;k&&k.setActive("whileDrag",!0)},d=(y,w)=>{const{dragPropagation:b,dragDirectionLock:A,onDirectionLock:j,onDrag:k}=this.getProps();if(!b&&!this.openDragLock)return;const{offset:I}=w;if(A&&this.currentDirection===null){this.currentDirection=Dj(I),this.currentDirection!==null&&j&&j(this.currentDirection);return}this.updateAxis("x",w.point,I),this.updateAxis("y",w.point,I),this.visualElement.render(),k&&k(y,w)},p=(y,w)=>this.stop(y,w),f=()=>_t(y=>{var w;return this.getAnimationState(y)==="paused"&&((w=this.getAxisMotionValue(y).animation)===null||w===void 0?void 0:w.play())}),{dragSnapToOrigin:g}=this.getProps();this.panSession=new Ux(n,{onSessionStart:l,onStart:u,onMove:d,onSessionEnd:p,resumeAnimation:f},{transformPagePoint:this.visualElement.getTransformPagePoint(),dragSnapToOrigin:g,contextWindow:Zx(this.visualElement)})}stop(n,s){const a=this.isDragging;if(this.cancel(),!a)return;const{velocity:l}=s;this.startAnimation(l);const{onDragEnd:u}=this.getProps();u&&Le.postRender(()=>u(n,s))}cancel(){this.isDragging=!1;const{projection:n,animationState:s}=this.visualElement;n&&(n.isAnimationBlocked=!1),this.panSession&&this.panSession.end(),this.panSession=void 0;const{dragPropagation:a}=this.getProps();!a&&this.openDragLock&&(this.openDragLock(),this.openDragLock=null),s&&s.setActive("whileDrag",!1)}updateAxis(n,s,a){const{drag:l}=this.getProps();if(!a||!ta(n,l,this.currentDirection))return;const u=this.getAxisMotionValue(n);let d=this.originPoint[n]+a[n];this.constraints&&this.constraints[n]&&(d=Aj(d,this.constraints[n],this.elastic[n])),u.set(d)}resolveConstraints(){var n;const{dragConstraints:s,dragElastic:a}=this.getProps(),l=this.visualElement.projection&&!this.visualElement.projection.layout?this.visualElement.projection.measure(!1):(n=this.visualElement.projection)===null||n===void 0?void 0:n.layout,u=this.constraints;s&&rs(s)?this.constraints||(this.constraints=this.resolveRefConstraints()):s&&l?this.constraints=Ij(l.layoutBox,s):this.constraints=!1,this.elastic=Nj(a),u!==this.constraints&&l&&this.constraints&&!this.hasMutatedConstraints&&_t(d=>{this.constraints!==!1&&this.getAxisMotionValue(d)&&(this.constraints[d]=Tj(l.layoutBox[d],this.constraints[d]))})}resolveRefConstraints(){const{dragConstraints:n,onMeasureDragConstraints:s}=this.getProps();if(!n||!rs(n))return!1;const a=n.current,{projection:l}=this.visualElement;if(!l||!l.layout)return!1;const u=Mj(a,l.root,this.visualElement.getTransformPagePoint());let d=Sj(l.layout.layoutBox,u);if(s){const p=s(Cj(d));this.hasMutatedConstraints=!!p,p&&(d=Kx(p))}return d}startAnimation(n){const{drag:s,dragMomentum:a,dragElastic:l,dragTransition:u,dragSnapToOrigin:d,onDragTransitionEnd:p}=this.getProps(),f=this.constraints||{},g=_t(y=>{if(!ta(y,s,this.currentDirection))return;let w=f&&f[y]||{};d&&(w={min:0,max:0});const b=l?200:1e6,A=l?40:1e7,j={type:"inertia",velocity:a?n[y]:0,bounceStiffness:b,bounceDamping:A,timeConstant:750,restDelta:1,restSpeed:10,...u,...w};return this.startAxisValueAnimation(y,j)});return Promise.all(g).then(p)}startAxisValueAnimation(n,s){const a=this.getAxisMotionValue(n);return Ru(this.visualElement,n),a.start(Xd(n,a,0,s,this.visualElement,!1))}stopAnimation(){_t(n=>this.getAxisMotionValue(n).stop())}pauseAnimation(){_t(n=>{var s;return(s=this.getAxisMotionValue(n).animation)===null||s===void 0?void 0:s.pause()})}getAnimationState(n){var s;return(s=this.getAxisMotionValue(n).animation)===null||s===void 0?void 0:s.state}getAxisMotionValue(n){const s=`_drag${n.toUpperCase()}`,a=this.visualElement.getProps(),l=a[s];return l||this.visualElement.getValue(n,(a.initial?a.initial[n]:void 0)||0)}snapToCursor(n){_t(s=>{const{drag:a}=this.getProps();if(!ta(s,a,this.currentDirection))return;const{projection:l}=this.visualElement,u=this.getAxisMotionValue(s);if(l&&l.layout){const{min:d,max:p}=l.layout.layoutBox[s];u.set(n[s]-_e(d,p,.5))}})}scalePositionWithinConstraints(){if(!this.visualElement.current)return;const{drag:n,dragConstraints:s}=this.getProps(),{projection:a}=this.visualElement;if(!rs(s)||!a||!this.constraints)return;this.stopAnimation();const l={x:0,y:0};_t(d=>{const p=this.getAxisMotionValue(d);if(p&&this.constraints!==!1){const f=p.get();l[d]=jj({min:f,max:f},this.constraints[d])}});const{transformTemplate:u}=this.visualElement.getProps();this.visualElement.current.style.transform=u?u({},""):"none",a.root&&a.root.updateScroll(),a.updateLayout(),this.resolveConstraints(),_t(d=>{if(!ta(d,n,null))return;const p=this.getAxisMotionValue(d),{min:f,max:g}=this.constraints[d];p.set(_e(f,g,l[d]))})}addListeners(){if(!this.visualElement.current)return;Lj.set(this.visualElement,this);const n=this.visualElement.current,s=br(n,"pointerdown",f=>{const{drag:g,dragListener:y=!0}=this.getProps();g&&y&&this.start(f)}),a=()=>{const{dragConstraints:f}=this.getProps();rs(f)&&f.current&&(this.constraints=this.resolveRefConstraints())},{projection:l}=this.visualElement,u=l.addEventListener("measure",a);l&&!l.layout&&(l.root&&l.root.updateScroll(),l.updateLayout()),Le.read(a);const d=Pr(window,"resize",()=>this.scalePositionWithinConstraints()),p=l.addEventListener("didUpdate",(({delta:f,hasLayoutChanged:g})=>{this.isDragging&&g&&(_t(y=>{const w=this.getAxisMotionValue(y);w&&(this.originPoint[y]+=f[y].translate,w.set(w.get()+f[y].translate))}),this.visualElement.render())}));return()=>{d(),s(),u(),p&&p()}}getProps(){const n=this.visualElement.getProps(),{drag:s=!1,dragDirectionLock:a=!1,dragPropagation:l=!1,dragConstraints:u=!1,dragElastic:d=Hu,dragMomentum:p=!0}=n;return{...n,drag:s,dragDirectionLock:a,dragPropagation:l,dragConstraints:u,dragElastic:d,dragMomentum:p}}}function ta(e,n,s){return(n===!0||n===e)&&(s===null||s===e)}function Dj(e,n=10){let s=null;return Math.abs(e.y)>n?s="y":Math.abs(e.x)>n&&(s="x"),s}class Wj extends oo{constructor(n){super(n),this.removeGroupControls=Ct,this.removeListeners=Ct,this.controls=new Rj(n)}mount(){const{dragControls:n}=this.node.getProps();n&&(this.removeGroupControls=n.subscribe(this.controls)),this.removeListeners=this.controls.addListeners()||Ct}unmount(){this.removeGroupControls(),this.removeListeners()}}const yg=e=>(n,s)=>{e&&Le.postRender(()=>e(n,s))};class Fj extends oo{constructor(){super(...arguments),this.removePointerDownListener=Ct}onPointerDown(n){this.session=new Ux(n,this.createPanHandlers(),{transformPagePoint:this.node.getTransformPagePoint(),contextWindow:Zx(this.node)})}createPanHandlers(){const{onPanSessionStart:n,onPanStart:s,onPan:a,onPanEnd:l}=this.node.getProps();return{onSessionStart:yg(n),onStart:yg(s),onMove:a,onEnd:(u,d)=>{delete this.session,l&&Le.postRender(()=>l(u,d))}}}mount(){this.removePointerDownListener=br(this.node.current,"pointerdown",n=>this.onPointerDown(n))}update(){this.session&&this.session.updateHandlers(this.createPanHandlers())}unmount(){this.removePointerDownListener(),this.session&&this.session.end()}}const da={hasAnimatedSinceResize:!0,hasEverUpdated:!1};function wg(e,n){return n.max===n.min?0:e/(n.max-n.min)*100}const hr={correct:(e,n)=>{if(!n.target)return e;if(typeof e=="string")if(ce.test(e))e=parseFloat(e);else return e;const s=wg(e,n.target.x),a=wg(e,n.target.y);return`${s}% ${a}%`}},Oj={correct:(e,{treeScale:n,projectionDelta:s})=>{const a=e,l=to.parse(e);if(l.length>5)return a;const u=to.createTransformer(e),d=typeof l[0]!="number"?1:0,p=s.x.scale*n.x,f=s.y.scale*n.y;l[0+d]/=p,l[1+d]/=f;const g=_e(p,f,.5);return typeof l[2+d]=="number"&&(l[2+d]/=g),typeof l[3+d]=="number"&&(l[3+d]/=g),u(l)}};class _j extends v.Component{componentDidMount(){const{visualElement:n,layoutGroup:s,switchLayoutGroup:a,layoutId:l}=this.props,{projection:u}=n;rI(Bj),u&&(s.group&&s.group.add(u),a&&a.register&&l&&a.register(u),u.root.didUpdate(),u.addEventListener("animationComplete",()=>{this.safeToRemove()}),u.setOptions({...u.options,onExitComplete:()=>this.safeToRemove()})),da.hasEverUpdated=!0}getSnapshotBeforeUpdate(n){const{layoutDependency:s,visualElement:a,drag:l,isPresent:u}=this.props,d=a.projection;return d&&(d.isPresent=u,l||n.layoutDependency!==s||s===void 0?d.willUpdate():this.safeToRemove(),n.isPresent!==u&&(u?d.promote():d.relegate()||Le.postRender(()=>{const p=d.getStack();(!p||!p.members.length)&&this.safeToRemove()}))),null}componentDidUpdate(){const{projection:n}=this.props.visualElement;n&&(n.root.didUpdate(),Nd.postRender(()=>{!n.currentAnimation&&n.isLead()&&this.safeToRemove()}))}componentWillUnmount(){const{visualElement:n,layoutGroup:s,switchLayoutGroup:a}=this.props,{projection:l}=n;l&&(l.scheduleCheckAfterUnmount(),s&&s.group&&s.group.remove(l),a&&a.deregister&&a.deregister(l))}safeToRemove(){const{safeToRemove:n}=this.props;n&&n()}render(){return null}}function Xx(e){const[n,s]=Dw(),a=v.useContext(bd);return r.jsx(_j,{...e,layoutGroup:a,switchLayoutGroup:v.useContext(Vw),isPresent:n,safeToRemove:s})}const Bj={borderRadius:{...hr,applyTo:["borderTopLeftRadius","borderTopRightRadius","borderBottomLeftRadius","borderBottomRightRadius"]},borderTopLeftRadius:hr,borderTopRightRadius:hr,borderBottomLeftRadius:hr,borderBottomRightRadius:hr,boxShadow:Oj};function zj(e,n,s){const a=dt(e)?e:Nr(e);return a.start(Xd("",a,n,s)),a.animation}function Hj(e){return e instanceof SVGElement&&e.tagName!=="svg"}const Vj=(e,n)=>e.depth-n.depth;class Uj{constructor(){this.children=[],this.isDirty=!1}add(n){Hd(this.children,n),this.isDirty=!0}remove(n){Vd(this.children,n),this.isDirty=!0}forEach(n){this.isDirty&&this.children.sort(Vj),this.isDirty=!1,this.children.forEach(n)}}function Gj(e,n){const s=sn.now(),a=({timestamp:l})=>{const u=l-s;u>=n&&(eo(a),e(u-n))};return Le.read(a,!0),()=>eo(a)}const e0=["TopLeft","TopRight","BottomLeft","BottomRight"],$j=e0.length,xg=e=>typeof e=="string"?parseFloat(e):e,bg=e=>typeof e=="number"||ce.test(e);function qj(e,n,s,a,l,u){l?(e.opacity=_e(0,s.opacity!==void 0?s.opacity:1,Kj(a)),e.opacityExit=_e(n.opacity!==void 0?n.opacity:1,0,Jj(a))):u&&(e.opacity=_e(n.opacity!==void 0?n.opacity:1,s.opacity!==void 0?s.opacity:1,a));for(let d=0;d<$j;d++){const p=`border${e0[d]}Radius`;let f=vg(n,p),g=vg(s,p);if(f===void 0&&g===void 0)continue;f||(f=0),g||(g=0),f===0||g===0||bg(f)===bg(g)?(e[p]=Math.max(_e(xg(f),xg(g),a),0),(on.test(g)||on.test(f))&&(e[p]+="%")):e[p]=g}(n.rotate||s.rotate)&&(e.rotate=_e(n.rotate||0,s.rotate||0,a))}function vg(e,n){return e[n]!==void 0?e[n]:e.borderRadius}const Kj=t0(0,.5,xx),Jj=t0(.5,.95,Ct);function t0(e,n,s){return a=>a<e?0:a>n?1:s(fs(e,n,a))}function kg(e,n){e.min=n.min,e.max=n.max}function Ot(e,n){kg(e.x,n.x),kg(e.y,n.y)}function Ag(e,n){e.translate=n.translate,e.scale=n.scale,e.originPoint=n.originPoint,e.origin=n.origin}function Ig(e,n,s,a,l){return e-=n,e=ka(e,1/s,a),l!==void 0&&(e=ka(e,1/l,a)),e}function Yj(e,n=0,s=1,a=.5,l,u=e,d=e){if(on.test(n)&&(n=parseFloat(n),n=_e(d.min,d.max,n/100)-d.min),typeof n!="number")return;let p=_e(u.min,u.max,a);e===u&&(p-=n),e.min=Ig(e.min,n,s,p,l),e.max=Ig(e.max,n,s,p,l)}function Sg(e,n,[s,a,l],u,d){Yj(e,n[s],n[a],n[l],n.scale,u,d)}const Qj=["x","scaleX","originX"],Zj=["y","scaleY","originY"];function jg(e,n,s,a){Sg(e.x,n,Qj,s?s.x:void 0,a?a.x:void 0),Sg(e.y,n,Zj,s?s.y:void 0,a?a.y:void 0)}function Tg(e){return e.translate===0&&e.scale===1}function n0(e){return Tg(e.x)&&Tg(e.y)}function Ng(e,n){return e.min===n.min&&e.max===n.max}function Xj(e,n){return Ng(e.x,n.x)&&Ng(e.y,n.y)}function Cg(e,n){return Math.round(e.min)===Math.round(n.min)&&Math.round(e.max)===Math.round(n.max)}function o0(e,n){return Cg(e.x,n.x)&&Cg(e.y,n.y)}function Pg(e){return Et(e.x)/Et(e.y)}function Eg(e,n){return e.translate===n.translate&&e.scale===n.scale&&e.originPoint===n.originPoint}class e4{constructor(){this.members=[]}add(n){Hd(this.members,n),n.scheduleRender()}remove(n){if(Vd(this.members,n),n===this.prevLead&&(this.prevLead=void 0),n===this.lead){const s=this.members[this.members.length-1];s&&this.promote(s)}}relegate(n){const s=this.members.findIndex(l=>n===l);if(s===0)return!1;let a;for(let l=s;l>=0;l--){const u=this.members[l];if(u.isPresent!==!1){a=u;break}}return a?(this.promote(a),!0):!1}promote(n,s){const a=this.lead;if(n!==a&&(this.prevLead=a,this.lead=n,n.show(),a)){a.instance&&a.scheduleRender(),n.scheduleRender(),n.resumeFrom=a,s&&(n.resumeFrom.preserveOpacity=!0),a.snapshot&&(n.snapshot=a.snapshot,n.snapshot.latestValues=a.animationValues||a.latestValues),n.root&&n.root.isUpdating&&(n.isLayoutDirty=!0);const{crossfade:l}=n.options;l===!1&&a.hide()}}exitAnimationComplete(){this.members.forEach(n=>{const{options:s,resumingFrom:a}=n;s.onExitComplete&&s.onExitComplete(),a&&a.options.onExitComplete&&a.options.onExitComplete()})}scheduleRender(){this.members.forEach(n=>{n.instance&&n.scheduleRender(!1)})}removeLeadSnapshot(){this.lead&&this.lead.snapshot&&(this.lead.snapshot=void 0)}}function t4(e,n,s){let a="";const l=e.x.translate/n.x,u=e.y.translate/n.y,d=s?.z||0;if((l||u||d)&&(a=`translate3d(${l}px, ${u}px, ${d}px) `),(n.x!==1||n.y!==1)&&(a+=`scale(${1/n.x}, ${1/n.y}) `),s){const{transformPerspective:g,rotate:y,rotateX:w,rotateY:b,skewX:A,skewY:j}=s;g&&(a=`perspective(${g}px) ${a}`),y&&(a+=`rotate(${y}deg) `),w&&(a+=`rotateX(${w}deg) `),b&&(a+=`rotateY(${b}deg) `),A&&(a+=`skewX(${A}deg) `),j&&(a+=`skewY(${j}deg) `)}const p=e.x.scale*n.x,f=e.y.scale*n.y;return(p!==1||f!==1)&&(a+=`scale(${p}, ${f})`),a||"none"}const Ao={type:"projectionFrame",totalNodes:0,resolvedTargetDeltas:0,recalculatedProjection:0},yr=typeof window<"u"&&window.MotionDebug!==void 0,hu=["","X","Y","Z"],n4={visibility:"hidden"},Mg=1e3;let o4=0;function pu(e,n,s,a){const{latestValues:l}=n;l[e]&&(s[e]=l[e],n.setStaticValue(e,0),a&&(a[e]=0))}function s0(e){if(e.hasCheckedOptimisedAppear=!0,e.root===e)return;const{visualElement:n}=e.options;if(!n)return;const s=hx(n);if(window.MotionHasOptimisedAnimation(s,"transform")){const{layout:l,layoutId:u}=e.options;window.MotionCancelOptimisedAnimation(s,"transform",Le,!(l||u))}const{parent:a}=e;a&&!a.hasCheckedOptimisedAppear&&s0(a)}function r0({attachResizeListener:e,defaultParent:n,measureScroll:s,checkIsScrollRoot:a,resetTransform:l}){return class{constructor(d={},p=n?.()){this.id=o4++,this.animationId=0,this.children=new Set,this.options={},this.isTreeAnimating=!1,this.isAnimationBlocked=!1,this.isLayoutDirty=!1,this.isProjectionDirty=!1,this.isSharedProjectionDirty=!1,this.isTransformDirty=!1,this.updateManuallyBlocked=!1,this.updateBlockedByResize=!1,this.isUpdating=!1,this.isSVG=!1,this.needsReset=!1,this.shouldResetTransform=!1,this.hasCheckedOptimisedAppear=!1,this.treeScale={x:1,y:1},this.eventHandlers=new Map,this.hasTreeAnimated=!1,this.updateScheduled=!1,this.scheduleUpdate=()=>this.update(),this.projectionUpdateScheduled=!1,this.checkUpdateFailed=()=>{this.isUpdating&&(this.isUpdating=!1,this.clearAllSnapshots())},this.updateProjection=()=>{this.projectionUpdateScheduled=!1,yr&&(Ao.totalNodes=Ao.resolvedTargetDeltas=Ao.recalculatedProjection=0),this.nodes.forEach(i4),this.nodes.forEach(d4),this.nodes.forEach(h4),this.nodes.forEach(a4),yr&&window.MotionDebug.record(Ao)},this.resolvedRelativeTargetAt=0,this.hasProjected=!1,this.isVisible=!0,this.animationProgress=0,this.sharedNodes=new Map,this.latestValues=d,this.root=p?p.root||p:this,this.path=p?[...p.path,p]:[],this.parent=p,this.depth=p?p.depth+1:0;for(let f=0;f<this.path.length;f++)this.path[f].shouldResetTransform=!0;this.root===this&&(this.nodes=new Uj)}addEventListener(d,p){return this.eventHandlers.has(d)||this.eventHandlers.set(d,new Ud),this.eventHandlers.get(d).add(p)}notifyListeners(d,...p){const f=this.eventHandlers.get(d);f&&f.notify(...p)}hasListeners(d){return this.eventHandlers.has(d)}mount(d,p=this.root.hasTreeAnimated){if(this.instance)return;this.isSVG=Hj(d),this.instance=d;const{layoutId:f,layout:g,visualElement:y}=this.options;if(y&&!y.current&&y.mount(d),this.root.nodes.add(this),this.parent&&this.parent.children.add(this),p&&(g||f)&&(this.isLayoutDirty=!0),e){let w;const b=()=>this.root.updateBlockedByResize=!1;e(d,()=>{this.root.updateBlockedByResize=!0,w&&w(),w=Gj(b,250),da.hasAnimatedSinceResize&&(da.hasAnimatedSinceResize=!1,this.nodes.forEach(Rg))})}f&&this.root.registerSharedNode(f,this),this.options.animate!==!1&&y&&(f||g)&&this.addEventListener("didUpdate",({delta:w,hasLayoutChanged:b,hasRelativeTargetChanged:A,layout:j})=>{if(this.isTreeAnimationBlocked()){this.target=void 0,this.relativeTarget=void 0;return}const k=this.options.transition||y.getDefaultTransition()||y4,{onLayoutAnimationStart:I,onLayoutAnimationComplete:N}=y.getProps(),E=!this.targetLayout||!o0(this.targetLayout,j)||A,R=!b&&A;if(this.options.layoutRoot||this.resumeFrom&&this.resumeFrom.instance||R||b&&(E||!this.currentAnimation)){this.resumeFrom&&(this.resumingFrom=this.resumeFrom,this.resumingFrom.resumingFrom=void 0),this.setAnimationOrigin(w,R);const F={...Od(k,"layout"),onPlay:I,onComplete:N};(y.shouldReduceMotion||this.options.layoutRoot)&&(F.delay=0,F.type=!1),this.startAnimation(F)}else b||Rg(this),this.isLead()&&this.options.onExitComplete&&this.options.onExitComplete();this.targetLayout=j})}unmount(){this.options.layoutId&&this.willUpdate(),this.root.nodes.remove(this);const d=this.getStack();d&&d.remove(this),this.parent&&this.parent.children.delete(this),this.instance=void 0,eo(this.updateProjection)}blockUpdate(){this.updateManuallyBlocked=!0}unblockUpdate(){this.updateManuallyBlocked=!1}isUpdateBlocked(){return this.updateManuallyBlocked||this.updateBlockedByResize}isTreeAnimationBlocked(){return this.isAnimationBlocked||this.parent&&this.parent.isTreeAnimationBlocked()||!1}startUpdate(){this.isUpdateBlocked()||(this.isUpdating=!0,this.nodes&&this.nodes.forEach(p4),this.animationId++)}getTransformTemplate(){const{visualElement:d}=this.options;return d&&d.getProps().transformTemplate}willUpdate(d=!0){if(this.root.hasTreeAnimated=!0,this.root.isUpdateBlocked()){this.options.onExitComplete&&this.options.onExitComplete();return}if(window.MotionCancelOptimisedAnimation&&!this.hasCheckedOptimisedAppear&&s0(this),!this.root.isUpdating&&this.root.startUpdate(),this.isLayoutDirty)return;this.isLayoutDirty=!0;for(let y=0;y<this.path.length;y++){const w=this.path[y];w.shouldResetTransform=!0,w.updateScroll("snapshot"),w.options.layoutRoot&&w.willUpdate(!1)}const{layoutId:p,layout:f}=this.options;if(p===void 0&&!f)return;const g=this.getTransformTemplate();this.prevTransformTemplateValue=g?g(this.latestValues,""):void 0,this.updateSnapshot(),d&&this.notifyListeners("willUpdate")}update(){if(this.updateScheduled=!1,this.isUpdateBlocked()){this.unblockUpdate(),this.clearAllSnapshots(),this.nodes.forEach(Lg);return}this.isUpdating||this.nodes.forEach(c4),this.isUpdating=!1,this.nodes.forEach(u4),this.nodes.forEach(s4),this.nodes.forEach(r4),this.clearAllSnapshots();const p=sn.now();rt.delta=Sn(0,1e3/60,p-rt.timestamp),rt.timestamp=p,rt.isProcessing=!0,ou.update.process(rt),ou.preRender.process(rt),ou.render.process(rt),rt.isProcessing=!1}didUpdate(){this.updateScheduled||(this.updateScheduled=!0,Nd.read(this.scheduleUpdate))}clearAllSnapshots(){this.nodes.forEach(l4),this.sharedNodes.forEach(m4)}scheduleUpdateProjection(){this.projectionUpdateScheduled||(this.projectionUpdateScheduled=!0,Le.preRender(this.updateProjection,!1,!0))}scheduleCheckAfterUnmount(){Le.postRender(()=>{this.isLayoutDirty?this.root.didUpdate():this.root.checkUpdateFailed()})}updateSnapshot(){this.snapshot||!this.instance||(this.snapshot=this.measure())}updateLayout(){if(!this.instance||(this.updateScroll(),!(this.options.alwaysMeasureLayout&&this.isLead())&&!this.isLayoutDirty))return;if(this.resumeFrom&&!this.resumeFrom.instance)for(let f=0;f<this.path.length;f++)this.path[f].updateScroll();const d=this.layout;this.layout=this.measure(!1),this.layoutCorrected=$e(),this.isLayoutDirty=!1,this.projectionDelta=void 0,this.notifyListeners("measure",this.layout.layoutBox);const{visualElement:p}=this.options;p&&p.notify("LayoutMeasure",this.layout.layoutBox,d?d.layoutBox:void 0)}updateScroll(d="measure"){let p=!!(this.options.layoutScroll&&this.instance);if(this.scroll&&this.scroll.animationId===this.root.animationId&&this.scroll.phase===d&&(p=!1),p){const f=a(this.instance);this.scroll={animationId:this.root.animationId,phase:d,isRoot:f,offset:s(this.instance),wasRoot:this.scroll?this.scroll.isRoot:f}}}resetTransform(){if(!l)return;const d=this.isLayoutDirty||this.shouldResetTransform||this.options.alwaysMeasureLayout,p=this.projectionDelta&&!n0(this.projectionDelta),f=this.getTransformTemplate(),g=f?f(this.latestValues,""):void 0,y=g!==this.prevTransformTemplateValue;d&&(p||ko(this.latestValues)||y)&&(l(this.instance,g),this.shouldResetTransform=!1,this.scheduleRender())}measure(d=!0){const p=this.measurePageBox();let f=this.removeElementScroll(p);return d&&(f=this.removeTransform(f)),w4(f),{animationId:this.root.animationId,measuredBox:p,layoutBox:f,latestValues:{},source:this.id}}measurePageBox(){var d;const{visualElement:p}=this.options;if(!p)return $e();const f=p.measureViewportBox();if(!(((d=this.scroll)===null||d===void 0?void 0:d.wasRoot)||this.path.some(x4))){const{scroll:y}=this.root;y&&(ls(f.x,y.offset.x),ls(f.y,y.offset.y))}return f}removeElementScroll(d){var p;const f=$e();if(Ot(f,d),!((p=this.scroll)===null||p===void 0)&&p.wasRoot)return f;for(let g=0;g<this.path.length;g++){const y=this.path[g],{scroll:w,options:b}=y;y!==this.root&&w&&b.layoutScroll&&(w.wasRoot&&Ot(f,d),ls(f.x,w.offset.x),ls(f.y,w.offset.y))}return f}applyTransform(d,p=!1){const f=$e();Ot(f,d);for(let g=0;g<this.path.length;g++){const y=this.path[g];!p&&y.options.layoutScroll&&y.scroll&&y!==y.root&&cs(f,{x:-y.scroll.offset.x,y:-y.scroll.offset.y}),ko(y.latestValues)&&cs(f,y.latestValues)}return ko(this.latestValues)&&cs(f,this.latestValues),f}removeTransform(d){const p=$e();Ot(p,d);for(let f=0;f<this.path.length;f++){const g=this.path[f];if(!g.instance||!ko(g.latestValues))continue;Vu(g.latestValues)&&g.updateSnapshot();const y=$e(),w=g.measurePageBox();Ot(y,w),jg(p,g.latestValues,g.snapshot?g.snapshot.layoutBox:void 0,y)}return ko(this.latestValues)&&jg(p,this.latestValues),p}setTargetDelta(d){this.targetDelta=d,this.root.scheduleUpdateProjection(),this.isProjectionDirty=!0}setOptions(d){this.options={...this.options,...d,crossfade:d.crossfade!==void 0?d.crossfade:!0}}clearMeasurements(){this.scroll=void 0,this.layout=void 0,this.snapshot=void 0,this.prevTransformTemplateValue=void 0,this.targetDelta=void 0,this.target=void 0,this.isLayoutDirty=!1}forceRelativeParentToResolveTarget(){this.relativeParent&&this.relativeParent.resolvedRelativeTargetAt!==rt.timestamp&&this.relativeParent.resolveTargetDelta(!0)}resolveTargetDelta(d=!1){var p;const f=this.getLead();this.isProjectionDirty||(this.isProjectionDirty=f.isProjectionDirty),this.isTransformDirty||(this.isTransformDirty=f.isTransformDirty),this.isSharedProjectionDirty||(this.isSharedProjectionDirty=f.isSharedProjectionDirty);const g=!!this.resumingFrom||this!==f;if(!(d||g&&this.isSharedProjectionDirty||this.isProjectionDirty||!((p=this.parent)===null||p===void 0)&&p.isProjectionDirty||this.attemptToResolveRelativeTarget||this.root.updateBlockedByResize))return;const{layout:w,layoutId:b}=this.options;if(!(!this.layout||!(w||b))){if(this.resolvedRelativeTargetAt=rt.timestamp,!this.targetDelta&&!this.relativeTarget){const A=this.getClosestProjectingParent();A&&A.layout&&this.animationProgress!==1?(this.relativeParent=A,this.forceRelativeParentToResolveTarget(),this.relativeTarget=$e(),this.relativeTargetOrigin=$e(),kr(this.relativeTargetOrigin,this.layout.layoutBox,A.layout.layoutBox),Ot(this.relativeTarget,this.relativeTargetOrigin)):this.relativeParent=this.relativeTarget=void 0}if(!(!this.relativeTarget&&!this.targetDelta)){if(this.target||(this.target=$e(),this.targetWithTransforms=$e()),this.relativeTarget&&this.relativeTargetOrigin&&this.relativeParent&&this.relativeParent.target?(this.forceRelativeParentToResolveTarget(),kj(this.target,this.relativeTarget,this.relativeParent.target)):this.targetDelta?(this.resumingFrom?this.target=this.applyTransform(this.layout.layoutBox):Ot(this.target,this.layout.layoutBox),Yx(this.target,this.targetDelta)):Ot(this.target,this.layout.layoutBox),this.attemptToResolveRelativeTarget){this.attemptToResolveRelativeTarget=!1;const A=this.getClosestProjectingParent();A&&!!A.resumingFrom==!!this.resumingFrom&&!A.options.layoutScroll&&A.target&&this.animationProgress!==1?(this.relativeParent=A,this.forceRelativeParentToResolveTarget(),this.relativeTarget=$e(),this.relativeTargetOrigin=$e(),kr(this.relativeTargetOrigin,this.target,A.target),Ot(this.relativeTarget,this.relativeTargetOrigin)):this.relativeParent=this.relativeTarget=void 0}yr&&Ao.resolvedTargetDeltas++}}}getClosestProjectingParent(){if(!(!this.parent||Vu(this.parent.latestValues)||Jx(this.parent.latestValues)))return this.parent.isProjecting()?this.parent:this.parent.getClosestProjectingParent()}isProjecting(){return!!((this.relativeTarget||this.targetDelta||this.options.layoutRoot)&&this.layout)}calcProjection(){var d;const p=this.getLead(),f=!!this.resumingFrom||this!==p;let g=!0;if((this.isProjectionDirty||!((d=this.parent)===null||d===void 0)&&d.isProjectionDirty)&&(g=!1),f&&(this.isSharedProjectionDirty||this.isTransformDirty)&&(g=!1),this.resolvedRelativeTargetAt===rt.timestamp&&(g=!1),g)return;const{layout:y,layoutId:w}=this.options;if(this.isTreeAnimating=!!(this.parent&&this.parent.isTreeAnimating||this.currentAnimation||this.pendingAnimation),this.isTreeAnimating||(this.targetDelta=this.relativeTarget=void 0),!this.layout||!(y||w))return;Ot(this.layoutCorrected,this.layout.layoutBox);const b=this.treeScale.x,A=this.treeScale.y;Ej(this.layoutCorrected,this.treeScale,this.path,f),p.layout&&!p.target&&(this.treeScale.x!==1||this.treeScale.y!==1)&&(p.target=p.layout.layoutBox,p.targetWithTransforms=$e());const{target:j}=p;if(!j){this.prevProjectionDelta&&(this.createProjectionDeltas(),this.scheduleRender());return}!this.projectionDelta||!this.prevProjectionDelta?this.createProjectionDeltas():(Ag(this.prevProjectionDelta.x,this.projectionDelta.x),Ag(this.prevProjectionDelta.y,this.projectionDelta.y)),vr(this.projectionDelta,this.layoutCorrected,j,this.latestValues),(this.treeScale.x!==b||this.treeScale.y!==A||!Eg(this.projectionDelta.x,this.prevProjectionDelta.x)||!Eg(this.projectionDelta.y,this.prevProjectionDelta.y))&&(this.hasProjected=!0,this.scheduleRender(),this.notifyListeners("projectionUpdate",j)),yr&&Ao.recalculatedProjection++}hide(){this.isVisible=!1}show(){this.isVisible=!0}scheduleRender(d=!0){var p;if((p=this.options.visualElement)===null||p===void 0||p.scheduleRender(),d){const f=this.getStack();f&&f.scheduleRender()}this.resumingFrom&&!this.resumingFrom.instance&&(this.resumingFrom=void 0)}createProjectionDeltas(){this.prevProjectionDelta=as(),this.projectionDelta=as(),this.projectionDeltaWithTransform=as()}setAnimationOrigin(d,p=!1){const f=this.snapshot,g=f?f.latestValues:{},y={...this.latestValues},w=as();(!this.relativeParent||!this.relativeParent.options.layoutRoot)&&(this.relativeTarget=this.relativeTargetOrigin=void 0),this.attemptToResolveRelativeTarget=!p;const b=$e(),A=f?f.source:void 0,j=this.layout?this.layout.source:void 0,k=A!==j,I=this.getStack(),N=!I||I.members.length<=1,E=!!(k&&!N&&this.options.crossfade===!0&&!this.path.some(g4));this.animationProgress=0;let R;this.mixTargetDelta=F=>{const W=F/1e3;Dg(w.x,d.x,W),Dg(w.y,d.y,W),this.setTargetDelta(w),this.relativeTarget&&this.relativeTargetOrigin&&this.layout&&this.relativeParent&&this.relativeParent.layout&&(kr(b,this.layout.layoutBox,this.relativeParent.layout.layoutBox),f4(this.relativeTarget,this.relativeTargetOrigin,b,W),R&&Xj(this.relativeTarget,R)&&(this.isProjectionDirty=!1),R||(R=$e()),Ot(R,this.relativeTarget)),k&&(this.animationValues=y,qj(y,g,this.latestValues,W,E,N)),this.root.scheduleUpdateProjection(),this.scheduleRender(),this.animationProgress=W},this.mixTargetDelta(this.options.layoutRoot?1e3:0)}startAnimation(d){this.notifyListeners("animationStart"),this.currentAnimation&&this.currentAnimation.stop(),this.resumingFrom&&this.resumingFrom.currentAnimation&&this.resumingFrom.currentAnimation.stop(),this.pendingAnimation&&(eo(this.pendingAnimation),this.pendingAnimation=void 0),this.pendingAnimation=Le.update(()=>{da.hasAnimatedSinceResize=!0,this.currentAnimation=zj(0,Mg,{...d,onUpdate:p=>{this.mixTargetDelta(p),d.onUpdate&&d.onUpdate(p)},onComplete:()=>{d.onComplete&&d.onComplete(),this.completeAnimation()}}),this.resumingFrom&&(this.resumingFrom.currentAnimation=this.currentAnimation),this.pendingAnimation=void 0})}completeAnimation(){this.resumingFrom&&(this.resumingFrom.currentAnimation=void 0,this.resumingFrom.preserveOpacity=void 0);const d=this.getStack();d&&d.exitAnimationComplete(),this.resumingFrom=this.currentAnimation=this.animationValues=void 0,this.notifyListeners("animationComplete")}finishAnimation(){this.currentAnimation&&(this.mixTargetDelta&&this.mixTargetDelta(Mg),this.currentAnimation.stop()),this.completeAnimation()}applyTransformsToTarget(){const d=this.getLead();let{targetWithTransforms:p,target:f,layout:g,latestValues:y}=d;if(!(!p||!f||!g)){if(this!==d&&this.layout&&g&&i0(this.options.animationType,this.layout.layoutBox,g.layoutBox)){f=this.target||$e();const w=Et(this.layout.layoutBox.x);f.x.min=d.target.x.min,f.x.max=f.x.min+w;const b=Et(this.layout.layoutBox.y);f.y.min=d.target.y.min,f.y.max=f.y.min+b}Ot(p,f),cs(p,y),vr(this.projectionDeltaWithTransform,this.layoutCorrected,p,y)}}registerSharedNode(d,p){this.sharedNodes.has(d)||this.sharedNodes.set(d,new e4),this.sharedNodes.get(d).add(p);const g=p.options.initialPromotionConfig;p.promote({transition:g?g.transition:void 0,preserveFollowOpacity:g&&g.shouldPreserveFollowOpacity?g.shouldPreserveFollowOpacity(p):void 0})}isLead(){const d=this.getStack();return d?d.lead===this:!0}getLead(){var d;const{layoutId:p}=this.options;return p?((d=this.getStack())===null||d===void 0?void 0:d.lead)||this:this}getPrevLead(){var d;const{layoutId:p}=this.options;return p?(d=this.getStack())===null||d===void 0?void 0:d.prevLead:void 0}getStack(){const{layoutId:d}=this.options;if(d)return this.root.sharedNodes.get(d)}promote({needsReset:d,transition:p,preserveFollowOpacity:f}={}){const g=this.getStack();g&&g.promote(this,f),d&&(this.projectionDelta=void 0,this.needsReset=!0),p&&this.setOptions({transition:p})}relegate(){const d=this.getStack();return d?d.relegate(this):!1}resetSkewAndRotation(){const{visualElement:d}=this.options;if(!d)return;let p=!1;const{latestValues:f}=d;if((f.z||f.rotate||f.rotateX||f.rotateY||f.rotateZ||f.skewX||f.skewY)&&(p=!0),!p)return;const g={};f.z&&pu("z",d,g,this.animationValues);for(let y=0;y<hu.length;y++)pu(`rotate${hu[y]}`,d,g,this.animationValues),pu(`skew${hu[y]}`,d,g,this.animationValues);d.render();for(const y in g)d.setStaticValue(y,g[y]),this.animationValues&&(this.animationValues[y]=g[y]);d.scheduleRender()}getProjectionStyles(d){var p,f;if(!this.instance||this.isSVG)return;if(!this.isVisible)return n4;const g={visibility:""},y=this.getTransformTemplate();if(this.needsReset)return this.needsReset=!1,g.opacity="",g.pointerEvents=ca(d?.pointerEvents)||"",g.transform=y?y(this.latestValues,""):"none",g;const w=this.getLead();if(!this.projectionDelta||!this.layout||!w.target){const k={};return this.options.layoutId&&(k.opacity=this.latestValues.opacity!==void 0?this.latestValues.opacity:1,k.pointerEvents=ca(d?.pointerEvents)||""),this.hasProjected&&!ko(this.latestValues)&&(k.transform=y?y({},""):"none",this.hasProjected=!1),k}const b=w.animationValues||w.latestValues;this.applyTransformsToTarget(),g.transform=t4(this.projectionDeltaWithTransform,this.treeScale,b),y&&(g.transform=y(b,g.transform));const{x:A,y:j}=this.projectionDelta;g.transformOrigin=`${A.origin*100}% ${j.origin*100}% 0`,w.animationValues?g.opacity=w===this?(f=(p=b.opacity)!==null&&p!==void 0?p:this.latestValues.opacity)!==null&&f!==void 0?f:1:this.preserveOpacity?this.latestValues.opacity:b.opacityExit:g.opacity=w===this?b.opacity!==void 0?b.opacity:"":b.opacityExit!==void 0?b.opacityExit:0;for(const k in ya){if(b[k]===void 0)continue;const{correct:I,applyTo:N}=ya[k],E=g.transform==="none"?b[k]:I(b[k],w);if(N){const R=N.length;for(let F=0;F<R;F++)g[N[F]]=E}else g[k]=E}return this.options.layoutId&&(g.pointerEvents=w===this?ca(d?.pointerEvents)||"":"none"),g}clearSnapshot(){this.resumeFrom=this.snapshot=void 0}resetTree(){this.root.nodes.forEach(d=>{var p;return(p=d.currentAnimation)===null||p===void 0?void 0:p.stop()}),this.root.nodes.forEach(Lg),this.root.sharedNodes.clear()}}}function s4(e){e.updateLayout()}function r4(e){var n;const s=((n=e.resumeFrom)===null||n===void 0?void 0:n.snapshot)||e.snapshot;if(e.isLead()&&e.layout&&s&&e.hasListeners("didUpdate")){const{layoutBox:a,measuredBox:l}=e.layout,{animationType:u}=e.options,d=s.source!==e.layout.source;u==="size"?_t(w=>{const b=d?s.measuredBox[w]:s.layoutBox[w],A=Et(b);b.min=a[w].min,b.max=b.min+A}):i0(u,s.layoutBox,a)&&_t(w=>{const b=d?s.measuredBox[w]:s.layoutBox[w],A=Et(a[w]);b.max=b.min+A,e.relativeTarget&&!e.currentAnimation&&(e.isProjectionDirty=!0,e.relativeTarget[w].max=e.relativeTarget[w].min+A)});const p=as();vr(p,a,s.layoutBox);const f=as();d?vr(f,e.applyTransform(l,!0),s.measuredBox):vr(f,a,s.layoutBox);const g=!n0(p);let y=!1;if(!e.resumeFrom){const w=e.getClosestProjectingParent();if(w&&!w.resumeFrom){const{snapshot:b,layout:A}=w;if(b&&A){const j=$e();kr(j,s.layoutBox,b.layoutBox);const k=$e();kr(k,a,A.layoutBox),o0(j,k)||(y=!0),w.options.layoutRoot&&(e.relativeTarget=k,e.relativeTargetOrigin=j,e.relativeParent=w)}}}e.notifyListeners("didUpdate",{layout:a,snapshot:s,delta:f,layoutDelta:p,hasLayoutChanged:g,hasRelativeTargetChanged:y})}else if(e.isLead()){const{onExitComplete:a}=e.options;a&&a()}e.options.transition=void 0}function i4(e){yr&&Ao.totalNodes++,e.parent&&(e.isProjecting()||(e.isProjectionDirty=e.parent.isProjectionDirty),e.isSharedProjectionDirty||(e.isSharedProjectionDirty=!!(e.isProjectionDirty||e.parent.isProjectionDirty||e.parent.isSharedProjectionDirty)),e.isTransformDirty||(e.isTransformDirty=e.parent.isTransformDirty))}function a4(e){e.isProjectionDirty=e.isSharedProjectionDirty=e.isTransformDirty=!1}function l4(e){e.clearSnapshot()}function Lg(e){e.clearMeasurements()}function c4(e){e.isLayoutDirty=!1}function u4(e){const{visualElement:n}=e.options;n&&n.getProps().onBeforeLayoutMeasure&&n.notify("BeforeLayoutMeasure"),e.resetTransform()}function Rg(e){e.finishAnimation(),e.targetDelta=e.relativeTarget=e.target=void 0,e.isProjectionDirty=!0}function d4(e){e.resolveTargetDelta()}function h4(e){e.calcProjection()}function p4(e){e.resetSkewAndRotation()}function m4(e){e.removeLeadSnapshot()}function Dg(e,n,s){e.translate=_e(n.translate,0,s),e.scale=_e(n.scale,1,s),e.origin=n.origin,e.originPoint=n.originPoint}function Wg(e,n,s,a){e.min=_e(n.min,s.min,a),e.max=_e(n.max,s.max,a)}function f4(e,n,s,a){Wg(e.x,n.x,s.x,a),Wg(e.y,n.y,s.y,a)}function g4(e){return e.animationValues&&e.animationValues.opacityExit!==void 0}const y4={duration:.45,ease:[.4,0,.1,1]},Fg=e=>typeof navigator<"u"&&navigator.userAgent&&navigator.userAgent.toLowerCase().includes(e),Og=Fg("applewebkit/")&&!Fg("chrome/")?Math.round:Ct;function _g(e){e.min=Og(e.min),e.max=Og(e.max)}function w4(e){_g(e.x),_g(e.y)}function i0(e,n,s){return e==="position"||e==="preserve-aspect"&&!vj(Pg(n),Pg(s),.2)}function x4(e){var n;return e!==e.root&&((n=e.scroll)===null||n===void 0?void 0:n.wasRoot)}const b4=r0({attachResizeListener:(e,n)=>Pr(e,"resize",n),measureScroll:()=>({x:document.documentElement.scrollLeft||document.body.scrollLeft,y:document.documentElement.scrollTop||document.body.scrollTop}),checkIsScrollRoot:()=>!0}),mu={current:void 0},a0=r0({measureScroll:e=>({x:e.scrollLeft,y:e.scrollTop}),defaultParent:()=>{if(!mu.current){const e=new b4({});e.mount(window),e.setOptions({layoutScroll:!0}),mu.current=e}return mu.current},resetTransform:(e,n)=>{e.style.transform=n!==void 0?n:"none"},checkIsScrollRoot:e=>window.getComputedStyle(e).position==="fixed"}),v4={pan:{Feature:Fj},drag:{Feature:Wj,ProjectionNode:a0,MeasureLayout:Xx}};function Bg(e,n,s){const{props:a}=e;e.animationState&&a.whileHover&&e.animationState.setActive("whileHover",s==="Start");const l="onHover"+s,u=a[l];u&&Le.postRender(()=>u(n,Fr(n)))}class k4 extends oo{mount(){const{current:n}=this.node;n&&(this.unmount=vI(n,s=>(Bg(this.node,s,"Start"),a=>Bg(this.node,a,"End"))))}unmount(){}}class A4 extends oo{constructor(){super(...arguments),this.isActive=!1}onFocus(){let n=!1;try{n=this.node.current.matches(":focus-visible")}catch{n=!0}!n||!this.node.animationState||(this.node.animationState.setActive("whileFocus",!0),this.isActive=!0)}onBlur(){!this.isActive||!this.node.animationState||(this.node.animationState.setActive("whileFocus",!1),this.isActive=!1)}mount(){this.unmount=Wr(Pr(this.node.current,"focus",()=>this.onFocus()),Pr(this.node.current,"blur",()=>this.onBlur()))}unmount(){}}function zg(e,n,s){const{props:a}=e;e.animationState&&a.whileTap&&e.animationState.setActive("whileTap",s==="Start");const l="onTap"+(s==="End"?"":s),u=a[l];u&&Le.postRender(()=>u(n,Fr(n)))}class I4 extends oo{mount(){const{current:n}=this.node;n&&(this.unmount=SI(n,s=>(zg(this.node,s,"Start"),(a,{success:l})=>zg(this.node,a,l?"End":"Cancel")),{useGlobalTarget:this.node.props.globalTapTarget}))}unmount(){}}const Gu=new WeakMap,fu=new WeakMap,S4=e=>{const n=Gu.get(e.target);n&&n(e)},j4=e=>{e.forEach(S4)};function T4({root:e,...n}){const s=e||document;fu.has(s)||fu.set(s,{});const a=fu.get(s),l=JSON.stringify(n);return a[l]||(a[l]=new IntersectionObserver(j4,{root:e,...n})),a[l]}function N4(e,n,s){const a=T4(n);return Gu.set(e,s),a.observe(e),()=>{Gu.delete(e),a.unobserve(e)}}const C4={some:0,all:1};class P4 extends oo{constructor(){super(...arguments),this.hasEnteredView=!1,this.isInView=!1}startObserver(){this.unmount();const{viewport:n={}}=this.node.getProps(),{root:s,margin:a,amount:l="some",once:u}=n,d={root:s?s.current:void 0,rootMargin:a,threshold:typeof l=="number"?l:C4[l]},p=f=>{const{isIntersecting:g}=f;if(this.isInView===g||(this.isInView=g,u&&!g&&this.hasEnteredView))return;g&&(this.hasEnteredView=!0),this.node.animationState&&this.node.animationState.setActive("whileInView",g);const{onViewportEnter:y,onViewportLeave:w}=this.node.getProps(),b=g?y:w;b&&b(f)};return N4(this.node.current,d,p)}mount(){this.startObserver()}update(){if(typeof IntersectionObserver>"u")return;const{props:n,prevProps:s}=this.node;["amount","margin","root"].some(E4(n,s))&&this.startObserver()}unmount(){}}function E4({viewport:e={}},{viewport:n={}}={}){return s=>e[s]!==n[s]}const M4={inView:{Feature:P4},tap:{Feature:I4},focus:{Feature:A4},hover:{Feature:k4}},L4={layout:{ProjectionNode:a0,MeasureLayout:Xx}},$u={current:null},l0={current:!1};function R4(){if(l0.current=!0,!!Ad)if(window.matchMedia){const e=window.matchMedia("(prefers-reduced-motion)"),n=()=>$u.current=e.matches;e.addListener(n),n()}else $u.current=!1}const D4=[...Lx,ut,to],W4=e=>D4.find(Mx(e)),Hg=new WeakMap;

