Rate My Professor Mona Sloane

Mona Sloane, Ph.D., is an Assistant Professor of Data Science and Media Studies at the University of Virginia, where she joined in 2023 and directs the Sloane Lab, conducting empirical research on technology's implications for social life with a focus on AI as a social phenomenon intersecting cultural, economic, material, and political conditions. Her education includes a Ph.D. in Sociology from the London School of Economics and Political Science in 2017, an M.Sc. in Sociology, graduating top of her class, from the same institution in 2012, and a B.A. in Communication and Cultural Management with a minor in Corporate Management and Economics from Zeppelin University Friedrichshafen in 2011. Prior appointments encompass Research Assistant Professor at NYU Tandon School of Engineering (2022–2023), Senior Research Scientist at NYU Center for Responsible AI (2022–2023), Founding Director of the This Is Not A Drill program at NYU Tisch School of the Arts (2021–2023), Adjunct Assistant Professor at NYU Tandon (2019–2022), Postdoctoral Researcher at University of Tübingen AI Center (2020–2022), Postdoctoral Researcher at University of the Arts London (2018), and roles at LSE including co-founder of the Configuring Light/Staging the Social research program (2012–2016) and Field Research Manager for the Global Executive Time Use Project (2013).

Sloane, a sociologist, examines the intersection of technology and society, specifically AI design, use, policy, auditing, transparency, procurement, participation, hiring applications, and responsible AI topics. Her forthcoming book Predicted: How AI Is Restructuring Social Life will be published by University of California Press in 2026. Selected publications feature “Materiality and Risk in the Age of Pervasive AI Sensors” (Nature Machine Intelligence, 2025, with co-authors), “Boolean Clashes: Discretionary Decision Making in AI-Driven Recruiting” (Communications of the ACM, 2025), “Making Bodies: Assumptions in the Design and Validation of Motion Capture Technology” (ACM Conference on Artificial Intelligence, Ethics, and Society, 2025), “A systematic review of regulatory strategies and transparency mandates in AI regulation in Europe, the US, and Canada” (Data & Policy, 2025, with co-author), and contributions to AI auditing (arXiv, 2021) and AI transparency (Nature Machine Intelligence, 2023). Awards include UVA Mead Endowment Honored Faculty (2024), Women in AI Ethics Hall of Fame (2020), Best Paper Award at Weizenbaum Conference (2019), and Hobhouse Memorial Prize from LSE (2012). She edits the Co-Opting AI book series for University of California Press (2023–present) and Technology section of Public Books (2019–present), serves on NASEM panels including co-chair on Organizational Factors in AI Risk Management (2023–2025), UVA AI working groups, and ACM FAccT social science area chair (2022), and convenes the Co-Opting AI public speaker series.