Elizabeth is currently an affiliate of Data & Society, after spending two years as a Research Analyst in the AI on the Ground research track. She uses empirical methods to study emergent issues around artificial intelligence. Her research illuminates how the introduction of AI into sociotechnical systems produces novel kinds of human labor and unforeseen risks.
She is completing her doctorate at Columbia University where she’s advised by David Stark. Trained as an organizational sociologist in the field of Communications, she uses interviews, analysis of online communities, and surveys to understand how people interpret and strategize around the algorithmic tools they use in their work. She has published or presented at the conferences on Computer-Human Interaction (CHI), Computer-Supported Cooperative Work (CSCW), Algorithmic Fairness, Accountability, and Transparency (FAccT), the security conference USENIX and co-located workshop USENIX FOCI, and the annual meetings of the Academy of Management (AOM), the International Communications Association (ICA), the International Sociological Association (ISA), and the Society for the Social Studies of Science (4S). She’s also a Research Associate at the Tow Center for Digital Journalism at Columbia, a member of the Center on Organizational Innovation at Columbia, and a member of the Future of Work and Organizations interest group at NYU Stern. She holds a BA from the University of California at Irvine and a Master of Science from the MIT School of Architecture + Planning. Before starting her doctorate she worked for several years as a researcher at Harvard Business School. Her published case studies have been taught at HBS, the Yale School of Management, and the MIT Sloan School of Management.
In 2021 she’ll be joining the Princeton Center for Information Technology Policy as a Postdoctoral Research Associate.