Friday, March 7

8:30–8:45 am
Coffee and Continental Breakfast
 
Morning Session 8:45-11:20

Session 1: Applied AI Ethics & Law
Session Chair: Edward L. Queen, Associate Teaching Professor; Director, D. Abbott Turner Program in Ethics and Servant Leadership, Emory University
 
8:45- 8:50 am     
Welcome: Anne-Elisabeth Courrier, PhD, AI Ethics Liaison, Emory Center for Ethics; Associate Professor in Public Law, University of Nantes  
 
8:50–9:00 am
Provocation: Milan Mossé, PhD candidate in Philosophy, University of California Berkeley
 
9:00–9:40 am
Ben Eva, Associate Professor of Philosophy, Duke University 
 
9:40 – 9:50 am
Break
 
9:50–10:30 am
Naftali Weinberger, Postdoctoral Fellow, Munich Center for Mathematical Philosophy
 
10:30–10:40 am
Break
 
10:40–11:20 am
Vincent Contizer, Professor of Computer Science (with courtesy appointments in Machine Learning, Philosophy, and at the Tepper School of Business), Carnegie Mellon University
 
11:20 am –12:15 pm
Lunch Break
 
Plenary Session 12:15–1:15 pm
Scott Aaronson, Schlumberger Centennial Chair of Computer Science, University of Texas, Austin
Chair/Commentator: Kavya Ravichandran, PhD candidate, Toyota Technological Institute at Chicago
 
1:15–1:25 pm
Break

Afternoon Session 1:25–3:55 pm

Session 2: Socially Sensitive Attributes and AI
Session Chair: Jessica Roberts, Professor of Law, Artificial Intelligence, Machine Learning and Data Science, Emory University 
 
1:25–1:35 pm
Provocation: Ashia Wilson, Assistant Professor in the Department of Electrical Engineering and Computer Science at MIT
 
1:35–2:15 pm
Miron Clay Gilmore, Postdoctoral Research Associate at Purdue University
 
2:15–2:25 pm
Break
 
2:25–3:05 pm
John Jackson, Associate Professor at the Johns Hopkins Bloomberg School of Public Health, with affiliations in Epidemiology, Biostatistics, and Mental Health
 
3:05–3:15 pm
Break
 
3:15–3:55 pm
Quayshawn Spencer, Robert S. Blank Presidential Associate Professor of Philosophy at the University of Pennsylvania
 
3:55–4:20 pm
Break
 
Plenary Session 4:20–5:20 pm
Leonard Harris, Professor of Philosophy, Purdue University
Chair/Commentator: Miron Clay Gilmore, Postdoctoral Research Associate, Purdue University
 
5:20–5:30 pm
Break
 
Plenary Session 5:30-5:30 pm
Anita Allen, Henry R. Silverman Professor of Law and Professor of Philosophy, the University of Pennsylvania Law School
Chair/Commentator: Lauren Klein, Associate Professor of Quantitative Theory & Methods and English, Emory University

Saturday, March 8

8:30–8:45 am
Coffee and Continental Breakfast
 
Morning Session 8:45–11:20 am

Session 3: Modeling Fairness in AI
Session Chair: Prasanna Parasurama, Assistant Professor of Information Systems & Operations Management, Emory University

8:45- 8:50 am     
Welcome: Anne-Elisabeth Courrier, PhD, AI Ethics Liaison, Emory Center for Ethics, Adjunct, Emory School of Law  
 
8:50–9:00 am
Provocation: Ira Globus-Harris, PhD candidate in Computer and Information Sciences, University of Pennsylvania
 
9:00–9:40 am
Wes Holliday, Professor of Philosophy, University of California, Berkeley
 
9:40–9:50 am
Break
 
9:50–10:30 am
Ben Recht, Professor in the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley
 
10:30–10:40 am
Break
 
10:40–11:20 am
Maggie Penn, Professor of Political Science and Quantitative Theory & Methods, Emory University
John Patty, Professor of Political Science and Quantitative Theory & Methods, Emory University
 
11:20 am –12:15 pm
Lunch Break
 
Plenary Session 12:15–1:15 pm
Avrim Blum, Professor and Chief Academic Officer at the Toyota Technological Institute, Chicago
Chair/Commentator: Ira Globus-Harris, PhD candidate in Computer and Information Sciences, University of Pennsylvania
 