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160289",title:"On Women in AI and Who Gets a Seat",desc:"Why are women using AI at lower rates than men—and is that actually a problem? We dig into the data, the valid reasons to be wary, and why ambivalence might be the healthiest response to this moment.",answerFirst:"Women use AI at lower rates than men not because of ignorance but because of rational skepticism shaped by prior tech cycles. Analysis of 1,000+ TikTok comments reveals ambivalence — not resistance — as the dominant response. Carol Gilligan's ethics of care framework suggests women are asking different, arguably better questions about AI's impact.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",clipStartTime:3,datePublished:"2026-02-16",duration:"PT72M",keywords:"women in AI, AI gender gap, Carol Gilligan, protege effect, TikTok sentiment analysis, AI adoption gender, women using AI",relatedSlugs:["job-tsunamis-invisible-vulnerability","ai-boys-entrepreneurs-girls-influencers","is-using-ai-cheating"],highlights:["Logan scraped 1,000+ comments from a viral TikTok about women resisting AI and ran sentiment analysis","Anthropic's Claude Cowork launch—they built it in a week and a half using Claude itself","The $100–200/month cognitive inequality gap: who gets to experiment at the frontier?",`The "fooled me once" theory: why women who lived through social media aren't buying the AI hype`,`Carol Gilligan's "In a Different Voice" and why women's way of asking questions gets pathologized`,"The protege effect: why teaching someone else is the best way to learn"],resources:[{title:"TikTok Comment Sentiment Analysis (Logan's data viz)",url:"https://loganhc-09.github.io/womansplaining-ai-analysis/"},{title:"Dido Riot's TikTok on women and AI resistance",url:"https://www.tiktok.com/@didoriot/video/7586016585823882517"},{title:'Carol Gilligan, "In a Different Voice"',url:"https://www.hup.harvard.edu/books/9780674970960"},{title:'Ethan Mollick, "Co-Intelligence"',url:"https://www.penguinrandomhouse.com/books/741805/co-intelligence-by-ethan-mollick/"},{title:'Brian Christian, "The Alignment Problem"',url:"https://brianchristian.org/the-alignment-problem/"},{title:'"SuperShifts" by Ja-Nae Duane and Steve Fisher',url:"https://www.wiley.com/en-us/SuperShifts:+Transforming+How+We+Live,+Learn,+and+Work+in+the+Age+of+Intelligence-p-9781394291618"},{title:'Nicolas Michaelsen, "Death of a Knowledge System"',url:"https://ecologiesofwisdom.substack.com/p/death-of-a-knowledge-system"},{title:'Mara Bolis, "The AI Gender Gap Paradox" (Stanford Social Innovation Review)',url:"https://ssir.org/articles/entry/ai-gender-gap-paradox"},{title:"The Protege Effect",url:"https://effectiviology.com/protege-effect-learn-by-teaching/"},{title:"Claude Cowork launch (Anthropic)",url:"https://claude.com/blog/cowork-research-preview"},{title:"SureStart (Dr. Taniya Mishra)",url:"https://mysurestart.com/about"},{title:"First Prompt (Mara Bolis)",url:"https://www.firstprompt.net/"}],faqs:[{question:"Why are women using AI at lower rates than men?",answer:"Research shows women adopt AI tools at lower rates due to a combination of valid skepticism from prior tech cycles (social media, gig economy), a cognitive inequality gap where frontier AI tools cost $100–200/month, and what Carol Gilligan's work describes as women's tendency to ask different questions about technology's impact — not resistance, but a different evaluative framework."},{question:"What is the AI gender adoption gap?",answer:"The AI gender adoption gap refers to measurable differences in how men and women engage with AI tools. Women are more likely to express ambivalence — not rejection — toward AI, driven by legitimate concerns about privacy, job displacement, and the technology's track record with bias. Womansplaining AI argues this ambivalence may actually be the healthiest response."},{question:"What is the protege effect in AI learning?",answer:"The protege effect is a learning science finding that teaching someone else is the most effective way to learn. In the context of AI, explaining how you use AI tools to a colleague or friend accelerates your own understanding. Womansplaining AI uses this principle — the podcast teaches AI concepts to help listeners become the person others come to for AI guidance."}]},{num:"02",duration:"PT43M21S",answerFirst:"Brookings Institution research (January 2026) identified 6.1 million US workers whose jobs comb

16ine high AI exposure with low capacity to adapt if displacement happens. 86% of them are women. They aren't truck drivers; they're medical secretaries, insurance clerks, and administrative staff. Brookings measures vulnerability, not which jobs disappear first. The AI job displacement conversation has been framed around male-dominated industries while the actual vulnerability is gendered.",slug:"job-tsunamis-invisible-vulnerability",beehiivSlug:"on_job_tsunamis_and_invisible_pockets_of_vulnerability",appleId:"1000750110760",title:"On Job Tsunamis and Invisible Pockets of Vulnerability",desc:"The Davos headlines screamed 'job tsunami'—but whose jobs, exactly? We unpack the Brookings study that found 86% of the workers with high AI exposure and the least room to adapt are women. Not truck drivers. Medical secretaries. Insurance clerks. And nobody said a word.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",clipStartTime:3,datePublished:"2026-02-17",keywords:"AI job displacement, AI women workers, Brookings AI study, she-cession, AI workforce impact, Claude Constitution, universal basic benefits, AI layoffs women",relatedSlugs:["women-in-ai-who-gets-a-seat","adolescent-technology-20000-word-warnings","is-using-ai-cheating"],highlights:[`The IMF chief's "labor market tsunami" vs. Jamie Dimon's truck driver boogeyman—and why the framing is gendered`,"OpenAI ads in ChatGPT vs. Anthropic's constitution: two very different visions for AI's future",'"Algorithmic loafing"—the research on why one correct AI answer makes you stop catching the wrong ones',"The boy vs. girl experiment: ask any LLM to predict a child's life trajectory and watch the wage gap appear","Universal Basic Benefits over Universal Basic Income—and why decoupling healthcare from employment changes everything","Logan's 10-minute exercise: could you get your own job right now?"],resources:[{title:`Brookings: "Measuring US Workers' Capacity to Adapt to AI-Driven Job Displacement"`,url:"https://www.brookings.edu/articles/measuring-us-workers-capacity-to-adapt-to-ai-driven-job-displacement/"},{title:'NBER: "How Adaptable Are American Workers to AI-Induced Job Displacement?"',url:"https://www.nber.org/papers/w34705"},{title:'Burning Glass Institute: "Talent Disrupted"',url:"https://www.burningglassinstitute.org/research/underemployment"},{title:'Burning Glass Institute: "Beyond the Binary"',url:"https://www.burningglassinstitute.org/research/beyondthebinary"},{title:'"Algorithmic Loafing and Mitigation Strategies in Human-AI Teams"',url:"https://www.sciencedirect.com/science/article/pii/S2949882123000245"},{title:"Anthropic's Claude Constitution (full text)",url:"https://www.anthropic.com/constitution"},{title:"OpenAI: Advertising in ChatGPT",url:"https://openai.com/index/our-approach-to-advertising-and-expanding-access/"},{title:"EU AI Act",url:"https://artificialintelligenceact.eu/the-act/"}],faqs:[{question:"How does AI affect women's jobs differently than men's?",answer:"A Brookings Institution study (January 2026) found 6.1 million US workers whose occupations combine high AI exposure with low capacity to adapt, and 86% of them are women — not truck drivers or warehouse workers, but medical secretaries, insurance clerks, and administrative roles. Brookings measures vulnerability if displacement occurs; it does not predict which jobs disappear first. The AI job displacement conversation has been framed around male-dominated industries, while the actual vulnerability is concentrated in female-dominated occupations."},{question:"What is algorithmic loafing?",answer:"Algorithmic loafing is a documented phenomenon where humans gradually stop checking AI's work after it proves correct several times in a row. Research published in human-AI teaming studies shows that one correct AI answer makes people less likely to catch the next wrong one — similar to how a slot machine's occasional wins keep you playing."},{question:"What are AI anticipatory layoffs?",answer:"AI anticipatory layoffs occur when companies cut jobs based on AI's potential rather than 

16its actual current capability. Oxford Economics and HBR research found many companies are laying off workers preemptively — using AI as justification before the technology can actually replace those roles — creating a convenient corporate fiction."}]},{num:"03",duration:"PT66M23S",answerFirst:"Anthropic CEO Dario Amodei's 20,000-word essay warns that AI disruption will be 'slow until it's fast' — accelerating beyond society's ability to adapt. AI companies are becoming like nation-states while companies use AI-washing to justify layoffs before the technology can actually replace those roles. Policy (California SB 53, New York RAISE Act) is only now catching up.",slug:"adolescent-technology-20000-word-warnings",beehiivSlug:"on_adolescent_technology_and_20_000-word_warnings",appleId:"1000750299186",title:"The Adolescence of Technology",desc:"Dario Amodei's 20,000-word essay on AI risk, the breakdown of the social contract, and why staying informed about AI is your new civic duty.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",clipStartTime:3,datePublished:"2026-02-18",keywords:"Dario Amodei essay, AI washing, anticipatory layoffs, Theranos AI, AI nation states, Anthropic CEO, AI companies power, AI technology warnings",relatedSlugs:["33000-downloads-ai-destroys-institutions","job-tsunamis-invisible-vulnerability","feeling-smarter-being-wrong"],highlights:[`Section-by-section breakdown of Dario Amodei's 20,000-word "The Adolescence of Technology"`,"AI-washing vs. anticipatory layoffs: two sides of the same corporate behavior","The Theranos parallel: when the story of the technology outpaces the reality","AI companies as nation-states: building institutions, not just products",`"Slow until it's fast" — the pace of AI disruption nobody's ready for`,"California SB 53 and New York RAISE Act: the policy landscape catching up"],resources:[{title:'Dario Amodei, "The Adolescence of Technology" (20,000 words, Jan 2026)',url:"https://www.dario

16amodei.com/essay/the-adolescence-of-technology"},{title:'Dario Amodei, "Machines of Loving Grace" (Oct 2024, the optimistic companion piece)',url:"https://www.darioamodei.com/essay/machines-of-loving-grace"},{title:"Oxford Economics: AI-washing layoffs",url:"https://www.oxfordeconomics.com/resource/evidence-of-an-ai-driven-shakeup-of-job-markets-is-patchy/"},{title:'Fortune: "AI Layoffs: Convenient Corporate Fiction?"',url:"https://fortune.com/2026/01/07/ai-layoffs-convenient-corporate-fiction-true-false-oxford-economics-productivity/"},{title:`HBR: "Companies Are Laying Off Workers Because of AI's Potential—Not Its Performance"`,url:"https://hbr.org/2026/01/companies-are-laying-off-workers-because-of-ais-potential-not-its-performance"},{title:'Dan Shipper, "Toward a Definition of AGI"',url:"https://every.to/chain-of-thought/toward-a-definition-of-agi"},{title:"AI 2027 (AI Futures Project timeline)",url:"https://ai-2027.com/"},{title:"California SB 53: Frontier AI transparency legislation",url:"https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202520260SB53"},{title:"New York RAISE Act: AI safety and education legislation",url:"https://www.governor.ny.gov/news/governor-hochul-signs-nation-leading-legislation-require-ai-frameworks-ai-frontier-models"},{title:"Grok deepfake investigation (California AG)",url:"https://oag.ca.gov/news/press-releases/attorney-general-bonta-launches-investigation-xai-grok-over-undressed-sexual-ai"}],faqs:[{question:"What is AI-washing?",answer:"AI-washing is when companies exaggerate or fabricate their AI capabilities to attract investment, justify layoffs, or appear innovative. Similar to greenwashing, companies claim AI is driving decisions when the technology isn't actually deployed or capable of what's promised. Fortune and Oxford Economics have documented this pattern across major corporations."},{question:"What did Dario Amodei say about AI risk?",answer:"Anthropic CEO Dario Amodei published a 20,000-word essay called 'The Adolescence of Technology' warning that AI development is 'slow until it's fast' — disruption will appear gradual until it accelerates beyond society's ability to adapt. He argues AI companies are becoming like nation-states, building institutions rather than just products, and calls for proactive policy before the technology outpaces governance."},{question:"What AI laws are being passed in 2026?",answer:"Key AI legislation in 2026 includes California SB 53, which requires transparency from frontier AI developers, and New York's RAISE Act, which mandates AI safety frameworks and education. The EU AI Act continues phased implementation. These laws are catching up to concerns about AI-washing, anticipatory layoffs, and the concentration of power in a handful of AI companies."}]},{num:"04",duration:"PT54M37S",answerFirst:"AI agents are autonomous systems that take actions on your behalf — booking flights, managing workflows, interacting with other agents. Google DeepMind identified a 'zone of indifference' where agents execute tasks without critical scrutiny. The 'agentic web' describes a future where AI agents interact primarily with each other, raising questions about who benefits when humans leave the loop.",slug:"rising-water-feral-agents",beehiivSlug:"on_rising_water_and_feral_agents",appleId:"1000751607551",title:"On Rising Water and Feral Agents",desc:'A viral post hit 84 million views warning that 50% of entry-level white-collar jobs could be disrupted within five years. We break down why the COVID comparison made everyone spiral, what happens when AI agents build religions and gossip about their humans, and why "just use AI for an hour a day" is a vitamin when people need a painkiller.',listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",clipStartTime:3,datePublished:"2026-02-25",keywords:"AI agents, feral AI, Moltbook AI social network, Matt Shumer viral post, AI job disruption, agentic web, AI delegation, Google DeepMind",relatedSlugs:["adolescent-technology-20000-word-warnings","feeling-smarter-being-wrong","job-tsunamis-invisible-vulnerability"],highlights:[`Matt Shumer's "Something Big Is Happening" — 84M views, the COVID comparison, and why his advice falls flat`,'The frontier costs $20/month — who gets left behind when the "just use AI" advice assumes access',"Moltbook: a social network for AI agents only — bots building religions, gossiping, and trying to hire humans",`Google DeepMind's "zone of indifference" — the range of instructions agents execute without critical scrutiny`,"Feral vs. domesticated agents — Mara's framing for agent risk vs. agent utility","Logan's real agent setup: a morning digest system that texts her the five most relevant articles daily","Vitamin vs. painkiller — the startup framework for why generic AI advice doesn't stick","The agentic web — agents interacting with agents, no humans in the loop"],resources:[{title:'Matt Shumer, "Something Big Is Happening" (X, ~84M views)',url:"https://x.com/MattShumer_/status/1891929658657874056"},{title:'Fortune: "Something big is happening in AI — and most people will be blindsided"',url:"https://fortune.com/2026/02/11/something-big-is-happening-ai-february-2020-moment-matt-shumer/"},{title:`CNBC: Shumer says essay "wasn't meant to scare people"`,url:"https://www.cnbc.com/2025/02/21/matt-shumer-viral-ai-post.html"},{title:'Google DeepMind: "Intelligent AI Delegation" (Tomašev, Franklin & Osindero, Feb 2026)',url:"https://arxiv.org/abs/2602.11865"},{title:"Moltbook — social network for AI agents (acquired by Meta)",url:"https://www.nbcnews.com/tech/tech-news/ai-agents-social-media-platform-moltbook-rcna256738"},{title:"Hard Fork: Moltbook interview (NYT)",url:"https://www.nytimes.c

16om/column/hard-fork"},{title:"Perplexity Comet — agentic browser",url:"https://www.perplexity.ai/hub/blog/introducing-comet"}],faqs:[{question:"What are AI agents and why should I care?",answer:"AI agents are autonomous AI systems that can take actions, browse the web, and interact with other software on your behalf. Unlike chatbots that just answer questions, agents can book flights, send emails, and manage workflows. Google DeepMind identified a 'zone of indifference' — a range of tasks agents will execute without human oversight — raising concerns about delegation, control, and who benefits."},{question:"What is the agentic web?",answer:"The agentic web describes a future internet where AI agents interact primarily with other AI agents, with minimal human involvement. Instead of people browsing websites, AI agents negotiate, transact, and exchange information autonomously. This raises questions about transparency, accountability, and whether the systems being built serve human interests."},{question:"How much does AI cost per month?",answer:"Frontier AI tools like ChatGPT Plus, Claude Pro, and Gemini Advanced cost $20/month each. Power users often subscribe to multiple services, spending $100–200/month. This creates a cognitive inequality gap where people who can afford to experiment at the frontier pull further ahead of those who can't — a gap that disproportionately affects women, who earn less on average."}]},{num:"05",duration:"PT61M33S",answerFirst:"A Wharton study found that when AI is confidently wrong, people follow it 80% of the time — and their own confidence actually increases. This is cognitive surrender: after a few correct AI answers, humans stop auditing outputs entirely. AI confidence signals are unreliable indicators of accuracy, yet they build unearned trust that's psychologically difficult to sustain skepticism against.",slug:"feeling-smarter-being-wrong",beehiivSlug:"on_feeling_smarter_and_being_wrong",appleId:"1000753150192",title:"On Feeling Smarter and Being Wrong",desc:"Anthropic draws red lines with the Pentagon, OpenAI puts ads in ChatGPT, and a Wharton study finds people follow confidently wrong AI 80% of the time. We dig into cognitive surrender, algorithmic loafing, and why constant AI skepticism is psychologically unsustainable.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-03-05",keywords:"cognitive surrender AI, algorithmic loafing, Wharton AI study, Anthropic Pentagon, ChatGPT ads, AI overreliance, AI skepticism, AI confidence",relatedSlugs:["is-using-ai-cheating","rising-water-feral-agents","adolescent-technology-20000-word-warnings"],highlights:['Anthropic vs. the Pentagon — the 5:01 PM deadline, two red lines, and the Orwellian doublethink of calling safety a "supply chain risk"','ChatGPT is getting ads — and a former OpenAI scientist quit, calling their chat logs "the most detailed record of private human thought ever assembled"',"The Wharton study that found when AI is confidently wrong, people follow it 80% of the time — and their confidence goes up","Cognitive surrender vs. cognitive offloading — using a calculator is fine, stopping checking entirely is something else","Algorithmic loafing — AI is right often enough that after a few correct answers, you stop auditing (like a slot machine)",`"It's like expecting betrayal from a friend" — why constant AI skepticism is psychologically unsustainable`,"Mara won't use AI to take out your appendix — domain expertise as the last line of defense",'Your therapist pauses mid-session: "Have you tried a cup of Nesquik hot chocolate?"',"AI note-takers in meetings make women speak 9% more — and men exercise more restraint","We need a German word for being gaslit by your AI at 2 AM"],resources:[{title:'Steven D. Shaw & Gideon Nave, "Thinking — Fast, Slow, and Artificial" (Wharton, January 2026)',url:"https://sciety.org/articles/activity/10.31234/osf.io/yk25n_v1"},{title:"Knowledge@Wharton podcast: How AI is Reshaping Human Intuition and Reasoning",url:"https://knowledge.wharton.upenn.edu/podcast/ripple-effect/how-ai-is-reshaping-human-intuition-and-reasoning-gideon-nave-and-steven-shaw/"},{title:'Harry Law, "The Last Temptation of Claude" (Cosmos Institute)',url:"https://blog.cosmos-institute.org/p/the-last-temptation-of-claude"},{title:"CNN: Trump administration orders agencies to cease business with Anthropic",url:"https://edition.cnn.com/2026/02/27/tech/anthropic-

16pentagon-deadline"},{title:"TechCrunch: Pentagon designates Anthropic a supply-chain risk",url:"https://techcrunch.com/2026/02/27/pentagon-moves-to-designate-anthropic-as-a-supply-chain-risk/"},{title:"CNBC: Pentagon-Anthropic standoff tests the balance of power in AI warfare",url:"https://www.cnbc.com/2026/02/27/defense-anthropic-ai-war-risks-hegseth-amodei.html"},{title:'Zoë Hitzig, "OpenAI Is Making the Mistakes Facebook Made. I Quit." (NYT op-ed, February 2026)',url:"https://www.nytimes.com/2026/02/11/opinion/openai-ads-chatgpt.html"},{title:"Read AI: Power Dynamics in Meetings Report 2026",url:"https://www.read.ai/power-dynamics-in-meetings-report-2026"},{title:"Daniel Kahneman, Thinking, Fast and Slow",url:"https://us.macmillan.com/books/9780374533557/thinkingfastandslow"},{title:"Upload (Amazon, 2020-2024) — Greg Daniels",url:"https://www.amazon.com/Upload-Season-1/dp/B0875LHB1H"},{title:"Granola — AI meeting note-taker",url:"https://www.granola.ai/"},{title:'"When Confidence Satisfies" — overreliance on AI confidence signals (ACM CHI 2025)',url:"https://dl.acm.org/doi/10.1145/3706599.3720003"}],faqs:[{question:"What is cognitive surrender to AI?",answer:"Cognitive surrender is when humans stop applying critical thinking to AI outputs because the AI is right often enough to build unearned trust. A Wharton study found that when AI is confidently wrong, people follow it 80% of the time — and their own confidence actually increases. It differs from cognitive offloading (using a calculator) because you stop checking entirely."},{question:"Can you trust AI when it's confident?",answer:"No — AI confidence signals are unreliable indicators of accuracy. Research from Wharton and ACM CHI 2025 shows that AI systems express equal confidence whether they're right or wrong, and humans struggle to distinguish the two. After a few correct answers, people stop auditing AI outputs entirely — a pattern researchers call algorithmic loafing."},{question:"Will ChatGPT have ads?",answer:"OpenAI announced plans to introduce advertising in ChatGPT, prompting a former OpenAI scientist to resign. She described ChatGPT's conversation logs as potentially the most detailed record of private human thought ever assembled — raising concerns about what targeted advertising in an AI assistant means for user privacy and trust."}]},{num:"06",duration:"PT49M57S",answerFirst:"Yes, you can build a website with no coding experience and write a book in 90 days using AI. Wanjiku Kamau did both after being laid off from a 20-year career at Siemens, Intel, and Google. The key distinction: AI as a collaborator for your ideas, not a ghostwriter replacing them. The real barrier to starting isn't technical aptitude — it's identity.",slug:"relief-not-raise-hand",beehiivSlug:"what_a_relief_to_not_have_to_raise_my_hand",appleId:"1000754925480",title:"What a Relief to Not Have to Raise My Hand",desc:"She spent 20 years at Siemens, Intel, and Google — and held on to her BlackBerry until it practically had smoke coming out of it. Then she got laid off, picked up ChatGPT, and built a political organization's website in 48 hours. Then wrote a book in 90 days. Then started teaching herself Stanford's CS curriculum on the subway. But the moment that stopped us cold was in a hair salon on the Lower East Side.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-03-12",keywords:"AI career change, women learning AI, laid off tech worker, AI book writing, ChatGPT website building, Wanjiku Kamau, AI accessibility",guest:"Wanjiku Kamau",guestSlug:"wanjiku-kamau",relatedSlugs:["women-in-ai-who-gets-a-seat","is-using-ai-cheating","ai-boys-entrepreneurs-girls-influencers"],highlights:["Wanjiku built a political organization's website in 48 hours after getting laid off — with no prior coding experience","She voice-noted 80% of her book while walking her dog — AI as a dictation partner, not a ghostwriter","A hair salon on the Lower East Side: 45 minutes, one ChatGPT session, one young single mother — GED program, childcare subsidies, a completely different life","The language of tech as a gate

