My dissertation research answers this question by building news archival datasets that examine the relationship between work and technological change. I develop a five-part typology of governance claims workers use and examine the ways that AI can circumvent certain claims through the decentralized, systematized nature of these technologies. I argue that using historical precedent allows us to understand what is truly integral to the relationship between work, technology, and human identity even as society undergoes rapid changes. Earlier versions of this work were published in The Oxford Handbook on AI Governance, ACM Fairness, Accountability, and Transparency in Computing (FAccT), and Industrial and Labor Relations (ILR) Review.

In addition to my dissertation research, I am the Future of Work Lead on the Responsible AI Initiative at the Berkeley AI Research Lab (BAIR) on three research projects. The first project asks what factors contribute to responsible use of generative AI technologies in the workplace. We surveyed and interviewed hundreds of product managers globally to understand what factors enable responsible AI practices and summarized our findings in an industry playbook and academic article (ACM FACCT 2026, forthcoming). The second project examines how different populations use AI transparency tools such as model cards and benchmarks and has similarly been published in an industry playbook. The third project includes designing an online course in responsible AI practices and uses experimental design to assess the impact of instruction on responsible AI practices.