1:15–1:25 pm
Break
 
Afternoon Session 1:25–3:55 pm

Session 4: Prediction vs. Intervention
Session Chair: Naftali Weinberger, Postdoctoral Fellow, Munich Center for Mathematical Philosophy
 
1:25–1:35 pm
Provocation: Ben Jantzen, Associate Professor of Philosophy, Virginia Tech
 
1:35–2:15 pm
Frederick Eberhardt, Professor of Philosophy, California Institute of Technology
 
2:15–2:25 pm
Break
 
2:25–3:05 pm
Omer Reingold, Rajeev Motwani Professor of Computer Science, Stanford University
 
3:05–3:15 pm
Break
 
3:15–3:55 pm
Daniel Malinsky, Assistant Professor of Biostatistics, Columbia University Mailman School of Public Health
 
3:55–4:20 pm
Break
 
Plenary Session 4:20-5:20 pm
Jim Woodward, Distinguished Professor Emeritus in the Department of History and Philosophy of Science, University of Pittsburgh
Chair/Commentator: Naftali Weinberger, Postdoctoral Fellow, Munich Center for Mathematical Philosophy

5:20–5:30 pm
Break
 
Plenary Session 5:30-–6:30 pm
Deborah Mayo, Professor Emerita of Philosophy, Virginia Tech
Chair/Commentator: Ben Jantzen, Associate Professor of Philosophy, Virginia Tech

Scott Aaronson is the Schlumberger Centennial Chair of Computer Science at the University of Texas at Austin. He received his BS in Computer Science from Cornell University in 2000 and went on to earn a PhD in Computer Science from the University of California, Berkeley (2004), under Umesh Vazirani. His research addresses the capabilities and limits of quantum computers, with additional work on post-quantum cryptography and the theoretical foundations of AI safety. He is the author of Quantum Computing Since Democritus and has held positions at the Institute for Advanced Study and MIT. Among other recognitions, he is a recipient of the Alan T. Waterman Award (2012) from the NSF, the Presidential Early Career Award for Scientists and Engineers, and is a Fellow of the ACM. In 2022–2023, he took leave to work at OpenAI, focusing on AI safety.
 
Anita L. Allen is the Henry R. Silverman Professor of Law and Professor of Philosophy at the University of Pennsylvania Law School. She holds both a JD from Harvard Law School and a PhD in Philosophy from the University of Michigan. A prominent figure in law, bioethics, and the philosophy of privacy, she has deeply shaped the discourse on data ethics, feminist philosophy, and confidentiality in digital contexts. She served as Vice Provost for Faculty at Penn and is noted for bridging philosophy with legal policy in her scholarship. Allen has been elected to the National Academy of Medicine, the American Law Institute, and the American Academy of Arts and Sciences. She received the 2021 Philip L. Quinn Prize from the American Philosophical Association for service to philosophy, reflecting her leadership in scholarship on privacy, women’s rights, and racial justice.
  
Avrim Blum is Professor and Chief Academic Officer at the Toyota Technological Institute at Chicago (TTIC). He earned his PhD in Computer Science from MIT in 1991 under the direction of Ron Rivest, after which he spent over two decades on the faculty of Carnegie Mellon University. Blum’s research delves into machine learning theory, approximation algorithms, algorithmic game theory, and Algorithmic Fairness.  Blum is recipient of the AI Journal Classic Paper Award, the ICML/COLT 10-Year Best Paper Award, the ACM Paris Kanellakis Award, the Sloan Fellowship, the NSF National Young Investigator Award, and the Herbert Simon Teaching Award, and he is a Fellow of the ACM.
 
Vincent Conitzer is a Professor of Computer Science (with courtesy appointments in Machine Learning, Philosophy, and at the Tepper School of Business) at Carnegie Mellon University, where he directs the Foundations of Cooperative AI Lab (FOCAL). He obtained his PhD in Computer Science from Carnegie Mellon University (2006) and completed an AB in Applied Mathematics at Harvard (2001). Conitzer’s research explores algorithmic economics, social choice, mechanism design, and the ethics of AI. He co-authored Moral AI: And How We Get There and has shaped the field of computational social choice with influential frameworks for fair division and AI alignment. His honors include the IJCAI Computers and Thought Award, an NSF CAREER Award, the Social Choice and Welfare Prize, and fellowships from the ACM and AAAI.