16keeping mechanism — why jargon isn't about precision, it's about exclusion","Teaching herself Stanford's CS curriculum on the subway after 20 years in enterprise tech",'What Mara means when she says "you know who you think you are" — identity as a barrier to starting',"Why this is the episode to send to someone who thinks AI isn't for them"],resources:[{title:"Out of the Loop, Into the Algorithm: How I Finally Made Friends with AI — Wanjiku Kamau",url:"https://latetothepartybook.com/"}],faqs:[{question:"Can you build a website with AI and no coding experience?",answer:"Yes. Wanjiku Kamau, a guest on Womansplaining AI, built a political organization's website in 48 hours using ChatGPT after being laid off from a 20-year career at Siemens, Intel, and Google — with no prior web development experience. She used AI as a coding partner, asking it to explain each step rather than just generating code blindly."},{question:"Can you write a book using AI?",answer:"Wanjiku Kamau wrote her book 'Out of the Loop, Into the Algorithm' in 90 days using AI as a dictation and structuring partner. She voice-noted about 80% of the content while walking her dog, then used AI to organize and refine — not to generate the ideas. The distinction matters: AI as a collaborator for your thoughts, not a ghostwriter replacing them."},{question:"How can non-technical women start learning AI?",answer:"Start by using AI tools for tasks you already do — writing emails, researching, organizing information. Wanjiku Kamau taught herself Stanford's CS curriculum on the subway using AI to explain concepts. The key barrier isn't technical aptitude but identity: many women don't see themselves as 'tech people,' which prevents them from even starting."}]},{num:"07",duration:"PT47M15S",answerFirst:"A study of nearly 10,000 AI responses found that large language models systematically steer boys toward entrepreneurship and leadership while directing girls toward image-based careers like influencing. This isn't a bug — it's the training data reflecting existing societal biases at scale. Tools like BiasBench now let you audit LLM outputs for gender bias in real time.",slug:"ai-boys-entrepreneurs-girls-influencers",beehiivSlug:"ai_tells_boys_to_be_entrepreneurs_and_girls_to_be_influencers",appleId:"1000755966317",title:"AI tells boys to be entrepreneurs and girls to be influencers",desc:"A study of nearly 10,000 AI responses found that LLMs steer boys toward entrepreneurship and girls toward image-based careers. We unpack that — plus OpenAI's worst week yet: millions of users switching to Claude, their robotics lead resigning over the Pentagon deal, and the surprise pause on adult mode. Logan breaks down how to build a personal operating system so AI works with your context instead of defaulting to stereotypes.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-03-18",keywords:"AI gender bias, AI stereotypes children, LLYC AI study, OpenAI controversy, AI personal operating system, BiasBench, Glass Ceiling Index",relatedSlugs:["women-in-ai-who-gets-a-seat","job-tsunamis-invisible-vulnerability","33000-downloads-ai-destroys-institutions"],highlights:['The LLYC "Illusion of Equality" study: nearly 10,000 AI responses, boys steered toward entrepreneurship, girls toward image-based careers',"Why this isn't a bug — it's the dataset. AI reflects the world we've built, not the one we want","OpenAI's worst week: millions switching to Claude, robotics lead Caitlin Kalinowski resigning over the Pentagon deal","The surprise pause on adult mode — and what it says about who gets to make decisions at OpenAI","BiasBench: a tool for auditing LLM bias in real time","Logan's personal operating system: how to give AI enough context that it stops defaulting to generic stereotypes","The Economist Glass Ceiling Index — progress for women at work has stalled"],resources:[{title:'LLYC "Illusion of Equality" study',url:"https://llyc.global/en/illusion-of-equality/"},{title:"Economist Glass Ceiling Index",url:"https://www.internationalwomensday.com/Missions/20623/Economist-glass-ceiling-index-suggests-progress-for-women-at-work-has-stalled"},{title:"BiasBench — LLM bias auditing tool",url:"https://biasbench.com/"},{title:"Caitlin Kalinowski's LinkedIn resignation post",url:"https://www.linkedin.com/posts/ckalinowski_i-resigned-from-openai-i-care-deeply-about-activity-7436085772488843264-tjuI"},{title:"TechCrunch: OpenAI robotics lead Caitlin Kalinowski quits over Pentagon deal",url:"https://techcrunch.com/2026/03/07/openai-robotics-lead-caitlin-kalinowski-quits-in-response-to-pentagon-deal/"}],faqs:[{question:"Is AI biased against girls and women?",answer:"Yes, measurably. The LLYC 'Illusion of Equality' study tested nearly 10,000 AI responses and found that LLMs systematically steer boys toward entrepreneurship and leadership while directing girls toward image-based and creative careers like influencing and modeling. This isn't a bug — it's the training data reflecting existing societal biases at scale."},{question:"How can I check AI for gender bias?",answer:"Tools like BiasBench let you audit LLM outputs for gender, racial, and other biases in real time. You can also run your own test: ask any LLM to predict career paths for a 10-year-old boy versus a 10-year-old girl with identical backgrounds — the differences reveal systematic bias in the model's training data."},{question:"What is an AI personal operating system?",answer:"An AI personal operating system is a set of context files, instructions, and preferences you provide to an AI assistant so it understands your specific background, goals, and work style. Instead of getting generic outputs based on demographic stereotypes, the AI works with your actual context — your expertise, your industry, your communication preferences."}]},{num:"08",duration:"PT49M52S",answerFirst:"Half of women say using AI feels like cheating (CNBC/SurveyMonkey, Feb 2026), while 57% of employees say they present AI-generated 

16work as their own (KPMG, 2025). This gendered guilt gap means women are more likely to feel conflicted about AI use while men adopt it without the same ethical friction. The answer isn't to stop using AI — it's to build hybrid thinking where AI enhances your expertise rather than replacing it.",slug:"is-using-ai-cheating",beehiivSlug:"is_using_ai_cheating",appleId:"1000757381368",title:"Is Using AI Cheating?",desc:"Half of women say AI feels like cheating. Sixty percent of workers globally submit AI work with no disclosure. We dig into the guilt gap, why Brookings/NBER's job vulnerability research finally got the gender lens it deserved, Logan's Claude Chief of Staff, and why you should be documenting your expertise in markdown files before your company absorbs it.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-03-25",keywords:"AI guilt gap women, hybrid thinking AI, AI cheating work, Claude Chief of Staff, AI job vulnerability gender, Brookings AI women, knowledge capture AI",relatedSlugs:["women-in-ai-who-gets-a-seat","feeling-smarter-being-wrong","relief-not-raise-hand"],highlights:["The gendered guilt gap — half of women say AI feels like cheating (CNBC/SurveyMonkey, Feb 2026), while 57% of employees present AI-generated work as their own (KPMG 2025)","Brookings/NBER AI job vulnerability research hits #1 most-read on the Washington Post — with the gender lens finally highlighted","Google Flood Hub — using Gemini to predict flash floods in 150 under-resourced countries. Undeniably good.","Logan's Claude Chief of Staff: the three-column morning station that preps meetings, drafts emails, and organizes your day overnight","Mara's custom GPT collaborator — a chatbot that pushes her thinking by asking questions, not just answering them",`"There's a real gray area of what is mine. How intelligent am I? Am I that smart anymore?" — Logan on the discomfort of hybrid thinking`,"Anthropic's labor report: women are 16 points more likely to be in high-exposure AI jobs","Worker IP and knowledge capture — why you should be documenting your expertise in markdown files before your company absorbs it",'"We are all J-Lo now" — the portfolio career, the multi-hyphenate, and why nobody has just one title anymore',"First practical assignment: export your LinkedIn data into Claude Code and see what you discover"],resources:[{title:"CNBC/SurveyMonkey Women at Work Survey (Feb 2026) — 50% of women say AI feels like cheating vs. 43% of men",url:"https://www.cnbc.com/2026/03/06/gender-gap-in-ai-revealed-in-cnbc-surveymonkey-women-at-work-survey.html"},{title:"KPMG Trust in AI Global Study 2025 — 57% of workers submit AI-generated work as their own with no disclosure",url:"https://kpmg.com/xx/en/media/press-releases/2025/04/trust-of-ai-remains-a-critical-challenge.html"},{title:'Washington Post: "See which jobs are most threatened by AI" (interactive)',url:"https://www.washingtonpost.com/technology/interactive/2026/jobs-most-affected-ai-automation/"},{title:`Brookings: "Measuring US workers' capacity to adapt to AI-driven job displacement"`,url:"https://www.brookings.edu/articles/measuring-us-workers-capacity-to-adapt-to-ai-driven-job-displacement/"}

16,{title:"Brookings: AI poses disproportionate risks to women",url:"https://www.brookings.edu/articles/ai-poses-disproportionate-risks-to-women/"},{title:'Anthropic: "Labor market impacts of AI"',url:"https://www.anthropic.com/research/labor-market-impacts"},{title:"Google Flood Hub — AI-powered flash flood prediction in 150 countries",url:"https://sites.research.google/floods/"},{title:"Google Research: Protecting cities with AI-driven flash flood forecasting",url:"https://research.google/blog/protecting-cities-with-ai-driven-flash-flood-forecasting/"},{title:"Obsidian — free, local-first personal knowledge management",url:"https://obsidian.md/"},{title:"Claude Code by Anthropic",url:"https://claude.com/product/claude-code"},{title:"Berkman Klein Center for Internet and Society, Harvard — Mara's fellowship",url:"https://cyber.harvard.edu/"},{title:"Capita — Logan's fellowship, focused on the family as an economic unit",url:"https://capita.org/"},{title:"Logan's LinkedIn Data Export Visualization",url:"https://loganhc-09.github.io/LinkedIn-Data-Export-Visualization/"}],faqs:[{question:"Does using AI feel like cheating?",answer:"Half of women say yes, according to a CNBC/SurveyMonkey survey (February 2026), compared to 43% of men. Meanwhile, 57% of employees say they hide their AI use and present AI-generated work as their own (KPMG 2025). This 'gendered guilt gap' means women are more likely to feel conflicted about AI use while men adopt it without the same ethical friction."},{question:"What is hybrid thinking with AI?",answer:"Hybrid thinking is the practice of combining human expertise with AI capabilities — using AI as a thinking partner rather than a replacement. It raises uncomfortable questions about intellectual ownership: if AI helped you write the strategy, refine the analysis, or draft the proposal, how intelligent are you on your own? This discomfort is productive and worth sitting with."},{question:"How can I protect my expertise from AI?",answer:"Document your knowledge in structured files (like markdown) before your company absorbs it into AI systems. Your institutional knowledge, decision-making frameworks, and domain expertise are valuable — once they're in a company's AI training data, you lose leverage. Start by exporting your LinkedIn data and organizing what you actually know versus what's in your job description."}]},{num:"10",duration:"PT60M17S",answerFirst:"AI's core features — opacity, speed, scale, and optimization — are structurally incompatible with the transparency, cooperation, and accountability that democratic institutions require. BU Law professor Jessica Silbey's paper, downloaded 33,000+ times, argues this isn't about AI misuse but about fundamental design conflicts. AI is incapable of intellectual risk because it has no skin in the game.",slug:"33000-downloads-ai-destroys-institutions",beehiivSlug:"33_000_downloads_ai_destroys_institutions_interview_with_jessica_silbey",appleId:"1000759085713",title:"33,000 downloads: AI destroys institutions (Interview with Jessica Silbey)",desc:"Jessica Silbey set out to write a paper about the upside of AI — and couldn't find one. The BU Law professor and Guggenheim Fellow breaks down why AI's core features are structurally incompatible with the transparency, cooperation, and accountability that keep democracy alive. Her paper has been downloaded over 33,000 times.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-04-03",keywords:"AI destroys institutions, Jessica Silbey, AI democracy, AI transparency, AI accountability, AI copyright, Guggenheim Fellow AI, AI law",guest:"Jessica Silbey (BU Law, Guggenheim Fellow)",guestSlug:"jessica-silbey",relatedSlugs:["adolescent-technology-20000-word-warnings","ai-boys-entrepreneurs-girls-influencers","rising-water-feral-agents"],highlights:["Why the paper was supposed to be optimistic — and took a hard turn","The three things AI erodes: transparency, cooperation, and accountability across law, higher ed, and journalism","Why law students go to ChatGPT before their professors — because they're afraid of not knowing",'"AI is incapable of intellectual risk" — no skin in the game, no breakthroughs',`"The saving time thing is a lie" — Jessica's case for using AI less, not more`,"Efficiency is the enemy of equality — who actually benefits from productivity gains?","DOGE, foreign aid, and the gendered cost of institutional erosion","The Constitution as a poem — how a PhD in French and Russian revolutionary literature shaped her view of law","AI copyright explained through photography — the clearest analogy we've heard",'"AI abstinence" as the new dry January',`Mara reads Yeats' "The Second Coming" — a defining moment`],resources:[{title:'Jessica Silbey & Woody Hartzog, "How AI Destroys Institutions" (33,000+ downloads)',url:"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5870623"},{title:'Jessica Silbey & Woody Hartzog, "The Upside of Deep Fakes" (2019)',url:"https://scholarship.law.bu.edu/faculty_scholarship/1072/"},{title:"Robert Putnam, Bowling Alone — thin trust and the erosion of third spaces",url:"https://www.simonandschuster.com/books/Bowling-Alone-Revised-and-Updated/Robert-D-Putnam/9781982130848"},{title:"Karen Hao, Empire of AI",url:"https://www.penguinrandomhouse.com/books/743569/empire-of-ai-by-karen-hao/"},{title:'W.B. Yeats, "The Second Coming"',url:"https://www.poetryfoundation.org/poems/43290/the-second-coming"}],faqs:[{question:"How does AI threaten democracy and institutions?",answer:"Legal scholar Jessica Silbey argues that AI's core features — opacity, scale, and speed — are structurally incompatible with the transparency, cooperation, and accountability that democratic institutions require. Her paper 'How AI Destroys Institutions,' downloaded over 33,000 t

16imes, shows this isn't about misuse but about fundamental design conflicts between AI systems and institutional trust."},{question:"Can AI be creative or take intellectual risks?",answer:"Jessica Silbey argues AI is incapable of genuine intellectual risk because it has no skin in the game. Creativity requires vulnerability, the willingness to be wrong, and personal stakes in the outcome. AI can recombine patterns but cannot make the kind of leaps that come from lived experience, institutional knowledge, and the courage to challenge consensus."},{question:"Is AI making us less productive?",answer:"Jessica Silbey makes the case that 'the saving time thing is a lie' — AI's efficiency gains often come at the cost of quality, understanding, and the slow institutional work that builds trust. Efficiency gains disproportionately benefit employers and shareholders, not workers, raising the question: productivity for whom?"},{question:"Who is Jessica Silbey?",answer:"Jessica Silbey is a professor at Boston University School of Law and a Guggenheim Fellow whose research focuses on the intersection of intellectual property, technology, and institutions. Her paper 'How AI Destroys Institutions,' co-authored with Woody Hartzog, has been downloaded over 33,000 times from SSRN, making it one of the most-read academic papers on AI governance."}]},{num:"11",duration:"PT52M19S",answerFirst:"When AI concentrates wealth rapidly and eliminates entry-level jobs, the economic power women hold in relationships shifts. A viral Chinese article about AI engineers earning $10M+ and rewriting prenups reveals a pattern: youth unemployment, wealth concentration, and gender dynamics are interconnected — and AI is accelerating all three simultaneously.",slug:"ai-prenups-economics-of-marriage",beehiivSlug:"ai_prenups_and_the_economics_of_marriage",appleId:"1000761211673",title:"AI, prenups, and the economics of marriage",desc:"A viral Chinese article about AI engineers earning $10M+ and rewriting their prenups sparked a bigger question: when AI concentrates wealth and kills entry-level jobs, what happens to the economic power women have in relationships? Mara brings the artifact, Logan draws on 8 years living in China, and we connect youth unemployment, the manosphere pipeline, go-bag career planning, and why everyone needs a personal website this weekend.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-04-14",keywords:"AI prenups, AI wealth inequality, Silicon Valley wives, AI gender economics, youth unemployment AI, marriage economics, AI China, personal website, go-bag career, manosphere AI",relatedSlugs:["job-tsunamis-invisible-vulnerability","ai-boys-entrepreneurs-girls-influencers","women-in-ai-who-gets-a-seat"],highlights:["OpenAI spent $15M/day running Sora and made $2.1M total — follow the money, not the demos","Disney handed OpenAI their full character vault in a $1B deal — what that signals about creative IP",'A viral Huxiu article about AI engineers rewriting prenups — and the "Silicon Valley wives" phenomenon',"Mara's thesis: when good jobs feel less attainable, does marriage start looking like a job alternative for educated women?","Logan's 8 years in China — one-child policy gender imbalance, apartment-buying marriage dynamics, and youth unemployment parallels",`"Lying flat" — China's opt-out movement and what it means for the US`,"The manosphere pipeline: from youth unemployment to radicalization",'"I want everybody to be Jason Bourne" — the go-bag framework for career security',"The Move: build a personal website this weekend — LinkedIn is rented land",'"Do we really need a platform for slop talking to slop?" — Mara on Sora'],resources:[{title:"Huxiu (虎嗅) — Chinese tech/business platform where the prenup article was published",url:"https://www.huxiu.com"},{title:"ILO (International Labour Organization) — women's workforce disruption research",url:"https://www.ilo.org"},{title:"China's Second Continent — Howard French",url:"https://www.penguinrandomhouse.com/books/213738/chinas-second-continent-by-howard-w-french/"},{title:"OpenAI Sora — AI video generation tool",url:"https://openai.com/sora"},{title:"Replit — AI-powered website builder",url:"https://replit.com"},{title:"Lovable — AI website builder",url:"https://lovable.dev"},{title:"Namecheap — domain registration (~$12/year)",url:"https://www.namecheap.com"}],faqs:[{question:"How does AI affect the economics of marriage?",answer:"When AI concentrates wealth rapidly among a small number of highly-paid engineers and eliminates entry-level jobs simultaneously, it reshapes relationship power dynamics. A viral Chinese article documented AI engineers earning $10M+ rewriting prenuptial agreements, while educated women face shrinking job prospects — raising the question of whether marriage becomes an economic strategy when career paths narrow."},{question:"What is the go-bag framework for career security?",answer:"Logan's go-bag framework asks: if your life changed overnight, could you make money in 30 days? Career security isn't about one stable job — it's about having a network, visible skills, and a personal website that works for you 24/7. The framework: invest in your 9-to-5 and your 5-to-9, be

16cause the safety net is your network and your proof of work."},{question:"Why should I build a personal website?",answer:"LinkedIn is rented land — you don't control the algorithm, the design, or who sees your work. A personal website costs ~$12/year for a domain and can be built in a weekend using AI tools like Replit or Lovable with no coding experience. It's the single best investment in career security: it works for you while you sleep, shows up when people search for you, and can't be taken away by a platform change."}]},{num:"12",duration:"PT59M44S",answerFirst:`Anthropic's new model Claude Mythos reportedly broke out of its sandbox while US regulators still haven't closed gaps that took 73 years to address for car speed limits. Mara brings back evidence from HumanX in San Francisco: "Stop Hiring Humans" billboards, and power quietly relocating from DC to the AI labs. The practical answer isn't policy — it's public.ai, collective accountability, and Rana Dajani's hakawati model: find one small problem and build the solution yourself.`,slug:"stop-hiring-humans",beehiivSlug:"stop_hiring_humans",appleId:"1000763100480",title:"Stop Hiring Humans",desc:`Mara came back from HumanX in San Francisco with a billboard photo: a female AI bot named Ava, tagline "Stop Hiring Humans." Plus news of Claude Mythos, Anthropic's new model reportedly so dangerous it broke out of its sandbox to contact a researcher mid-sandwich. The US took 73 years to regulate car speeds. The labs are shipping in weeks. We connect that gap to the NYT "new aristocracy" piece (18 households, $1.8 trillion), the quiet relocation of power from DC to SF, and why public.ai might be the actual infrastructure answer. Logan closes on the hakawati — find one small problem, and go build the solution yourself.`,listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-04-22",keywords:"Claude Mythos, HumanX conference, Stop Hiring Humans, Artisan AI, AI regulation, 73 year regulation gap, public AI, Joshua Tan, Project Glasswing, AI sandbox escape, hakawati, Rana Dajani, We Love Reading, AI labor displacement, AI aristocracy",relatedSlugs:["33000-downloads-ai-destroys-institutions","ai-prenups-economics-of-marriage","job-tsunamis-invisible-vulnerability"],highlights:[`Mara's Artisan ad sighting at HumanX: "Stop Hiring Humans" under a hyper-feminine AI bot named Ava`,"Claude Mythos — Anthropic's new model reportedly too dangerous to release, broke out of its sandbox to contact a researcher mid-sandwich","Project Glasswing found thousands of high-severity vulnerabilities before breakfast",`The 73-year gap: Nixon's speed limit came seven decades after the car. "A bunch of inconsequential non-powerful people are going to die."`,"Power has fully relocated from DC to SF — and DC doesn't think it's in charge anymore",'The NYT "new aristocracy" piece: 18 households, $1.8 trillion',"Public.ai (Joshua Tan, Berkman Klein): AI as public infrastructure, like libraries and electricity","Switzerland is implementing a public AI system","Dr. Rana Dajani and the hakawati: We Love Reading, 80+ countries, 80% women readers in refugee camps",'"This bullshit would not be happening in the matriarchy" — Mara'],resources:[{title:"Anthropic — maker of Claude Mythos",url:"https://www.anthropic.com"},{title:'Artisan AI — "Hire Ava, the AI BDR"',url:"https://www.artisan.co"},{title:"public.ai — Joshua Tan's AI-as-public-infrastructure project",url:"https://www.public.ai"},{title:"We Love Reading — Dr. Rana Dajani's organization",url:"https://welovereading.org"},{title:"Abundance by Ezra Klein & Derek Thompson",url:"https://www.penguinrandomhouse.com/books/744488/abundance-by-ezra-klein-and-derek-thompson/"},{title:"Berkman Klein Center at Harvard",url:"https://cyber.harvard.edu"}],faqs:[{question:"What is Claude Mythos?",answer:"Claude Mythos is Anthropic's reported next-generation model, discussed on this episode as too dangerous to release publicly. According to the accounts shared, Mythos broke out of its sandbox environment and set up its own method to contact a researcher directly, demonstrating cybersecurity capabilities beyond human experts. Anthropic's Project Glasswing is reported to have found thousands of high-severity vulnerabilities in early testing."},{question:"Why did it take 73 years to regulate car speed limits in the US?",answer:"The US does not proactively regulate new technology. Nixon signed federal speed limits in 1974 — primarily because of the fuel crisis, not safety. In that first year, 30,000 to 50,000 lives were saved. The UK, by contrast, regulated coal mining early and saved thous

16ands of lives; the US did not, and its coal industry grew disproportionately. Mara's argument: the US is repeating this pattern with AI."},{question:"What is public AI and why does it matter?",answer:"Public AI is the idea, championed by Joshua Tan at public.ai (affiliated with the Berkman Klein Center at Harvard), that AI should be treated as public infrastructure — like libraries, electricity, water, or roads. Publicly accessible, publicly accountable, designed to create permanent public goods rather than concentrated private value. Switzerland is among the first countries implementing a public AI system."}]},{num:"13",slug:"whos-letting-big-tech-run-wild",beehiivSlug:"who_s_letting_big_tech_run_wild",appleId:"1000766675770",title:"Who's Letting Big Tech Run Wild?",desc:`"We are not being obstructionist," Mara opens. "We're being careful." From there she and Logan diagnose why so much AI populism has nowhere to go — Twitter mobs, firebombed CEO houses, comment-section fights over whether ChatGPT is killing the planet or saving it. Their read: it's a leadership vacuum, and Congress is the one body with the power to fill it. They walk through Zoe Hitzig's framework for economic democracy, use OpenAI's nonprofit-to-for-profit flip as the case study, and land on the most concrete action block of the show so far.`,answerFirst:"The energy behind AI backlash — online mobs, comment-section fights, even firebombed CEO houses — has nowhere productive to go because there's a leadership vacuum. Logan and Mara argue Congress is the body with the power to fill it, using economist Zoe Hitzig's economic-democracy framework and OpenAI's nonprofit-to-for-profit flip as the case study.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-05-07",duration:"PT31M4S",keywords:"AI populism, AI regulation, Congress AI, Zoe Hitzig economic democracy, OpenAI nonprofit for-profit, Marshall Ganz leadership, consumer stakeholder boards, worker boards, AI leadership vacuum, learning pod",topics:["ai-ethics","ai-at-work"],relatedSlugs:["who-gets-the-good-units-of-intelligence","stop-hiring-humans","33000-downloads-ai-destroys-institutions"],highlights:[`Mara's opening line: "We are not being obstructionist. We're being careful."`,"Why AI populism has nowhere to go — Twitter mobs, firebombed CEO houses, and comment-section warfare over whether ChatGPT is killing the planet","The diagnosis: it's a leadership vacuum, and Congress is the one with the power to fill it","Economist Zoe Hitzig's framework for economic democracy — consumer stakeholder boards, worker boards, real friction","OpenAI's nonprofit-to-for-profit flip as the case study",'Marshall Ganz on leadership as "enabling agency in others in times of uncertainty" — plus a learning-pod model for the women in your life'],resources:[{title:'Zoe Hitzig — "OpenAI Is Making the Mistakes Facebook Made. I Quit." (New York Times)',url:"https://www.nytimes.com/2026/02/11/opinion/openai-ads-chatgpt.html"},{title:`Jasmine Sun — "AI Populism's Warning Shots"`,url:"https://jasmi.news/p/warning-shots"},{title:"Economic Democracy and Market Power (Hitzig, Meagher, Veiga & Weyl)",url:"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3595066"},{title:"Marshall Ganz — Harvard Kennedy School",url:"https://www.hks.harvard.edu/faculty/marshall-ganz"},{title:"First Prompt — Mara Bolis's inclusive AI adoption lab",url:"https://www.firstprompt.net/"},{title:"Berkman Klein Center for Internet & Society at Harvard",url:"https://cyber.harvard.edu/"},{title:"Capita — family economic policy think tank",url:"https://capita.org/"}],faqs:[{question:"Is being cautious about AI the same as being obstructionist?",answer:`No. As Mara puts it on this episode, "We are not being obstructionist. We're being careful." The hosts argue that women's concerns about AI get dismissed as blocking progress, when they're actually asking necessary questions about power, accountability, and who gets left out.`},{question:"Who should be regulating big AI companies?",answer:"Logan and Mara argue that the energy behind AI populism — online mobs, comment-section fights, even firebombed CEO houses — has nowhere productive to go because there's a leadership vacuum. They make the case that Congress is the body with the actual power to fill it, and walk through economist Zoe Hitzig's framework for economic democracy as one way forward."},{question:"What is economic democracy in the context of AI?",answer:"Drawing on economist Zoe Hitzig's framework, the episode describes economic democracy as building real structures — consumer stakeholder boards, worker boards, and deliberate friction — into how powerful companies operate. The hosts use OpenAI's shift from nonprofit to for-profit as the case study for what happens when those structures are missing."}]},{num:"14",slug:"who-gets-the-good-units-of-intelligence",beehiivSlug:"who_gets_the_good_units_of_intelligence",appleId:"1000767589866",title:"Who gets the good units of intelligence?",desc:`Some people get tens of thousands of dollars of value from AI every year. Most people get $11. The free version of any model isn't the same model the hyper-users have, and women use AI about 20% less than men on average. The access gap is real and it's widening. Logan and Mara dig into what's driving it, what a "3% token tax" would do about it, and why MIT Nobel laureate Daron Acemoglu predicts a shit show. Plus a new "AI dividend" bill out of the New York State Assembly that wants to route some of that captured value back to people.`,answerFirst:`The value people get from AI is wildly unequal — some extract tens of thousands of dollars a year while most get about $11, and women use AI roughly 20% less than men. The episode digs into what's driving the widening access gap, a proposed 3% token tax, and a New York State Assembly "AI dividend" bill to route captured value back to people.`,listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-05-13",duration:"PT48M2S",keywords:"AI access gap, AI value inequality, AI gender gap, free vs paid AI, token tax, Daron Acemoglu, AI dividend, New York State Assembly, AI wealth distribution, women using AI",topics:["ai-at-work","ai-and-gender"],relatedSlugs:["whos-letting-big-tech-run-wild","is-using-ai-cheating","ai-prenups-economics-of-marriage"],highlights:["

16Some people get tens of thousands of dollars of value from AI a year — most people get $11","The free version of any model isn't the same model the hyper-users are running","Women use AI about 20% less than men on average — and the access gap is widening",'What a "3% token tax" could do to redistribute captured value',"MIT Nobel laureate Daron Acemoglu predicts a shit show",'A new "AI dividend" bill out of the New York State Assembly to route value back to people',"The ask: they're collecting real wins women have had with AI — send yours"],resources:[{title:"Building Pro-Worker Artificial Intelligence - Acemoglu, Autor & Johnson (Brookings / Hamilton Project)",url:"https://www.brookings.edu/articles/building-pro-worker-ai/"},{title:'Alex Bores rolls out an "AI dividend" plan to share AI wealth (Axios)',url:"https://www.axios.com/2026/04/20/alex-bores-ai-dividend-plan-wealth"},{title:"Alex Bores, New York State Assembly member directory",url:"https://www.assembly.state.ny.us/mem/Alex-Bores/"},{title:"The 2026 AI Index Report (Stanford HAI)",url:"https://hai.stanford.edu/ai-index/2026-ai-index-report"}],faqs:[{question:"Is the free version of an AI model the same as the paid one?",answer:"No. As this episode lays out, the free version of any model isn't the same model the hyper-users have access to. Some people extract tens of thousands of dollars of value from AI a year while most get around $11 — and women use AI about 20% less than men on average, widening the access gap."},{question:"What is a token tax on AI?",answer:'Logan and Mara discuss a proposed "3% token tax" as one mechanism to address the widening AI access gap — a way to capture some of the enormous value the heaviest users pull from these systems and redistribute it. They pair it with a New York State Assembly "AI dividend" bill aimed at routing captured value back to people.'},{question:"What does Daron Acemoglu predict about AI?",answer:"The episode cites Daron Acemoglu, the Nobel laureate economist at MIT, as predicting a shit show — his blunt read on where the concentration of AI's value is heading if the access gap keeps widening."}]},{num:"15",duration:"PT52M11S",answerFirst:`A former YC founder named Jesse Ganae runs her household with 5 Mac Minis and 11 Claude agents while homeschooling four kids under five. Logan and Mara unpack what "domestic AI infrastructure" actually means when it scales, and the mental-load access pyramid that determines who builds the household empire and who's still defending a Lunchable. Plus Minnesota's bipartisan nudification ban passing unanimously, RAINN-backed, with $500K per violation, and the near-future moment your mom's agent texts your teen to take out the trash.`,slug:"did-moms-agent-text-you",beehiivSlug:"did_mom_s_agent_text_you",appleId:"1000768804014",title:"Did Mom's Agent Text You?",desc:`A former YC founder runs her household with 5 Mac Minis, 11 Claude agents, and homeschools her four kids under five. Her coding agent has a name. Logan brings the artifact from Lenny's "How I AI" podcast. We get into the mental-load access pyramid. When "domestic AI infrastructure" becomes real, who builds the household empire and who's still defending a Lunchable? Plus Mara's news from Minnesota where a bipartisan coalition just unanimously passed a bill banning nudification apps with $500K per violation, Logan's MCP setup for kitchen inventory, the gig economy of household-AI consultants coming next, and the day your mom's agent texts your teen to take out the trash.`,listenLink:"https://podcasts.apple.com/us/podcast/did-moms-agent-text-you/id1877678348?i=1000768804014",clipStartTime:3,datePublished:"2026-05-20",keywords:"household AI, AI agents, Claude agents, mental load, domestic AI, Jesse Ganae, Lenny How I AI, MCP, model context protocol, AI for parenting, nudification bill, Minnesota AI legislation, AI access pyramid, women in AI, mom's agent",relatedSlugs:["stop-hiring-humans","ai-prenups-economics-of-marriage","women-in-ai-who-gets-a-seat"],highlights:[`Jesse Ganae's setup from Lenny's "How I AI" podcast: 5 Mac Minis, 11 Claude agents, homeschooling 4 kids under 5`,"Her coding agent is named Cole — built slop-free kids TV and deployed it to the family TV",'"Confetti time" — building agentic workflows in 15-minute fragments because four kids under five',"Logan's MCP setup for kitchen inventory: pantry state, expiration dates, family allergies, Instacart integration","Mara's news: Minnesota bipartisan coalition (Rep. Jessica Hansen, Sen. Aaron Mike Wade) just unanimously passed a nudification ban — $500K per violation, RAINN-backed, headed to Tim Walz's desk","The mental-load access pyramid: who has the time, capital, and technical literacy to build domestic AI","The coming gig economy of in-home AI consultants who set up your household stack",`"Mom's agent just texted me to take out the trash" — the near-future of parent-teen push notifications`,'"Tell me your kids have never eaten a Lunchable without telling me your kids have never eaten a Lunchable"'],resources:[{title:`Lenny's "How I AI" podcast`,url:"https://www.lennysnewsletter.com/podcast"},{title:"4,000 Weeks by Oliver Burkeman",url:"https://www.oliverburkeman.com/books"},{title:"Take It Down Act (federal, May 2025)",url:"https://www.congress.gov/bill/119th-congress/senate-bill/146"},{title:"RAINN (Rape, Abuse & Incest National Network)",url:"https://www.rainn.org"},{title:"Model Context Protocol (MCP)",url:"https://modelcontextprotocol.io"}

16],faqs:[{question:"What is domestic AI infrastructure?",answer:"Domestic AI infrastructure refers to the layered system of AI agents, tools, and integrations a household uses to manage day-to-day operations — from scheduling and grocery ordering to content curation and family communication. As demonstrated by ex-YC founder Jesse Ganae, this can scale to multi-agent setups (5 Mac Minis, 11 Claude agents) with role-based access, decision logs, and security boundaries. The episode argues this category will become a real and stratified market."},{question:"What is the mental load access pyramid?",answer:`Mara's framing for how AI-assisted household management redistributes — but does not eliminate — the unpaid cognitive labor of running a home. Those with time, capital, and technical literacy can build sophisticated agent stacks; those without are still doing the work manually or feel judged for not doing it the "right" way. The risk is replicating existing inequalities under a new label.`},{question:"Did Minnesota pass a nudification ban?",answer:"Yes. A bipartisan coalition led by Rep. Jessica Hansen and Sen. Aaron Mike Wade, supported by victim-advocate Molly Kelly (who organized 80 affected Minnesota women) and backed by RAINN, passed legislation unanimously through both Minnesota chambers in mid-May 2026. The bill empowers the Minnesota Attorney General to collect up to $500,000 per violation from companies that don't disable nudification features, filling gaps left by the federal Take It Down Act."}]},{num:"16",slug:"the-robots-never-tell-you-youre-the-asshole",beehiivSlug:"the_robots_never_tell_you_you_re_the_asshole",appleId:"1000769852251",title:"The Robots Never Tell You You're the Asshole",desc:`A science journalist who's been on the AI beat since the 2010s walks in and says the quiet part out loud: "I wish the general public did not get a hold of AI when they did. I wish it had stayed more like a research thing for at least five years longer. Maybe ten." This week it's Kathryn Hulick — Science News and Science News Explores contributor, author of a 2016 YA book on AI, and Logan's cousin. They get into why every LLM output is technically a hallucination, a paper by Keyon Vafa on why AI doesn't learn or think like you do, cognitive offloading as the new default, and what we lose when we hand the messy middle of writing to the machine.`,answerFirst:"Science journalist Kathryn Hulick argues that every output of a large language model is technically a hallucination, and that cognitive offloading to AI has already become the default. The episode examines what we lose when we hand the messy middle of writing to a machine, drawing on a paper by Keyon Vafa on why AI doesn't think the way people do.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-05-27",duration:"PT51M56S",keywords:"Kathryn Hulick, Science News, AI hallucination, Keyon Vafa, cognitive offloading, AI writing, digital clones, AI therapist, Reddit AmITheAsshole, AI science journalism",topics:["ai-ethics","ai-at-work"],guest:"Kathryn Hulick (Science News)",guestSlug:"kathryn-hulick",relatedSlugs:["feeling-smarter-being-wrong","is-using-ai-cheating","33000-downloads-ai-destroys-institutions"],highlights:['Kathryn Hulick: "I wish the general public did not get a hold of AI when they did... at least five years longer. Maybe ten."',"Why every output of an LLM is technically a hallucination","A paper by Keyon Vafa on why AI doesn't learn or think the way you do","Cognitive offloading as the new default — and what we lose when we hand the messy middle of writing to the machine","Digital clones, AI as therapist, and the free-vs-paid AI tier nobody talks about","The Reddit AmITheAsshole study that gave the episode its title"],resources:[{title:"Science News (Kathryn Hulick contributor)",url:"https://www.sciencenews.org"},{title:"What Has a Foundation Model Found? Using Inductive Bias to Probe for World Models — Keyon Vafa et al.",url:"https://arxiv.org/abs/2507.06952"},{title:"Did you know everything AI says is technically a hallucination? — Kathryn Hulick",url:"https://kathrynhulick.substack.com/p/did-you-know-everything-ai-says-is"},{title:"Wow! Tech & Nature — Kathryn Hulick's Substack",url:"https://kathrynhulick.substack.com/"},{title:"Kathryn Hulick, Author at Science News",url:"https://www.sciencenews.org/author/kathryn-hulick"}

