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77		<h1 class="mt-12 md:mt-24 mb-0"><!-- HTML_TAG_START -->Fair Lending and AI<!-- HTML_TAG_END --></h1></div>
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86			<p><!-- HTML_TAG_START -->As the use of artificial intelligence in the financial industry continues to grow, it is important to ensure that these technologies meet fundamental fair lending principles aimed toward preventing discrimination on the basis of characteristics such as race, ethnicity, and gender. AI can play a powerful role in achieving this goal. However, it is crucial to consider the ethical implications of using AI in the lending process and to ensure that it is designed and deployed in a responsible manner and aligned with the concepts outlined on this website. MoreThanFair has identified the National Institute of Standards and Technology, the White House, and the National Fair Housing Alliance as currently proposing three of the leading standards, and we have generated the below based on those principles.<!-- HTML_TAG_END --></p>
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91			<p><!-- HTML_TAG_START --><a href="#a-guide-to-ai-frameworks"><b>Read more about each AI Framework</b></a><!-- HTML_TAG_END --></p>
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96			<p><!-- HTML_TAG_START --><b>Download the graphic below and share</b><!-- HTML_TAG_END --></p>
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101			<p><!-- HTML_TAG_START --><a class="button" href="/images/evaluating-ai-systems.pdf" download>Download PDF<i class="fa-regular fa-download"></i></a><!-- HTML_TAG_END --></p>
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107				<figure class="my-4">
108					<a href="/images/evaluating-ai-systems.pdf" target="" rel="" title="MoreThanFair’s guide to creating automated systems responsibly.">
109							<img class="w-full svelte-jjtj6d" src="/images/evaluating-ai-systems.svg" alt="MoreThanFair’s guide to creating automated systems responsibly." loading="eager" draggable="false" decoding="async" width="612" height="911">
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113					<figcaption class="sr-only">MoreThanFair’s guide to creating automated systems responsibly.</figcaption></figure>
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117			
118			<h2 id="a-guide-to-ai-frameworks"><!-- HTML_TAG_START -->A Guide to AI Frameworks<!-- HTML_TAG_END --></h2>
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123			<p><!-- HTML_TAG_START -->Key stakeholders, including advocacy organizations and the U.S. government, have released AI frameworks for public discourse. We’ve highlighted key tenets from three that we believe have the leading standards for consideration:<!-- HTML_TAG_END --></p>
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130<div class="masonry flex w-full box-border justify-start my-6 svelte-12dzv8j" style=""><div class="col grid h-max w-full  svelte-12dzv8j"><div><a class="card  svelte-11a5bx3" href="/fair-lending-ai/ai-bill-of-rights" data-sveltekit-preload-data="">
131
132	<span class="body-sm label font-normal text-primary svelte-11a5bx3"><!-- HTML_TAG_START -->The White House<!-- HTML_TAG_END --></span>
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134	<span class="body font-bold text-primary-dark svelte-11a5bx3 mr-5"><!-- HTML_TAG_START -->Blueprint for an AI Bill of Rights<!-- HTML_TAG_END --></span>
135
136	<div class="content my-0 mr-5"><p class="text-primary-dark svelte-11a5bx3"><!-- HTML_TAG_START -->The White House's AI Bill of Rights is a set of five principles to guide the design, use, and deployment of automated systems across a wide range of sectors to protect the rights of the American public in the age of artificial intelligence.<!-- HTML_TAG_END --></p></div>
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141</a>
142					</div><div><a class="card  svelte-11a5bx3" href="/fair-lending-ai/purpose-process-monitoring" data-sveltekit-preload-data="">
143
144	<span class="body-sm label font-normal text-primary svelte-11a5bx3"><!-- HTML_TAG_START -->The National Fair Housing Alliance<!-- HTML_TAG_END --></span>
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146	<span class="body font-bold text-primary-dark svelte-11a5bx3 mr-5"><!-- HTML_TAG_START -->Purpose, Process, and Monitoring<!-- HTML_TAG_END --></span>