Anne-Elisabeth Courrier is an Associate Professor in Public Law at the French University of Nantes. She joined the Center for Ethics, Emory University in April 2019 as a Visiting Fellow. From her PhD in Law on the “Ethos of Public Service in a comparative study between Great Britain and France” at the University of Paris I, Panthéon-Sorbonne, in collaboration with Oxford University, she has centered her research interests to the relationship between Law and Ethics from a comparative perspective.

Frederick Eberhardt is Professor of Philosophy at the California Institute of Technology. He completed his PhD in Philosophy at Carnegie Mellon University (2007) and holds an MS in Machine Learning from CMU. Eberhardt’s research concerns causal discovery, unifying philosophical conceptions of causation with formal methods from machine learning and statistics. He has extensively studied the conditions under which structural models can be inferred from observational and experimental data, including cases with hidden confounders. He has also done historical work on Hans Reichenbach’s frequentist account of probability. Eberhardt held a James S. McDonnell Foundation grant (2011–2013) for advanced inquiry into causal discovery methods.
 
Ben Eva is Associate Professor of Philosophy at Duke University, having received a PhD in Philosophy from the University of Bristol (2011). His research involves formal epistemology, logic, and the conceptual underpinnings of algorithmic fairness and interpretability in AI systems. He has authored theoretical work that unites philosophical reasoning with computational approaches to discrimination detection and prevention.
 
Miron Clay-Gilmore is a Postdoctoral Research Associate at Purdue University. He earned his PhD in Philosophy from the University of Edinburgh (2023), after commencing graduate study at Texas A&M University. His scholarship centers on the intersection of Africana philosophy, race, and ethics in AI. He draws on the radical frameworks of Frantz Fanon and Huey P. Newton to examine how emergent technologies both reflect and transform structural oppression. Gilmore is a recipient of the 2024 Laura Bassi (Essay) Scholarship and leads reading groups on Sylvia Wynter’s critiques of colonial modernity in AI discourse.

Ira Globus-Harris is a PhD candidate in Computer and Information Sciences at at the University of Pennsylvania, co-advised by Aaron Roth and Michael Kearns. Their work, which is grounded in the algorithmic foundations of responsible computing, broadly looks at mechanisms to resolve potential harms incurred by AI-driven decision-making. In particular, it focuses on using algorithmic techniques which are scalable for real-world use, holistically consider an algorithm in its broader context, and which flexibly incorporate human input. 

Leonard Harris is Professor of Philosophy at Purdue University, where he directed the Philosophy and Literature PhD program and headed the African American Studies and Research Center. He received his PhD in Philosophy from Cornell University in 1974. His influential scholarship spans insurrectionist ethics, critical pragmatism, and Africana philosophy. He is especially recognized for linking the work of Alain Locke to contemporary social and moral theory, and for his “insurrectionist ethics” approach, which emphasizes emancipatory activism. Harris has received the Franz Fanon Lifetime Achievement Award (2014) from the Caribbean Philosophical Association and the 2018 Herbert Schneider Award for his contributions to American philosophy.
 
Wesley H. Holliday is Professor of Philosophy and Chair of the Group in Logic and the Methodology of Science at the University of California, Berkeley. He earned his PhD from Stanford University with a dissertation in logic that won the 2013 E. W. Beth Dissertation Prize from the Association for Logic, Language, and Information. His current research is in logic and social choice theory, including applications of social choice to AI alignment and safety. He is a co-organizer of the workshop series on Social Choice for AI Ethics and Safety (SC4AI) and an affiliate of the Institute for Mathematics and Democracy and the Center for Human-Compatible AI.
 
John W. Jackson is Associate Professor at the Johns Hopkins Bloomberg School of Public Health, with affiliations in Epidemiology, Biostatistics, and Mental Health. He earned his ScD in Epidemiology from Harvard University (2013) and a BS in Biology from the University of Maryland, Baltimore County (1996). His research focuses on causal inference methodology, intersectionality, pharmacoepidemiology, and advanced observational study designs. He aims to develop translational approaches to health equity and policy. His honors include the 2016 Kenneth Rothman Prize for best paper in Epidemiology, and he has served as PI or co-PI on several NIH-funded projects bridging data science and public health.
 
