What are the ethics & privacy implications of the rise of AI?
Update: Watch a professionally captioned recording of this session. You can also watch the recording with audio descriptions.
Join us Friday, July 21, for a discussion about the ethics and privacy implications of the rise of artificial intelligence (AI), led by UW–Madison faculty members Kaiping Chen and Yonatan Mintz.
Related reading:
- “How GPT-3 responds to different publics on climate change and Black Lives Matter: A critical appraisal of equity in conversational AI” (arXiv 2023, by Kaiping Chen, Anqi Shao, Jirayu Burapacheep, Yixuan Li)
- “Hard choices in artificial intelligence” (Artificial Intelligence, volume 300, Nov 2021, by Roel Dobbe, Thomas Krendl Gilbert and Yonatan Mintz)
AI Ethics and Privacy
- Date: Fri, Jul 21
- Time: 9:15am to 10am Central Time
- Location: Zoom
- Cost: Free
About the speakers
Kaiping Chen
Kaiping Chen, Ph.D., is an assistant professor of computational communication in the Department of Life Sciences Communication and an affiliate of the Department of Political Science, the UW–Madison Robert & Jean Holtz Center for Science and Technology Studies, the Center for East Asian Studies, the African Study Programs, Wisconsin Energy Institute and the Nelson Institute for Environmental Studies. Chen’s research employs data science, machine learning methods and interviews to examine how digital media and technologies affect political accountability to public well-being. Her research also examines how deliberative designs can improve the quality of public discourse on controversial and emerging technologies. Chen’s work is interdisciplinary and draws from theories in communication, political science and computer science.
Yonatan Mintz
Yonatan Mintz, Ph.D., is an assistant professor in the Department of Industrial and Systems Engineering. His research focuses on the application of machine learning and automated decision-making to human-sensitive contexts. One application of his research has been on using patient-level data to create precision weight-loss interventions that increase patient adherence. Mintz is also interested in the socio-technical implications of machine learning algorithms and has worked on fairness, accountability and transparency in automated decision-making.