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Tom Zick has her PhD from UC Berkeley and researches the intersection of open data governance, AI ethics, and cybersecurity. Trained in machine learning, Tom is especially interested in how to craft safe and equitable policy surrounding the adoption of AI in high-stakes domains. Within academia, 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 worked with graduate students across social science and engineering to advocate for pedagogy reform focused on infusing social context into technical coursework. Tom has also worked on digital transparency in the public realm for the city of Boston as a Mayor’s Office for New Urban Mechanics fellow. Her current research focuses on the near term policy concerns surrounding reinforcement learning. 


BKC Medium Collection

Between Games and Apocalyptic Robots

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

Apr 16, 2021