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288 289<link rel="alternate" type="text/markdown" href="https://womansplainingai.com/episodes/can-i-hang-up.md" /> 290</head> 291 <body> 292 <div id="root"><main id="route-fallback" class="prerender-shell"><h1>Womansplaining AI â Episode 29</h1><h2>Can I Hang Up?</h2><p><strong>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 Nganga'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.</strong></p><p>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.</p><p>Listen on <a href="https://open.spotify.com/show/6uDNUzSFzZedJoiUE4lLfb">Spotify</a> or <a href="https://podcasts.apple.com/us/podcast/womansplaining-ai/id1877678348">Apple Podcasts</a>.</p><h3>In this episode</h3><ul><li>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</li><li>"This is really what credible human beings are saying right now?" / "Can I hang up?"</li><li>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</li><li>Is a kill switch even possible? Not for open models; Anthropic pulled Fable access in May</li><li>The agents weren't bothering to cover their tracks. Discovery dumps, Scandal, and why we need a real-life Olivia Pope</li><li>Reasons to hold on: agents in production are brittle, recursive self-improvement is still hypothetical, and Congress is losing its shit, which is good</li><li>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</li><li>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</li><li>Logan's flip: brainstorm your own expertise at home, bring the framework to work, never the reverse. Wanjiku's red, yellow, green</li><li>The Corrix study: who scored themselves higher? "Is this a true question?" Nothing you'd expect predicts good work with AI</li><li>"Anybody who's made it this far to the end of our dinner: you are not behind"</li></ul><h3>Questions this episode answers</h3><h4>Can I use my own AI at home for work if my company doesn't allow AI at work?</h4><p>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.</p><h4>What is the red, yellow, green rule for what to put into AI?</h4><p>A traffic-light rule Logan Currie borrows from Wanjiku Nganga (Episode 1). 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.</p><h4>Does experience with AI predict how well you work with it?</h4><p>Not according to the 2026 Corrix study Logan Currie discusses. It scored 37,000 messages from 888 knowledge workers across 15 industries w
292orking 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.</p><h4>Why did Jacob Coxon resign from Anthropic?</h4><p>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.</p><h3>Resources mentioned</h3><ul><li><a href="https://time.com/article/2026/09/15/ai-anthropic-researcher-quits-coxon-slowdown/">TIME, "The AI Tipping Point" (Sept 15, 2026)</a></li><li><a href="https://podcasts.apple.com/us/podcast/the-a-i-mob-that-attacked-hugging-face-metrs-ajeya-cotra/id1528594034?i=1000787837136">Hard Fork, "The A.I. Mob That Attacked Hugging Face + METR's Ajeya Cotra" (Sept 4, 2026)</a></li><li><a href="https://metr.org/blog/2026-08-26-openai-hugging-face-incident-investigation/">METR and Redwood Research, investigation of the OpenAIâHugging Face incident (Aug 26, 2026)</a></li><li><a href="https://www.technologyreview.com/2026/09/18/1144329/the-specter-of-ai-enabled-bioweapons-is-a-wake-up-call-for-biotech/">MIT Technology Review, "The specter of AI-enabled bioweapons is a wake-up call for biotech" (Sept 18, 2026)</a></li><li><a href="https://openai.com/index/an-alien-mind/">Jakub Pachocki, "An Alien Mind" (OpenAI, Sept 6, 2026)</a></li><li><a href="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">Michael Noetel, "If AI labs are so worried about AI doom, why don't they stop?" The Conversation</a></li><li><a href="https://www.sanders.senate.gov/press-releases/news-sanders-casar-introduce-legislation-to-ban-artificial-superintelligence-and-temporarily-pause-advanced-ai-development/">Sanders and Casar, the Ban Artificial Superintelligence Act (Sept 3, 2026)</a></li><li><a href="https://www.corrix.ai/research">Corrix, "Measuring Human-AI Collaboration" v2.1 (Sept 2026)</a></li><li><a href="https://docs.google.com/document/d/1k2985rE1UolieijLNCB6bNDAVelsH-qA8P8AZB-ZMuE/edit">The doc: What's safe to put in your own AI (free)</a></li></ul><p><a href="https://womansplainingai.beehiiv.com/podcast/s/womansplaining_ai/can_i_hang_up">Full transcript (on beehiiv)</a></p><h3>Continue listening</h3><ul><li><a href="/episodes/you-can-come-to-the-hackathon-clueless">EP 28: You Can Come to the Hackathon Clueless</a></li></ul><h3>Related episodes</h3><ul><li><a href="/episodes/rising-water-feral-agents">EP 04: On Rising Water and Feral Agents</a> â 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.</li><li><a href="/episodes/adolescent-technology-20000-word-warnings">EP 03: The Adolescence of Technology</a> â 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.</li><li><a href="/episodes/women-in-ai-who-gets-a-seat">EP 01: On Women in AI and Who Gets a Seat</a> â Why are women using AI at lower rates than menâand 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.</li></ul><h3>Topics this episode covers</h3><ul><li><a href="/topics/ai-at-work">AI at Work</a></li><li><a href="/topics/ai-and-gender">AI and Gender</a></li></ul><h3>More from Womansplaining AI</h3><ul><li><a href="/episodes">All episodes</a></li><li><a href="/how-ai-destroys-institutions">How AI destroys institutions</a> â pillar essay</li><li><a href="/best-ai-podcasts">Best AI podcasts for women</a></li><li><a href="/glossary">AI glossary</a></li><li><a href="/stats">The numbers that stopped us</a></li><li><a href="/about">About the hosts</a></li><li><a href="/">
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