Abigail Jacobs

Assistant Professor of Information, School of Information and Assistant Professor of Complex Systems, College of Literature, Science, and the Arts at University of Michigan

Systems thinking and structural explanations in responsible AI

March 24, 2022 - 12:00 PM Eastern Time

Virtual Location:

Zoom

Talk Abstract:

Recently the concepts of trustworthy and responsible AI have gained prominence in industry, academia, government and civil society as an AI governance rallying cry. These umbrella terms serve as useful, albeit often vacuous, ways to conceptually organize the myriad efforts to establish common standards, rules, and guardrails for the development and use of data-driven decision making systems. The key gap in the efforts to make algorithmic systems---and the decision making they effect---responsible is an understanding of complex systems and social structures. Furthermore, this gap is revealed when algorithmic systems lead to unintended harms, where 'AI accidents' reveal underlying social structure. Drawing on examples from ranking systems, the mortgage market, and algorithmic discovery and algorithmic accidents, I will discuss several recent efforts to bridge understandings of complex social systems with this emerging field.

Speaker Bio:

Abigail Jacobs is an Assistant Professor of Information and of Complex Systems at the University of Michigan, where she is also an affiliate of the Center for Ethics, Society, and Computing (ESC) and the Michigan Institute for Data Science (MIDAS). Previously she was a postdoctoral fellow at the University of California Berkeley in the Haas School of Business and in the Algorithmic Fairness and Opacity Working Group. She received a PhD in Computer Science from the University of Colorado Boulder, during which she spent time at Microsoft Research NYC and received an NSF Graduate Research Fellowship. She received a BA in Mathematical Methods in the Social Sciences (MMSS) and Mathematics from Northwestern University.