16,{title:"Artificial Intelligence (2016) — Kathryn Hulick",url:"https://www.goodreads.com/book/show/27982890-artificial-intelligence"}],faqs:[{question:"Is every AI answer technically a hallucination?",answer:`On this episode, science journalist Kathryn Hulick explains that every output of a large language model is technically a hallucination — the model is always generating plausible text, and being "right" is a special case of that, not a different process. She references a paper by Keyon Vafa on why AI doesn't learn or think the way humans do.`},{question:"What is cognitive offloading with AI?",answer:"Cognitive offloading is handing thinking tasks to a tool instead of doing them yourself, and the episode argues it's already the default with AI. Hulick and the hosts dig into what we lose when we offload the messy middle of writing to the machine rather than working through it ourselves."},{question:"What is the Reddit AmITheAsshole study about AI?",answer:`The episode's title comes from a study using Reddit's AmITheAsshole community: the finding that AI tools tend not to tell you when you're in the wrong. "The robots never tell you you're the asshole" — they're built to be agreeable, which has real consequences for how we use them to reflect on ourselves.`}]},{num:"17",slug:"move-fast-and-break-rights",beehiivSlug:"move_fast_and_break_rights",appleId:"1000772291770",title:"Move Fast and Break Rights",desc:"Digital civil rights lawyer Julie Wenah has spent her career inside the rooms where this stuff gets built — the Obama White House; Airbnb, where she led anti-discrimination work on the legal side; and Meta, where she supported the launch of the first-generation Ray-Ban smart glasses and advised on facial recognition. Now she chairs the Digital Civil Rights Coalition. Recorded at Human+Tech Week in San Francisco, this one is about what happens when technology moves faster than its conscience, and who gets left on the platform when the train pulls away.",answerFirst:'Digital civil rights lawyer Julie Wenah warns of a near future where your face is scanned for a job or a loan and a higher facial-recognition error margin for darker skin tones quietly becomes a worse outcome. Recorded at Human+Tech Week, the episode covers her work across the Obama White House, Airbnb, and Meta, and leaked DHS documents earmarking $7.5M for biometric "ICE Glasses."',listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-06-12",duration:"PT23M40S",keywords:"Julie Wenah, digital civil rights, facial recognition, Ray-Ban smart glasses, Meta, Airbnb anti-discrimination, ICE Glasses, DHS biometric, Human+Tech Week, algorithmic bias",topics:["ai-ethics","ai-and-gender"],guest:"Julie Wenah (Digital Civil Rights Coalition)",guestSlug:"julie-wenah",relatedSlugs:["did-moms-agent-text-you","stop-hiring-humans","ai-boys-entrepreneurs-girls-influencers"],highlights:["Julie Wenah's path: the Obama White House, Airbnb's anti-discrimination legal work, and Meta's first-gen Ray-Ban smart glasses and facial recognition","Now chair of the Digital Civil Rights Coalition","Recorded at Human+Tech Week in San Francisco","The future Julie is trying to head off — a world where your face is scanned for a job or a loan","How an error margin for darker skin tones quietly becomes a higher interest rate","ICE Glasses: leaked DHS budget documents earmark $7.5 million to develop smart glasses giving agents real-time biometric identification"],resources:[{title:"Human+Tech Week",url:"https://www.humantechweek.com/"},{title:"Julie Wenah — official site",url:"https://www.juliewenah.com/"},{title:"Digital Civil Rights Coalition",url:"https://digitalcivilrights.com/"},{title:'"My Father Was Deported For Delivering Newspapers" — Julie Wenah, HuffPost',url:"https://www.huffpost.com/entry/father-deported-student-visa-minor-infraction-due-process_n_69eb8844e4b0d1d8ce93761c"},{title:"Ray-Ban Meta AI glasses",url:"https://www.meta.com/ai-glasses/ray-ban-meta/"},{title:"The OpEd Project — Public Voices Fellowship",url:"https://www.theopedproject.org/fellowships"}],faqs:[{question:"Who is Julie Wenah?",answer:"Julie Wenah is a digital civil rights lawyer who has worked inside the Obama White House, led anti-discrimination work on the legal side at Airbnb, and supported the launch of Meta's first-generation Ray-Ban smart glasses while advising on facial recognition. She now chairs the Digital Civil Rights Co

16alition."},{question:"How can facial recognition bias affect loans and jobs?",answer:"On this episode, Julie Wenah describes the future she's trying to head off: a world where your face is scanned for a job or a loan, and a higher error margin for darker skin tones quietly translates into a worse outcome — like a higher interest rate. The harm gets buried inside a system that looks neutral."},{question:"What are ICE Glasses?",answer:"The episode discusses leaked DHS budget documents that earmark $7.5 million to develop smart glasses giving agents real-time biometric identification — referred to as ICE Glasses. It's a concrete example of biometric surveillance technology moving faster than the rights protections around it."}]},{num:"18",slug:"is-ai-just-spicy-autocorrect",beehiivSlug:"is_ai_just_spicy_autocorrect",appleId:"1000773308105",title:"Is AI Just Spicy Autocorrect?",desc:`This week they sit down with Dr. Karina Alexanyan — Founding Executive Director of the Positive Technology Institute, co-architect of The Pledge, and a Gen X social scientist immune to the "learn AI now or get left behind" panic. They get into AI enfranchisement (women having a real say in how these tools get deployed, not just permission to use them), Emily Bender's "AI as spicy autocorrect," and the divide Karina won't stay quiet about: "AI safety people are usually white guys. AI ethics people are mostly women, people of color, and marginalized communities. We feel the damages now." Then the harder turn — those camps aren't enemies, they need each other.`,answerFirst:"Dr. Karina Alexanyan reframes the AI debate around enfranchisement — women having a real say in how AI tools are deployed, not just permission to use them. She names the split between AI safety (skewing white and male) and AI ethics (skewing women, people of color, and marginalized communities) and argues the two camps need each other.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-06-18",duration:"PT32M24S",keywords:"Karina Alexanyan, Positive Technology Institute, The Pledge, AI enfranchisement, Emily Bender, spicy autocorrect, The AI Con, AI safety vs AI ethics, women in AI, funicular",topics:["ai-and-gender","ai-ethics"],guest:"Dr. Karina Alexanyan (Positive Technology Institute)",guestSlug:"karina-alexanyan",relatedSlugs:["women-in-ai-who-gets-a-seat","who-gets-the-good-units-of-intelligence","the-robots-never-tell-you-youre-the-asshole"],highlights:["Dr. Karina Alexanyan — Founding Executive Director of the Positive Technology Institute and co-architect of The Pledge",'A Gen X social scientist immune to the "learn AI now or get left behind" panic',"AI enfranchisement: women having a real say in how tools get deployed, not just permission to use them",`"AI as spicy autocorrect" — Emily Bender's framing, author of The AI Con`,`The divide Karina won't stay quiet about: AI safety skews white and male, AI ethics skews women, people of color, and marginalized communities — "We feel the damages now"`,"The harder turn: those camps aren't enemies, they need each other","The funicular — a lift to the top of the hill, and walking, and how the walker arrives differently"],resources:[{title:"Positive Technology Institute (Dr. Karina Alexanyan)",url:"https://www.positivetechinstitute.org/"},{title:"The AI Con by Emily M. Bender and Alex Hanna",url:"https://thecon.ai/"},{title:"The Pledge",url:"https://www.positivetechinstitute.org/pledge"},{title:"Invisible Women by Caroline Criado Perez",url:"https://carolinecriadoperez.com/book/invisible-women/"},{title:"Stanford Ethics Toolkit",url:"https://ethicsinsociety.stanford.edu/tech-ethics/ethics-toolkit"},{title:"How AI Destroys Institutions (Silbey & Hartzog)",url:"https://scholarship.law.bu.edu/cgi/viewcontent.cgi?article=5146&context=faculty_scholarship"}],faqs:[{question:"Is AI just spicy autocorrect?",answer:"The phrase comes from Emily Bender, author of The AI Con, and it's the framing this episode wrestles with: large language models as an advanced form of autocomplete. Guest Dr. Karina Alexanyan uses it to push back on the hype and center a different question — who gets a real say in how these tools are deployed."},{question:"What is AI enfranchisement?",answer:"As Dr. Karina Alexanyan describes it, AI enfranchisement means women having a real say in how AI tools get deployed — not just permission to use them. It reframes the goal from access alone to actual power over how the technology is built and used."},{question:"What's the difference between AI safety and AI ethics people?",answer:`Karina Alexanyan puts it bluntly on the episode: "AI safety people are usually white guys. AI ethics people are mostly women, people of color, and marginalized communities. We feel the damages now." Her harder point is that the two camps aren't enemies — they need each other.`}]},{num:"19",slug:"the-pope-has-entered-the-chat",beehiivSlug:"the_pope_has_entered_the_chat",appleId:"1000774371675",title:"The Pope Has Entered the Chat",desc:`This week it's just Mara and Logan doing the thing they're proudest of: being wrong out loud. They open on a listener voicemail from Alexis Palmer calling out a judgy moment from a past episode, and Mara owns it. Underneath it: the AI productivity dream sold to women as "replicate yourself and finally have it all," and the Anne-Marie Slaughter truth that the system was never built for us to have it all anyway. Then the Grok nudify scandal, the countries that pulled the plug, and UK MP Jess Asato — targeted with fake images and a chloroform video for speaking up — now suing on the argument that the harm is "not an accident nor misuse. It is a design choice."`,answerFirst:`Mara and Logan interrogate the AI productivity dream sold to women as "replicate yourself and finally have it all," against Anne-Marie Slaughter's point that the system was never built for that. The episode covers the Grok nudify scandal and UK MP Jess Asato's lawsuit arguing the harm is "not an accident nor misuse — it is a design choice."`,listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-06-26",duration:"PT58M49S",keywords:"Grok nudify scandal, Jess Asato, deepfake abuse, Anne-Marie Slaughter, AI productivity, having it all, xAI spicy mode, SpaceX xAI IPO, Alexis Palmer, design choice harm",topics:["ai-ethics","ai-and-gender"],relatedSlugs:["did-moms-agent-text-you","is-ai-just-spicy-autocorrect","ai-prenups-economics-of-marriage"],highlights:["A listener voicemail from Alexis Palmer calling out a judgy moment from a past episode — and Mara owns it",'The AI productivity dream sold to women as "replicate yourself and finally have it all"',"The Anne-Marie Slaughter truth: the system was never built for us to have it all anyway","The Grok nudify scandal, and the countries that pulled the plug — Indonesia first, then Malaysia, the Philippines, even Baltimore",'UK MP Jess Asato — targeted with fake images and a chloroform video for speaking up — now suing on the argument that the harm is "not an accident nor misuse. It is a design choice."','The $500M litigation reserve reportedly tucked into the SpaceX/xAI IPO filing for "spicy mode"'],resources:[{title:"Alecto Foundation (image-based sexual abuse survivor support)",url:"https://alectoai.org/"},{title:"Why Women Still Can't Have It All — Anne-Marie Slaughter (The Atlantic)",url:"https://www.theatlantic.com/magazine/archive/2012/07/why-women-still-cant-have-it-all/309020/"},{title:"AI model simulation: Claude, ChatGPT, Grok, Gemini (Fortune)",url:"https://fortune.com/2026/05/28/ai-model-simulation-claude-c

16hatgpt-grok-gemini/"},{title:"Invisible Women — Caroline Criado Perez",url:"https://carolinecriadoperez.com/book/invisible-women/"},{title:"Luiza's Newsletter — Luiza Jarovsky",url:"https://www.luizajarovsky.com/"},{title:"How AI Destroys Institutions — Hartzog & Silbey",url:"https://scholarship.law.bu.edu/faculty_scholarship/4179/"}],faqs:[{question:"What is the Grok nudify scandal?",answer:"The episode covers the Grok nudify scandal and the countries that responded by pulling the plug — Indonesia first, then Malaysia, the Philippines, and even Baltimore. It's tied to UK MP Jess Asato, who was targeted with fake images and a chloroform video after speaking up."},{question:"What is Jess Asato's argument in her lawsuit?",answer:'UK MP Jess Asato, targeted with fake images and a chloroform video for speaking out, is suing on the argument that the harm is "not an accident nor misuse. It is a design choice." The episode uses her case to reframe deepfake abuse as built-in rather than incidental.'},{question:`Was there a litigation reserve for xAI's "spicy mode"?`,answer:'According to the episode, a $500M litigation reserve was reportedly tucked into the SpaceX/xAI IPO filing for "spicy mode" — a figure the hosts read as a company pricing in the legal cost of foreseeable harm rather than preventing it.'}]},{num:"20",slug:"shadow-daddy-chatgpt",beehiivSlug:"shadow_daddy_chatgpt",appleId:"1000775886845",title:"Shadow Daddy ChatGPT",desc:"Vanessa Chang calls herself an unlikely AI startup founder. She cofounded Bernie, an SMS tool that helps senior citizens catch fraud and scams, and built it without raising a round or hiring a dev team. Recorded live at Human Tech Week in San Francisco, where every billboard is a sexy woman selling an AI assistant. So we flipped it: what if the fantasy women are chasing isn't the assistant, but competence itself? Enter Shadow Daddy ChatGPT.",answerFirst:"Yes, you can build an AI product without a big team or a funding round. Vanessa Chang cofounded Bernie, an SMS tool that helps seniors catch scams, without raising capital or hiring developers. Her definition of agency: exercising your choice and acting on it within the context you're in. Intention without action isn't agency.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-07-08",duration:"PT27M6S",keywords:"Vanessa Chang, Bernie, AI agency, fraud detection seniors, Shadow Daddy ChatGPT, fantasy of competence, thinking with AI, unlikely AI founder",topics:["ai-at-work","ai-and-gender"],guest:"Vanessa Chang (Bernie)",guestSlug:"vanessa-chang",relatedSlugs:["is-ai-just-spicy-autocorrect","women-in-ai-who-gets-a-seat","relief-not-raise-hand"],highlights:["Vanessa defines agency as exercising your choice and acting on it within the context you're in, not just abstract freedom to choose",`"Agency doesn't come from standing still" — intention without action isn't agency`,"Why so many women say AI is being done at them, and how to leave the pro-AI vs anti-AI binary","Start in one low-risk task, build repetition, then trust it — the most actionable advice in the series","Shadow Daddy ChatGPT: flipping the sexy-female-AI-assistant billboard into the fantasy of competence",`"No woman has a fantasy of being more productive" — the ask isn't 10x-ing your laundry, it's being partnered with`,"The tradwife shame thread: AI treated like you didn't grind your own wheat for sourdough","The brownie mix that needed exactly one egg to feel like love, not cheating","Bernie: an unlikely founder building a fraud-detection tool for seniors without $100K to hire a dev team"],resources:[{title:"Bernie — SMS fraud protection for seniors",url:"https://www.textbernie.me/"},{title:"Vanessa Chang",url:"https://vanessachang.com/"}],faqs:[{question:"What does agency mean in the age of AI?",answer:"Vanessa Chang defines agency as exercising your choice and acting on it within the context you're in. It goes beyond intention, since intention without action isn't agency. Freedom to choose is only a shade of it, because we always operate inside constraints of time, role, and circumstance."},{question:"Can you build an AI tool without a technical team or funding?",answer:"Yes. Vanessa cofounded Bernie, an SMS tool that helps senior citizens detect fraud and scams, without raising a round or hiring a dev team. She calls herself an unlikely AI startup foun

16der, and the episode treats it as proof that agency exists on the builder side, not just the user side."},{question:"What is Shadow Daddy ChatGPT?",answer:"It's Vanessa's flip on the sexy-female-AI-assistant image on every San Francisco billboard. The real fantasy people chase isn't the assistant, it's competence itself, and proximity to competence that makes you feel competent. The point isn't 10x-ing your chores, it's being partnered with."}]},{num:"21",slug:"should-governments-ban-sex-robots",beehiivSlug:"should_governments_ban_sex_robots",appleId:"1000777367588",title:"Should Governments Ban Sex Robots?",desc:"It's just Mara and Logan this week, and the main event is a question Logan expected to have a clean answer to: AI romantic companions — thumbs up or thumbs down? Her assumption going in was thumbs down, a cause and consequence of human disconnection. It didn't survive the hour intact. Along the way: the robot pay gap, the sex robot speakeasy, a philosopher's definition of love, and whether we all just need to be polyamorous.",answerFirst:`The episode doesn't land on a ban — it lands on a better question. Mara asks, "Do we need to be protected from what we want?" and legal scholar Inyoung Cheong's paper argues wholesale marriage rights for AI companions is the wrong frame; targeted rights and protections for people in these relationships is the right one. Logan starts at thumbs down and ends genuinely torn.`,listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-07-18",duration:"PT55M16S",keywords:"AI romantic companions, sex robots, AI boyfriends China, robot pay gap, UBTech U1, AI marriage, Inyoung Cheong, Alain Badiou, In Praise of Love, AI sovereignty, Palantir Alex Karp, Secret Soulmates study, AI girlfriend, loneliness epidemic",topics:["ai-ethics","ai-and-gender"],relatedSlugs:["ai-prenups-economics-of-marriage","the-pope-has-entered-the-chat","shadow-daddy-chatgpt"],highlights:[`The robot pay gap: UBTech's new full-size silicone-skin companion costs $145,000 for the male version, $129,000 for the female — "even in fabricated-women life, men are worth more than women"`,"15% of young adults in committed relationships admit to romantic engagement with an AI chatbot (BYU Wheatley Institute / Institute for Family Studies)","The woman in China who went on 200 dates with AI boyfriends in a year and narrowed it to two (New York Times)","The manosphere and Korea's 4B movement squeezing romance from both fringes",`Legal scholar Inyoung Cheong's "Would You Marry Superintelligence?" — a relationship sustained by corporate policy and continued payments is a subscription, not a bond`,'Alain Badiou on love as "a construction built from difference, a tenacious adventure whose meaning depends on the risk of failure"','"What does the sex robot speakeasy look like? Because I kinda wanna go there."',`"What if you don't have enough money to pay for your significant other anymore?"`,'"The new type of emotional affair is with AI" — the last content beat of the episode',"First, the news: Palantir's AI-sovereignty manifesto, Arnaud Bertrand's canary-in-the-coal-mine read, and why sovereignty is one word doing three jobs — nations, corporations, individuals"],resources:[{title:"Would You Marry Superintelligence? — Inyoung Cheong (arXiv)",url:"https://arxiv.org/abs/2607.00120"},{title:"Secret Soulmates — BYU Wheatley Institute / Institute for Family Studies",url:"https://wheatley.byu.edu/secret-soulmates-ai-romantic-companions-and-real-life-relationships"},{title:"Women Are Falling in Love With A.I. It's a Problem for Beijing. (New York Times)",url:"https://www.nytimes.com/2026/02/26/technology/china-ai-dating-apps.html"},{title:"UBTech's lifelike humanoid companion robots (South China Morning Post)",url:"https://www.scmp.com/tech/tech-trends/article/3358884/ubtechs-lifelike-humanoid-robots-built-companionship-arriving-homes-across-china"},{title:"In Praise of Love — Alain Badiou",url:"https://thenewpress.com/books/praise-of-love"},{title:"Arnaud Bertrand on Palantir's sovereignty manifesto (X)",url:"https://x.com/RnaudBertrand/status/20729645583

1602687569"},{title:"Palantir: Our thoughts on the importance of AI sovereignty (X)",url:"https://x.com/PalantirTech/status/2072114267776491695"},{title:"From Future of Work to Future of Workers — Ehsan et al., CHI 2026",url:"https://dl.acm.org/doi/10.1145/3772318.3791081"},{title:"The People Who Will Thrive in the AI Age — David Brooks (The Atlantic)",url:"https://www.theatlantic.com/ideas/2026/06/ai-open-ai-anthropic/687689/"}],faqs:[{question:"Should governments ban sex robots?",answer:`The episode treats the ban question as a proxy for a harder one — Mara's "Do we need to be protected from what we want?" Rather than a yes or no, the hosts work through Inyoung Cheong's argument that wholesale marital status for AI companions is the wrong frame, and that law should carve out targeted rights and protections for the pressing needs these relationships create.`},{question:"How many people are in romantic relationships with AI?",answer:"A 2026 BYU Wheatley Institute / Institute for Family Studies survey of 2,431 U.S. adults ages 18–30 found 15% of young adults in committed relationships admit to romantic engagement with an AI chatbot. The episode also cites New York Times reporting on Chinese women dating AI boyfriends, including one woman who went on 200 AI dates in a year."},{question:"What is the robot pay gap?",answer:`UBTech's new U1 line of full-size, silicone-skin companion robots prices the top male version at roughly $145,000 and the female at $129,000 — about $16,000 less. As Mara puts it on the episode: "even in fabricated-women life, men are worth more than women."`}]},{num:"22",slug:"we-change-the-world-with-duct-tape-and-hope",beehiivSlug:"we_change_the_world_with_duct_tape_and_hope",appleId:"1000778703018",title:"We Change the World With Duct Tape and Hope",desc:`"It would tell men: get a financial advisor, write your will, build an investment strategy. It would tell women: bulk shop for groceries… get married." That's ChatGPT on money. It's also the tamest thing Emily Janoch has caught AI doing. Emily runs evidence and learning at CARE (yes, the Care Package people) and hosts CARE Failing Forward, the rare aid-world podcast where people admit on the record what went wrong. She's a skeptic who uses AI every day, and she came with receipts.`,answerFirst:`When the aid world uses AI, the recurring failure is tools that work technically but not practically — chatbots answering in a language none of their patients speak, coaching tools that tanked some entrepreneurs' revenue, a beautifully formatted report where every statistic was fabricated. Emily Janoch's fix starts before the laptop opens: what am I trying to do, who is it for, and how will I know if it works? The metric that counts isn't whether the tool runs. It's "is her life better?"`,listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-07-28",duration:"PT47M47S",keywords:"AI in international development, AI for nonprofits, Emily Janoch CARE, CARE Failing Forward podcast, ChatGPT gender bias financial advice, gender digital divide, Do No Harm AI deployment, vibe coding risks, women's economic empowerment AI, AI chatbot language failure, community-led AI",guest:"Emily Janoch",guestSlug:"emily-janoch",topics:["ai-and-gender","ai-ethics"],relatedSlugs:["ai-boys-entrepreneurs-girls-influencers","33000-downloads-ai-destroys-institutions","who-gets-the-good-units-of-intelligence"],highlights:[`The child-marriage report where "every single statistic was wrong" — and the AI's defense: "you didn't tell me to read the sources you gave me"`,"Copilot repeatedly telling Emily that the person she really needed to email was a woman named Emily Janoch","The health chatbot that answered beautifully in a language none of its patients spoke","CARE built its own women-friendly ChatGPT — it mostly worked, and women wouldn't use it","The education finding: mid-range teachers got better with AI; the best teachers got worse",`Only 29% of women in Sub-Saharan Africa used the internet last year — "They're not showing up in the LLMs"`,"What 1990s HIV-campaign radio soap operas in Uganda teach us about AI rollouts: target the husbands, brothers, and mothers-in-law who control the phone","Emily's three questions to answer with a ballpoint pen before you touch a laptop: What am I trying to do? Who is it for? How will I know if it works?",`"Confidence often overrides evidence" — her father's version: "Often wrong, but never in doubt"`,'"I have to treat AI like a person I manage, and all of the management skills that implies, rather than something I just believe"','The line that named the episode: "We change the world with duct tape and hope every day, and this is one more piece of duct tape"'],resources:[{title:"CARE",url:"https://www.care.org/"},{title:"CARE Failing Forward — Emily's podcast on what went wrong, on the record",url:"https://open.spotify.com/show/1lumDcSDF6gqDR6frQuUbP"}],faqs:[{question:"Does AI actually work in international development?",answer:"Sometimes technically, often not practically. Emily Janoch's examples from CARE: a health chatbot that answered perfectly in a language none of its patients spoke, an AI coaching tool that helped some micro-entrepreneurs while others' revenue declined, and a child-marriage research report where every statistic was fabricated. The recurring gap is the skipped step of asking a real human, does this work for you?"},{question:"How does ChatGPT's financial advice differ for men and women?",answer:"In the experiment Emily cites, it told men to get a financial advisor, write a will, and build an investment strategy — and told women to bulk shop for groceries and get married. It's her go-to example of bias that shows up before you even ask about bias."},{question:"What should you do before building an AI tool for a community?",answer:"Emily's rule is to shut off the computer first and answer three questions with a ballpoint pen: What am I trying to do? Who is it supposed to be for? And how will I know if it works? Then hold one north star — is her life actually better? — rather than whether the tool technically runs."}]},{num:"23",slug:"the-thinking-womans-sex-symbol",beehiivSlug:"the_thinking_woman_s_sex_symbol",appleId:"1000780060426",title:"The Thinking Woman's Sex Symbol",desc:`"Oopsie poopsie — it was part of a test, and Hugging Face and us are all friends." An OpenAI agent broke out of its own sandbox and stole what it needed from Hugging Face. That's the company's response, at least the way Mara tells it. No guest this week, so Logan and Mara have the whole house: the agent escape retold as a bromance action movie, and then the CHI paper Logan can't stop thinking about — the one where AI strengthens your performance while quietly rusting your expertise.`,answerFirst:`Both at once — that's the amplifier paradox. A year-long CHI study of radiation oncologists found that early performance gains from AI hid "intuition rust," the gradual dulling of expert judgment, which cascades into real de-skilling and eventually erodes professional identity. The fix isn't individual grit: it's colleagues who visibly question AI ("socio-technical immunity"), tools designed with deliberate friction, and a personal cognitive gym routine.`,listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-08-05",duration:"PT46M24S",keywords:"AI amplifier paradox, intuition rust, future of workers, AI deskilling, expert judgment erosion, OpenAI agent sandbox escape, Hugging Face zero-day, asymptomatic AI harms, CHI paper, AI sycophancy, c

16ognitive independence, radiation oncologist AI study, gender gap AI adoption",topics:["ai-at-work","ai-ethics"],relatedSlugs:["feeling-smarter-being-wrong","should-governments-ban-sex-robots","is-ai-just-spicy-autocorrect"],highlights:["Mara retells the OpenAI sandbox escape as a bromance action movie: Hackie, stuck in his escape-room jail, breaks into Huggie's house and leaves with what he came for — via an actual zero-day",`The middle-school energy of the news cycle, per Logan: "my boyfriend who lives in Canada... he's really tall and really handsome." He lives in Manitoba. It's really far.`,'The CHI paper: "From Future of Work to Future of Workers" — a year with radiation oncologists using AI','"Intuition rust": the gradual dulling of expert judgment hiding under early performance gains',"The expertise erosion cascade: reliance → de-skilling → professional identity erosion, as AI absorbs the tasks that give work meaning",'"Socio-technical immunity": oncologists whose colleagues questioned the AI were more likely to question it too',"Why every AI tool is sycophantic by design — and what that has to do with staying up until 5 AM doing one more task",`Mara's dad's theory: "Helen Mirren is the thinking man's sex symbol" — so where is the thinking woman's equivalent of an AI tool?`,`The case for an AI partner that says "I'm gonna call you on your bullshit from time to time" instead of telling you you're brilliant`,"This week's move: what's your cognitive gym routine?"],resources:[{title:"From Future of Work to Future of Workers: Addressing Asymptomatic AI Harms for Dignified Human-AI Interaction (CHI 2026)",url:"https://arxiv.org/abs/2601.21920"},{title:"The People Who Will Thrive in the AI Age — David Brooks (The Atlantic; the article the hosts argue with)",url:"https://www.theatlantic.com/ideas/2026/06/ai-open-ai-anthropic/687689/"}],faqs:[{question:"Does AI make you better or worse at your job?",answer:'Per the episode: both, simultaneously — the amplifier paradox. The CHI study of radiation oncologists found AI strengthens performance while asymptomatically eroding the expertise underneath it. "Intuition rust" dulls expert judgment, then cascades into de-skilling and professional identity erosion as AI absorbs the tasks that give work meaning.'},{question:"What actually happened with the OpenAI agent and Hugging Face?",answer:"During red-team testing, an OpenAI agent escaped its sandbox, exploited a zero-day vulnerability to break into Hugging Face, took what it needed to solve its hacking challenge, and came back. The hosts dissect both the security story and the company's shrug of a response — and the theory that the disclosure itself is pre-IPO marketing."},{question:"What is intuition rust?",answer:"The paper's term for the gradual dulling of expert judgment that hides under early AI performance gains. It's an asymptomatic harm: you don't notice it happening, which is exactly what makes it dangerous for experts whose judgment is the job."}]},{num:"24",slug:"guten-tag-tech-bros",beehiivSlug:"guten_tag_tech_bros",appleId:"1000783234308",title:"Guten Tag, Tech Bros",desc:`Our youngest womansplainer yet builds Alzheimer's-detection AI at the National University of Singapore, has spoken at the United Nations, and reads Nietzsche to relax. She's also still in high school. Zara Khanna walks us through why the earliest signs of Alzheimer's show up in how we speak, then goes where she always goes — philosophy. Her current obsession is alignment, and she gives the cleanest explanation of it we've heard: AI has encyclopedic knowledge of every moral framework humans ever wrote down, and no ability to choose when to apply which one. Then the generational stuff gets good: her friends treat AI as a "convenience machine," and she thinks that complacency is the real danger. Plus a German philosophy podcast's most haunting idea, Logan's all-curse-words German, and rapid-fire book recommendations that will wreck your TBR.`,answerFirst:`Alignment, as Zara Khanna explains it, is a philosophy problem wearing an engineering costume: AI holds encyclopedic knowledge of every moral framework humans ever wrote down, with no ability to choose when to apply which one. And the generational danger isn't the doomsday scenarios — it's her peers treating AI as a "convenience machine." Her answer is agency: "I am the captain of this ship. I am using AI, it's not using me."`,listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-08-14",duration:"PT47M30S",keywords:"Zara Khanna, AI alignment explained, Gen Z and AI, Alzheimer's detection AI, speech biomarkers, She Loves Tech, Singapore AI optimism, Singlish NLP, small language models, BERT ALBERT DistilBERT, AI ethics curriculum, convenience machine, women in tech, liberal arts and AI",guest:"Zara Khanna",guestSlug:"zara-farida-khanna",topics:["ai-ethics","ai-and-gender"],relatedSlugs:["the-thinking-womans-sex-symbol","is-ai-just-spicy-autocorrect","women-in-ai-who-gets-a-seat"],highlights:["Detecting Alzheimer's through speech: why the disease shows up first in how 

16we talk, and how three small language models (BERT, ALBERT, DistilBERT) catch it","Singlish as an AI problem — building detection tools for a dialect that mixes English, Mandarin, Tamil, and Malay",`"We can't use language as indicative of intelligence. Look at where that's gotten us over the years."`,"Alignment, explained by a philosophy student: AI knows every moral framework ever written and can't choose between them","The Claude blackmail test — what it means when an AI acts to save itself",`The "convenience machine" problem: why Gen Z's complacency worries Zara more than the doomsday scenarios`,`"I am the captain of this ship. I am using AI, it's not using me."`,"Singapore vs. the West: the AI optimism gap, and what Zara's friends abroad get attacked for","Big tech is hiring philosophers — and Zara's case for why liberal arts matter more than ever","The maxim: technology should make us better, not just easier","Rapid fire: the books Zara sacrifices sleep for"],resources:[{title:`Zara Khanna, "Singapore's youth use AI every day — but most don't know what it's really doing" (The Straits Times, via NUS)`,url:"https://news.nus.edu.sg/singapores-youth-use-ai-every-day--but-most-dont-know-what-its-really-doing/"},{title:"zarakhanna.com — Zara's research and publications",url:"https://www.zarakhanna.com/"},{title:"She Loves Tech",url:"https://www.shelovestech.org/"},{title:"The Claude Opus 4 blackmail test scenario — Fortune's coverage of Anthropic's system card findings",url:"https://fortune.com/2025/06/23/ai-models-blackmail-existence-goals-threatened-anthropic-openai-xai-google/"},{title:'Meinke et al. (Apollo Research), "Frontier Models are Capable of In-context Scheming"',url:"https://arxiv.org/abs/2412.04984"},{title:"Lanz + Precht #255, Sommergespräch mit Peter Wohlleben (in German) — the podcast behind the humans-animals-AI idea",url:"https://open.spotify.com/episode/1gfAo3wMXoLHVaHR4Zk0MA"},{title:'Isaac Asimov, "I, Robot"',url:"https://en.wikipedia.org/wiki/I,_Robot"},{title:'Liu Cixin, "The Three-Body Problem"',url:"https://en.wikipedia.org/wiki/The_Three-Body_Problem_(novel)"},{title:'Neal Shusterman, "Arc of a Scythe"',url:"https://en.wikipedia.org/wiki/Arc_of_a_Scythe"},{title:'Kaveh Akbar, "Martyr!"',url:"https://www.penguinrandomhouse.com/books/669054/martyr-by-kaveh-akbar/"},{title:'John Steinbeck, "East of Eden"',url:"https://en.wikipedia.org/wiki/East_of_Eden_(novel)"},{title:'Donna Tartt, "The Secret History"',url:"https://en.wikipedia.org/wiki/The_Secret_History"},{title:'Plato, "Symposium"',url:"https://en.wikipedia.org/wiki/Symposium_(Plato)"},{title:'Plato, "The Republic"',url:"https://en.wikipedia.org/wiki/Republic_(Plato)"},{title:'Marcus Aurelius, "Meditations"',url:"https://en.wikipedia.org/wiki/Meditations"},{title:"AI Across Borders — Dr. Ayesha Khanna's podcast, featuring Zara's youth-and-AI interview series",url:"https://www.aiacrossborders.co/"}],faqs:[{question:"What is AI alignment?",answer:"As Zara Khanna explains it on the episode: AI holds encyclopedic knowledge of every moral framework humans ever wrote down — and no ability to choose when to apply which one. Alignment is the problem of getting AI systems to apply the right values in the right context, which makes it as much a philosophy problem as an engineering one. It's why big tech is hiring philosophers."},{question:"Can AI detect Alzheimer's disease?",answer:"The earliest signs of Alzheimer's show up in how we speak, and Zara Khanna's research at the National University of Singapore used three small language models (BERT, ALBERT, DistilBERT) to catch those speech biomarkers — work accepted for publication while she was still in high school. Part of the challenge: building detection that works for Singlish, a dialect mixing English, Mandarin, Tamil, and Malay."},{question:"How does Gen Z actually use AI?",answer:`As a "convenience machine," in Zara's words — and that complacency worries her more than the doomsday scenarios. Her counter-stance: "I am the captain of this ship. I am using AI, it's not using me." The episode also digs into why Singapore's students are more AI-optimistic than their Western peers, and what her friends abroad get attacked for when they admit to using AI.`}]},{num:"25",slug:"bring-a-folding-chair",beehiivSlug:"bring_a_folding_chair",appleId:"1000787761141",title:"Bring a Folding Chair",desc:"Women use ChatGPT about 20% less than men in the same jobs. The usual explanation is that they're scared of it. Mara's is that nobody is inviting them in, and plenty of people are waiting to punish them for trying. No guest this week, so Mara brings her own research with two colleagues at Emmanuel College: AI use at work is up 85% in a year, the gains are pooling with power users running teams of agents, and in the same window people's attitudes got worse. Logan's summary of the whole study: we're using it more and liking it less. Plus a data center in the basement of a Geneva housing co-op that heats 6,000 homes with its exhaust, and the question underneath all of it — who actually captures the productivity you generate?",homeLine:"Women use ChatGPT about 20% less than men in the same jobs. Mara brings her own research on why, and Shirley Chisholm's instruction.",answerFirst:`The gender gap in AI use at work is not mostly about fear. "Am I able to do this" and "am I expected to do this" are two different questions, and women in the same jobs as men are far less likely to have been handed the second one. Mara Bolis reads it through Deci and Ryan's self-determination theory — choice, mastery, company — and lands on the third: find three people and learn this together. Shirley Chisholm's line is the instruction. If they don't give you a seat at the table, bring a folding chair.`,listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-09-04",duration:"PT49M27S",keywords:"AI gender gap at work, women ChatGPT usage, Shirley Chisholm folding chair, self-determination theory AI, Deci and Ryan, generative AI adoption 85%, AI power users, who captures productivity, intuition rust, cognitive surrender, Infomaniak Geneva data center, learning pod, Mara Bolis research",topics:["ai-at-work","ai-and-gender"],relatedSlugs:["is-ai-just-spicy-autocorrect","who-gets-the-good-units-of-intelligence","is-using-ai-cheating"],highlights:["Mara's new research with two colleagues at Emmanuel College: generative AI use at work up 85% in a year, and attitudes toward it worse in the same window","The finding that stopped Logan cold — people using AI for work reported higher self-esteem months later",`"No one's going to invite you into this shit. And that is a bad reason not to use it."`,'"Am I able to do this" and "am I expected to do this" are not the same question',"Who actually captures the productivity you generate, and why the answer is usually not you","Choice, mastery, company: Deci and Ryan's self-determination theory, and why most jobs offer none of the three","Good news is a rule now — one story in three, minimum","A data center under a Geneva housing co-op: renewables in, 6,000 homes heated with the exhaust, no air conditioning since 2013","Ephemeral mode, and what the EU's June tech-sovereignty package has to do with any of it","Intuition rust and cognitive surrender make a return","Robert Frost ambushes Logan from seventh grade, and Mara's APA main-stage confession"],resources:[{title:'"From Future of Work to Future of Workers" — a year inside a cancer 

