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Tom Zick earned her PhD from UC Berkeley and is currently pursuing her JD at Harvard. Her research bridges between AI ethics and law, with a focus on how to craft safe and equitable policy surrounding the adoption of AI in high-stakes domains. In the past, she has worked as a data scientist at the Berkeley Center for Law and Technology, evaluating the capacity of regulations to promote open government data. She has also collaborated with graduate students across social science and engineering to advocate for pedagogy reform focused on infusing social context into technical coursework. Outside of academia, Tom has crafted digital policy for the City of Boston as a fellow for the Mayor’s Office for New Urban Mechanics and developed responsible AI resources for founders as a VC fellow at Bloomberg BETA. Her current research centers on the near term policy concerns surrounding reinforcement learning.


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Between Games and Apocalyptic Robots

Tom Zick considers the near-term societal risks of reinforcement learning

Apr 16, 2021