Serena Booth

Assistant Professor of Computer Science

serena_booth@brown.edu

CIT 427

Personal Website

Areas of Expertise Labor, Science & Technology Policy, Technology & Innovation, Technology and Policy

Areas of Interest AI Policy, Technology Policy, Economic Policy & Labor, Consumer Protection

Biography

Serena Booth is an Assistant Professor in Computer Science. Serena studies how people write specifications for AI systems and how people assess whether AI systems are successful in learning from their specifications, as well as how to govern these complex systems. Serena was previously a UC Berkeley Simons Institute for the Theory of Computing Law and Society Senior Fellow (2025). Prior to that, she worked in the U.S. Senate as a AAAS AI Policy Fellow (2023--2025) on issues related to AI and consumer protection, economic policy, and labor. Serena co-chairs an ACM Technology Policy Subcommittee on AI and Algorithms. She has received an NSF CAREER award and has been named a Senior Fellow at the Microsoft AI Economy Institute as well as a CIFAR Global Scholar. She received her PhD at MIT CSAIL in 2023 and her BA from Harvard in 2016.

Research

AI systems increasingly shape decisions that affect workers, consumers, and society. The GIRAFFE Lab and I develop technical and policy approaches for governing these systems. We combine ethnographic research with workers and other stakeholders to understand how AI is changing the workplace, identify gaps in existing legal protections, and inform the design of AI systems that better reflect human needs. Building on this empirical foundation, we study how existing legal and regulatory frameworks can be applied to constrain AI development and deployment, and where new governance mechanisms are needed. Our goal is to develop approaches to AI governance that ensure AI advances human well-being, protects workers, and supports a people-first vision for the future of AI.

Publications

TMLR ‘26 Stephane Hatgis-Kessell, W. Bradley Knox, Serena Booth, Scott Niekum, & Peter Stone, Influencing Humans to Conform to Preference Models for RLHF, Transactions on ML Research.

AIES ‘26 Malihe Alikhani, Jeongeun Kim, Anna Haensch, Saki Imai, Serena Booth, Andrea Stith, & Adriana Bankston, Bridging AI Research and Policy: A Framework for Effective Co production, AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society.

AIES ‘26 Isaac Sheidlower, Tomo Lazovich, Harini Suresh, & Serena Booth, Sharing (Robots) is Caring: Shared Robot Ownership as an Alternative to Private and Corporate Models, AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society.

CACM‘26 Cynthia Bailey, Serena Booth, Soribel Felix, Eoghan Stafford, Rebecca Voglewede, & Kiri Wagstaff, Working on AI and Technology Policy In the U.S. Senate, Communications of the ACM (CACM).

FAccT ‘26 Samantha D’Alonzo, Frauke Kreuter, & Serena Booth, Helpful, Harmless, Honest? Reconsidering RLHF as Survey Design and Content Moderation.

HRI ‘26 Tiffany Horter, Andrew Markham, Niki Trigoni, & Serena Booth, Should robots comply with our instructions or intentions?, ACM/IEEE International Conference on Human-Robot Interaction (HRI)

Teaching

CSCI 1952A: Human-AI Interaction
CSCI 0410/1411: Foundations of AI and ML