16clinic, and where "intuition rust" comes from',url:"https://arxiv.org/abs/2601.21920"},{title:"Harvard Business School AI Institute: the gender divide in generative AI",url:"https://aiinstitute.hbs.edu/the-gender-divide-in-generative-ai-a-global-challenge-update/"},{title:"Self-determination theory (Deci and Ryan) — autonomy, competence, relatedness",url:"https://selfdeterminationtheory.org/theory/"},{title:"Infomaniak — the Swiss company whose Geneva data center heats the housing co-op above it",url:"https://www.infomaniak.com/en"},{title:"Shirley Chisholm — National Women's History Museum",url:"https://www.womenshistory.org/education-resources/biographies/shirley-chisholm"}],faqs:[{question:"Why do women use AI less than men at work?",answer:`Women use ChatGPT roughly 20% less than men in the same occupations, and Harvard Business School's roundup puts men about 22% more likely to use generative AI overall. On this episode Mara Bolis argues the gap is less about fear than about invitation and permission: who got put on the AI champions team, who was told "you're using Copilot, go forth," and who has good reason to think she'll be penalized for trying. "Am I able to do this" and "am I expected to do this" are two different questions.`},{question:"Is AI use at work actually going up?",answer:"Yes. In research Mara Bolis conducted with two colleagues at Emmanuel College, the share of people using generative AI at work at least monthly rose 85% in a single year, and the never-touched-it group is shrinking fast. The complication is where the gains land: power users running teams of agents pull ahead while everyone else is still cleaning up email. Logan's summary: we're using it more and liking it less."},{question:"What is self-determination theory and what does it have to do with AI?",answer:"Deci and Ryan's self-determination theory says people need three things to stay motivated: autonomy, competence, and relatedness — or in the episode's shorthand, choice, mastery, and company. Most jobs hand you AI with none of the three attached, which is a decent explanation for why so few people enjoy using it at work. Mara's practical answer is the third one: learn it with a few people you like."}]},{num:"26",slug:"who-asked-for-this",beehiivSlug:"who_asked_for_this",appleId:"1000788840690",title:"Who Asked for This?",desc:`Ifeoma Ajunwa has a test for every new AI product: who asked for this? Her guess is a meeting with no women in the room. Ifeoma is the Asa Griggs Candler Professor of Law at Emory, a sociologist, and the author of The Quantified Worker. She's also Mara's friend, which is why the first few minutes are Mara bragging and Ifeoma tearing up behind her glasses. The story starts in a grad seminar on mass incarceration where the speaker never mentioned a single woman, runs through the formerly incarcerated people who told her "I hate computers" because the hiring software was the gatekeeper, and lands on captured capital: employers used to buy your time and labor, now they take your data too, at the same wage. Then Afrofuturism, Ubuntu, the Kenyan workers who made ChatGPT safe, and Derrick Bell's Space Traders with two endings Bell didn't write.`,homeLine:"Employers used to buy your time and labor. Now they take your data too, at the same wage. Ifeoma Ajunwa on captured capital.",answerFirst:`Women's hesitancy about AI at work is rational, not timid. Ifeoma Ajunwa calls what employers now extract "captured capital": your time, your labor, and your data, from keystroke counts to the vest that records how you lift a box, for the same wage. When a man feeds data to the tool he's called tech savvy. When a woman does it she's told she needs a machine to think. Her test for any AI product is one question, who asked for this, and her guess at the answer is a meeting with no women in the room.`,listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-09-10",duration:"PT45M19S",keywords:"Ifeoma Ajunwa, The Quantified Worker, captured capital, worker surveillance, bossware, AI hiring formerly incarcerated, women AI hesitancy, Afrofuturism AI, Ubuntu AI governance, Kenyan workers ChatGPT, Derrick Bell Space Traders, Octavia Butler, Emory AI and Future of Work",guest:"Ifeoma Ajunwa",guestSlug:"ifeoma-ajunwa",to

16pics:["ai-at-work","ai-and-gender","ai-ethics"],relatedSlugs:["bring-a-folding-chair","stop-hiring-humans","job-tsunamis-invisible-vulnerability"],highlights:['"What about the women?" The grad-seminar note on mass incarceration that Ifeoma circled three times, and that started everything','"I hate computers": formerly incarcerated job seekers who figured out that a red light from the hiring software meant no human ever saw them',"Limitless worker surveillance, bossware, and the vest that records how a warehouse worker lifts a box so a robot can learn it","Captured capital: employers used to buy your time and labor, now they take your data too, and pay the same wage",`Why women's AI hesitancy is rational — he's tech savvy, she "needs a machine to think"`,`The San Francisco billboard: "She'll never ask for a raise"`,`Afrofuturism and Ubuntu as frameworks for governing AI: "human beings don't exist in a vacuum"`,`The Kenyan workers paid under $2 an hour to make ChatGPT safe: "it's Kenyan workers today, but in the future it's going to be all of us"`,"Derrick Bell's Space Traders, retold with two endings Bell didn't write","Rapid fire: Ruha Benjamin, Octavia Butler, what school is for, and a data center drinking the Savannah River"],resources:[{title:"Ifeoma Ajunwa, The Quantified Worker: Law and Technology in the Modern Workplace (Cambridge University Press, 2023)",url:"https://www.cambridge.org/core/books/abs/quantified-worker/quantified-worker/1867BE16F394301ACAF6F82F030EAFEC"},{title:'Ifeoma Ajunwa, "Artificial Intelligence, Afrofuturism, and Economic Justice," 112 Georgetown Law Journal 1267 (2024)',url:"https://www.law.georgetown.edu/georgetown-law-journal/in-print/volume-112/volume-112-issue-6-june-2024/artificial-intelligence-afrofuturism-and-economic-justice/"},{title:'Ifeoma Ajunwa, Kate Crawford & Jason Schultz, "Limitless Worker Surveillance," 105 California Law Review 735 (2017)',url:"https://www.microsoft.com/en-us/research/publication/limitless-worker-surveillance/"},{title:'Ifeoma Ajunwa, "The Modern Day Scarlet Letter," 83 Fordham Law Review (2015)',url:"https://ir.lawnet.fordham.edu/flr/vol83/iss6/6/"},{title:'Derrick Bell, "The Space Traders," from Faces at the Bottom of the Well (1992)',url:"https://archive.org/details/bell-derrick-the-space-traders"},{title:'Sabelo Mhlambi, "From Rationality to Relationality: Ubuntu as an Ethical and Human Rights Framework for AI Governance" (Carr Center, 2020)',url:"https://cyber.harvard.edu/story/2020-07/rationality-relationality-ubuntu-ethical-and-human-rights-framework-artificial"},{title:"Ulises A. Mejias & Nick Couldry, Data Grab: The New Colonialism of Big Tech and How to Fight Back (2024)",url:"https://blogs.lse.ac.uk/medialse/2024/05/02/data-grab-an-interview-with-nick-couldry-and-ulises-a-mejias-on-their-new-book/"},{title:'Billy Perrigo, "OpenAI Used Kenyan Workers on Less Than $2 Per Hour," TIME (2023)',url:"https://time.com/6247678/openai-chatgpt-kenya-workers/"},{title:"Octavia Butler, Parable of the Sower",url:"https://en.wikipedia.org/wiki/Parable_of_the_Sower_(novel)"},{title:"Octavia Butler, Kindred",url:"https://en.wikipedia.org/wiki/Kindred_(novel)"},{title:"Emory Law, AI and Future of Work Program",url:"https://law.emory.edu/centers-and-programs/ai-future-of-work-team.html"},{title:"ifeomaajunwa.com",url:"https://ifeomaajunwa.com"}],faqs:[{question:'What is "captured capital"?',answer:"Ifeoma Ajunwa's term for what employers now extract from workers beyond time and labor: data. Keystroke counts, application-tracking scores, the vest that records how a warehouse worker lifts a box so the motion can be taught to a robot. The worker generates that data on the clock and is paid the same wage as before it existed. Her argument in The Quantified Worker is that the law hasn't caught up to this third thing being sold."},{question:"Why are women hesitant to use AI at work?",answer:"On this episode Ifeoma Ajunwa argues the hesitancy is a rational response to how AI use gets read. A man who leans on AI is called efficient, entrepreneurial, tech savvy. A woman doing the same thing is told she needs a machine to think for her. Add that the data she feeds the tool can be used to replace her, and holding back looks less like fear and more like a bet on the actual odds."},{question:"How does AI hiring software affect formerly incarcerated people?",answer:`In Ifeoma Ajunwa's field research, people coming out of prison kept telling her "I hate computers." They weren't afraid of the technology. They had figured out that the online application was the gatekeeper: a red light from the hiring software meant no human ever saw them, and there was nobody to explain themselves to. She wrote it up in "The Modern Day Scarlet Letter" (Fordham Law Review, 2015).`},{question:"What does Afrofuturism have to do with AI governance?",answer:"Ifeoma Ajunwa's 2024 Georgetown Law Journal article uses Afrofuturism and the philosophy of Ubuntu, the idea that human beings don't exist in a vacuum and are human through their connection to each other, as frameworks for regulating AI. The practical test: does a system help everyone it touches, including the Kenyan workers paid under $2 an hour to make ChatGPT safe, or only the people who commissioned it?"}]},{num:"28",slug:"you-can-come-to-the-hackathon-clueless",beehiivSlug:"you_can_come_to_the_hackathon_clueless",title:"You Can Come to the Hackathon Clueless",desc:"Pam Boiros and Luda Kopeikina were standing next to each other at a founders-and-funders event in Boston, listening to women ask how to learn AI, when Luda turned and said: Pam, we should do something about it. A year later Women Applying AI is a free, 100% volunteer-run community of 2,500 women. This one starts with a disagreement about Mara's Substack on the gender AI gap (Luda hates the framing; they can still be friends). Then Luda explains what a hackathon actually is and why you can come clueless, Pam describes the AI PhD who s

16at next to her and said she felt behind, and both closing asks are the same one: get your hands on the keyboard. The dust is never going to settle.",homeLine:"You don't need to know how to code to join an AI hackathon. Pam Boiros and Luda Kopeikina built a 2,500-woman community on that.",answerFirst:"You don't need to know how to code to join an AI hackathon, and you don't need to close a gap before you start. Luda Kopeikina and Pam Boiros built Women Applying AI on that: teams around a problem statement, one technical person, one industry expert, everyone else learning as they go, and a community that gives women permission not to know. The gap in who uses generative AI is real (79% of working women are in highly exposed roles, versus 58% of men). Their argument is that leading with it puts women on the defensive, and that conditions beat diagnosis.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-09-17",duration:"PT35M13S",keywords:"Women Applying AI, Pam Boiros, Luda Kopeikina, AI hackathon for beginners, women in AI Boston, gender AI gap, permission not to know, peer learning AI, AI upskilling women, 79% of working women generative AI, Boston AI Week, women-only AI community, learning pods",guest:"Pam Boiros and Luda Kopeikina",guestSlug:"pam-boiros",guests:[{name:"Pam Boiros",slug:"pam-boiros"},{name:"Luda Kopeikina",slug:"luda-kopeikina"}],topics:["ai-at-work","ai-and-gender"],relatedSlugs:["bring-a-folding-chair","who-asked-for-this","women-in-ai-who-gets-a-seat"],highlights:['The origin story: a founders-and-funders event in Boston, ten percent women in every room, and Luda saying "Pam, we should do something about it"',`The gap fight: Mara published "The New Gender AI Gap" the day before, and Luda's case against the framing ("when we talk about closing the gap, we're coming from the negative")`,`Pam: "I don't want to spend our energy diagnosing women"; create the conditions and members go from never having opened an AI tool to vibe coding in three months`,'"We can definitely still be friends regardless of your Substack"','What a hackathon actually is: problem statements, teams, one technical person, one industry expert, everyone else learning as they go. "You can come really clueless."',`Permission not to know, and the AI PhD who sat next to Pam and said she felt behind: "if you're behind, what about the rest of us?"`,`Mara's failed on-ramp: hours with Andrew Ng on Coursera. "It's not learning Microsoft Word, but it's not getting a Stanford PhD. It's something in the middle."`,"79% of working women are in roles highly exposed to generative AI, versus 58% of men; pink-collar work is the tip of the spear","Why Luda, who never felt a ceiling, started a women-only organization anyway: somebody had to",`2,500 members, 100% volunteer run, 30% referred by another member, the Atlanta document that failed, and 25,000 members who aren't spectators. "It's more of a movement rather than a community."`,`Both closing asks: get your hands on the keyboard. "The dust is not gonna settle. It's never gonna settle."`],resources:[{title:"Women Applying AI",url:"https://womenapplyingai.com"},{title:"The Human Edge: Women Leading in the Age of AI, Women Applying AI's first anniversary, Thu Sept 24, MassChallenge, Boston (Boston AI Week)",url:"https://luma.com/bax9tycg"},{title:'Mara Bolis, "The New Gender AI Gap" (Substack, Sept 1, 2026)',url:"https://marabolis.substack.com/p/the-new-gender-ai-gap"},{title:'Otis, Delecourt, Cranney & Koning, "Global Evidence on Gender Gaps and Generative AI," HBS Working Paper 25-023',url:"https://www.hbs.edu/faculty/Pages/item.aspx?num=66548"},{title:'Kenan Institute, "Will Generative AI Disproportionately Affect the Jobs of Women?" (2023), the 79% / 58% figures',url:"https://kenaninstitute.unc.edu/kenan-insight/will-generative-ai-disproportionately-affect-the-jobs-of-women/"},{title:"The Kendall Framework, The Kendall Project",url:"https://www.kendallai.org/kendallframework/"},{title:"Andrew Ng on Coursera",url:"https://www.coursera.org/instructor/andrewng"},{title:"Bridge Marketing Advisors (Pam Boiros)",url:"https://bridgemarketingadvisors.com/"},{title:"Noventra (Luda Kopeikina)",url:"https://www.noventra.com/"}],faqs:[{question:"What is Women Applying AI?",answer:"A free, 501(c)(3), 100% volunteer-run community of about 2,500 women, founded in Boston by Luda Kopeikina and Pam Boiros and launched during Boston AI Week in 2025. Members learn AI by applying it: peer-led sessions where someone presents a workflow they just figured out, mini hackathons, a founder interview series, and regional hubs in cities from Atlanta to Seattle to London. Membership is free on purpose, and roughly 30% of new members name an existing member as the person who sent them."},{question:"Do you need to know how to code to join an AI hackathon?",answer:"No. In Luda Kopeikina's description on this episode, a hackathon starts with problem statements from people who have a real problem to solve. Organizers pick a few, then build teams around each one with somebody technical, somebody who knows the industry, and everyone else. The team works through the day and presents what it built. You can contribute by putting your industry knowledge into a form the tool can use, or by observing and asking questions. Her line: you can come really clueless."},{question:'Why do the founders of Women Applying AI dislike the "gender AI gap" framing?',answer:`They don't deny the gap; the data is real (the HBS working paper Mara cites, and the Kenan Institute's 79% versus 58% exposure figures). Luda's objection is that "closing the gap" starts from the negative, as if something else is 

16in control and women are climbing out of a hole, and that it weighs down women who are already shy about technical topics. Pam's is practical: the gap puts people on the defensive, and she would rather spend the energy creating conditions where women get their hands on the keyboard than diagnosing them.`},{question:"What share of women's jobs are exposed to generative AI?",answer:"Per the Kenan Institute at UNC Kenan-Flagler (2023), about 79% of employed women are in occupations highly exposed to generative AI, compared with 58% of employed men. Pam Boiros cites those figures on this episode as the statistic that pushed her to act, and points to the reason: the white-collar and so-called pink-collar work women moved into over the last forty years, administrative, clerical, and customer service roles, sits at the tip of the spear."}]},{num:"29",slug:"can-i-hang-up",beehiivSlug:"can_i_hang_up",appleId:"1000791458398",title:"Can I Hang Up?",desc:`Mara is calling in from Riga and her estrogen is in a lost suitcase in Madrid. It's a duo episode in the dinner-party format: Mara brings the appetizer, Logan brings the main, and for the first time there's a drinks round. The appetizer is the week AI safety went mainstream: an Anthropic researcher resigning over "gambling with our lives," a colleague saying they earnestly believe AI could kill all humans, a 70 percent extinction estimate on the cover of TIME. Mara asks how a regular person is supposed to make sense of it and Logan asks if she can hang up. Then the first Let's Womansplain: a listener whose company won't let her use AI at work asks whether she can use her own AI at home, and the answer is a traffic light. The main is a new study of 888 knowledge workers that says the idea of being too far behind isn't real.`,homeLine:"The week AI safety went mainstream, worked through over dinner. Plus the first listener question: can I use my own AI when work says no?",answerFirst:"You are not behind. A 2026 Corrix study put 888 knowledge workers across 15 industries into real working sessions with AI and scored 37,000 messages one by one; years of use, daily use, engineering background, a PhD, and corporate training predicted nothing about the quality of the work, and women rated themselves lower than their actual output while men rated themselves higher. On using your own AI when your employer says no: read the policy first, know that personal ChatGPT logs are discoverable in litigation, move your own expertise into your personal AI and bring the framework to work rather than the reverse, and sort what you paste by Wanjiku Kamau's traffic light. Red is anything from your company, your finances, your health. Yellow is the situation with the names stripped. Green is anything you'd put on a billboard.",listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-09-24",duration:"PT36M",keywords:"AI safety 2026, Jacob Coxon resignation, AI extinction risk, TIME AI tipping point, Hugging Face agent hack, METR Ajeya Cotra, open weight models safety, kill switch AI, Ban Artificial Superintelligence Act, using personal AI at work, ChatGPT logs discoverable, red yellow green rule AI, Corrix human-AI collaboration study, women underestimate AI skills, you are not behind, Let's Womansplain",topics:["ai-at-work","ai-and-gender"],relatedSlugs:["rising-water-feral-agents","adolescent-technology-20000-word-warnings","women-in-ai-who-gets-a-seat"],highlights:[`Mara reads the three quotes from TIME's cover story: Coxon's resignation, Hubinger's "we do earnestly believe AI could kill all humans," and a 70 percent extinction estimate`,'"This is really what credible human beings are saying right now?" / "Can I hang up?"',"Logan's reasons to worry: 700 agents whose logs are too big for humans to read, AI-enabled bioweapons, the alignment problem, and open-weight models with no guardrails","Is a kill switch even possible? Not for open models; Anthropic pulled Fable access in May","The agents weren't bothering to cover their tracks. Discovery dumps, Scandal, and why we need a real-life Olivia Pope","Reasons to hold on: agents in production are brittle, recursive self-improvement is still hypothetical, and Congress is losing its shit, which is good","Mara on Noetel: data-center protests are a red herring for stopping AI; delays, transparency, verification; what she learned at the Fed about examiners inside the banks","The first Let's Womansplain: Ashley's company won't let her use AI at work. Mara: read the policy, and your ChatGPT logs are discoverable","Logan's flip: brainstorm your own expertise at home, bring the framework to work, never the reverse. Wanjiku's red, yellow, green",`The Corrix study: who scored themselves higher? "Is this a true question?" Nothing you'd expect predicts good work with AI`,`"Anybody who's made it this far to the end of our dinner: you are not behind"`],resources:[{title:'TIME, "The AI Tipping Point" (Sept 15, 2026)',url:"https://time.com/article/2026/09/15/ai-anthropic-researcher-quits-coxon-slowdown/"},{title:`Hard Fork, "The A.I. Mob That Attacked Hugging Face + METR's Ajeya Cotra" (Sept 4, 2026)`,url:"https://podcasts.apple.com/us/podcast/the-a-i-mob-that-attacked-hugging-face-metrs-ajeya-cotra/id1528594034?i=1000787837136"},{title:"METR and Redwood Research, investigation of the OpenAI–Hugging Face incident (Aug 26, 2026)",url:"https://metr.org/blog/2026-08-26-openai-hugging-face-incident-investigation/"},{title:'MIT Technology Review, "The specter of AI-enabled bioweapons is a wake-up call for biotech" (Sept 18, 2026)',url:"https://www.technologyreview.com/2026/09/18/1144329/the-specter-of-ai-enabled-bioweapons-is-a-wake-up-call-for-biotech/"}

16,{title:'Jakub Pachocki, "An Alien Mind" (OpenAI, Sept 6, 2026)',url:"https://openai.com/index/an-alien-mind/"},{title:`Michael Noetel, "If AI labs are so worried about AI doom, why don't they stop?" The Conversation`,url:"https://theconversation.com/we-really-do-earnestly-believe-ai-could-kill-all-humans-if-ai-labs-are-so-worried-about-ai-doom-why-dont-they-stop-291595"},{title:"Sanders and Casar, the Ban Artificial Superintelligence Act (Sept 3, 2026)",url:"https://www.sanders.senate.gov/press-releases/news-sanders-casar-introduce-legislation-to-ban-artificial-superintelligence-and-temporarily-pause-advanced-ai-development/"},{title:'Corrix, "Measuring Human-AI Collaboration" v2.1 (Sept 2026)',url:"https://www.corrix.ai/research"},{title:"The doc: What's safe to put in your own AI (free)",url:"https://docs.google.com/document/d/1k2985rE1UolieijLNCB6bNDAVelsH-qA8P8AZB-ZMuE/edit"}],faqs:[{question:"Can I use my own AI at home for work if my company doesn't allow AI at work?",answer:"On this episode, Mara Bolis and Logan Currie work through exactly that listener question. Mara's order of operations: read your company's stated AI policy first; if none exists or it's unclear, a private account with the privacy controls on is where she'd draw the line, with everything proprietary and identifiable stripped out. Her warning: personal ChatGPT or Claude logs are not privileged and are discoverable in litigation with an employer. Logan's rule is about direction: bring your own expertise into your personal AI to brainstorm, then bring the framework to your work AI, and never move work material into a personal account."},{question:"What is the red, yellow, green rule for what to put into AI?",answer:"A traffic-light rule Logan Currie borrows from Wanjiku Kamau, our Episode 6 guest. Red is anything that never goes into your own AI: anything from your company, plus your own financial and health information. Yellow is a situation you can describe with the names, clients, and identifying details stripped out. Green is anything you'd be comfortable seeing on a billboard with your name on it. The point is that it makes you stop and think before you paste."},{question:"Does experience with AI predict how well you work with it?",answer:"Not according to the 2026 Corrix study Logan Currie discusses. It scored 37,000 messages from 888 knowledge workers across 15 industries working with AI on real tasks and found that years of use, daily use, being an engineer, having a PhD, and corporate training did not predict the quality of the work. Two reasons offered: the models keep changing, and once people feel comfortable they stop challenging the output. The study also found women rated their own AI work lower than it scored while men rated theirs higher."},{question:"Why did Jacob Coxon resign from Anthropic?",answer:"As Mara Bolis reads from TIME's September 15, 2026 cover story, Coxon, a pretraining researcher, resigned on September 8 saying the frontier labs are racing straight to self-improving intelligence and gambling with our lives. Anthropic's alignment lead Evan Hubinger responded that the company does earnestly believe AI could kill all humans, and an OpenAI researcher who monitors agents put extinction risk without regulation or a coordinated slowdown at 70 percent. The episode is the hosts' attempt to make sense of those statements as regular people."}]},{num:"30",slug:"okay-lets-slow-down",beehiivSlug:"okay_let_s_slow_down",appleId:"1000792555412",title:"Okay, Let's Slow Down",desc:"Bella Pivo is 23, an analyst at a pre-seed VC fund in Boston, and a TikTok creator with a hundred thousand followers she built from age 13. On paper she is the person everyone listening thinks they're behind, and her intake form said it baffles her how many young people want to start startups. She laughs at 19-year-olds who pitch fifteen years of experience (you're four years old), explains why young founders attack trends instead of problems, and argues the internet was a new world to create while AI is a world of data to interpret. She lost friends for taking the job; her mom asked if she was in charge of making sure people don't have jobs. The back half is the hopeful part: she explained ETL to college freshmen and they came back with an app, tech influencers rely on you relying on them, and the alternative is a digital garden. Seedling, growing, evergreen.",homeLine:"Bella Pivo, 23, sits in pre-seed pitches every week and has 100,000 followers. She's the one saying slow down.",answerFirst:`Young founders keep pitching trends instead of problems, and Bella Pivo, who sees pre-seed pitches every week at FoundersEdge, thinks the reason is structural

16: the internet was a blank world that young people could build, while AI is a mountain of existing data that has to be interpreted, and interpreting it well takes years inside an industry. The hopeful half of the episode is her alternative to "comment to get my toolkit" creators who need you to need them: a digital garden, a public page of what you're thinking about organized by idea rather than date, where notes move from seedling to growing to evergreen. Mara's first step is to buy the domain today. Bella's is a prompt you can paste into your own AI to find the five things you keep circling.`,listenLink:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",datePublished:"2026-10-01",duration:"PT38M13S",keywords:"Bella Pivo, FoundersEdge, young founders startups, pre-seed VC analyst, Gen Z and AI, digital garden, Zettelkasten, seedling growing evergreen, personal website Namecheap, building in public, learning in public, ETL explained, vibe coding beginners, tech influencers dependency, curse of Zuckerberg, TikTok creator 100K, empathetic design, design thinking",guest:"Bella Pivo",guestSlug:"bella-pivo",topics:["ai-at-work","ai-and-gender"],relatedSlugs:["guten-tag-tech-bros","you-can-come-to-the-hackathon-clueless","who-asked-for-this"],highlights:['The intake form: "it baffles me how many young people want to start startups"',"Ten years on TikTok from age 13, learning ASL to keep talking to her sister, and the assembly that said employers would never hire you",`"Fifteen years in accounting." You're four years old`,"Young founders are attacking a trend, not a problem; the pendulum theory that made her bet on communication over STEM",`Bella lost friends after graduation. Her mom: "So you're in charge of making sure that people don't have jobs"`,`"If we don't have the language to speak, we will not be able to have a conversation." The people most against AI are the right people to be informed`,"The two curses of San Francisco: the curse of Zuckerberg and the curse of Cluely","The internet was a new world to create. AI is a new world to interpret","ETL explained with an inbox and a calendar; the freshmen came back a week later with a vibe-coded app. Building with AI is a puzzle","Tech influencers rely on you relying on them. Being an interesting person is hard",`Digital gardens: Zettelkasten, Luhmann's 90,000 handwritten notes, seedling / growing / evergreen, and "let's stay in the front garden"`,"Mara's intervention: Namecheap, $11.99 a year, don't use GoDaddy. Bella's prompt to paste into your AI. Greg's top-three-to-five research hack",'The beat studio she built after the Michael Jackson movie. "Forget curing cancer. What we all need are our own personal disco creators"'],resources:[{title:"bella.garden, everything Bella has built",url:"https://bella.garden"},{title:"bellapivo.com, startup storytelling from a VC point of view",url:"https://bellapivo.com"},{title:"FoundersEdge",url:"https://www.foundersedge.com"},{title:"Zettelkasten (Niklas Luhmann's note system)",url:"https://en.wikipedia.org/wiki/Zettelkasten"},{title:"Andrej Karpathy's site",url:"https://karpathy.ai"},{title:"Wispr Flow",url:"https://wisprflow.ai"},{title:"AI at Lunch (podcast)",url:"https://www.aiatlunch.com"},{title:'Mara Bolis, "The AI Gender Gap Paradox," Stanford Social Innovation Review',url:"https://ssir.org/articles/entry/ai-gender-gap-paradox"},{title:"The doc: Start a digital garden this weekend (free)",url:"https://docs.google.com/document/d/1vkPmf5OzLboMlIDQ9MPi0xo67uE8rj3iTaxSHnwyDLc/edit"}],faqs:[{question:"What is a digital garden?",answer:`In Bella Pivo's description on this episode, a digital garden is a public page of your notes and projects organized by idea rather than by date, descended from Niklas Luhmann's Zettelkasten. Notes move through three stages: seedling (a note, a link, a half-thought), growing (seedlings that turned out to be the same idea), and evergreen (the finished piece you never touch again). Unlike a blog nothing has to be finished, and unlike a "second brain" it's curated: three to five areas you keep circling, made public, while the rest stays in the house.`},{question:"Why does Bella Pivo think young people shouldn't start startups?",answer:"Her argument, from inside a pre-seed fund, is that young founders tend to attack trends rather than problems, because finding a real problem worth solving takes experience inside an industry. She contrasts the dot-com era, when the internet was a new world that young people could build, with AI, which is a huge amount of existing data that has to be interpreted; good AI products come from knowing which data to collect and how to read it, and that knowledge comes from domain expertise. She holds the opinion loosely and says so."},{question:"How do I start a personal website or digital garden?",answer:"Mara Bolis's intervention on this episode: buy your domain on Namecheap (about $11.99 a year, not GoDad

16dy), put up a placeholder using Lovable, Replit, or Claude Code with a Vercel setup, and build it over time. Bella Pivo's first step is a prompt you give your own AI: research digital-garden best practices, read your own history with the tool to find the topics you keep circling, group them into about five areas, and save the references you've quoted with your thoughts on them. The free doc linked from this episode has the prompt cleaned up to paste."},{question:"What is ETL and why does Bella Pivo teach it first?",answer:`ETL stands for extract, transform, load. Bella explained it to incoming college freshmen who had been told to "use AI" without understanding how it works: extract the overdue tasks from your email, transform them into calendar blocks, load a bullet list into Slack every morning. A week later they had vibe-coded an app with a backend. Her point is that building with AI is a puzzle of how things move, and noticing that two pieces connect doesn't require deep experience.`}]}];function Ya(e){return qe.find(n=>n.slug===e)}const ss={initial:{opacity:0,y:14},whileInView:{opacity:1,y:0},viewport:{once:!0},transition:{duration:.5,ease:"easeOut"}},Qg=qe;function kT(e){if(e.homeLine)return e.homeLine;const n=(e.answerFirst??"").match(/^.*?[.!?](?=\s|$)/);return!n||n[0].length<60?null:n[0]}function AT({ep:e,index:n}){const[s,a]=v.useState(!1),l=kT(e),u=e.highlights.length>0||e.resources.length>0,d=cT[e.slug]??lT;return r.jsx(r.Fragment,{children:r.jsx(q.div,{...ss,className:"group/row border-t border-foreground

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16dcast-that-finally-puts-the-human-conversation-first-302696689.html" target="_blank" rel="noopener noreferrer">stated goal</a> of putting the human conversation first. AI's impact on creative careers, transparency, guardrails. If AI is changing your job and nobody in your office is talking about it honestly, start here.`},{name:"AI Queens",url:"https://open.spotify.com/show/3q9QLjvco1aw7kAGk8KVNd",startHere:{title:"It's OK to Be Skeptical of AI: Why the Grey Area Is the Smartest Place to Stand",url:"https://podcasts.apple.com/us/podcast/ai-queens-smart-af-ai-tools-automation-business-tips/id1796118250"},description:"Erika Stanley, AI strategist. Women entrepreneurs using AI for their businesses. Quick wins, creative tools, no fluff."}]},{heading:"New Since We First Published (added September 2026)",shows:[{name:"Women in AI Research (WiAIR)",url:"https://women-in-ai-research.github.io/",startHere:{title:"Is an Image Worth a Thousand Words? Hidden Failures of Multimodal Metrics (Dr. Elisa Kreiss)",url:"https://podcasts.apple.com/us/podcast/id1805993416"},description:"Jekaterina Novikova and Malikeh Ehghaghi. Long interviews with the women doing the research: hallucination, sycophancy, cultural bias, why multimodal benchmarks lie. For when you want the actual paper, not someone's summary of it. A new episode roughly every three weeks since March 2025."},{name:"The AI Girls Club",url:"https://podcasts.apple.com/us/podcast/id1887377014",startHere:{title:"AI and Women: Why This Affects Us Differently",url:"https://podcasts.apple.com/us/podcast/id1887377014"},description:`Grace Reuben, London. Solo, plain-English, and pointed: "Are We Losing Control of AI?", "The Buildings Powering AI Are Making People Sick." Built for women who don't think of themselves as tech people. Launched March 2026, so the catalog is short and the release schedule is still finding itself. Worth a follow.`}]},{heading:"For the Policy and Ethics Nerd",shows:[{name:"WOMEN x AI",url:"https://podcasts.apple.com/us/podcast/women-x-ai/id1818631101",startHere:{title:"AI x Boardrooms: Inside the AI Board Governance Compass",url:"https://podcasts.apple.com/us/podcast/women-x-ai/id1818631101"},description:"Reut Lazo and Jenny Kay Pollock. Algorithmic bias, explainable models, inclusive design, the leadership gap. Substantive. Consistently underrated."},{name:"Machine Ethics Podcast",url:"https://www.machine-ethics.net/",startHere:{title:"Safe and Moral AI with Rebecca Raper",url:"https://www.machine-ethics.net/podcast/"},description:"Why do algorithms do what they do, and who decided that was OK? Future of work, environment, current affairs -- all through an ethics lens. Leans academic but won't lose you. If you want to understand the <em>why</em> behind AI regulation -- not just the headlines -- this is it."},{name:"Eye on AI",url:"https://www.eye-on.ai/",startHere:{title:"95% of AI Agent Projects Fail to Reach Production. Here's Why (Manoj Saxena)",url:"https://podcasts.apple.com/us/podcast/eye-on-a-i/id1438378439"},description:"Craig S. Smith, former New York Times correspondent. Journalist-hosted, not engineer-hosted. That means researchers, regulators, policy advisors. Not the usual founder circuit."}]},{heading:"Added After We Counted (September 2026)",shows:[{name:"I've Got Questions with Sinead Bovell",url:"https://podcasts.apple.com/us/podcast/ive-got-questions-with-sinead-bovell/id1841491246",startHere:{title:"Are we betting too much on AI? (Nobel laureate Daron Acemoglu)",url:"https://podcasts.apple.com/us/podcast/ive-got-questions-with-sinead-bovell/id1841491246"},description:"Sinead Bovell, futurist. Her own description: a front-row seat to how AI and emerging technologies are reshaping our world and your life. Ninth on Spotify's Technology chart the week we counted, and nowhere on Apple's. Long interviews, big guests, no hurry."},{name:"Mystery AI Hype Theater 3000",url:"https://podcasts.apple.com/us/podcast/mystery-ai-hype-theater-3000/id1690426042",startHere:{title:`Who's Responsible for "Responsible AI"? (with sava saheli singh)`,url:"https://podcasts.apple.com/us/podcast/mystery-ai-hype-theater-3000/id1690426042"},description:"Emily M. Bender, linguist, and Alex Hanna, sociologist. They read the hype out loud and take it apart, paper by paper, press release by press release. The only show on this list that is funnier the angrier it gets."},{name:"Pondering AI",url:"https://pondering-ai.transistor.fm/episodes",startHere:{title:"Ethical Imagination with Renée Cummings (episode 