Benjamin C. Jantzen is Associate Professor of Philosophy at Virginia Tech. He obtained his PhD in Logic, Computation, and Methodology from Carnegie Mellon University (2010) following an MS in Physics at Cornell University. Jantzen investigates how to create algorithms for automated scientific discovery, exploring logic-of-discovery questions and bridging philosophy of science with computational modeling. He has also published on classification, the concept of natural kinds, and experimental evidence in science. In 2015, Jantzen received an NSF CAREER Award to pursue integrative work on data-driven logic and philosophical conceptions of natural kind classification.

Lauren Klein is Associate Professor of Quantitative Theory & Methods and English at Emory University. She also serves as director of the Emory Digital Humanities Lab and PI of the Mellon-funded Atlanta Interdisciplinary AI Network. Before moving to Emory, she taught in the School of Literature, Media, and Communication at Georgia Tech. Klein’s research brings together computational and critical methods in order to explore questions of gender, race, and justice.

Daniel Malinsky is Assistant Professor of Biostatistics at the Columbia University Mailman School of Public Health. He received his PhD in Logic, Computation, and Method- ology from Carnegie Mellon University (2017) after completing an MS there in 2015. His research explores data-driven causal modeling, focusing on partial identification, structural learning, and unmeasured confounding. He also integrates advanced methods into environmental health, epidemiology, and public policy. Malinsky holds a K25 Career Development Award from NIH/NIEHS and collaborates widely on bridging formal causal approaches with real-world public health challenges.
 
Deborah Mayo is the author of Error and the Growth of Experimental Knowledge (1996) which won the 1998 Lakatos Prize awarded to the most outstanding contribution to the philosophy of science during the previous six years. She was elected a Fellow of The British Academy in 2022. Mayo co-edited (with A. Spanos) Error and Inference (2010, CUP). Her most recent book is Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (2018, CUP). She founded the Fund for Experimental Reasoning, Reliability and the Objectivity and Rationality of Science (E.R.R.O.R) which sponsored a 2 week summer seminar in Philosophy of Statistics in 2019 for 15 faculty in philosophy, psychology, statistics, law and computer science (co-directed with A. Spanos), and a number of seminars and workshops. She has been a Visiting Professor and a Research Associate at the Centre for the Philosophy of Natural and Social Science (CPNSS) at the London School of Economics and Political Science for many years. She publishes in philosophy of science, philosophy of inductive-statistics, and philosophy of experiment. She blogs at errorstatistics.com and phil-stat-wars.com

Milan Mossé is PhD candidate in Philosophy, University of California Berkeley, advised by Johann Frick and R. Jay Wallace. Before that, he studied philosophy, math, and computer science at Stanford, with a thesis supervised by Michael Bratman and Barry Maguire.

John W. Patty is Professor of Political Science and Professor of Quantitative Theory & Methods at Emory University. He holds a PhD in Economics and Political Science from the California Institute of Technology (2001), where his dissertation was titled “Voting Games of Incomplete Information.” He previously served as a professor at the University of Chicago, Washington University in St. Louis, Harvard University, and Carnegie Mellon University. His research focuses on formal models in political science, examining the design of political institutions, delegation, and bureaucracy. Alongside Sean Gailmard, Patty co-authored Learning While Governing: Information, Accountability, and Executive Branch Institutions (University of Chicago Press, 2012), which received the 2013 William H. Riker Book Prize in Political Economy and the 2017 Herbert A. Simon Book Prize. He has served in editorial roles for Journal of Theoretical Politics, American Journal of Political Science, and other top journals, and has been recognized with “Best Paper in the American Journal of Political Science” (2008) for “Equilibrium Party Government.”
 
Maggie Penn is Professor of Political Science and Quantitative Theory & Methods at Emory University, having previously been a professor at the University of Chicago and an associate professor at Washington University in St. Louis. She earned her PhD in Social Science from the California Institute of Technology in 2003. Penn’s work applies formal political theory, social choice, and computational modeling to questions of democratic representation, fairness, and institutional design. She is co-author (with John W. Patty) of Social Choice and Legitimacy: The Possibilities of Impossibility (Cambridge University Press, 2014). Penn has led several NSF-funded initiatives on modeling political processes and analyzing big data in political contexts.