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148	<div class="content my-0 mr-5"><p class="text-primary-dark svelte-11a5bx3"><!-- HTML_TAG_START -->The National Fair Housing Alliance has proposed a new auditing framework called Purpose, Process, and Monitoring to help assess the fairness and efficacy of algorithmic systems.<!-- HTML_TAG_END --></p></div>
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153</a>
154					</div><div><a class="card  svelte-11a5bx3" href="/fair-lending-ai/nist-ai-risk-management-framework-playbook" data-sveltekit-preload-data="">
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156	<span class="body-sm label font-normal text-primary svelte-11a5bx3"><!-- HTML_TAG_START -->National Institute of Standards and Technology<!-- HTML_TAG_END --></span>
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158	<span class="body font-bold text-primary-dark svelte-11a5bx3 mr-5"><!-- HTML_TAG_START -->NIST AI Risk Management Framework Playbook<!-- HTML_TAG_END --></span>
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160	<div class="content my-0 mr-5"><p class="text-primary-dark svelte-11a5bx3"><!-- HTML_TAG_START -->NIST has developed an AI Risk Management Framework, which provides a structure for organizations to identify, assess, and mitigate risks associated with the use of AI.<!-- HTML_TAG_END --></p></div>
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210					data: [{type:"data",data:{tag:"MoreThanFair",title:"Fair Lending and AI",description:"Several government agencies, including the White House, have released guidance on how automated systems should be designed and governed. Read our guide on these frameworks.",url:"https:\u002F\u002Fwww.morethanfair.com",authors:[{name:"MoreThanFair Community",href:"https:\u002F\u002Fwww.morethanfair.com\u002Fabout"}],organization:{name:"MoreThanFair",description:"America needs more inclusive credit. Here's why and how.",href:"https:\u002F\u002Fwww.morethanfair.com"},socials:{twitter:"@morethanfair",email:"[email protected]"},image:{alt:"The landing art for MoreThanFair with the headline \"America needs more inclusive credit.\" and subtitle \"Here's why and how\". To the right, a collage of graphics and images used throughout the site featuring key statistics.",large:{src:"\u002F1200x630.png",width:1200,height:630},small:{src:"\u002F1012x506.png",width:1012,height:506}},date_created:"2023-02-17T00:00:00",date_updated:"2023-02-17T00:00:00",colors:{background:"#f5f5f5",theme:"#f5f5f5"},slug:"\u002Ffair-lending-ai",type:"hub",blocks:[{type:"text",value:"As the use of artificial intelligence in the financial industry continues to grow, it is important to ensure that these technologies meet fundamental fair lending principles aimed toward preventing discrimination on the basis of characteristics such as race, ethnicity, and gender. AI can play a powerful role in achieving this goal. However, it is crucial to consider the ethical implications of using AI in the lending process and to ensure that it is designed and deployed in a responsible manner and aligned with the concepts outlined on this website. MoreThanFair has identified the National Institute of Standards and Technology, the White House, and the National Fair Housing Alliance as currently proposing three of the leading standards, and we have generated the below based on those principles."},{type:"text",value:"\u003Ca href=\"#a-guide-to-ai-frameworks\"\u003E\u003Cb\u003ERead more about each AI Framework\u003C\u002Fb\u003E\u003C\u002Fa\u003E"},{type:"text",value:"\u003Cb\u003EDownload the graphic below and share\u003C\u002Fb\u003E"},{type:"text",value:"\u003Ca class=\"button\" href=\"\u002Fimages\u002Fevaluating-ai-systems.pdf\" download\u003EDownload PDF\u003Ci class=\"fa-regular fa-download\"\u003E\u003C\u002Fi\u003E\u003C\u002Fa\u003E"},{type:"img",value:{src:"\u002Fimages\u002Fevaluating-ai-systems.svg",alt:"MoreThanFair’s guide to creating automated systems responsibly.",loading:"eager",width:"612",height:"911",link:{href:"\u002Fimages\u002Fevaluating-ai-systems.pdf",target:"_blank"}}},{type:"h2",value:"A Guide to AI Frameworks"},{type:"text",value:"Key stakeholders, including advocacy organizations and the U.S. government, have released AI frameworks for public discourse. 