How can we avoid an instrumentalist orientation when it comes to the generative AI tools that should be available? Researchers and practitioners will come together to discuss the conversation on how generative AI can be used to solve real-world problems through user-centered design principles.

Speakers:

Prof. A.T Kingsmith - Humber College

A.T. (Adam) Kingsmith is a writer, technologist, and mental health researcher. His work focuses on the political economy of anxiety and the development of emotion-AI systems to improve social and economic outcomes. He completed his PhD at York University and currently teaches in Faculty of Arts and Science at OCADU. He is also co-founder of EiQ Technologies Inc., an emotion-AI startup formerly based at Toronto Metropolitan University’s Creative Innovation Studio. He has written numerous books and articles on these topics, including the forthcoming Anxiety as a Weapon: From Public Secret to Anxious Solidarity. For more, visit his website.

Mr. Ivan Alfaro - Relativity

Ivan Alfaro is a Senior AI Product Manager at Relativity, where he has worked for seven years. He manages a portfolio of AI products, including sentiment analysis, and has co-authored white papers on Relativity’s approach to developing responsible AI solutions for e-Discovery and Investigation. Ivan holds an MSc and PhD in Management of Information Systems.

Prof. Hoda Heidari - Carnegie Mellon School of Computer Science

Hoda Heidari is the K&L Gates Career Development Assistant Professor in Ethics and Computational Technologies at Carnegie Mellon University, with joint appointments in Machine Learning and Societal Computing. She is affiliated with the Human-Computer Interaction Institute and Heinz College of Information Systems and Public Policy. Her research is broadly concerned with the social, ethical, and economic implications of Artificial Intelligence, particularly issues of fairness and accountability through the use of Machine Learning in socially consequential domains. Her work in this area has won a best-paper award at the ACM Conference on Fairness, Accountability, and Transparency (FAccT), an exemplary track award at the ACM Conference on Economics and Computation (EC), and a best-paper award at the IEEE Conference on Secure and Trustworthy Machine Learning (SAT-ML). Dr. Heidari co-founded and co-leads the university-wide Responsible AI Initiative at CMU. She has organized several scholarly events on Responsible and Trustworthy AI, including tutorials and workshops at top-tier Artificial Intelligence academic venues, such as NeurIPS, ICLR, and the Web conference. She is particularly interested in translating research contributions into positive impact on AI policy and practice. She has organized multiple campus-wide events and policy convenings to address AI governance and accountability. Dr. Heidari completed her doctoral studies in Computer and Information Science at the University of Pennsylvania. She holds an M.Sc. degree in Statistics from the Wharton School of Business. Before joining Carnegie Mellon as a faculty member, she was a postdoctoral scholar at the Machine Learning Institute of ETH Zurich, followed by a year at the Artificial Intelligence, Policy, and Practice (AIPP) initiative at Cornell University.

Chair:

Mrs. Emmanuelle Demers - WOODS LLP

Commercial Litigation and International Arbitration Lawyer at WOODS LLP