Zoe Kahn

PhD Student


algorithmic decision making, responsible innovation.


Zoe Kahn is a PhD Candidate at the UC Berkeley School of Information where her research explores how AI/ML systems may result in unanticipated dynamics, including harms to people and society. She uses qualitative methods to understand the perspectives and experiences of impacted communities; she then leverages storytelling to influence the design of technical systems and the policies that surround its use. Zoe's research seeks to understand the impacts of algorithms in two contexts: in Togo, to determine the allocation of cash aid to people living in extreme poverty; and in the San Francisco Bay Area, to determine the allocation of housing and services to people experiencing homelessness.

Zoe is part of the innagural cohort of AI Policy Hub Fellows. She is also a fellow with the UC Berkeley Center for Technology, Society and Policy, Center for Long-Term Cybersecurity, and Algorithmic Fairness and Opacity Working Group. Her research has received funding from the Social Science Research Council. 

Prior to graduate school, Zoe graduated summa cum laude from NYU in Sociology and then worked first as a product manager at a technology startup, and then as a legal assistant at a plaintiff's employment law firm.



Zoe Kahn and Jenna Burrell. 2021. A Sociocultural Explanation of Internet-Enabled Work in Rural Regions. ACM Trans. Comput.-Hum. Interact. 28, 3, Article 17 (July 2021), 22 pages. DOI:https://doi.org/10.1145/3443705

Jenna Burrell, Zoe Kahn, Anne Jonas, and Daniel Griffin. 2019. When Users Control the Algorithms: Values Expressed in Practices on Twitter. Proc. ACM Hum.-Comput. Interact. 3, CSCW, Article 138 (November 2019), 20 pages. DOI:https://doi.org/10.1145/3359240


Last updated:

December 3, 2022