Kavya Ravichandran is a PhD candidate in Computer and Information Sciences at the Toyota Technological Institute at Chicago. She is advised by Avrim Blum and has also worked with Nati Srebro. Her work focuses on algorithmic decision-making in social problems and understanding theoretical problems that emerge with machine learning at scale related to data and deep learning theory.

Ben Recht is Professor in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. After receiving a BS in Mathematics from the University of Chicago, he went on to earn his MS and PhD from the MIT Media Lab. He was an Assistant Professor at the University of Wisconsin–Madison before joining Berkeley. Recht is a leading expert on optimization in machine learning, bridging theoretical advances with systems-level concerns of fairness, interpretability, and performance. He is a Presidential Early Career Award for Scientists and Engineers laureate and an Alfred P. Sloan Research Fellow, and he has received multiple “Test of Time” awards at NeurIPS for his influential work.
 
Omer Reingold is the Rajeev Motwani Professor of Computer Science at Stanford University. He received a PhD in Computer Science from the Weizmann Institute of Science in 1998. Reingold is noted for breakthroughs in pseudorandomness, derandomization, and cryptography. He has also made important contributions to fairness in machine learning, directing the Simons Collaboration on the Theory of Algorithmic Fairness. Reingold won the 2005 Grace Murray Hopper Award for his deterministic log-space algorithm for undirected ST-connectivity, was a co-recipient of the 2009 G¨odel Prize for the zig-zag product (with Avi Wigderson and Salil Vadhan) and is a Fellow of the ACM.

Jessica L. Roberts is a Professor of Law, Artificial Intelligence, Machine Learning and Data Science at Emory University School of Law. She specializes in the legal and ethical issues related to genetics and other emerging health technologies, disability rights, and antidiscrimination law.

Quayshawn Spencer is the Robert S. Blank Presidential Associate Professor of Philosophy at the University of Pennsylvania. He completed a PhD in Philosophy (2009) and an MS in Biology (2008) at Stanford University, building on a BA in Philosophy and Chemistry from Cornell University. Spencer is well-known for contributions to the philosophy of race, especially the intersection of population genetics and the conceptual underpinnings of “race.” He co-authored What is Race? Four Philosophical Views (Oxford University Press, 2019). In 2021, Spencer was elected as a Hastings Center Fellow, acknowledging his significant influence on ethical, legal, and social issues in race and genomics.

Naftali Weinberger is a postdoctoral research fellow at the Munich Center for Mathematical Philosophy. He completed his Ph.D. at the University of Wisconsin, Madison in 2015 and has previously done research at the Pittsburgh Center for Philosophy of Science and the Tilburg Center for Logic, Ethics, and Philosophy of Science. Naftali uses recently developed causal modeling methods to address foundational questions concerning causal inference and explanation. His current projects one on causation in dynamical systems as well as a separate project on causally modeling discrimination.

Ashia Wilson is an Assistant Professor in the Department of Electrical Engineering and Computer Science at MIT. She earned a BA in Applied Mathematics from Harvard and a PhD in Statistics from UC Berkeley. Her research focuses on the foundations of optimization, large-scale learning systems, and algorithmic fairness. She has worked at Microsoft and Google AI on bridging theoretical insights with practical machine learning pipelines. Wilson has received a National Science Foundation Graduate Research Fellowship and was recognized with a Spotlight Paper Award at NeurIPS 2017 for “The Marginal Value of Adaptive Methods in Machine Learning.”
 
Jim Woodward is Distinguished Professor Emeritus in the Department of History and Philosophy of Science at the University of Pittsburgh and previously served as the J.O. and Juliette Koepfli Professor of Humanities at Caltech. He completed his PhD in Philosophy at the University of Texas at Austin and has profoundly influenced studies of causation, intervention, and scientific explanation through his Making Things Happen: A Theory of Causal Explanation. Woodward received the 2005 Lakatos Award for that work and has been elected a Fellow of the American Academy of Arts and Sciences. He continues to elaborate an interventionist theory of causation relevant to policy design and algorithmic decision-making.