Mapping the Landscape: Antidiscrimination Law and AI
This session explores the evolving relationship between AI and antidiscrimination law. The panel will map points of friction between AI and antidiscrimination law, including different conceptions of discrimination, measurement, and proof. The session will also consider the possibilities AI opens for antidiscrimination law. These include new tools for diagnosing disparate impact, improving methods for detecting discrimination in institutions and markets, and designing more bespoke interventions.
Foundations of AI and Antidiscrimination Law
This session provides a foundational overview of the intersection of AI and antidiscrimination law. It focuses on contemporary AI systems, their design, and their limitations, while equipping participants with conceptual tools to assess how AI may advance or inhibit the goals of antidiscrimination law. The session bridges legal and technical perspectives by introducing core concepts of antidiscrimination law for AI developers and policymakers, and by clarifying how discrimination is defined across different legal domains. It covers key legal frameworks and doctrines to address evidentiary and epistemic uncertainty in evaluating discriminatory outcomes in AI-driven systems. What do lawyers, specifically antidiscrimination advocates and scholars, need to know about AI? What legal doctrines are most relevant to both regulate AI’s engagement with antidiscrimination law? Specifically, what is the law(s) of disparate impact and how relevant is it to AI regulation? This session will be divided into two parts. Part one consists of two concurrent sessions in which technologists and lawyers will address the session’s central questions. Part two consists of facilitated discussion groups designed to foster greater understanding, engagement, and depth.
Litigation: Possibilities and Limits of Existing Doctrines
This session will survey the emerging landscape of AI discrimination litigation, from the DOJ’s landmark settlement with Meta (the first federal case challenging algorithmic ad delivery under the Fair Housing Act), to the recent Mobley v. Workday collective action AI vendor liability in employment case. This session will consider the possibilities and limits of litigation with respect to AI and machine learning. It will explore how plaintiffs and courts are grappling with traditional antidiscrimination frameworks, with special attention to disparate impact.
Case Study Breakouts
This session uses hypothetical case studies—many based on real-world disputes—to explore how AI might reshape, confound, or challenge the enforcement of antidiscrimination law in a variety of sectors. Breakout participants will grapple with how AI systems may perpetuate or obscure discrimination based on a range of protected characteristics, including race, gender, disability, language, national origin, religion, and family status. The session pushes attendees to think strategically about both legal frameworks and technological design choices, examining how discrimination is identified, proven, and addressed in AI contexts. Through interdisciplinary discussion, participants will consider how antidiscrimination law and AI governance may need to evolve to meet these emerging challenges.
Corporate Governance and Industry Norms
As artificial intelligence and emerging technologies are increasingly embedded in decisions affecting employment, housing, credit, healthcare, surveillance, and access to opportunity, corporate norms and internal “best practices” shape the definition, application and enforcement of antidiscrimination protections. This panel examines how companies operationalize concepts such as fairness, bias mitigation, transparency, and accountability—and how those choices influence litigation, regulatory oversight, and policy development. Panelists will explore when voluntary standards, audits, and governance frameworks meaningfully advance antidiscrimination goals, and when they risk narrowing legal accountability or displacing democratic decision-making. Bringing together perspectives from industry, civil-rights advocacy, and legal scholarship, the discussion will consider how evolving corporate practices may shape the future interpretation of antidiscrimination law and what guardrails are needed to ensure that emerging technologies promote inclusion rather than reproduce or exacerbate existing inequities.
Creating New Law: Regulations and Legislation
This session examines emerging approaches and continuing challenges to regulating AI discrimination, exploring international, federal, state, and city initiatives—including the EU AI Act, federal AI Bill of Rights, the California Civil Rights Department’s AI discrimination regulations, and Denver’s approach and Colorado’s AI Act. Panelists will discuss how these frameworks address the safe and responsible deployment of AI and define liability, compliance obligations, and enforcement mechanisms. Their discussion will highlight the possibilities and challenges of regulating AI, addressing the complex balance between ensuring AI is both beneficial to society and does not produce discriminatory outcomes.
Case Study Working Groups
This session uses hypothetical case studies—many based on real-world disputes—to explore how AI is reshaping antidiscrimination law in a variety of sectors. Breakout participants will grapple with how AI systems may perpetuate or obscure discrimination based on a range of protected characteristics, including race, gender, disability, language, national origin, religion, and family status. The session pushes attendees to think strategically about both legal frameworks and technological design choices, examining how discrimination is identified, proven, and addressed in AI contexts. Through interdisciplinary discussion, participants will consider how antidiscrimination law and AI governance may need to evolve to meet these emerging challenges.
What’s Next?: Building a Policy, Regulatory, and Research Agenda
This interactive session invites participants to collaboratively develop the next steps for research, regulation, and policy at the intersection of AI and antidiscrimination law. By the end of the session, each group will develop a roadmap for advancing scholarship, policy, and practice for antidiscrimination law within the era of rapid AI advancement. These roadmaps will be collected and synthesized to sketch promising policy reforms and a robust research agenda. Range of considerations include:
- Noting specifically the ambiguities in law and doctrine that make regulating AI difficult and make it harder for AI to achieve its potential to contribute to a more just society
- Articulating the challenges that AI poses for law and lawyers
- Identifying specific and key research questions as well as pathways for interdisciplinary collaboration; what are the open social science, CS/Tech, legal, and interdisciplinary research questions that are pressing and open and require more?
- Laying out the potential policies or policy considerations that civil rights lawyers and activists should pursue