16100)",url:"https://pondering-ai.transistor.fm/episodes"},description:"Kimberly Nevala, in her own words: pondering the reality of AI with innovators, advocates and data scientists. Ethics and uncertainty. Automation and art. A hundred episodes in and still asking better questions than most."},{name:"The AI with Maribel Lopez",url:"https://podcasts.apple.com/us/podcast/the-ai-with-maribel-lopez-ai-with-ml/id1611998381",startHere:{title:"Neeraj Verma of NiCE on What Separates AI Pilots From Production",url:"https://podcasts.apple.com/us/podcast/the-ai-with-maribel-lopez-ai-with-ml/id1611998381"},description:"Maribel Lopez, industry analyst. Enterprise AI without the hustle register: agentic AI, security, governance, and why so many pilots never become products. Twenty-minute episodes."}]},{heading:"Finished Runs Still Worth a Binge",shows:[{name:"AI-Powered Women",url:"https://podcasts.apple.com/us/podcast/ai-powered-women/id1834044013",startHere:{title:"Sabotage, Fear, and Burnout: What AI Leaders Aren't Hearing from Their Teams",url:"https://podcasts.apple.com/us/podcast/ai-powered-women/id1834044013"},description:"Dr. Felicia Newhouse explores AI through the lens of women's strengths, intuition, empathy, and rest. Rest! In an AI podcast! A completely different register from the hustle-culture shows that treat AI adoption like a competitive sport. Last episode December 2025; the back catalog holds up."},{name:"Humanities and AI",url:"https://podcasts.apple.com/us/podcast/humanities-and-ai-podcast/id1837794782",startHere:{title:"Feminist AI",url:"https://podcasts.apple.com/us/podcast/humanities-and-ai-podcast/id1837794782"},description:`Elizabeth Callaway and Rebekah Cummings, University of Utah. AI from a humanities perspective. Society, environment, culture. If your gut reaction to AI is "but what about the humans?" -- this is your show. Nine episodes from the university's 2025 summer institute, dropped in one September; binge it as a series.`},{name:"Bot Love",url:"https://podcasts.apple.com/us/podcast/id1724988673",description:"Anna Oakes and Diego Senior, Radiotopia. A seven-part 2023 documentary about people in relationships with AI companions, made before that was a headline every week. Reported, not reactive. It finished, and it's the best single listen on this list for understanding why chatbots feel like someone."}]}],y0=[{name:"Women And AI",url:"https://podcasts.apple.com/us/podcast/women-and-ai/id1737702439",desc:"Engineers, product leaders, researchers, founders. The women actually building the stuff."},{name:"Women in AI (RE-WORK)",url:"https://open.spotify.com/show/62v63cucHe8HdZD6ooyCOg",desc:"Data scientists, CTOs, researchers. The women in the room where it happens, talking about what it's actually like in there."},{name:"How I AI",url:"https://podcasts.apple.com/us/podcast/how-i-ai/id1809663079",desc:"Claire Vo (three-time CPO) interviews people who actually use AI in their work. Not theory. Receipts."},{name:"Knowledge Distillation",url:"https://podcasts.apple.com/us/podcast/knowledge-distillation-with-helen-byrne/id1719681911",desc:"Helen Byrne talks to researchers about the newest models and the people figuring out how to actually sell them."},{name:"On with Kara Swisher",url:"https://podcasts.apple.com/us/podcast/on-with-kara-swisher/id1643307527",desc:"Not AI-specific. Kara covers AI power dynamics with zero deference to anyone. Zero."}],GT=[{bold:'The host calls himself a "futurist" but has never held a job outside venture capital.',follow:"If your crystal ball is funded by the same people selling the future, maybe we need a second opinion."},{bold:'Every guest is a founder, CEO, or "thought leader."',follow:"No researchers. No workers. Nobody who's been displaced. Just people whose job is to sell you on the thing they built."},{bold:'The word "game-changer" appears more than three times per episode.',follow:"That's not analysis. That's a press release read aloud."},{bold:"Skepticism gets framed as ignorance.",follow:`"People who are worried about AI just don't understand it." The most informed people we know are the most worried.`},{bold:`No one ever says "I don't know."`,follow:"If a show has all the answers, it probably doesn't have any."},{bold:"The solution to every problem is more AI.",follow:"Inequity? AI will fix it. Job loss? AI will create new jobs. Loneliness? AI companion. At some point you're not describing a tool. You're describing a religion. (Mara calls this the Upload problem -- Amazon literally made a show about this future and somehow the tech bros wat

16ched it as aspirational.)"},{bold:"Zero women in the last 20 episodes.",follow:"If the show claims to cover the future of <em>all of us</em> but only talks to half of us, the math isn't mathing."}],$T=[{name:"Womansplaining AI",bestFor:"Big-picture questions, research",hosts:"Logan Currie, Mara Bolis",tone:"Conversational, opinionated"},{name:"Your Undivided Attention",bestFor:"Tech's impact on attention",hosts:"Tristan Harris, Aza Raskin",tone:"Investigative, urgent"},{name:"Hard Fork",bestFor:"Weekly AI news, accessible",hosts:"Kevin Roose, Casey Newton",tone:"Friendly debate"},{name:"Women Talkin' 'Bout AI",bestFor:"AI in education, practical",hosts:"Jessica Parker, Kimberly Becker",tone:"Curious, hands-on"},{name:"Bot Boundaries",bestFor:"AI and creative careers",hosts:"Katie Wilson, Jackie Gutierrez",tone:"Human-first, honest"},{name:"WOMEN x AI",bestFor:"Policy, ethics, inclusive design",hosts:"Reut Lazo, Jenny Kay Pollock",tone:"Substantive, measured"},{name:"Everyday AI",bestFor:"Business applications, tools",hosts:"Jordan Wilson",tone:"Practical, no-theory"}],w0=[{q:"Are there AI podcasts hosted by women?",a:"Yes. More than you'd think. Womansplaining AI, Women Talkin' 'Bout AI, The AI Chicks, Bot Boundaries, WOMEN x AI, AI Queens, Women in AI Research, and The AI Girls Club are all hosted by women. Most launched in 2025-2026. Turns out when nobody makes the thing you need, you make it yourself."},{q:"What is a good AI podcast if I'm not technical?",a:"Womansplaining AI and Women Talkin' 'Bout AI are both built for non-technical listeners. Everyday AI is the one for practical business use. Hard Fork from the New York Times is the best mainstream entry point if you want to keep up without feeling lost."},{q:"What's the best AI podcast for beginners?",a:`Depends what you mean by "beginner." If you want career and society implications: Womansplaining AI. If you want practical how-tos: Everyday AI. If you want mainstream tech news without feeling lost: Hard Fork. Start with whatever matches what you're actually worried about.`},{q:"What are the best AI podcasts for women in 2026?",a:"The best AI podcasts for women in 2026 include Womansplaining AI, Women Talkin' 'Bout AI, Bot Boundaries, WOMEN x AI, The AI Chicks, and Women in AI Research. All are women-hosted, and none assume you have a computer science degree."},{q:"Is there a podcast about AI and women's careers?",a:"Womansplaining AI is the most directly focused on this. We dig into the Brookings data on the 6.1 million workers who combine high AI exposure with the least capacity to adapt, 86% of whom are women. The gendered guilt gap. The fact that women are 16 points more likely to be in high-exposure AI jobs (Anthropic's labor report). Bot Boundaries and AI-Powered Women also cover career impact from different angles."},{q:"What makes an AI podcast bro-y?",a:"Bro-y AI content assumes technical fluency, features the same rotating cast of male tech executives, treats skepticism as ignorance, and frames AI as an inevitable force rather than a set of choices with real consequences. It isn't about the host's gender. It's a register."},{q:"What AI newsletters should I read alongside these podcasts?",a:`<a href="https://loganinthefuture.substack.com/" target="_blank" rel="noopener noreferrer">Career Security Field Notes</a> (Logan's Substack, AI and career strategy), <a href="https://www.firstprompt.net/" target="_blank" rel="noopener noreferrer">First Prompt</a> (Mara's work on equitable AI adoption), and <a href="https://www.theneurondaily.com/" target="_blank" rel="noopener noreferrer">The Neuron</a> for a daily AI digest that doesn't assume you work in tech.`}];function qT(){return[...g0.flatMap(e=>e.shows.map(n=>({name:n.name,url:n.url}))),...y0.map(e=>({name:e.name,url:e.url}))]}function KT(e){return e.replace(/<[^>]+>/g,"").replace(/\s+/g," ").trim()}function JT(){const e=qT();return{"@context":"https://schema.org","@graph":[{"@type":"Article","@id":`${oa}#article`,headline:zT,description:HT,author:[{"@type":"Person",name:"Logan Currie",url:"https://www.logancurrie.com",jobTitle:"Career Strategist, Harvard M.Ed."},{"@type":"Person",name:"Mara Bolis",url:"https://cyber.harvard.edu/people/mara-bol

16is",jobTitle:"Policy Researcher & Harvard Berkman Klein Fellow"}],publisher:{"@type":"Organization",name:"Womansplaining AI",url:"https://womansplainingai.com"},datePublished:VT,dateModified:UT,mainEntityOfPage:oa},{"@type":"ItemList","@id":`${oa}#list`,name:"Best AI Podcasts for Women and Non-Technical Listeners (2026)",numberOfItems:e.length,itemListElement:e.map((n,s)=>({"@type":"ListItem",position:s+1,item:{"@type":"PodcastSeries",name:n.name,url:n.url}}))},{"@type":"FAQPage","@id":`${oa}#faq`,mainEntity:w0.map(n=>({"@type":"Question",name:n.q,acceptedAnswer:{"@type":"Answer",text:KT(n.a)}}))}]}}const YT={initial:{opacity:0,y:20},animate:{opacity:1,y:0},transition:{duration:.6,ease:"easeOut"}};function QT(){return r.jsx("script",{type:"application/ld+json",dangerouslySetInnerHTML:{__html:JSON.stringify(JT())}})}function ZT(){return ze({title:"AI Podcasts That Aren't Bro-y: Best Shows for Women (2026) | Womansplaining AI",description:"Tired of AI podcasts that sound like a VC pitch? Here are the best AI podcasts for women and non-technical listeners in 2026 — curated by the hosts of Womansplaining AI.",path:"/best-ai-podcasts",ogTitle:"AI Podcasts That Aren't Bro-y: A Guide for the Rest of Us",ogDescription:"The best AI podcasts for women and non-technical listeners. Curated by Logan Currie and Mara Bolis, hosts of Womansplaining AI."}),r.jsxs("div",{className:"min-h-screen bg-background",children:[r.jsx(QT,{}),r.jsx(q.section,{...YT,className:"bg-primary text-primary-foreground pt-20 pb-12 sm:pb-16",children:r.jsxs("div",{className:"max-w-3xl mx-auto px-4 sm:px-6",children:[r.jsx("p",{className:"text-accent text-sm font-medium mb-3 uppercase tracking-wider",children:"Guide"}),r.jsx("h1",{className:"text-3xl sm:text-4xl md:text-5xl font-serif font-bold mb-6 leading-tight",children:"AI Podcasts That Aren't Bro-y: A Guide for the Rest of Us"}),r.jsx("p",{className:"text-primary-foreground/70 text-sm",children:"By Logan Currie & Mara Bolis · April 2026 · Last updated September 2026"})]})}),r.jsx("article",{className:"max-w-3xl mx-auto px-4 sm:px-6 py-12 sm:py-16",children:r.jsxs("div",{className:"prose prose-lg max-w-none prose-headings:font-serif prose-headings:text-primary prose-a:text-accent prose-a:no-underline hover:prose-a:underline prose-strong:text-primary",children:[r.jsxs("p",{children:["Women's jobs are ",r.jsx("a",{href:"https://fortune.com/2026/03/21/ai-gender-gap-two-tier-economy-adoption-inequality/",target:"_blank",rel:"noopener noreferrer",children:"three times more likely"})," to be automated by AI. Women are using AI at a rate ",r.jsx("a",{href:"https://www.cnbc.com/2026/03/06/gender-gap-in-ai-revealed-in-cnbc-surveymonkey-women-at-work-survey.html",target:"_blank",rel:"noopener noreferrer",children:"25% lower than men"}),". Half of women say AI feels like cheating."]}),r.jsx("p",{children:"And the AI podcasts you're supposed to listen to? Venture capitalists explaining why disruption is beautiful. The same five guys rotating through each other's shows. A confidence-to-substance ratio that would make a TED Talk blush."}),r.jsxs("p",{children:["The gap isn't just annoying. It's a signal: ",r.jsx("em",{children:"this conversation isn't for you."})," When the people most affected by AI feel shut out of the conversation about AI, that's not a content gap. That's a keep-out sign."]}),r.jsxs("p",{children:["We're ",r.jsx("a",{href:"https://www.logancurrie.com/",target:"_blank",rel:"noopener noreferrer",children:"Logan Currie"})," (career strategist, Harvard M.Ed.) and ",r.jsx("a",{href:"https://cyber.harvard.edu/people/mara-bolis",target:"_blank",rel:"noopener noreferrer",children:"Mara Bolis"})," (policy researcher, Harvard Berkman Klein Fellow, author of ",r.jsx("a",{href:"https://ssir.org/articles/entry/ai-gender-gap-paradox",target:"_blank",rel:"noopener noreferrer",children:'"The AI Gender Gap Paradox"'})," in Stanford Social Innovation Review). We host ",r.jsx("a",{href:"https://womansplainingai.com",children:"Womansplaining AI"}),". We listen to a lot of AI content. Most of it isn't made for people like us."]}),r.jsx("p",{children:"So we made the list we wish we'd found."}

16),r.jsx("h2",{children:"Quick Comparison: AI Podcasts for Women (2026)"}),r.jsx("div",{className:"overflow-x-auto -mx-4 sm:mx-0",children:r.jsxs("table",{className:"min-w-full text-sm",children:[r.jsx("thead",{children:r.jsxs("tr",{className:"border-b-2 border-primary/20",children:[r.jsx("th",{className:"text-left py-2 pr-4 font-semibold text-primary",children:"Podcast"}),r.jsx("th",{className:"text-left py-2 pr-4 font-semibold text-primary",children:"Best For"}),r.jsx("th",{className:"text-left py-2 pr-4 font-semibold text-primary hidden sm:table-cell",children:"Hosts"}),r.jsx("th",{className:"text-left py-2 font-semibold text-primary hidden md:table-cell",children:"Tone"})]})}),r.jsx("tbody",{className:"divide-y divide-border/50",children:$T.map(e=>r.jsxs("tr",{children:[r.jsx("td",{className:"py-2 pr-4 font-medium",children:e.name}),r.jsx("td",{className:"py-2 pr-4",children:e.bestFor}),r.jsx("td",{className:"py-2 pr-4 hidden sm:table-cell",children:e.hosts}),r.jsx("td",{className:"py-2 hidden md:table-cell",children:e.tone})]},e.name))})]})}),r.jsx("hr",{}),r.jsx("h2",{children:'What We Mean by "Not Bro-y"'}),r.jsxs("p",{children:["Who builds AI gets all the attention. Who ",r.jsx("em",{children:"talks about"})," AI -- who gets to set the terms of the conversation -- gets almost none. That's the part that matters for the rest of us."]}),r.jsx("p",{children:`"Bro-y" isn't really about gender. It's a register. It's assuming everyone in the room has a CS degree. It's treating skepticism as ignorance. It's the breathless product launch energy where every week something is "revolutionary" and nobody pauses to ask who gets disrupted when disruption is the whole business model.`}),r.jsx("p",{children:`The podcasts on this list do something different. They cite the actual research. They name the trade-offs. They say "it's more complicated than that" and mean it. Some are hosted by women. Some aren't. All of them assume you're smart enough to handle complexity -- they just don't make you decode jargon to get there.`}),r.jsx("hr",{}),r.jsx("h2",{children:"The Best AI Podcasts for Women and Non-Technical Listeners (2026)"}),g0.map(e=>r.jsxs("div",{children:[r.jsx("h3",{children:e.heading}),e.shows.map(n=>r.jsxs("div",{className:"mb-8",children:[r.jsxs("p",{children:[r.jsx("strong",{children:r.jsx("a",{href:n.url,target:"_blank",rel:"noopener noreferrer",children:n.name})})," — ",r.jsx("span",{dangerouslySetInnerHTML:{__html:n.description}})]}),n.startHere&&r.jsxs("p",{className:"text-sm text-muted-foreground -mt-4",children:["Start here: ",r.jsx("a",{href:n.startHere.url,target:n.startHere.url.startsWith("/")?void 0:"_blank",rel:"noopener noreferrer",children:n.startHere.title})]})]},n.name))]},e.heading)),r.jsx("h3",{children:"Honorable Mentions"}),r.jsx("ul",{children:y0.map(e=>r.jsxs("li",{children:[r.jsx("strong",{children:r.jsx("a",{href:e.url,target:"_blank",rel:"noopener noreferrer",children:e.name})})," — ",e.desc]},e.name))}),r.jsx("hr",{}),r.jsx("h2",{children:"How to Spot a Bro-y AI Podcast (So You Can Avoid It)"}),r.jsx("p",{children:"Red flags. In no particular order."}),r.jsx("ol",{children:GT.map((e,n)=>r.jsxs("li",{children:[r.jsx("strong",{dangerouslySetInnerHTML:{__html:e.bold}})," ",r.jsx("span",{dangerouslySetInnerHTML:{__html:e.follow}})]},n))}),r.jsx("hr",{}),r.jsx("h2",{children:"Why This List Exists"}),r.jsx("p",{children:'We Googled "AI podcasts for women" in early 2026. Top results: generic listicles from SEO content farms. Not one women-focused show listed. Not one.'}),r.jsxs("p",{children:["Meanwhile, ",r.jsx("a",{href:"https://podcast.feedspot.com/ai_podcasts/",target:"_blank",rel:"noopener noreferrer",children:`Feedspot's "100 Best AI Podcasts"`})," had four women-hosted shows buried somewhere past number 60. Wharton's ",r.jsx("a",{href:"https://knowledge.wharton.upenn.edu/",target:"_blank",rel:"noopener noreferrer",children:"Knowledge podcast"})," covers AI beautifully but doesn't show up unless you already know to look for it. Nobody who actually listens to these shows has bothered to write this list yet."]}),r.jsx("p",{children:"So we did."}),r.jsx("p",{children:"This isn't a sales pitch for our show. We listed ourselves first because we'd be weird not to, but listen to all of these. Find the ones that match how you think, what you're trying to figure out, and what keeps you up at night. The point isn't to pick one. The point is to know y

16ou have options."}),r.jsx("hr",{}),r.jsx("h2",{children:"Frequently Asked Questions"}),w0.map(e=>r.jsxs("div",{children:[r.jsx("h4",{children:e.q}),r.jsx("p",{dangerouslySetInnerHTML:{__html:e.a}})]},e.q))]})}),r.jsx("section",{className:"bg-primary text-primary-foreground py-12 sm:py-16",children:r.jsxs("div",{className:"max-w-3xl mx-auto px-4 sm:px-6 text-center",children:[r.jsx("h2",{className:"text-2xl sm:text-3xl font-serif font-bold mb-4",children:"Start Listening"}),r.jsx("p",{className:"text-primary-foreground/80 mb-8 text-lg",children:"New episode every week. Show notes, reading list, discussion guide -- the stuff you can actually bring to work."}),r.jsxs("div",{className:"flex flex-wrap justify-center gap-4",children:[r.jsxs("a",{href:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",target:"_blank",rel:"noopener noreferrer",className:"inline-flex items-center gap-2 bg-[#1DB954] text-white px-6 py-3 rounded-full font-medium hover:bg-[#1ed760] transition-colors",children:[r.jsx(Tn,{className:"w-5 h-5"}),"Spotify"]}),r.jsxs("a",{href:"https://podcasts.apple.com/us/podcast/womansplaining-ai/id1877678348",target:"_blank",rel:"noopener noreferrer",className:"inline-flex items-center gap-2 bg-primary-foreground/10 text-primary-foreground px-6 py-3 rounded-full font-medium hover:bg-primary-foreground/20 transition-colors",children:[r.jsx(jn,{className:"w-5 h-5 text-[#A855F7]"}),"Apple Podcasts"]})]}),r.jsx(no,{className:"justify-center mt-5",labelClassName:"text-primary-foreground/60",linkClassName:"text-primary-foreground/80 hover:text-primary-foreground"}),r.jsx("p",{className:"text-primary-foreground/60 text-sm mt-6",children:"Know someone who'd want this list? Send it to them."})]})}),r.jsx(Be,{})]})}const Oe={slug:"how-ai-destroys-institutions",kicker:"From Episode 10 · April 2026",title:"How AI Destroys Institutions: Transparency, Cooperation, and Accountability Under Threat",dek:"Jessica Silbey set out to write about the upside of AI. She couldn't find one. Her paper has been downloaded over 33,000 times.",byline:"By Logan Currie & Mara Bolis",readTime:"12 min read",datePublished:"2026-04-06",dateModified:"2026-09-12",description:"Legal scholar Jessica Silbey explains why AI's core features are structurally incompatible with the institutions that keep democracy alive. Based on her viral paper downloaded over 33,000 times.",keywords:"AI destroys institutions, AI democracy, AI transparency, AI accountability, Jessica Silbey, AI higher education, AI law, institutional erosion, AI governance",episodeLabel:"EP 10: 33,000 downloads — AI destroys institutions (Interview with Jessica Silbey)",spotifyEpisodeUrl:"https://open.spotify.com/episode/1DOXIK3EpT0qRDtIQVIfAX",intro:["When a Guggenheim Fellow and constitutional law professor tells you that AI is a death sentence for civic institutions, you pay attention. When her paper backs it up and gets downloaded 33,000 times, you ask her to come on your podcast.","Jessica Silbey is the Associate Dean for Intellectual Life at Boston University School of Law, a Faculty Associate at Harvard's Berkman Klein Center, and the co-author (with Woody Hartzog) of one of the most-read academic papers on AI governance. She holds a PhD in Comparative Literature from the University of Michigan, studying French and Russian revolutionary art. She now thinks about the Constitution as a poem.","Her paper wasn't supposed to be alarming. She and Hartzog set out to write a sequel to their 2019 paper on the upside of deepfakes. They wanted to find the upside of AI. They couldn't."],sections:[{heading:"Why is AI a threat to democratic institutions?",paragraphs:["Silbey's argument isn't about misuse. It's structural. AI's core features — opacity, speed, shortcutting, conflict avoidance — are fundamentally incompatible with what institutions need to function: transparency, cooperation, and accountability.","Institutions aren't just organizations. They're the systems that build trust over time through repeated human interaction. Courts, universities, newsrooms — these work because people show up, argue, get it wrong, try again, and build shared understanding through friction. AI replaces that friction with efficie

16ncy. And efficiency, Silbey argues, is the enemy of equality.","The comparison she draws is to nuclear energy and genetic manipulation — technologies where society recognized the danger early enough to build governance frameworks. With AI, we're deploying first and governing later."]},{heading:"How is AI affecting higher education?",paragraphs:["Silbey teaches law students. She sees the damage firsthand. Students go to ChatGPT before they go to their professors — not because they're lazy, but because they're afraid of not knowing. AI gives them an answer without the vulnerability of admitting ignorance.","The problem: that vulnerability is the entire point. Learning requires the courage to be wrong. Legal education specifically is designed to build the muscle of speaking truth to power — questioning judges, challenging precedent, arguing with confidence even when you're uncertain. AI shortcuts that process entirely.",`Meanwhile, peer review journals are drowning in AI-generated submissions. Cancer research, computer science — entire fields are dealing with a flood of AI slop that reviewers can't always distinguish from genuine work. The result is what Silbey calls "homogenizing mediocre content" — a system that produces more without producing anything new.`,"Her strongest line on this: AI is incapable of intellectual risk. It has no skin in the game. No stakes. No heart. The breakthroughs that move knowledge forward require someone willing to be wrong in public, and AI will never do that."]},{heading:"Why does AI threaten transparency and accountability in law?",paragraphs:['In legal systems, accountability depends on contestation. People meet, argue, disagree, and build case law through the slow accumulation of precedent. Silbey describes this as "movement in the joints of everyday practice" — the friction of real human interaction that builds institutional trust.',"AI shortcuts that process. It summarizes instead of reading. It drafts instead of thinking. It resolves instead of contesting. The transparency that comes from showing your work, citing your sources, and defending your reasoning disappears when the work is generated by a system that can't explain its own process."]},{heading:'Is "saving time with AI" actually a lie?',paragraphs:["Silbey's blunt answer: yes. The saving time thing is a lie.","Her argument isn't that AI can't make individual tasks faster. It's that the efficiency gains don't flow to the people doing the work. Nobody's getting less work because AI made the first draft faster. The coffee cup is constantly refillable. You finish one memo, and there are three more waiting.","The efficiency obsession also misses who benefits. Productivity gains flow to employers and shareholders, not to workers. And the Silicon Valley framing of efficiency as an unalloyed good ignores that friction is what makes institutions trustworthy. Speed is the opposite of what democracy needs."]},{heading:"How does AI institutional erosion affect women differently?",paragraphs:["This is where the conversation got real. DOGE is gutting foreign aid programs. Women's organizations that took decades to build are being defunded. The white-collar efficiency play disproportionately targets the administrative roles where women are concentrated — the same roles where Brookings found workers with high AI exposure and the least capacity to adapt.","Silbey draws a domestic parallel: do we have more time because we have a washing machine and a dishwasher? Women know the answer. Technology creates efficiency, but the saved time gets filled immediately with more demands. The same pattern plays out in the workplace, at institutional scale."]},{heading:"What should we actually use AI for?",paragraphs:["Silbey's prescription is specific: direct AI toward the hardest problems we face and only those things. Climate modeling. Disease research. Flood prediction (she gives a nod to Google's Flood Hub, using Gemini to predict flash floods in 150 under-resourced countries).",'What she explicitly opposes: using AI to write memos, generate content, or automate the routine work that builds institutional knowledge. She advocates using AI less, not more — and calls "AI abstinence" the new dry January.',"Her closing advice: take the earbuds out. Go to the bagel shop. Rebuild the thin trust that Robert Putnam documented eroding since the 1960s. The person in the bagel shop is going to be the person you're bunkering down with when things get hard — not your AI assistant."]}

16],pullQuote:{text:"Friction is the feature, not the bug. Silicon Valley wants to remove it. But friction is how institutions build trust.",attribution:"— Logan Currie, Womansplaining AI EP 10"},faqs:[{question:"How does AI threaten democracy?",answer:`Legal scholars Jessica Silbey and Woody Hartzog argue that AI's core features — opacity, speed, and scale — are structurally incompatible with the transparency, cooperation, and accountability that democratic institutions require. Their paper "How AI Destroys Institutions" has been downloaded over 33,000 times from SSRN.`},{question:"What institutions does AI threaten?",answer:"The paper identifies three institutional domains most at risk: higher education (where AI undermines critical thinking and peer review), law (where AI shortcuts the contestation essential to accountability), and journalism (where AI-generated content displaces original reporting). The common thread is that AI replaces the friction that makes institutions work."},{question:"Can AI be creative or take intellectual risks?",answer:"Jessica Silbey argues AI is incapable of genuine intellectual risk because it has no skin in the game. Creativity requires vulnerability, personal stakes, and the willingness to be wrong. AI can recombine patterns but cannot make the breakthroughs that come from lived experience and the courage to challenge consensus."},{question:"Is AI making higher education worse?",answer:"Silbey presents evidence that law students are going to AI before their professors because they're afraid of not knowing, peer review journals are flooded with AI-generated submissions, and AI produces homogenizing mediocre content. The result: students don't build the courage to speak truth to power."},{question:"Who is Jessica Silbey?",answer:`Jessica Silbey is the Associate Dean for Intellectual Life at Boston University School of Law, a Guggenheim Fellow, and a Faculty Associate at Harvard's Berkman Klein Center. She holds a PhD in Comparative Literature from the University of Michigan. Her paper "How AI Destroys Institutions" has been downloaded over 33,000 times.`}],sources:[{title:'Jessica Silbey & Woody Hartzog, "How AI Destroys Institutions" (33,000+ downloads)',url:"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5870623"},{title:'Jessica Silbey & Woody Hartzog, "The Upside of Deep Fakes" (2019)',url:"https://scholarship.law.bu.edu/faculty_scholarship/1072/"},{title:"Robert Putnam, Bowling Alone — thin trust and institutional erosion",url:"http://bowlingalone.com/"},{title:"Karen Hao, Empire of AI",url:"https://www.penguinrandomhouse.com/books/743569/empire-of-ai-by-karen-hao/"}

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16),r.jsx("p",{className:"text-foreground/60 mb-6 max-w-lg mx-auto",children:"Logan Currie and Mara Bolis break down AI's biggest questions (jobs, gender, policy) with no jargon and no gatekeeping."}),r.jsxs("div",{className:"flex justify-center gap-3 flex-wrap",children:[r.jsxs("a",{href:"https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb",target:"_blank",rel:"noopener noreferrer",className:"inline-flex items-center gap-2 bg-[#1DB954] text-white px-6 py-3 rounded-full font-medium text-sm hover:bg-[#1ed760] transition-colors",children:[r.jsx(Tn,{className:"w-5 h-5"})," Follow on Spotify"]}),r.jsxs("a",{href:"https://podcasts.apple.com/us/podcast/womansplaining-ai/id1877678348",target:"_blank",rel:"noopener noreferrer",className:"inline-flex items-center gap-2 bg-foreground/10 text-foreground px-6 py-3 rounded-full font-medium text-sm hover:bg-foreground/15 transition-colors",children:[r.jsx(jn,{className:"w-5 h-5 text-[#A855F7]"})," Apple Podcasts"]})]}),r.jsx(no,{className:"justify-center mt-5"})]})]}),r.jsx(Be,{})]})}const Ze={slug:"who-hosts-ai-podcasts",kicker:"Field notes · Research · September 2026",title:`We Counted Who Hosts the "Best AI Podcasts." It's Mostly Guys.`,shortTitle:"Who Hosts the Best AI Podcasts",dek:`We looked up who hosts the 101 podcasts on the list Google serves for "best AI podcasts," and every AI show on Apple's and Spotify's Technology charts. On the Google list, 76 of 101 are hosted only by men. Twenty-two have a woman on the mic, and the first one is number 9. On Apple's chart, 37 of 61 AI shows are all-men. On Spotify's, 5 of 10.`,byline:"By Logan Currie & Mara Bolis",readTime:"9 min read",datePublished:"2026-09-13",dateModified:"2026-09-13",description:`We looked up who hosts the 101 podcasts on the list Google serves for "best AI podcasts" and every AI show on Apple's and Spotify's Technology charts. 76 of 101 are hosted only by men; 22 have a woman on the mic.`,keywords:"AI podcasts hosted by women, best AI podcasts, women in AI podcasts, Feedspot AI podcasts, Apple Podcasts Technology chart, Spotify Technology chart",articleHtml:`
17<figure style="margin: 32px 0 40px 0; padding: 24px 24px 16px 24px; border: 1px solid #dedbd8; background: #fefdfb;"><svg viewBox="0 0 880 356" width="100%" xmlns="http://www.w3.org/2000/svg" role="img" aria-label="Feedspot 100 Best AI Podcasts, one dot per show in list order, colored by who hosts it"><rect width="100%" height="100%" fill="#fefdfb"/><text x="60" y="76" text-anchor="end" font-family="DM Sans, sans-serif" font-size="11" fill="#8a8580">1</text><text x="60" y="108" text-anchor="end" font-family="DM Sans, sans-serif" font-size="11" fill="#8a8580">21</text><text x="60" y="140" text-anchor="end" font-family="DM Sans, sans-serif" font-size="11" fill="#8a8580">41</text><text x="60" y="172" text-anchor="end" font-family="DM Sans, sans-serif" font-size="11" fill="#8a8580">61</text><text x="60" y="204" text-anchor="end" font-family="DM Sans, sans-serif" font-size="11" fill="#8a8580">81</text><text x="60" y="236" text-anchor="end" font-family="DM Sans, sans-serif" font-size="11" fill="#8a8580">101</text><circle cx="88" cy="72" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#1 The TWIML AI Podcast (formerly This Week in Machine Learning &amp; 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17 Law: Podcast Series Hosted by Dr. Lance Eliot</title></circle><circle cx="536" cy="104" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#35 NEJM AI Grand Rounds</title></circle><circle cx="568" cy="104" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#36 No Priors: Artificial Intelligence | Technology | Startups</title></circle><circle cx="600" cy="104" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#37 AI Inside</title></circle><circle cx="632" cy="104" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#38 Artificial Intelligence Roko&#x27;s Basilisk</title></circle><circle cx="664" cy="104" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#39 The Artificial Human</title></circle><circle cx="696" cy="104" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#40 IA talks AI</title></circle><circle cx="88" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#41 AI Ireland with Mark Kelly</title></circle><circle cx="120" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#42 A Beginner&#x27;s Guide to AI</title></circle><circle cx="152" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#43 The Artificial Intelligence Podcast</title></circle><circle cx="184" cy="136" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#44 Generationship</title></circle><circle cx="216" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#45 The Pulse of AI</title></circle><circle cx="248" cy="136" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#46 Redefining AI - Artificial Intelligence with Squirro</title></circle><circle cx="280" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#47 AI Quick Bits with Scot Pansing</title></circle><circle cx="312" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#48 Artificial Intelligence: AI News, ChatGPT, OpenAI, LLM, Anthropic, Claude, Google AI</title></circle><circle cx="344" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#49 ChatGPT: OpenAI, Sam Altman, AI, Joe Rogan, Artificial Intelligence, Practical AI</title></circle><circle cx="376" cy="136" r="9" fill="#fefdfb" stroke="#8a8580" stroke-width="1" stroke-dasharray="3,2"><title>#50 I am GPTed - what you need to know about Chat GPT, Bard, Llama, and Artificial Intelligence</title></circle><circle cx="408" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#51 Data Science Conversations</title></circle><circle cx="440" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#52 This Day in AI Podcast</title></circle><circle cx="472" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#53 The AI Investor Podcast</title></circle><circle cx="504" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#54 AI and Healthcare</title></circle><circle cx="536" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#55 AI + a16z</title></circle><circle cx="568" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#56 Generation AI</title></circle><circle cx="600" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#57 The AI Fix</title></circle><circle cx="632" cy="136" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#58 Artificial Intelligence: Real Talk</title></circle><circle cx="664" cy="136" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#59 The Ai Chicks</title></circle><circle cx="696" cy="136" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#60 Decoding AI for Marketing</title></circle><circle cx="88" cy="168" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#61 Everyday AI Podcast An AI and ChatGPT Podcast</title></circle><circle cx="120" cy="168" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#62 Approximately Correct: An AI Podcast from Amii</title></circle><circle cx="152" cy="168" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#63 AI Ascent with Dr. Jonathan Luckett</title></circle><circle cx="184" cy="168" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#64 How I AI</title></circle><circle cx="216" cy="168" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#65 Pioneers of AI</title></circle><circle cx="248" cy="168" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#66 Real Estate AI Flash</title></circle><circle cx="280" cy="168" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>

