Title: Equitable Access to Quality Information and Generative AI

Abstract: Quality public affairs information is essential to democracy, and news organizations have historically served as trustworthy institutions for accurate, accessible, diverse, and relevant public affairs information. Today, people are increasingly turning to generative AI (genAI) systems for such information; yet, the effects of this change are unclear: while genAI can help summarize information across myriad sources or provide direct answers to citizens’ questions, it can also obscure (and sometimes invent) sources, amplify bias or errors, and reduce plurality in information. These new information-seeking dynamics also weaken connections between the public and newsrooms. This talk discusses how we use state-of-the-art methods to train new AI systems and measure their effects in large online experiments as well as work with non-profit Meedan to build and deploy generative AI systems with media and other public-interest organizations. 

Prof. Scott A. Hale is Professor of Social Data Science and Director of the Oxford Internet Institute, a multidisciplinary department at the University of Oxford focused on understanding the effects of new technologies on society. He is also Director of Research at Meedan, a technology nonprofit building public interest AI tools. At Oxford, he leads the Equitable Access to Quality Information Lab (eaqilab), which focuses on developing and applying new machine learning approaches to understand and improve how people discover, evaluate, and make use of online information in their daily lives. He is particularly interested in LLM alignment and multilingual Natural Language Processing applications as well as putting research into practice with community and media organizations.