Zoe Kahn is a PhD candidate at the UC Berkeley School of Information. Her research explores how AI/ML systems may result in unanticipated dynamics, including harms, to people and society. To do so, she currently uses qualitative methods to understand the perspectives and experiences of impacted communities. In this research, Kahn also uses storytelling to influence the design of technical systems and the policies that surround its use. She has conducted fieldwork in rural communities in the United States, worked on issues of homelessness in the Bay Area, and is currently working on a project that uses data-intensive methods to allocate humanitarian aid to people in Togo who are living in extreme poverty. Kahn's research has received funding from the SSRC’s Just Tech Covid-19 Rapid-Response Grant; UC Berkeley Algorithmic, Fairness, and Opacity Group; UC Berkeley Center for Long-Term Cybersecurity, and UC Berkeley Center for Technology, Society, and Policy.