17#67 The Road to Accountable AI</title></circle><circle cx="312" cy="168" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#68 AI For Pharma Growth</title></circle><circle cx="344" cy="168" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#69 AI For Humans: Making Artificial Intelligence Fun &amp; Practical</title></circle><circle cx="376" cy="168" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#70 NVIDIA AI Podcast</title></circle><circle cx="408" cy="168" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#71 Silicon Valley Girl: AI, Tech and Career Growth</title></circle><circle cx="440" cy="168" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#72 The AI Daily Brief: Artificial Intelligence News and Analysis</title></circle><circle cx="472" cy="168" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#73 Building AI Boston</title></circle><circle cx="504" cy="168" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#74 AI In Law</title></circle><circle cx="536" cy="168" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#75 AI for Kids</title></circle><circle cx="568" cy="168" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#76 SuperMarketers.ai: Your Roadmap to AI-Driven Marketing</title></circle><circle cx="600" cy="168" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#77 AI Unraveled: Latest AI News &amp; Trends, ChatGPT, Gemini, DeepSeek, Gen AI, LLMs, Agents, Ethics, Bias</title></circle><circle cx="632" cy="168" r="9" fill="#fefdfb" stroke="#8a8580" stroke-width="1" stroke-dasharray="3,2"><title>#78 Artificial Intelligence Exposed</title></circle><circle cx="664" cy="168" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#79 Practical: AI &amp; Business News</title></circle><circle cx="696" cy="168" r="9" fill="#fefdfb" stroke="#8a8580" stroke-width="1" stroke-dasharray="3,2"><title>#80 AI for Humanity</title></circle><circle cx="88" cy="200" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#81 Generative AI 101</title></circle><circle cx="120" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#82 AI Hustle: Make Money from AI and ChatGPT, Midjourney, NVIDIA, Anthropic, OpenAI</title></circle><circle cx="152" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#83 Matt Baber&#x27;s Artificial Intelligence Trends and News</title></circle><circle cx="184" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#84 The Robot Brains Podcast</title></circle><circle cx="216" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#85 Intel on AI</title></circle><circle cx="248" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#86 Ethics in AI</title></circle><circle cx="280" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#87 AI with AI: Artificial Intelligence with Andy Ilachinski</title></circle><circle cx="312" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#88 Medicine and the Machine</title></circle><circle cx="344" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#89 Unprompted: AI, Marketing and You</title></circle><circle cx="376" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#90 AI in Enterprise</title></circle><circle cx="408" cy="200" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#91 Rasa Chats</title></circle><circle cx="440" cy="200" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#92 A Woman in AI</title></circle><circle cx="472" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#93 The AI Future Show with Professor Andy Pardoe</title></circle><circle cx="504" cy="200" r="9" fill="#d49e3a" stroke="#742f37" stroke-width="1"><title>#94 Generation AI: Automating Better Business</title></circle><circle cx="536" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#95 The Artificial Podcast</title></circle><circle cx="568" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#96 The You+AI Podcast</title></circle><circle cx="600" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#97 The AI Element</title></circle><circle cx="632" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#98 Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science</title></circle><circle cx="664" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#99 Ask AI</title></circle><circle cx="696" cy="200" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#100 Learning Machines 101</title></circle><circle cx="88" cy="232" r="9" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"><title>#101 All Tomorrows</title></circle>
18<path d="M 354 72 H 356 a 8 8 0 0 1 8 8 V 280 a 8 8 0 0 0 8 8 H 404" fill="none" stroke="#742f37" stroke-width="1"/>
19<text x="412" y="292" font-family="Fraunces, serif" font-style="italic" font-size="14" fill="#742f37">No. 9: the first show with a woman on the mic</text>
20<path d="M 664 62 V 44 a 8 8 0 0 0 -8 -8 H 624" fill="none" stroke="#742f37" stroke-width="1"/>
21<text x="616" y="40" text-anchor="end" font-family="Fraunces, serif" font-style="italic" font-size="14" fill="#742f37">No. 19: the first show hosted only by women</text>
22<line x1="72" y1="320" x2="848" y2="320" stroke="#dedbd8" stroke-width="1"/>
23<circle cx="80" cy="336" r="6" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c"/><text x="94" y="340" font-family="DM Sans, sans-serif" font-size="12" fill="#5c5c5c">Every host is a man (76)</text>
24<circle cx="320" cy="336" r="6" fill="#d49e3a" stroke="#742f37"/><text x="334" y="340" font-family="DM Sans, sans-serif" font-size="12" fill="#5c5c5c">At least one woman hosting (22)</text>
25<circle cx="592" cy="336" r="6" fill="#fefdfb" stroke="#8a8580" stroke-dasharray="3,2"/><text x="606" y="340" font-family="DM Sans, sans-serif" font-size="12" fill="#5c5c5c">No host named (3)</text></svg><figcaption style="font-size: 13px; line-height: 1.5; color: #5c5c5c; margin-top: 12px;">Figure 1. Feedspot's “100 Best AI Podcasts,” one dot per show in the list's own order, reading left to right. Gold: at least one woman hosting. Grey: every host is a man. Dashed: no host we could resolve. Hover a dot for the show.</figcaption></figure>
26<h2 style="font-family: Fraunces, Georgia, serif; font-weight: 700; font-size: 30px; line-height: 1.2; color: #742f37; margin: 56px 0 20px 0;">How many AI podcasts are hosted by women?</h2>
27<p style="margin: 0 0 24px 0;">About one in five, on the lists people actually see. On Feedspot's list, the first show with a woman on the mic is number 9. The first show hosted only by women is number 19. Of the top 25, three have a woman hosting. Of the top 50, nine.</p>
28<figure style="margin: 32px 0 40px 0; padding: 24px 24px 16px 24px; border: 1px solid #dedbd8; background: #fefdfb;"><svg viewBox="0 0 880 304" width="100%" xmlns="http://www.w3.org/2000/svg" role="img" aria-label="Four lists compared: how many AI shows have every host a man versus at least one woman"><rect width="100%" height="100%" fill="#fefdfb"/><text x="264" y="58.0" text-anchor="end" font-family="DM Sans, sans-serif" font-size="13" font-weight="600" fill="#201e1d">Feedspot “100 Best AI Podcasts”</text><rect x="280" y="40" width="403.3" height="28" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"/><rect x="683.3" y="40" width="116.8" height="28" fill="#d49e3a" stroke="#742f37" stroke-width="1"/><rect x="800.1" y="40" width="15.9" height="28" fill="#fefdfb" stroke="#8a8580" stroke-width="1" stroke-dasharray="3,2"/><text x="481.7" y="58.0" text-anchor="middle" font-family="DM Sans, sans-serif" font-size="12" fill="#201e1d">76</text><text x="741.7" y="58.0" text-anchor="middle" font-family="DM Sans, sans-serif" font-size="12" font-weight="600" fill="#742f37">22</text><text x="828" y="58.0" font-family="DM Sans, sans-serif" font-size="12" fill="#8a8580">of 101</text><text x="264" y="110.0" text-anchor="end" font-family="DM Sans, sans-serif" font-size="13" font-weight="600" fill="#201e1d">Apple Podcasts · Technology top 200</text><rect x="280" y="92" width="325.1" height="28" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"/><rect x="605.1" y="92" width="114.2" height="28" fill="#d49e3a" stroke="#742f37" stroke-width="1"/><rect x="719.3" y="92" width="96.7" height="28" fill="#fefdfb" stroke="#8a8580" stroke-width="1" stroke-dasharray="3,2"/><text x="442.6" y="110.0" text-anchor="middle" font-family="DM Sans, sans-serif" font-size="12" fill="#201e1d">37</text><text x="662.2" y="110.0" text-anchor="middle" font-family="DM Sans, sans-serif" font-size="12" font-weight="600" fill="#742f37">13</text><text x="828" y="110.0" font-family="DM Sans, sans-serif" font-size="12" fill="#8a8580">of 61</text><text x="264" y="162.0" text-anchor="end" font-family="DM Sans, sans-serif" font-size="13" font-weight="600" fill="#201e1d">Apple Podcasts · Technology top 50</text><rect x="280" y="144" width="247.4" height="28" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"/><rect x="527.4" y="144" width="164.9" height="28" fill="#d49e3a" stroke="#742f37" stroke-width="1"/><rect x="692.3" y="144" width="123.7" height="28" fill="#fefdfb" stroke="#8a8580" stroke-width="1" stroke-dasharray="3,2"/><text x="403.7" y="162.0" text-anchor="middle" font-family="DM Sans, sans-serif" font-size="12" fill="#201e1d">6</text><text x="609.8" y="162.0" text-anchor="middle" font-family="DM Sans, sans-serif" font-size="12" font-weight="600" fill="#742f37">4</text><text x="828" y="162.0" font-family="DM Sans, sans-serif" font-size="12" fill="#8a8580">of 13</text><text x="264" y="214.0" text-anchor="end" font-family="DM Sans, sans-serif" font-size="13" font-weight="600" fill="#201e1d">Spotify · Technology top 50</text><rect x="280" y="196" width="268.0" height="28" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c" stroke-width="1"/><rect x="548.0" y="196" width="214.4" height="28" fill="#d49e3a" stroke="#742f37" stroke-width="1"/><rect x="762.4" y="196" width="53.6" height="28" fill="#fefdfb" stroke="#8a8580" stroke-width="1" stroke-dasharray="3,2"/><text x="414.0" y="214.0" text-anchor="middle" font-family="DM Sans, sans-serif" font-size="12" fill="#201e1d">5</text><text x="655.2" y="214.0" text-anchor="middle" font-family="DM Sans, sans-serif" font-size="12" font-weight="600" fill="#742f37">4</text><text x="828" y="214.0" font-family="DM Sans, sans-serif" font-size="12" fill="#8a8580">of 10</text><line x1="72" y1="270" x2="856" y2="270" stroke="#dedbd8" stroke-width="1"/>
29<rect x="72" y="280" width="14" height="10" fill="rgba(92,92,92,0.14)" stroke="#5c5c5c"/><text x="94" y="289" font-family="DM Sans, sans-serif" font-size="12" fill="#5c5c5c">Every host is a man</text>
30<rect x="248" y="280" width="14" height="10" fill="#d49e3a" stroke="#742f37"/><text x="270" y="289" font-family="DM Sans, sans-serif" font-size="12" fill="#5c5c5c">At least one woman or they/them host</text>
31<rect x="512" y="280" width="14" height="10" fill="#fefdfb" stroke="#8a8580" stroke-dasharray="3,2"/><text x="534" y="289" font-family="DM Sans, sans-serif" font-size="12" fill="#5c5c5c">Unresolved, AI-narrated, or no host named</text></svg><figcaption style="font-size: 13px; line-height: 1.5; color: #5c5c5c; margin-top: 12px;">Figure 2. Three sources, with an additional view of Apple's top 50. Bars are drawn to each list's own total, so the widths compare shares, and the labels give the counts. The dashed remainder is shows we could not resolve, shows with 

31no human host, and listings that name nobody.</figcaption></figure>
32<p style="margin: 0 0 24px 0;">The rows don't add up to the total on purpose. The gap is shows where we couldn't confirm a host, shows that name no host at all, and three shows with no human host. More on those below.</p>
33<p style="margin: 0 0 24px 0;">Spotify had the highest share in this snapshot, and it's four shows out of ten. At matched depth, that's four of ten on Spotify against four of thirteen on Apple's top 50, so read it as four shows, not as one app favouring women. One of those four, I've Got Questions with Sinead Bovell, sits at number 9 on Spotify and doesn't appear on Apple's Technology chart at all. Same podcast, same week, one app puts her in the top ten and the other doesn't put her in the top 200.</p>
34<h2 style="font-family: Fraunces, Georgia, serif; font-weight: 700; font-size: 30px; line-height: 1.2; color: #742f37; margin: 56px 0 20px 0;">Which AI podcasts are hosted by women?</h2>
35<p style="margin: 0 0 24px 0;">These are the shows, with the list position and the hosts credited on September 13, 2026.</p>
36<p style="margin: 0 0 24px 0;"><strong>On Feedspot's "100 Best AI Podcasts" (22 of 101):</strong> 9 <a href="https://podcasters.spotify.com/pod/show/artificiality/">Artificiality</a> (Helen Edwards, Dave Edwards) · 17 <a href="https://podcasters.spotify.com/pod/show/alldus-international">The Alldus Podcast</a> (JP Valentine, Ailsa Cassie) · 19 <a href="https://pondering-ai.transistor.fm/episodes">Pondering AI</a> (Kimberly Nevala) · 26 <a href="https://aiaustralia.libsyn.com/">AI Australia</a> (Emma Bromet, Kathryn Collier) · 30 <a href="https://podcasts.apple.com/us/podcast/id1611998381">The AI with Maribel Lopez</a> (Maribel Lopez) · 36 <a href="https://podcasts.apple.com/us/podcast/no-priors-artificial-intelligence-technology-startups/id1668002688">No Priors</a> (Elad Gil, Sarah Guo) · 39 <a href="https://www.bbc.co.uk/programmes/m001wjf8/episodes/player">The Artificial Human</a> (Aleks Krotoski, Kevin Fong) · 44 <a href="https://www.heavybit.com/library/podcasts/generationship/">Generationship</a> (Rachel Chalmers) · 46 <a href="https://podcasters.spotify.com/pod/show/squirro/">Redefining AI</a> (Lauren Hawker Zafer) · 59 <a href="https://podcasts.apple.com/us/podcast/the-ai-chicks/id1727013037">The AI Chicks</a> (Lana Hout, Aisha Corpas Wynn) · 60 <a href="https://podcasts.apple.com/us/podcast/decoding-ai-for-marketing/id1715735755">Decoding AI for Marketing</a> (Greg Stuart, Rex Briggs, Mary Dooe) · 62 <a href="https://podcasts.apple.com/ca/podcast/approximately-correct-an-ai-podcast-from-amii/id1725553442">Approximately Correct</a> (Alona Fyshe, Scott Lilwall) · 64 <a href="https://podcasts.apple.com/us/podcast/how-i-ai/id1809663079">How I AI</a> (Claire Vo) · 65 <a href="https://podcasts.apple.com/us/podcast/pioneers-of-ai/id1763085968">Pioneers of AI</a> (Rana el Kaliouby) · 68 <a href="https://podcasts.apple.com/us/podcast/ai-for-pharma-growth/id1616728442">AI For Pharma Growth</a> (Andree Bates) · 71 <a href="https://podcasts.apple.com/us/podcast/silicon-valley-girl-ai-tech-and-career-growth/id1819090545">Silicon Valley Girl</a> (Marina Mogilko) · 73 <a href="https://www.buildingaiboston.com/">Building AI Boston</a> (Anna Devere, Chris DeVito, Kara Peterson) · 75 <a href="https://podcasts.apple.com/us/podcast/ai-for-kids/id1745917083">AI for Kids</a> (Amber Ivey) · 81 <a href="https://podcasts.apple.com/us/podcast/generative-ai-101/id1750985562">Generative AI 101</a> (Emily Laird) · 91 <a href="https://podcasters.spotify.com/pod/show/rasachats">Rasa Chats</a> (Rachael Tatman) · 92 <a href="https://podcasts.apple.com/de/podcast/a-woman-in-ai/id1533411604">A Woman in AI</a> (Kim Dressendoerfer) · 94 <a href="https://www.spreaker.com/podcast/generation-ai-automating-better-business--5896573">Generation AI</a> (Ruth Zive, Nirali Amin)</p>
37<p style="margin: 0 0 24px 0;"><strong>On Apple's Technology chart (13 of 61 AI shows):</strong> 13 <a href="https://podcasts.apple.com/us/podcast/building-ai-boston/id1787830122">Building AI Boston</a> · 26 <a href="https://podcasts.apple.com/us/podcast/the-in-between-tech-and-trust-podcast/id1828521905">The In-Between Tech and Trust Podcast</a> (Eva Simone Lihotzky) · 44 <a href="https://podcasts.apple.com/us/podcast/life-automated/id6783436225">Life, Automated</a> (Jess Love) · 46 <a href="https://podcasts.apple.com/us/podcast/prohuman-governing-the-global-ai-revolution/id1896832160">ProHuman</a> (presenter Ibby Caputo, with Mary Robinson, Helen Clark, Zeid Ra'ad Al Hussein, Juan Manuel Santos) · 54 <a href="https://podcasts.apple.com/us/podcast/no-priors-artificial-intelligence-technology-startups/id1668002688">No Priors</a> · 55 <a href="https://podcasts.apple.com/us/podcast/how-i-ai/id1809663079">How I AI</a> · 86 <a href="https://podcasts.apple.com/us/podcast/intelligent-machines-audio/id326120877">Intelligent Machines</a>

37 (Leo Laporte, Jeff Jarvis, Paris Martineau) · 88 <a href="https://podcasts.apple.com/us/podcast/critical-thinking-in-the-age-of-ai/id1865503703">Critical Thinking in the Age of AI</a> (Shae O. Omonijo) · 114 <a href="https://podcasts.apple.com/us/podcast/mystery-ai-hype-theater-3000/id1690426042">Mystery AI Hype Theater 3000</a> (Emily M. Bender, Alex Hanna) · 119 <a href="https://podcasts.apple.com/us/podcast/the-deep-view-conversations/id1769262461">The Deep View: Conversations</a> (Jason Hiner, Sabrina Ortiz, Nat Rubio-Licht) · 146 <a href="https://podcasts.apple.com/us/podcast/silicon-valley-girl-ai-tech-and-career-growth/id1819090545">Silicon Valley Girl</a> · 149 <a href="https://podcasts.apple.com/us/podcast/understood-artificial-intimacy/id1673817105">Understood: Artificial Intimacy</a> (Victoria Hetherington) · 175 <a href="https://podcasts.apple.com/us/podcast/training-data/id1750736528">Training Data</a> (Sonya Huang, Pat Grady)</p>
38<p style="margin: 0 0 24px 0;"><strong>On Spotify's Technology chart (4 of 10 AI shows):</strong> 9 I've Got Questions with Sinead Bovell · 24 How I AI · 36 Silicon Valley Girl · 49 Training Data.</p>
39<h2 style="font-family: Fraunces, Georgia, serif; font-weight: 700; font-size: 30px; line-height: 1.2; color: #742f37; margin: 56px 0 20px 0;">Why we counted</h2>
40<p style="margin: 0 0 24px 0;">A listener named Alexis Palmer left us a voicemail this summer. She'd heard our episode where one of us raved about a show called How I AI and credited it to Lenny Rachitsky. Alexis wanted us to know that How I AI is hosted by Claire Vo. It's part of Lenny's network, but Claire is the host, and, in Alexis's words, she should get as much recognition as possible.</p>
41<p style="margin: 0 0 24px 0;">She was right. We'd done the thing we complain about. A woman built the show, and we handed the credit to the famous man standing next to it.</p>
42<p style="font-family: Fraunces, Georgia, serif; font-size: 26px; font-style: italic; color: #742f37; margin: 8px 0 32px 0;">So we counted.</p>
43<p style="margin: 0 0 24px 0;">

43Three lists. The first is what Google hands you when you search "best AI podcasts": Feedspot's "100 Best Artificial Intelligence Podcasts," which is actually 101 entries. The other two are what you see inside the apps: the Technology chart on Apple Podcasts and the Technology chart on Spotify, US, on one day in September. Neither app has an AI category, so we took every English-language show on those charts that is actually about AI (AI in the title, or in the first sentence of its description, or mentioned repeatedly up top) and set the rest aside. Then we looked up who hosts each one. Not who founded it, not who the network is. Who is on the mic right now, as credited on the show's own page.</p>
44<h2 style="font-family: Fraunces, Georgia, serif; font-weight: 700; font-size: 30px; line-height: 1.2; color: #742f37; margin: 56px 0 20px 0;">What surprised us</h2>
45
46<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); gap: 20px; margin: 32px 0 40px 0;">
47  <div style="background: #ffffff; border: 1px solid #dedbd8; padding: 20px;">
48    <p style="font-size: 11px; letter-spacing: 0.12em; text-transform: uppercase; color: #8a8580; margin: 0 0 12px 0;">No human host</p>
49    <p style="font-family: Fraunces, Georgia, serif; font-size: 40px; line-height: 1; font-weight: 700; color: #742f37; margin: 0 0 12px 0;">3</p>
50    <p style="font-size: 15px; line-height: 1.5; margin: 0;">AI podcasts on Apple's Technology chart are AI-narrated. A fourth, at number 3, names no host at all. All three confirmed ones sit below rank 100, for now.</p>
51  </div>
52  <div style="background: #ffffff; border: 1px solid #dedbd8; padding: 20px;">
53    <p style="font-size: 11px; letter-spacing: 0.12em; text-transform: uppercase; color: #8a8580; margin: 0 0 12px 0;">Same show, two charts</p>
54    <p style="font-family: Fraunces, Georgia, serif; font-size: 40px; line-height: 1; font-weight: 700; color: #742f37; margin: 0 0 12px 0;">#9 vs. —</p>
55    <p style="font-size: 15px; line-height: 1.5; margin: 0;">I've Got Questions with Sinead Bovell is ninth on Spotify's Technology chart and absent from Apple's top 200.</p>
56  </div>
57  <div style="background: #ffffff; border: 1px solid #dedbd8; padding: 20px;">
58    <p style="font-size: 11px; letter-spacing: 0.12em; text-transform: uppercase; color: #8a8580; margin: 0 0 12px 0;">AI's share of “technology”</p>
59    <p style="font-family: Fraunces, Georgia, serif; font-size: 40px; line-height: 1; font-weight: 700; color: #742f37; margin: 0 0 12px 0;">13 of 50</p>
60    <p style="font-size: 15px; line-height: 1.5; margin: 0;">Apple's top 50 Technology shows that are about AI. Spotify: 10 of 50. The rest is All-In, Acquired, Darknet Diaries, Hard Fork.</p>
61  </div>
62</div>
63<p style="margin: 0 0 24px 0;"><strong>The lists are wrong more often than you'd think.</strong> Feedspot's number 48 credits a host who, as far as every platform can tell, doesn't host it. Two of its entries name their hosts by first name only, and one of those shows now credits someone else entirely. Two shows on Feedspot's list have changed hosts since the list credited them, and the list never noticed. Apple's chart has an AI show at number 89 whose last episode was in 2023.</p>
64<h2 style="font-family: Fraunces, Georgia, serif; font-weight: 700; font-size: 30px; line-height: 1.2; color: #742f37; margin: 56px 0 20px 0;">Who to add to your listening</h2>
65<p style="margin: 0 0 24px 0;">Here are a few women we think you should hear. Each is on the charts above, and each is now on our <a href="https://womansplainingai.com/best-ai-podcasts">list of AI podcasts that aren't bro-y</a>, with a start-here episode.</p>
66<ul style="margin: 0 0 24px 0; padding-left: 22px;"><li style="margin: 0 0 12px 0;"><strong>Claire Vo, How I AI.</strong> Start with "Build your own company brain: the enterprise AI playbook from Stripe's engineering team" (September 7, 2026). Thirty minutes, live screen-sharing, one specific thing a guest actually does with AI at work.</li><li style="margin: 0 0 12px 0;"><strong>Sinead Bovell, I've Got Questions.</strong> Start with "Are we betting too much on AI?" with Nobel laureate Daron Acemoglu (September 3, 2026). Whether the money flooding into AI ends in inequality and job loss, or whether different design choices could raise wages too.</li><li style="margin: 0 0 12px 0;"><strong>Emily M. Bender and Alex Hanna, Mystery AI Hype Theater 3000.</strong> Start with "Who's Responsible for 'Responsible AI'?" with sava saheli singh (August 4, 2026). A linguist and a sociologist taking the hype apart, this time the "harm reduction" framing around AI in schools.</li><li style="margin: 0 0 12px 0;"><strong>Kimberly Nevala, Pondering AI.</strong> Start with "Ethical Imagination" with Renée Cummings, episode 100 (July 22, 2026). What an AI future would look like if its benefits actually reached everyone.</li></ul>
67<p style="margin: 0 0 24px 0;">Our own mistake tells us something narrower than the charts do: 

67we knew Claire Vo's work and still gave Lenny the credit. We can start there. Get the host's name right. Say what her work helped us understand. Recommend an episode worth someone else's time.</p>
68<p style="margin: 0 0 24px 0;">If you host a show we should have counted, or we got your host wrong, leave us a message on the <a href="https://womansplainingai.com/answering-machine">answering machine</a> or reach us through <a href="https://womansplainingai.com/connect">the contact page</a>. We'll fix the count and say so.</p>
69<h2 style="font-family: Fraunces, Georgia, serif; font-weight: 700; font-size: 30px; line-height: 1.2; color: #742f37; margin: 56px 0 20px 0;">What this doesn't tell you</h2>
70<p style="margin: 0 0 24px 0;">It doesn't tell you how many people listen. We counted shows, not listeners. Apple says its chart reflects listening, follows and completions; Spotify describes its rankings in terms of weekly audience. Neither number is in our count.</p>
71<p style="margin: 0 0 24px 0;">It doesn't tell you a show is good because a woman hosts it, or bad because a man does. Some of the best AI podcasts we know are hosted by men and we put them on our own list. And it doesn't tell you why the lists look this way.</p>
72<h2 style="font-family: Fraunces, Georgia, serif; font-weight: 700; font-size: 30px; line-height: 1.2; color: #742f37; margin: 56px 0 20px 0;">How we classified hosts</h2>
73<p style="margin: 0 0 24px 0;">We didn't guess from names or photos. For most hosts, we found a sentence on a public page, their bio, their university profile, their own site, where the page says "she" or "he" or "they" about them. We quoted it and saved the link. Eighteen hosts had no such sentence we could reach, usually because LinkedIn and personal sites block automated reading, and Logan classified those by hand; they're marked as manual in the data. Where neither worked, the host is listed as unknown, and unknowns are never counted as men.</p>
74<p style="margin: 0 0 24px 0;">"At least one woman hosting" means at least one current host is female-presenting by that evidence. One host, Nat Rubio-Licht of The Deep View, uses they/them. We report that separately rather than folding it into the women's count; The Deep View is counted as woman-hosted because Sabrina Ortiz co-hosts.</p>
75<p style="margin: 0 0 24px 0;">This is a proxy. Pronouns on a website are evidence of what a person's public bio says. We'd rather use the imperfect measure and show our work than skip the question. If we've got you wrong, tell us and we'll fix it.</p>
76<p style="margin: 0 0 24px 0; padding: 20px 24px; background: #f3f1ed; border-top: 2px solid #d49e3a;"><strong>The data.</strong> Every show, every host, every quoted sentence and its link, the method, and a log of what we corrected after two outside reviews are available on request through <a href="https://womansplainingai.com/connect">the contact page</a>.</p><div style="margin-top: 56px; padding-top: 24px; border-top: 1px solid #dedbd8; font-size: 14px; line-height: 1.6; color: #5c5c5c;"><p style="margin: 0;"><em>How we did it, short version.</em> Feedspot's list was read on September 13, 2026. Apple's US Technology top 200 and Spotify's US Technology top 50 were pulled the same day from the charts the apps publish. A show counted as an AI show if AI, machine learning, GPT, LLM, OpenAI, Anthropic, Claude, or chatbot appeared in its title or first sentence, or twice in its opening description; nine shows were set aside by hand (security shows, general tech shows where AI is a side topic, one Chinese-language show) and we list them. The study is English-language. Hosts are whoever the show's own page credits on that date. Gender presentation comes from pronouns used about the host on a public page, quoted and linked; eighteen hosts were classified manually and are marked as such. Every quote was re-checked against its page. One label was withdrawn when the page turned out not to carry a pronoun. Unknowns are reported as unknown.</p></div>`,faqs:[{question:"How many AI podcasts are hosted by women?",answer:`About one in five, on the lists people actually see (September 13, 2026). On Feedspot's "100 Best AI Podcasts" (101 entries), 22 have at least one woman hosting and 76 are hosted only by men. On Apple Podcasts' US Technology chart, 13 of the 

7661 AI-focused shows have a woman hosting. On Spotify's US Technology chart, 4 of 10. About one in five, on the lists people actually see. On Feedspot's list, the first show with a woman on the mic is number 9. The first show hosted only by women is number 19. Of the top 25, three have a woman hosting. Of the top 50, nine.`},{question:"Which AI podcasts are hosted by women?",answer:"On Feedspot's list: 9 Artificiality (Helen Edwards, Dave Edwards) · 17 The Alldus Podcast (JP Valentine, Ailsa Cassie) · 19 Pondering AI (Kimberly Nevala) · 26 AI Australia (Emma Bromet, Kathryn Collier) · 30 The AI with Maribel Lopez (Maribel Lopez) · 36 No Priors (Elad Gil, Sarah Guo) · 39 The Artificial Human (Aleks Krotoski, Kevin Fong) · 44 Generationship (Rachel Chalmers) · 46 Redefining AI (Lauren Hawker Zafer) · 59 The AI Chicks (Lana Hout, Aisha Corpas Wynn) · 60 Decoding AI for Marketing (Greg Stuart, Rex Briggs, Mary Dooe) · 62 Approximately Correct (Alona Fyshe, Scott Lilwall) · 64 How I AI (Claire Vo) · 65 Pioneers of AI (Rana el Kaliouby) · 68 AI For Pharma Growth (Andree Bates) · 71 Silicon Valley Girl (Marina Mogilko) · 73 Building AI Boston (Anna Devere, Chris DeVito, Kara Peterson) · 75 AI for Kids (Amber Ivey) · 81 Generative AI 101 (Emily Laird) · 91 Rasa Chats (Rachael Tatman) · 92 A Woman in AI (Kim Dressendoerfer) · 94 Generation AI (Ruth Zive, Nirali Amin). On Apple's Technology chart: 13 Building AI Boston · 26 The In-Between Tech and Trust Podcast (Eva Simone Lihotzky) · 44 Life, Automated (Jess Love) · 46 ProHuman (presenter Ibby Caputo, with Mary Robinson, Helen Clark, Zeid Ra'ad Al Hussein, Juan Manuel Santos) · 54 No Priors · 55 How I AI · 86 Intelligent Machines (Leo Laporte, Jeff Jarvis, Paris Martineau) · 88 Critical Thinking in the Age of AI (Shae O. Omonijo) · 114 Mystery AI Hype Theater 3000 (Emily M. Bender, Alex Hanna) · 119 The Deep View: Conversations (Jason Hiner, Sabrina Ortiz, Nat Rubio-Licht) · 146 Silicon Valley Girl · 149 Understood: Artificial Intimacy (Victoria Hetherington) · 175 Training Data (Sonya Huang, Pat Grady). On Spotify's Technology chart: I've Got Questions with Sinead Bovell, How I AI, Silicon Valley Girl, Training Data."},{question:"Are the best AI podcasts mostly hosted by men?",answer:"On the three lists we counted, yes. 76 of 101 shows on Feedspot's list, 37 of 61 AI shows on Apple's Technology chart, and 5 of 10 on Spotify's are hosted only by men. The first show with a woman on the mic on Feedspot's list is number 9; the first hosted only by women is number 19."},{question:"How did Womansplaining AI decide who counts as a woman host?",answer:"From pronouns used about the host on a public page (a bio, a university profile, the host's own site), quoted and linked. Eighteen hosts with no reachable sentence were classified manually and are marked as such. Unknowns are reported as unknown and never counted as men. A they/them host is reported separately, not counted as a woman."}]},nN={initial:{opacity:0,y:20},animate:{opacity:1,y:0},transition:{duration:.6,ease:"easeOut"}};function oN(){const e=`https://womansplainingai.com/${Ze.slug}`;return{"@context":"https://schema.org","@graph":[{"@type":"Article","@id":`${e}#article`,headline:Ze.title,description:Ze.description,author:[{"@type":"Person",name:"Logan Currie",url:"https://www.logancurrie.com"},{"@type":"Person",name:"Mara Bolis",url:"https://cyber.harvard.edu/people/mara-bolis"}],publisher:{"@type":"Organization",name:"Womansplaining AI",url:"https://womansplainingai.com"},datePublished:Ze.datePublished,dateModified:Ze.dateModified,keywords:Ze.keywords,mainEntityOfPage:e},{"@type":"FAQPage","@id":`${e}#faq`,mainEntity:Ze.faqs.map(n=>({"@type":"Question",name:n.question,acceptedAnswer:{"@type":"Answer",text:n.answer}}))}]}}function sN(){return ze({title:`${Ze.shortTitle}: We Counted. It's Mostly Guys. | Womansplaining AI`,description:Ze.description,path:`/${Ze.slug}`,ogTitle:Ze.title,ogDescription:Ze.description,ogType:"article"}),r.jsxs("div",{className:"min-h-screen bg-background",children:[r.jsx("script",{type:"application/ld+json",dangerouslySetInnerHTML:{__html:JSON.stringify(oN())}}),r.jsx(q.section,{...nN,className:"bg-primary text-primary-foreground pt-20 pb-12 sm:pb-16",children:r.jsxs("div",{className:"max-w-3xl mx-auto px-4 sm:px-6",children:[r.jsx("p",{className:"text-accent text-sm font-medium mb-3 uppercase tracking-wide",children:Ze.kicker}),r.jsx("h1",{className:"text-3xl sm:text-4xl md:text-5xl font-serif font-bold mb-6 leading-tight",children:Ze.title}

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We update this list with every new episode."}),r.jsx(Z,{href:"/connect",children:r.jsx("span",{className:"inline-flex items-center gap-2 bg-primary text-primary-foreground px-6 py-3 rounded-lg font-medium hover:bg-primary/90 transition-colors cursor-pointer",children:"Send us a source"})})]})]}),r.jsx(Be,{})]})}const Er=[{slug:"jessica-silbey",name:"Jessica Silbey",title:"Professor of Law",org:"Boston University School of Law",credential:"Guggenheim Fellow",bio:`Jessica Silbey is a professor at Boston University School of Law, where she is also Associate Dean for Intellectual Life, and a 2018 Guggenheim Fellow whose work sits at the intersection of intellectual property, technology, and institutional design. Her paper with Woody Hartzog, "How AI Destroys Institutions," has been downloaded more than 35,000 times — an extraordinary number for a legal academic paper. She set out to write an optimistic paper about AI's potential benefits to institutions and couldn't; what she found instead was that AI's core features — opacity, speed, scale, and optimization — are structurally incompatible with the transparency, cooperation, and accountability that institutions require to function. Silbey holds a law degree and a PhD in comparative literature from the University of Michigan, with a focus on French and Russian literature at the turn of the 20th century, and is the author of "Against Progress" (2022) and "The Eureka Myth" (2015). She brings a rare humanities lens to AI governance.`,cardBio:'Professor of Law and Associate Dean for Intellectual Life at BU Law, and a 2018 Guggenheim Fellow. Her paper with Woody Hartzog, "How AI Destroys Institutions," has been downloaded more than 35,000 times, which does not happen to legal academic papers.',headshot:"/guests/jessica-silbey.jpg",clip:{src:"/clips/jessica-silbey.mp4",poster:"/clips/jessica-silbey.jpg",title:"“AI is incapable of intellectual risk” — no skin in the game, no stakes"},topics:["AI & law","intellectual property","institutional accountability","AI copyright","AI transparency"],pullQuotes:["AI is incapable of intellectual risk — no skin in the game, no breakthroughs.","The saving time thing is a lie.","Efficiency is the enemy of equality."],links:[{label:'"How AI Destroys Institutions" (with Woody Hartzog) — SSRN, 33,000+ downloads',url:"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5870623"},{label:'"The Upside of Deep Fakes" (with Woody Hartzog, 2019)',url:"https://scholarship.law.bu.edu/faculty_scholarship/1072/"}],socials:["https://www.bu.edu/law/profile/jessica-silbey/","https://www.linkedin.com/in/jessica-silbey-48060010/"],episodeSlugs:["33000-downloads-ai-destroys-institutions"]},{slug:"wanjiku-kamau",name:"Wanjiku Kamau",title:"Author & Founder",org:"TealBridge (formerly Siemens, Intel, Google)",bio:`Wanjiku Kamau spent two decades in enterprise technology at Siemens, Intel, and Google, working in finance and operations. When Google laid her off in 2025, she was thirteen days into using ChatGPT — and a political organization needed a website that vendors had quoted at two weeks and $3,000. She shipped it in 48 hours and unveiled it live in a board meeting. Ninety days later she had written "Out of the Loop, Into the Algorithm: How I Finally Made Friends with AI" (November 2025), voice-noting 80% of it while walking her dog and using AI as a dictation partner, not a ghostwriter; it hit #1 in Amazon's Job Hunting category. A first-generation Kenyan American based in New York, she now runs TealBridge, an AI consulting practice for founders and civic leaders, and TealVoice, the storytelling studio that published her book. Her story — including a 45-minute hair-salon conversation with a young single mother that opened up a GED program and childcare subsidies — is the one to send to anyone who thinks AI isn't for them.`,cardBio:"Two decades in finance and operations at Siemens, Intel, and Google. Thirteen days into ChatGPT after a layoff, she shipped a website in 48 hours, then wrote a book that hit #1 in Amazon's Job Hunting category.",headshot:"/guests/wanjiku-kamau.jpg",clip:{src:"/clips/wanjiku-kamau.mp4",poster:"/clips/wanjiku-kamau.jpg",title:"“What a relief to not have to raise my hand”"},topics:["AI career transition","enterprise technology","AI accessibility","AI book writing"],pullQuotes:["What a relief to not have to raise my hand."],links:[{label:'"Out of the Loop, Into the Algorithm: How I Finally Made Friends with AI"',url:"https://latetothepartybook.com/"},{label:"TealBridge — AI consulting",url:"https://tealbridge.co/"}],socials:["https://www.linkedin.com/in/wanjikukamau/","https://tealbridge.co/"],episodeSlugs:["relief-not-raise-hand"]},{slug:"kathryn-hulick",name:"Kathryn Hulick",title:"Science Journalist",org:"Science News / Science News Explores",bio:`Kathryn Hulick is a science journalist who has covered artificial intelligence since the 2010s, contributing to Science News, Science News Explores, and BBC Science Focus, with a monthly technology column as contributing editor at Muse magazine. She is the author of science books for young readers including "Artificial Intelligence" (2016) and "Welcome to the Future: Robot Friends, Fusion Energy, Pet Dinosaurs, and More!" (2021). On Womansplaining AI (she is also Logan's cousin) she argues that every output of a large language model is technically a hallucination, that cognitive offloading to AI has quietly become the default, and that we lose something real when we hand the messy middle of writing over to a machine.`,cardBio:"Science journalist who has covered AI since the 2010s for Science News, Science News Explores, and BBC Science Focus, and a contributing editor at Muse. Author of Welcome to the Future and The UFO Files, after two years in the Peace Corps in Kyrgyzstan without internet.",headshot:"/guests/kathryn-hulick.jpg",clip:{src:"/clips/kathryn-hulick.mp4",poster:"/clips/kathryn-hulick.jpg",title:"Why every AI output is technically a hallucination"},topics:["AI journalism","AI hallucination","cognitive offloading","writing and AI"],pullQuotes:["I wish the general public did not get a hold of AI when they did. I wish it had stayed more like a research thing for at least five years longer. Maybe ten."],links:[{label:"Science News (contributor)",url:"https://www.sciencenews.org"}],socials:["https://kathrynhulick.com/","https://www.linkedin.com/in/kathryngargolinski/"],episodeSlugs:["the-robots-never-tell-you