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The principles are intended to help ensure that automated systems are aligned with democratic values and protect civil rights, civil liberties, and privacy."},{type:"h2",value:"Key Tenets"},{type:"text",value:"The AI Bill of Rights rests on five key principles:"},{type:"ol",value:[{type:"li",value:[{type:"text",value:"\u003Cb\u003ESafe and Effective Systems:\u003C\u002Fb\u003E People should be protected from unsafe or ineffective systems. Automated systems should be developed with consultation from diverse communities, stakeholders, and domain experts to identify potential risks and impacts. Systems should undergo pre-deployment testing, risk identification and mitigation, and ongoing monitoring to ensure they are safe and effective based on their intended use."}]},{type:"li",value:[{type:"text",value:"\u003Cb\u003EAlgorithmic Discrimination Protections:\u003C\u002Fb\u003E Automated systems should be designed and used in an equitable way, and measures should be taken to prevent algorithmic discrimination against individuals based on their race, sex, religion, age, and other protected characteristics."}]},{type:"li",value:[{type:"text",value:"\u003Cb\u003EData Privacy:\u003C\u002Fb\u003E People should be protected from abusive data practices, including the unauthorized collection and use of their personal data, and should be able to control how their data is used."}]},{type:"li",value:[{type:"text",value:"\u003Cb\u003ENotice and Explanation:\u003C\u002Fb\u003E People should be informed when they are interacting with an automated system, and should be provided with information about the system's capabilities and limitations."}]},{type:"li",value:[{type:"text",value:"\u003Cb\u003EHuman Alternatives, Consideration, and Fallback:\u003C\u002Fb\u003E Automated systems should be designed with the option for human intervention or oversight, and that the potential for human alternatives should be available if the decision made by the system is harmful or unfair."}]}]}
210,{type:"h2",value:"Learn More"},{type:"cards",value:[{eyebrow:"The White House",title:"Blueprint for an AI Bill of Rights",link:"https:\u002F\u002Fwww.whitehouse.gov\u002Fostp\u002Fai-bill-of-rights\u002F"},{eyebrow:"The White House",title:"Bill of Rights PDF",link:"https:\u002F\u002Fwww.whitehouse.gov\u002Fwp-content\u002Fuploads\u002F2022\u002F10\u002FBlueprint-for-an-AI-Bill-of-Rights.pdf"}]},{type:"h2",value:"Join Us"},{type:"contact",value:{}}]},{slug:"\u002Ffair-lending-ai\u002Fpurpose-process-monitoring",type:"post",style:"post",eyebrow:"The National Fair Housing Alliance",title:"Purpose, Process, and Monitoring",description:"The National Fair Housing Alliance has proposed a new auditing framework called Purpose, Process, and Monitoring to help assess the fairness and efficacy of algorithmic systems.",date_created:"2023-02-17T00:00:00",date_updated:"2023-02-17T00:00:00",showDate:"false",showAuthors:"true",authors:[{name:"Michael Akinwumi"},{name:"Lisa Rice"},{name:"Snigdha Sharma"}],blocks:[{type:"h2",value:"Purpose"},{type:"text",value:"The National Fair Housing Alliance (NFHA) has proposed a new auditing framework called Purpose, Process, and Monitoring (PPM) to help assess the fairness and efficacy of algorithmic systems in housing and lending. The PPM framework is designed to provide an equity-centered roadmap for auditors to assess the potential risks that algorithmic systems may pose to consumers, institutions, and society, and to ensure that they are fair, equitable, explainable, and transparent."},{type:"h2",value:"Key Tenets"},{type:"text",value:"The PPM framework is composed of three stages: Purpose, Process, and Monitoring."},{type:"ol",value:[{type:"li",value:[{type:"text",value:"\u003Cb\u003EThe Purpose stage\u003C\u002Fb\u003E examines project goals as well as the expectations, requirements, and objectives of stakeholders who are trying to solve a business problem. During this phase, auditors are guided to seek information to make educated decisions about risks the business problem may pose to consumers, institutions, and society at large."}]},{type:"li",value:[{type:"text",value:"\u003Cb\u003EThe Process stage\u003C\u002Fb\u003E evaluates the design, theory, and logic used to develop an algorithmic solution in the context of business-use cases and design objectives. This stage includes five elements:"},{type:"ul",value:[{type:"li",value:[{type:"text",value:"Staff Profile: To ensure the model is built by a diverse and inclusive team that’s trained to spot and prevent issues that lead to unfavorable outcomes."