AI's power needs to be coupled with a great sense of responsibility of those who develop AI or use AI. Responsible AI, however, is a complex concept that consists of theoretical framework and practical consideration, grassroots efforts and best practices, and top-down policy and regulation. The Michigan Institute for Data Science (MIDAS) and the Microsoft Responsible AI Office have started a joint funding program aiming to support academic research on developing frameworks, practical approaches and policies to enable responsible AI. This session will feature the awardees of the first round of this funding program, who use interdisciplinary research methods from social science, computer science and so on to address significant research challenges in responsible AI. We hope that their presentations will stimulate new ideas and collaboration for further research under this theme.
Speakers:
Evaluating GenAI and Team-based Solutions to Reverse the Decline of Online Knowledge Communities
Jingyi Qiu, [email protected]
Innovating, Applying, and Educating on Fairness and Bias Methods for Educational Predictive Models
Christopher Brooks, [email protected]
Advancing Responsible AI by Rethinking the Roles of Marginalized Communities in the Innovation Lifecycle: Developing the UBEC Approach
Shobita Parthasarathy, [email protected]
A Joint Human-AI Framework for Responsible AI
Colleen Seifert, [email protected]