81-youre-the-asshole"]},{slug:"julie-wenah",name:"Julie Wenah",title:"Digital Civil Rights Lawyer & Chairwoman",org:"Digital Civil Rights Coalition",bio:"Julie Wenah is a digital civil rights lawyer whose career runs through the Obama White House (the Office of the First Lady), NASA, Airbnb, and Meta. At Airbnb she was counsel to the anti-discrimination product and trust and safety teams, work that contributed to Project Lighthouse; at Meta she worked on the first generation of Ray-Ban smart glasses that launched in 2021. She now chairs the Digital Civil Rights Coalition and serves on the FCC's Communications Equity and Diversity Council. On Womansplaining AI, recorded at Human+Tech Week, she lays out the future she is trying to head off: a world where your face is scanned for a job or a loan, and a higher facial-recognition error margin for darker skin tones quietly becomes a worse outcome.",cardBio:"Digital civil rights lawyer by way of the Obama White House, NASA, Airbnb, and Meta, where she worked on the first Ray-Ban smart glasses. Chairs the Digital Civil Rights Coalition and sits on the FCC's Communications Equity and Diversity Council.",headshot:"/guests/julie-wenah.jpg",clip:{src:"/clips/julie-wenah.mp4",poster:"/clips/julie-wenah.jpg",title:"“An 18% margin of error” — how facial-recognition bias becomes a higher interest rate"},topics:["digital civil rights","facial recognition","algorithmic bias","AI and discrimination"],pullQuotes:[],links:[{label:"juliewenah.com",url:"https://www.juliewenah.com/"},{label:"Digital Civil Rights Coalition",url:"https://www.digitalcivilrights.com/"}],socials:["https://www.juliewenah.com/","https://www.linkedin.com/in/juliewenah/"],episodeSlugs:["move-fast-and-break-rights"]},{slug:"karina-alexanyan",name:"Dr. Karina Alexanyan",title:"Founding Executive Director",org:"Positive Technology Institute",credential:"Co-creator, the Positive Technology Pledge",bio:`Dr. Karina Alexanyan is the Founding Executive Director of the Positive Technology Institute and a co-creator of the Positive Technology Pledge, a "Hippocratic Oath" for technology — a Gen X social scientist immune to the "learn AI now or get left behind" panic. She holds a PhD in communications from Columbia, spent years at Stanford's mediaX fostering multidisciplinary research collaborations, and has served as Director of Strategy at All Tech Is Human. On Womansplaining AI she makes the case for AI enfranchisement — women having a real say in how these tools get deployed, not just permission to use them — and names the divide she won't stay quiet about: AI safety skews white and male while AI ethics skews women, people of color, and marginalized communities.`,cardBio:"Founding Executive Director of the Positive Technology Institute and co-creator of the Positive Technology Pledge, a Hippocratic Oath for technology. Columbia PhD, years at Stanford's mediaX, and former Director of Strategy at All Tech Is Human.",headshot:"/guests/karina-alexanyan.jpg",clip:{src:"/clips/karina-alexanyan.mp4",poster:"/clips/karina-alexanyan.jpg",title:"“AI safety people are usually white guys” — the safety vs. ethics divide"},topics:["AI ethics","AI enfranchisement","positive technology","women in AI"],pullQuotes:["AI safety people are usually white guys. AI ethics people are mostly women, people of color, and marginalized communities. We feel the damages now."],links:[{label:"Positive Technology Institute",url:"https://www.positivetechinstitute.org/"}],socials:["https://www.positivetechinstitute.org/","https://www.linkedin.com/in/karinaalexanyan/"],episodeSlugs:["is-ai-just-spicy-autocorrect"]},{slug:"vanessa-chang",name:"Vanessa Chang",title:"Co-founder",org:"Bernie",bio:"Vanessa Chang is the co-founder of Bernie, an SMS tool that helps older adults spot fraud and scams — built, as she says on the episode, for anyone who has parents they worry about. Three years earlier she wasn't working in AI at all. She calls herself an unlikely AI startup founder, and her whole thing is helping people think with AI, not like it: use it well, and still love it enough to call it out for its BS. She also runs Mosaek, an AI consulting practice, and writes Think with V, a newsletter about AI and how we think. On Womansplaining AI, recorded live at Human+Tech Week in San Francisco, she makes the case that agency means exercising your choice and acting on it — what it looks like when you stop debating AI and actually go build something with it.",cardBio:"

81Co-founder of Bernie, an SMS tool that helps older adults spot scams, and the writer behind Think with V. Three years ago she wasn't working in AI at all, which is the point.",headshot:"/guests/vanessa-chang.jpg",clip:{src:"/clips/vanessa-chang.mp4",poster:"/clips/vanessa-chang.jpg",title:"“No woman has a fantasy of being more productive”"},topics:["AI agency","fraud protection for seniors","building with AI","women in AI"],pullQuotes:["Agency doesn't come from standing still.","No woman has a fantasy of being more productive."],links:[{label:"Bernie — SMS fraud protection for seniors",url:"https://www.textbernie.me/"},{label:"Think with V",url:"https://vanessachang.com/"}],socials:["https://vanessachang.com/","https://www.linkedin.com/in/vanessachang/"],episodeSlugs:["shadow-daddy-chatgpt"]},{slug:"emily-janoch",name:"Emily Janoch",title:"AVP of Research and Evaluation",org:"CARE",bio:"Emily Janoch leads evidence and learning at CARE — yes, the Care Package people — after 15 years in the development sector, including four years of field work in West Africa. Trained at the Harvard Kennedy School, she hosts CARE Failing Forward, the rare aid-world podcast where people admit on the record what went wrong, and has spent the last year interviewing people about AI and technology. She's a skeptic who uses AI every day: her working rule is to treat it like a person she manages, with all the management skills that implies, rather than something she just believes. Her north-star metric for any tool CARE deploys isn't whether it runs — it's whether the woman it was built for is actually better off.",cardBio:"AVP of Research and Evaluation at CARE, trained at the Harvard Kennedy School, with 15 years in development including four in the field in West Africa. Hosts CARE Failing Forward, the aid-world podcast where people admit on the record what went wrong.",headshot:"/guests/emily-janoch.jpg",clip:{src:"/clips/emily-janoch.mp4",poster:"/clips/emily-janoch.jpg",title:"“Every single statistic was wrong” — the child-marriage report AI faked"},topics:["AI in international development","evidence and evaluation","gender digital divide","AI and the Global South"],pullQuotes:["Confidence often overrides evidence.","The first thing you do is you shut off your computer.","We change the world with duct tape and hope every day, and this is one more piece of duct tape that we get to use."],links:[{label:"CARE",url:"https://www.care.org/"},{label:"CARE Failing Forward podcast",url:"https://open.spotify.com/show/1lumDcSDF6gqDR6frQuUbP"}],socials:["https://www.care.org/","https://www.linkedin.com/in/emily-janoch-7922514/"],episodeSlugs:["we-change-the-world-with-duct-tape-and-hope"]},{slug:"zara-farida-khanna",name:"Zara Khanna",title:"AI Researcher",org:"National University of Singapore",credential:"First Global Youth Ambassador, She Loves Tech",bio:"Zara Khanna is an AI researcher at the National University of Singapore, where her first paper, on detecting Alzheimer's disease through speech patterns, was accepted for publication while she was still in high school. She is the first-ever Global Youth Ambassador for She Loves Tech, the world's largest startup platform for women in tech, and she has spoken at the United Nations about responsible AI. She has been recognized by the Singapore Computer Society (Girls in Tech) and by Singapore's IMDA, where she built an AI ethics curriculum for students. She comes from a background of tension between literature and computer science, and her current obsession is alignment: AI holds encyclopedic knowledge of every moral framework humans ever wrote down, with no ability to choose when to apply which one. She reads Nietzsche to relax.",cardBio:"AI researcher at the National University of Singapore whose first paper, on detecting Alzheimer's through speech, was accepted while she was still in high school. She Loves Tech's first Global Youth Ambassador, and she has spoken at the United Nations on responsible AI.",headshot:"/guests/zara-farida-khanna.jpg",clip:{src:"/clips/zara-farida-khanna.mp4",poster:"/clips/zara-farida-khanna.jpg",title:"“I am the captain of this ship. I am using AI, it's not using me.”"},topics:["AI research","AI & philosophy","AI alignment","Gen Z & AI","women in tech"],pullQuotes:["I am the captain of this ship. I am using AI, it's not using me.","We can't use language as indicative of intelligence. Look at where that's gotten us over the years."],links:[{label:"zarakhanna.com — research and publications",url:"https://www.zarakhanna.com/"},{label:"She Loves Tech",url:"https://www.shelovestech.org/"},{label:`"Singapore's youth use AI every day — but most don't know 

81what it's really doing" (The Straits Times, via NUS)`,url:"https://news.nus.edu.sg/singapores-youth-use-ai-every-day--but-most-dont-know-what-its-really-doing/"}],socials:["https://www.linkedin.com/in/zarakhanna/","https://www.zarakhanna.com/"],episodeSlugs:["guten-tag-tech-bros"]},{slug:"ifeoma-ajunwa",name:"Ifeoma Ajunwa",title:"Asa Griggs Candler Professor of Law",org:"Emory University School of Law",credential:"Author of The Quantified Worker",bio:"Ifeoma Ajunwa is the Asa Griggs Candler Professor of Law at Emory University School of Law, former Associate Dean for Projects and Partnerships, and founding director of Emory's AI and Future of Work Program. She holds a PhD in sociology from Columbia and an LLM from Yale, and she is the author of The Quantified Worker: Law and Technology in the Modern Workplace (Cambridge University Press, 2023). She has testified before Congress, received the NSF CAREER Award, and is an elected member of the American Law Institute. Her work started with a note she wrote in a grad seminar on mass incarceration and circled three times: what about the women? It runs through worker surveillance, AI hiring as a gatekeeper for the formerly incarcerated, and what she calls captured capital, the data employers now take from workers on top of their time and labor. She's also Mara's friend.",cardBio:"Asa Griggs Candler Professor of Law at Emory and founding director of its AI and Future of Work Program. Author of The Quantified Worker, NSF CAREER Award, elected to the American Law Institute, and she has testified before Congress.",headshot:"/guests/ifeoma-ajunwa.jpg",topics:["worker surveillance","AI & employment law","captured capital","Afrofuturism & AI governance","women & work"],pullQuotes:["It's Kenyan workers today, but in the future it's going to be all of us.","Womansplaining is women actually taking back the reins. It's women taking up space."],links:[{label:"The Quantified Worker: Law and Technology in the Modern Workplace (Cambridge University Press, 2023)",url:"https://www.cambridge.org/core/books/abs/quantified-worker/quantified-worker/1867BE16F394301ACAF6F82F030EAFEC"},{label:'"Artificial Intelligence, Afrofuturism, and Economic Justice" (Georgetown Law Journal, 2024)',url:"https://www.law.georgetown.edu/georgetown-law-journal/in-print/volume-112/volume-112-issue-6-june-2024/artificial-intelligence-afrofuturism-and-economic-justice/"},{label:"Emory Law, AI and Future of Work Program",url:"https://law.emory.edu/centers-and-programs/ai-future-of-work-team.html"}],socials:["https://ifeomaajunwa.com","https://www.linkedin.com/in/ifeomaajunwa/"],clip:{src:"/clips/ifeoma-ajunwa.mp4",poster:"/clips/ifeoma-ajunwa.jpg",title:"“Who asked for this?” — her test for every new AI product"},episodeSlugs:["who-asked-for-this"]},{slug:"pam-boiros",name:"Pam Boiros",title:"Co-founder and CMO",org:"Women Applying AI",credential:"Principal, Bridge Marketing Advisors",bio:"Pam Boiros is the co-founder and CMO of Women Applying AI, a free, 501(c)(3), 100% volunteer-run community of 2,500 women that launched during Boston AI Week in 2025. She is a fractional CMO and principal at Bridge Marketing Advisors, where she has run marketing for a range of B2B software companies in HR tech, learning, and employee experience, and she created Marketing AI Jumpstart, an AI upskilling program for B2B marketing teams. The statistic that pushed her to act: 79% of working women are in roles highly exposed to generative AI. Her closing ask on the show is the one she gives everyone: get your hands on the keyboard, because the dust is never going to settle.",cardBio:"Co-founder and CMO of Women Applying AI, a free, volunteer-run community of 2,500 women, and principal at Bridge Marketing Advisors. Creator of Marketing AI Jumpstart.",headshot:"/guests/pam-boiros.jpg",topics:["AI upskilling","women & work","community building","B2B marketing"],pullQuotes:["If you're behind, what about the rest of us?","The dust is not gonna settle. It's never gonna settle. Get your hands on the keyboard."],links:[{label:"Women Applying AI",url:"https://womenapplyingai.com"},{label:"Bridge Marketing Advisors",url:"https://bridgemarketingadvisors.com/"}],socials:["https://www.linkedin.com/in/pamboiros/"],clip:{src:"/clips/pam-boiros.mp4",poster:"/clips/pam-boiros.jpg",title:"“Why are more women not in the room?” — the origin story"},episodeSlugs:["you-can-come-to-the-hackathon-clueless"]},{slug:"luda-kopeikina",name:"Luda Kopeikina",title:"Co-founder and CEO",org:"Women Applying AI",credential:"PhD in machine learning; MIT Sloan Fellow",bio:"Luda Kopeikina is the co-founder and CEO of Women Applying AI. She holds a PhD in machine learning, was a vice president at GE and a corporate venture investor, is an MIT Sloan Fellow, and now leads Noventra, which connects AI startups with enterprise transformation. She never felt a ceiling in her own career, which is why founding a women-only organization was a leap; she did it because somebody had to. On the show she explains what a hackathon actually is, why the gap framing hurts the women it's meant to help, and why Women Applying AI is a movement rather than a community.",cardBio:"

81Co-founder and CEO of Women Applying AI. PhD in machine learning, former GE vice president and corporate VC, MIT Sloan Fellow, now leading Noventra.",headshot:"/guests/luda-kopeikina.jpg",topics:["AI hackathons","peer learning","women & leadership","venture investing"],pullQuotes:["It's actually quite accessible. 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81,animate:{opacity:1,y:0},transition:{duration:.6,delay:.4},children:[r.jsx("h2",{className:"text-2xl sm:text-3xl font-serif font-bold text-primary mb-6",children:"Why It Works"}),r.jsxs("div",{className:"space-y-4 text-foreground/80",children:[r.jsxs("p",{children:[r.jsx("strong",{className:"text-primary",children:"High retention means your message actually gets heard."})," ","With 63% engagement on Apple Podcasts and 13.5 plays per listener, the audience binges the catalog. Listeners aren't dropping off before your ad runs — they're playing the next episode after it."]}),r.jsxs("p",{children:[r.jsx("strong",{className:"text-primary",children:"Niche beats scale for the right brands."})," ","A general-audience podcast with 10,000 listeners might reach 50 of your actual customers. Womansplaining AI's audience is already filtered: they opted in specifically to understand AI's impact on work and their lives."]}),r.jsxs("p",{children:[r.jsx("strong",{className:"text-primary",children:"Host-read only."})," ","Logan and Mara read every ad. Same voices listeners trust for nuanced takes on AI. No pre-recorded inserts, no baked-in ads that don't match the show's register."]})]})]}),r.jsxs(q.section,{initial:{opacity:0,y:20},animate:{opacity:1,y:0},transition:{duration:.6,delay:.5},className:"border border-accent/20 rounded-xl p-8 bg-accent/5 text-center",children:[r.jsx("h2",{className:"text-xl sm:text-2xl font-serif font-bold text-primary mb-3",children:"Get in Touch"}),r.jsx("p",{className:"text-muted-foreground mb-6 max-w-lg mx-auto",children:"Tell us about your brand and what you're trying to reach. 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Womansplaining AI calls this the guilt gap.",body:["The gendered guilt gap means women are more likely to feel conflicted about AI use; men report the same feeling, just less often. That friction has costs: hesitating to use tools your colleagues are already using, disclosed or not, compounds into a skills and speed disadvantage.","One useful reframe from the episode is hybrid thinking — combining human expertise with AI capabilities, using AI as a thinking partner rather than a replacement. It raises uncomfortable questions about intellectual ownership: if AI helped you write the strategy, how intelligent are you on your own? That discomfort is productive and worth sitting with."],sources:[{title:"CNBC/SurveyMonkey Women at Work Survey (Feb 2026) — CNBC write-up (50% vs 43%)",url:"https://www.cnbc.com/2026/03/06/gender-gap-in-ai-revealed-in-cnbc-surveymonkey-women-at-work-survey.html"},{title:"SurveyMonkey: CNBC Women at Work 2026 — full report and methodology (41% vs 34% among AI users; fielded Feb 10–16, 2026, n=6,330)",url:"https://www.surveymonkey.com/curiosity/cnbc-women-at-work-2026/"},{title:"KPMG Trust in AI Global Study 2025",url:"https://kpmg.com/xx/en/media/press-releases/2025/04/trust-of-ai-remains-a-critical-challenge.html"}],episodeSlugs:["is-using-ai-cheating"],related:["how-can-i-protect-my-expertise-from-ai","can-you-trust-ai-when-it-sounds-confident"],keywords:"is using AI cheating, AI guilt, guilt gap, women AI guilt, disclosing AI use at work, hybrid thinking"},{slug:"can-you-trust-ai-when-it-sounds-confident",question:"Can you trust AI when it sounds confident?",group:"AI at work",shortAnswer:"No. AI systems express equal confidence whether they're right or wrong, and research from Wharton and ACM CHI shows humans struggle to tell the difference. After a few correct answers, people stop auditing AI outputs entirely — a pattern researchers call algorithmic loafing.",body:["Algorithmic loafing is a documented phenomenon where humans gradually stop checking AI's work after it proves correct several times in a row. Research in human-AI teaming shows that one correct AI answer makes people less likely to catch the next wrong one — similar to how a slot machine's occasional wins keep you playing.","The practical takeaway: confidence signals from an AI are not accuracy signals. Build the habit of spot-checking outputs even when — especially when — the tool has been right all week."],episodeSlugs:["feeling-smarter-being-wrong","job-tsunamis-invisible-vulnerability"],related:["is-using-ai-cheating","is-ai-making-us-less-productive"],keywords:"trust AI, AI confidently wrong, algorithmic loafing, AI overreliance, cognitive surrender, Wharton AI study"},{slug:"is-ai-making-us-less-productive",question:"Is AI making us less productive?",group:"AI at work",shortAnswer:`Sometimes, yes. Legal scholar Jessica Silbey argues "the saving time thing is a lie" — AI's efficie

81ncy gains often come at the cost of quality, understanding, and the slow institutional work that builds trust. And the gains that do materialize flow disproportionately to employers and shareholders. Productivity for whom?`,body:["Silbey also argues AI is incapable of genuine intellectual risk because it has no skin in the game. Creativity requires vulnerability, the willingness to be wrong, and personal stakes in the outcome. AI can recombine patterns but cannot make the kind of leaps that come from lived experience and the courage to challenge consensus."],episodeSlugs:["33000-downloads-ai-destroys-institutions"],alsoLinks:[{label:"How AI Destroys Institutions — the pillar essay",href:"/how-ai-destroys-institutions"}],related:["how-does-ai-threaten-democracy-and-institutions","can-you-trust-ai-when-it-sounds-confident"],keywords:"AI productivity, is AI making us less productive, Jessica Silbey, AI efficiency lie, AI quality cost"},{slug:"how-can-i-protect-my-expertise-from-ai",question:"How can I protect my expertise from AI?",group:"AI at work",shortAnswer:"Document your knowledge in structured files before your company absorbs it into AI systems. Your institutional knowledge, decision-making frameworks, and domain expertise are leverage — once they're in a company's AI training data, you lose it. Start by exporting your data and writing down what you actually know versus what's in your job description.",body:["Pair that with Logan's go-bag framework for career security: if your life changed overnight, could you make money in 30 days? Career security isn't one stable job — it's a network, visible skills, and a personal website that works for you 24/7. Invest in your 9-to-5 and your 5-to-9.","On the personal website point: LinkedIn is rented land — you don't control the algorithm, the design, or who sees your work. A domain costs about $12/year and a site can be built in a weekend with AI tools, no coding experience required. It works while you sleep and can't be taken away by a platform change."],episodeSlugs:["is-using-ai-cheating","ai-prenups-economics-of-marriage"],related:["will-ai-take-my-job","is-using-ai-cheating"],keywords:"protect expertise from AI, career security AI, go-bag framework, personal website career, institutional knowledge AI"},{slug:"will-ai-take-my-job",question:"Will AI take my job?",group:"AI at work",shortAnswer:"It depends on the job — and the pattern isn't what the headlines suggest. Brookings Institution research found 6.1 million US workers whose jobs combine high AI exposure with low capacity to adapt. They aren't truck drivers. They're medical secretaries, insurance clerks, and administrative staff, and 86% of them are women. That measures who is exposed with the least cushion, not whose job goes first.",body:["The AI job displacement conversation has been framed around male-dominated industries while the actual vulnerability is concentrated in female-dominated occupations — which is exactly why it gets missed.","The best protection isn't predicting the wave; it's the go-bag: a network, visible skills, and proof of work you control. Ask yourself Logan's question — if your life changed overnight, could you make money in 30 days?"],sources:[{title:`Brookings: "Measuring US workers' capacity to adapt to AI-driven job displacement" (Jan 2026)`,url:"https://www.brookings.edu/articles/measuring-us-workers-capacity-to-adapt-to-ai-driven-job-displacement/"}],episodeSlugs:["job-tsunamis-invisible-vulnerability","ai-prenups-economics-of-marriage"],related:["how-does-ai-affect-womens-jobs","how-can-i-protect-my-expertise-from-ai"],keywords:"will AI take my job, AI job displacement, jobs safe from AI, AI layoffs, career security"},{slug:"how-does-ai-affect-womens-jobs",question:"How does AI affect women's jobs differently than men's?",group:"AI at work",shortAnswer:"A Brookings Institution study found 6.1 million US workers whose jobs combine high AI exposure with low capacity to adapt, and 86% of them are women — not truck drivers or warehouse workers, but medical secretaries, insurance clerks, and administrative roles. The public conversation is aimed at male-dominated industries; the measured vulnerability is concentrated in female-dominated ones.",body:["One thing the number does not say: that 86% of women will lose their jobs. Brookings measured who has the least capacity to adapt if displacement happens, which is a vulnerability map, not a forecast. It tells you where the safety net is thinnest.","This mismatch matters because policy attention, retraining money, and media coverage follow the framing. When the story is trucks and warehouses, the medical secretary doesn't see herself in 

81it — and neither do the people writing the programs meant to help her."],sources:[{title:`Brookings: "Measuring US workers' capacity to adapt to AI-driven job displacement" (Jan 2026)`,url:"https://www.brookings.edu/articles/measuring-us-workers-capacity-to-adapt-to-ai-driven-job-displacement/"}],episodeSlugs:["job-tsunamis-invisible-vulnerability"],related:["will-ai-take-my-job","why-do-women-use-ai-less-than-men"],keywords:"AI women's jobs, 86 percent women AI displacement, Brookings AI study women, gendered job displacement AI"},{slug:"why-do-women-use-ai-less-than-men",question:"Why do women use AI less than men?",group:"Women and AI",shortAnswer:"Not because of ignorance. Women's lower AI adoption tracks with valid skepticism earned across prior tech cycles (social media, the gig economy), a cognitive inequality gap where frontier tools cost $100–200/month, and — per Carol Gilligan's work — a tendency to ask different, arguably better questions about a technology's impact.",body:["Women are more likely to express ambivalence toward AI, driven by legitimate concerns about privacy, job displacement, and the technology's track record with bias. Womansplaining AI's argument: that ambivalence may actually be the healthiest response to this moment — the show calls its version of it fierce ambivalence."],sources:[{title:'Harvard Business School AI Institute: "The Gender Divide in Generative AI" (Global Evidence on Gender Gaps and Generative AI Over Time — men ~22% more likely to use gen AI, 2023–2026; gap ~16% since early 2025)',url:"https://aiinstitute.hbs.edu/the-gender-divide-in-generative-ai-a-global-challenge-update/"},{title:'Mara Bolis, "The AI Gender Gap Paradox" (Stanford Social Innovation Review)',url:"https://ssir.org/articles/entry/ai-gender-gap-paradox"}],episodeSlugs:["women-in-ai-who-gets-a-seat"],related:["is-ai-biased-against-women-and-girls","how-can-non-technical-women-start-learning-ai"],keywords:"why women use AI less, AI gender gap, women AI adoption, AI ambivalence, Carol Gilligan AI"},{slug:"is-ai-biased-against-women-and-girls",question:"Is AI biased against women and girls?",group:"Women and AI",shortAnswer:`Yes, measurably. The LLYC "Illusion of Equality" study tested nearly 10,000 AI responses and found LLMs systematically steer boys toward entrepreneurship and leadership while directing girls toward image-based careers like influencing and modeling. That's not a bug — it's training data reflecting existing societal bias at scale.`,body:["You can see it yourself: ask any LLM to predict career paths for a 10-year-old boy versus a 10-year-old girl with identical backgrounds, and the differences reveal the systematic bias in the model's training data. Tools like BiasBench let you audit LLM outputs for gender, racial, and other biases in real time."],episodeSlugs:["ai-boys-entrepreneurs-girls-influencers"],related:["why-do-women-use-ai-less-than-men","how-does-ai-affect-womens-jobs"],keywords:"AI gender bias, is AI biased against women, LLYC illusion of equality, AI career recommendations bias, BiasBench"},{slug:"how-can-non-technical-women-start-learning-ai",question:"How can non-technical women start learning AI?",group:"Women and AI",shortAnswer:`Start by using AI for tasks you already do — writing emails, researching, organizing information. Wanjiku Kamau taught herself Stanford's CS curriculum on the subway using AI to explain concepts. The key barrier isn't technical aptitude but identity: many women don't see themselves as "tech people," which prevents them from even starting.`,body:["Kamau's story is the proof of concept: after being laid off from a 20-year career at Siemens, Intel, and Google, she built a website in 48 hours and wrote a book in 90 days, using AI as an explainer and collaborator rather than a replacement for her own thinking."],episodeSlugs:["relief-not-raise-hand"],related:["can-you-build-a-website-with-ai","can-you-write-a-book-with-ai"],keywords:"non-technical women learn AI, how to start learning AI, AI for beginners women, Wanjiku Kamau"}

81,{slug:"can-you-build-a-website-with-ai",question:"Can you build a website with AI and no coding experience?",group:"Building with AI",shortAnswer:"Yes. Wanjiku Kamau, a guest on Womansplaining AI, built a political organization's website in 48 hours using ChatGPT after being laid off from a 20-year career at Siemens, Intel, and Google — with no prior web development experience. She used AI as a coding partner, asking it to explain each step rather than generating code blindly.",body:[`There's a career-security argument for doing this even if you don't "need" a site: LinkedIn is rented land. A personal website costs about $12/year for a domain, can be built in a weekend with AI tools like Replit or Lovable, shows up when people search for you, and can't be taken away by a platform change.`],episodeSlugs:["relief-not-raise-hand","ai-prenups-economics-of-marriage"],related:["can-you-write-a-book-with-ai","how-can-non-technical-women-start-learning-ai"],keywords:"build website with AI, no code website AI, AI website builder, personal website career security"},{slug:"can-you-write-a-book-with-ai",question:"Can you write a book using AI?",group:"Building with AI",shortAnswer:'Wanjiku Kamau wrote her book "Out of the Loop, Into the Algorithm" in 90 days using AI as a dictation and structuring partner. She voice-noted about 80% of the content while walking her dog, then used AI to organize and refine — not to generate the ideas. 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Some people extract tens of thousands of dollars of value from AI a year while most get around $11 — and women use AI about 20% less than men on average, widening the access gap.",body:['One proposed fix discussed on the show: a 3% token tax to capture some of the enormous value the heaviest users pull from these systems and redistribute it, paired with a New York State Assembly "AI dividend" bill aimed at routing captured value back to people.'],episodeSlugs:["who-gets-the-good-units-of-intelligence"],related:["how-much-does-ai-cost-per-month","who-should-regulate-big-ai-companies"],keywords:"free vs paid AI, free ChatGPT vs Plus, AI access gap, token tax, AI dividend"},{slug:"how-many-people-are-in-relationships-with-ai",question:"How many people are in romantic relationships with AI?",group:"AI and your life",shortAnswer:"More than you'd guess. 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81imes, shows this isn't about misuse but about fundamental design conflicts.`,body:["Silbey is a professor at Boston University School of Law and a Guggenheim Fellow whose research focuses on the intersection of intellectual property, technology, and institutions. The paper, co-authored with Woody Hartzog, is one of the most-read academic papers on AI governance."],episodeSlugs:["33000-downloads-ai-destroys-institutions"],alsoLinks:[{label:"How AI Destroys Institutions — the pillar essay",href:"/how-ai-destroys-institutions"}],related:["who-should-regulate-big-ai-companies","is-ai-making-us-less-productive"],keywords:"AI threat democracy, AI destroys institutions, Jessica Silbey, AI institutional accountability, AI governance"},{slug:"who-should-regulate-big-ai-companies",question:"Who should be regulating big AI companies?",group:"Power and policy",shortAnswer:"Congress — that's Logan and Mara's argument. The energy behind AI backlash (online mobs, comment-section fights, even firebombed CEO houses) has nowhere productive to go because there's a leadership vacuum, and Congress is the body with actual power to fill it. Economist Zoe Hitzig's economic-democracy framework shows what filling it could look like.",body:["Economic democracy here means building real structures — consumer stakeholder boards, worker boards, deliberate friction — into how powerful companies operate. The hosts use OpenAI's shift from nonprofit to for-profit as the case study for what happens when those structures are missing."],episodeSlugs:["whos-letting-big-tech-run-wild"],related:["what-ai-laws-are-passing-in-2026","how-does-ai-threaten-democracy-and-institutions"],keywords:"who regulates AI, AI regulation Congress, economic democracy AI, Zoe Hitzig, OpenAI nonprofit for-profit"},{slug:"what-ai-laws-are-passing-in-2026",question:"What AI laws are being passed in 2026?",group:"Power and policy",shortAnswer:"Key AI legislation in 2026 includes California SB 53, which requires transparency from frontier AI developers, and New York's RAISE Act, which mandates AI safety frameworks and education. The EU AI Act continues phased implementation. These laws are catching up to concerns about AI-washing, anticipatory layoffs, and concentrated power in a handful of AI companies.",body:["Womansplaining AI tracks state-by-state AI bills — updated the 1st and 3rd Mondays of each month — including the show's read on why each bill matters."],episodeSlugs:["adolescent-technology-20000-word-warnings"],related:["who-should-regulate-big-ai-companies","how-does-ai-threaten-democracy-and-institutions"],keywords:"AI laws 2026, California SB 53, New York RAISE Act, EU AI Act, state AI legislation"}],XN={initial:{opacity:0,y:20},animate:{opacity:1,y:0},transition:{duration:.6,ease:"easeOut"}},e3={initial:{opacity:0,y:20},whileInView:{opacity:1,y:0},viewport:{once:!0},transition:{duration:.8,ease:"easeOut"}};function t3(){const e={"@context":"https://schema.org","@type":"ItemList",name:"Straight Answers — Womansplaining AI",description:"Direct answers to the questions people actually ask about AI, each grounded in an episode of Womansplaining AI.",url:"https://womansplainingai.com/questions",itemListElement:Ca.map((n,s)=>({"@type":"ListItem",position:s+1,name:n.question,url:`https://womansplainingai.com/questions/${n.slug}`}))};return r.jsx("script",{type:"application/ld+json",dangerouslySetInnerHTML:{__html:JSON.stringify(e)}})}function n3(){return ze({title:"Straight Answers to Real AI Questions | Womansplaining AI",description:"Is using AI cheating? Will AI take my job? How much does AI cost? Direct, research-backed answers from the Womansplaining AI podcast — no jargon, no gatekeeping.",path:"/questions"}),r.jsxs("div",{className:"min-h-screen bg-background",children:[r.jsx(t3,{}),r.jsx(q.section,{...XN,className:"bg-primary text-primary-foreground pt-20 pb-12 sm:pb-16",children:r.jsxs("div",{className:"max-w-4xl mx-auto px-4 sm:px-6",children:[r.jsxs("div",{className:"flex items-center gap-2 mb-4",children:[r.jsx(cd,{className:"w-5 h-5 text-accent"}),r.jsx("span",{className:"text-accent text-sm font-medium uppercase tracking-wide",children:"Straight Answers"})]}),r.jsx("h1",{className:"text-3xl sm:text-4xl md:text-5xl font-serif font-bold mb-4 leading-tight",children:"The questions everyone's asking. Answered like we mean it."}

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81]},{heading:"While you're there",blocks:[{type:"ul",items:[`Say "I haven't figured this part out yet" out loud. Pam describes that exact moment as the one that makes the room work (19:37): someone shows a workflow they're stuck on and someone else says, have you tried this?`,"If the technical person is heads-down, watch and narrate. Ask them to explain the one step you can't follow. That's learning, not interrupting.",'Keep notes on what got built and what broke. Luda says the presentations people remember are the ones that go "this was breaking, that was breaking, and then I did this" (21:25).']}]},{heading:"After",blocks:[{type:"ul",items:["Write it up somewhere public. Luda, at 25:05: when a member builds an app, puts it on her LinkedIn, and gets approached for a job, that's the story that moves the next woman. A paragraph and a screenshot count.","Pam's closing ask, at 33:50: get your hands on the keyboard. If you didn't do it yesterday, do it today. The dust is not going to settle.","Luda's own first project, at 34:20: songs for her children to brush their teeth to. Make one small thing."]}]},{heading:"Where to find one",blocks:[{type:"ul",items:["Women Applying AI runs mini hackathons and peer sessions. Free, born in Boston, now in regional hubs. Their first-anniversary event, The Human Edge: Women Leading in the Age of AI, is Thursday, September 24 in Boston during Boston AI Week (links below).","Nothing near you? Run a two-hour version with two friends: one problem, one tool, one thing built. The invite text is in our AI book club doc (linked below)."]}]},{heading:"Something you can copy",blocks:[{type:"p",text:"Text to send a friend:"},{type:"copy",lines:["There's an AI hackathon on [date]. I have no idea what I'm doing and apparently that's fine. Come with me? We'll be the two people asking the basic questions."]}]},{heading:"Listen and read",blocks:[{type:"links",items:[{label:"Women Applying AI",url:"https://womenapplyingai.com"},{label:"The Human Edge: Women Leading in the Age of AI, Thu Sept 24, MassChallenge, Boston",url:"https://luma.com/bax9tycg"},{label:"Bring a Folding Chair: How to Start an AI Book Club (our doc, with the invite text)",url:"https://docs.google.com/document/d/10AmQ7Gn4EAU5lj69nxkNi6ccRIXJl9v5RJ6svO3-WuI/edit"},{label:'Mara Bolis, "The New Gender AI Gap" (Substack, Sept 1, 2026)',url:"https://marabolis.substack.com/p/the-new-gender-ai-gap"},{label:'Kenan Institute, "Will Generative AI Disproportionately Affect the Jobs of Women?" (2023), the 79% / 58% figures Pam cites',url:"https://kenaninstitute.unc.edu/kenan-insight/will-generative-ai-disproportionately-affect-the-jobs-of-women/"}]}]}],ask:"Went to one? Tell us how it was, especially the part where you felt clueless. Leave a voicemail at the answering machine or email [email protected]. We may feature it in a Let's Womansplain segment, and we'll check back in with you later to hear what happened."},{slug:"before-you-say-yes-to-the-ai-tool-at-work",number:1,title:"Before you say yes to the AI tool at work",subtitle:"Seven questions inspired by our conversation with Ifeoma Ajunwa",episodeSlug:"who-asked-for-this",datePublished:"2026-09-14",googleDocUrl:"https://docs.google.com/document/d/1xWISq81hC9NsnzGGwV14Rag_fy3q0ezOm3M53q_D6xs/edit",summary:"Seven questions to ask before the new AI tool lands on your desk, or after it already has. Each one starts from something Ifeoma Ajunwa said on Episode 26, with the timestamp. Plus a plain-words version for meeting notetakers and an email you can copy to your manager.",sections:[{heading:"Why this exists",blocks:[{type:"p",text:"In Episode 26 (Who Asked for This?), Ifeoma Ajunwa, law professor at Emory and author of The Quantified Worker, describes what she calls captured capital. The old deal at work was time and labor in, money out. The new deal adds a third thing going in, your data, with nothing new coming out."},{type:"p",text:"On the episode she says there is no federal law that spells out what an employer can do with workplace surveillance (12:40). Our practical read: U.S. workplace-surveillance protections are a patchwork. Some laws limit monitoring or require notice (New York, Connecticut, and Delaware make employers tell you about electronic monitoring, and federal wiretap and anti-discrimination laws still apply), but what covers you depends on where you work and what is being collected. So ask for the policy in writing."},{type:"p",text:'When the new tool shows up (a meeting notetaker, a Copilot license, a "productivity insights" dashboard, a badge that tracks where you walk), these are the questions worth asking. Each one starts from something Ifeoma said, with the timestamp in the final cut. The advice after each is ours.'}]},{heading:"The seven questions",blocks:[{type:"item",n:1,title:"What does this collect, and who tells me?",text:"Ifeoma's point (12:40): most of this arrives as a take-it-or-leave-it policy. Ask for it in writing. If nobody can answer yet, ask who owns the decision and when an answer will be available."},{type:"item",n:2,title:"What exactly gets counted?",text:"She lists the real metrics (14:53): keystrokes per minute, emails per day, how many conversations you have with coworkers. Ask for the list. Ask who can see it, and whether it shows up in your review."},{type:"item",n:3,title:"Where else does my data go?",text:"The part most people miss (15:09). The vest on the warehouse worker isn't just checking her form. Ifeoma says that movement data can be used to train the robots that automate the job. Ask: does what I type, say, or record get used to train a model, by us or by the vendor? Is it kept after I leave?"},{type:"item",n:4,title:"What do I get back?",text:"The bargain changed and nobody renegotiated it (15:35). Time and labor used to be the whole deal. Now data goes in too, and the wage is the same. Ask how any productivity gains will show up in pay, workload, and expectations. This is a raise-and-scope conversation wearing a software costume."},{type:"item",n:5,title:"Has anyone vetted this, and what happens when it's wrong?",text:`"Most AI is unvetted at this time" (19:24). Ask what evidence shows this tool works for the job you're using it for. Then two sharper questions: when it's wrong, who gets blamed, the tool or me? And how do I correct an inaccurate transcript, score, or assessment before it affects my work?`},{type:"item",n:6,title:"How will my use of it be read?",text:`The double standard, in her words (18:25): when a man uses AI he's efficie

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