}]},{type:"li",value:[{type:"text",value:"Data Assessment: To audit data sources and data fields to determine if the data used is appropriate, representative, fair, and accurate."}]},{type:"li",value:[{type:"text",value:"Model Assessment: To evaluate information about training algorithms, parameters, hyper-parameters, and any fairness constraints used during the development of the model."}]},{type:"li",value:[{type:"text",value:"Outcome Assessment: To determine if the performance of the final model is in line with its original design objectives, which include minimizing risks to consumers, institutions, and society."}]},{type:"li",value:[{type:"text",value:"Model Use and Limitation: To document known limitations and assumptions of the model, as well as identify where the model may or may not be used outside of its intended scope."}]}]}]},{type:"li",value:[{type:"text",value:"\u003Cb\u003EThe Monitoring stage\u003C\u002Fb\u003E focuses on the post-development phase of an algorithmic model’s lifecycle. This stage includes two main considerations:"},{type:"ul",value:[{type:"li",value:[{type:"text",value:"Ongoing Validation of Production Model: To ensure that the data used to train the model isn’t statistically different from the data encountered in the real world."}]},{type:"li",value:[{type:"text",value:"Clear Defense and Security Measures: To protect the model against attacks that jeopardize consumer data or the system’s integrity, and ensure the defenses used guarantee fairness and accountability."}]}]}]}]},{type:"h2",value:"Learn more"},{type:"cards",value:[{eyebrow:"NFHA",title:"PPM Announcement",link:"https:\u002F\u002Fnationalfairhousing.org\u002Fjust-launched-purpose-process-and-monitoring-framework-ppm\u002F"},{eyebrow:"NFHA",title:"PPM Framework PDF",link:"https:\u002F\u002Fnationalfairhousing.org\u002Fwp-content\u002Fuploads\u002F2022\u002F02\u002FPPM_Framework_02_17_2022.pdf"}]},{type:"h2",value:"Join Us"},{type:"contact",value:{}}]},{slug:"\u002Ffair-lending-ai\u002Fnist-ai-risk-management-framework-playbook",type:"post",style:"post",eyebrow:"National Institute of Standards and Technology",title:"NIST AI Risk Management Framework Playbook",description:"NIST has developed an AI Risk Management Framework, which provides a structure for organizations to identify, assess, and mitigate risks associated with the use of AI.",date_created:"2023-02-17T00:00:00",date_updated:"2023-02-17T00:00:00",showDate:"false",showAuthors:"false",blocks:[{type:"h2",value:"Purpose"},{type:"text",value:"The National Institute of Standards and Technology (NIST) has developed an AI Risk Management Framework (AI RMF), which provides a structure for organizations to identify, assess, and mitigate risks associated with the use of Artificial Intelligence (AI). 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It can be broken down into four functions:"},{type:"ol",value:[{type:"li",value:[{type:"text",value:"\u003Cb\u003EThe Govern function\u003C\u002Fb\u003E revolves around cultivating and implementing a culture of risk management when it comes to the development of AI systems. It’s meant to provide a structure that aligns an organization’s ambitions in AI with its policies and strategic priorities."}]},{type:"li",value:[{type:"text",value:"\u003Cb\u003EThe Map function\u003C\u002Fb\u003E establishes the context to frame risks related to an AI system and enables risk prevention, recognition of system limitations, and assessment of impacts to inform a decision about whether the organization should design and develop an AI system at all."}]},{type:"li",value:[{type:"text",value:"\u003Cb\u003EThe Measure function\u003C\u002Fb\u003E uses knowledge from the Map function and applies quantitative, qualitative, and mixed-method tools, techniques, and methodologies to analyze and monitor AI risk and related impacts. It recommends independent review to improve the effectiveness of testing and mitigate internal biases."}]},{type:"li",value:[{type:"text",value:"\u003Cb\u003EThe Manage function\u003C\u002Fb\u003E entails allocating risk management resources to mapped and measured risks on a regular basis to decrease the likelihood of system failures and negative impacts."}]}]}
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