Co-sponsored by the MIT Schwarzman College of Computing and Laboratory for Information and Decision Systems.
Join us for an engaging seminar series featuring distinguished scholars exploring AI’s impact on society, ethics, governance, and human-computer interaction. Open to all students, faculty, and the public.
Spring/Fall 2025 Organizers: Hadeel Alnegheimish, Kate Donahue, Shomik Jain, Olawale Salaudeen, Rakshit Trivedi, Edward Vendrow, and the amazing SCC and LIDS administrative team.
Fall 2025
Diyi Yang
Assistant Professor of Computer Science at Stanford University
Talk Date: September 16, 2025
Lily Xu
Assistant Professor of Industrial Engineering and Operations Research at Columbia University
Talk Date: October 6, 2025
Emily Black
Assistant Professor of Computer Science and Engineering at New York University
Talk Date: October 21, 2025
Angelina Wang
Assistant Professor of Information Science at Cornell University
Talk Date: November 3, 2025
Nikhil Garg
Assistant Professor of Operations Research and Information Engineering at Cornell University
Talk Date: November 18, 2025
Spring 2025
Kathleen Creel
Assistant Professor of Philosophy and Religion and Computer Science at Northeastern University
Talk Date/Time: March 18, 2025 at 4 PM
Location: 32-141
Talk Title: Ethics of Algorithmic Monoculture and Systemic Exclusion
Talk Abstract: Mistakes are inevitable, but fortunately human mistakes are typically heterogenous. Using the same machine learning model for high stakes decisions creates consistency while amplifying the weaknesses, biases, and idiosyncrasies of the original model. When the same person re-encounters the same model or models trained on the same dataset, she might be wrongly rejected again and again. Thus algorithmic monoculture could lead to consistent ill-treatment of individual people by homogenizing the decision outcomes they experience. Is it unfair to allow the quirks of an algorithmic system to consistently exclude a small number of people from consequential opportunities? And if it is unfair, does its unfairness depend on correlation with bias? I will present an ethical argument for why and under what circumstances algorithmic homogenization of outcomes is unfair.
Speaker Bio: Kathleen Creel is an assistant professor at Northeastern University appointed in the Department of Philosophy and Religion and in Khoury College of Computer Sciences. Her research explores the moral, political, and epistemic implications of machine learning as it is used in automated decision making and in science.
Elena Glassman
Assistant Professor of Computer Science at Harvard John A. Paulson School Of Engineering And Applied Sciences
Talk Date/Time: April 15, 2025 at 4 PM
Location: 45-102
Talk Title: Leveraging Theories of Human Cognition to Build Reliable Tools from Unreliable AI
Talk Abstract: AI is powerful, but it can make choices that result in objective errors, contextually inappropriate outputs, and disliked options. This is especially critical when AI-powered systems are used for context- and preference-dominated open-ended AI-assisted tasks—like ideating, summarizing, searching, sensemaking, and the reading and writing of text or code. We need AI-resilient interfaces that help users notice and recover from AI choices that are not right, or not right for them given their goals and context. We have derived design implications from key theories of human cognition to help us build more AI-resilient interfaces and reliable tools from unreliable AI. This talk will walk through two new systems that demonstrate this approach: CorpusStudio, an AI-powered writing environment, and MOCHA, a tool for co-adaptive machine teaching.
Speaker Bio: Elena L. Glassman is an Assistant Professor of Computer Science at the Harvard John A. Paulson School of Engineering & Applied Sciences, specializing in human-computer interaction. Prior to that, she was a postdoctoral scholar at UC Berkeley, and obtained a BS, MEng, and PhD in Electrical Engineering and Computer Science from MIT. She has been named a Stanley A. Marks & William H. Marks Professor at the Radcliffe Institute for Advanced Study and a National Academy of Sciences Kavli Fellow. Her work has been funded by the NSF, private industry, the Berkeley Institute for Data Science, and the Sloan Research Fellowship. This work has received Best Paper and Honorable Mention awards at top-tier human-computer interaction research venues.
Chinasa T. Okolo
Fellow – Governance Studies, Center for Technology Innovation at the Brookings Institution
Talk Date/Time: April 29, 2025 at 4 PM
Location: 45-102
Talk Title: Broadening Perspectives on African Governance in the Era of AI
Talk Abstract: The intensifying development of machine learning (ML) models and the adoption of artificial intelligence (AI) tools, particularly generative AI, has dramatically shifted practices around data, spurring the development of new industries and unveiling unprecedented forms of exploitation. These new complexities around the production, refinement, and use of data indicate severe implications for African countries, including the widescale spread of generative AI-driven disinformation, increased manipulation exacerbated by digital platforms, and the continuation of colonial-era marginalization through datafication practices. These concerns elevate a need for comprehensive and harmonized data regulation efforts across the African continent, given existing challenges with fragmented policy implementation and limited capacity for regulatory enforcement. This talk examines the burgeoning AI and data governance landscape in Africa, analyzing the impact of AI on democratic processes, outlining best measures for data governance policy reform, and delineating priorities to democratize African participation in global AI governance.
Speaker Bio: Chinasa T. Okolo, Ph.D., is a Fellow at The Brookings Institution and a recent Computer Science Ph.D. graduate from Cornell University. Her research focuses on AI governance for the Global Majority, datafication and algorithmic marginalization, and the socioeconomic impact of data work. Dr. Okolo has been recognized as one of the world’s most influential people in AI by TIME, honored in the inaugural Forbes 30 Under 30 AI list, and advises numerous multilateral institutions, national governments, corporations, and nonprofits. In addition to her work at Brookings, Dr. Okolo serves as a Drafting Member of the Nigerian National AI Strategy, a Consulting Expert to the African Union AI Continental Strategy, an Expert Contributing Writer to the International AI Safety Report, and the Editor-in-Chief of ACM SIGCAS Computers and Society. Her research has been covered widely in media outlets and published at top-tier venues in human-computer interaction and sociotechnical computing.
