Mona Sloane, Ph.D., is an Assistant Professor of Data Science and Media Studies at the University of Virginia (UVA). As a sociologist, she studies the intersection of technology and society, specifically in the context of AI design, use, and policy. She also convenes the Co-Opting AI series, a public speaker series focused on all aspects of AI technology and its application, ranging from security to food, games, and more, and serves as the editor of the Co-Opting AI book series at the University of California Press as well as the Technology Editor for Public Books.
Mona Sloane, Ph.D., is an Assistant Professor of Data Science and Media Studies at the University of Virginia (UVA). As a sociologist, she studies the intersection of technology and society, specifically in the context of AI design, use, and policy. She also convenes the Co-Opting AI series, a public speaker series focused on all aspects of AI technology and its application, ranging from security to food, games, and more, and serves as the editor of the Co-Opting AI book series at the University of California Press as well as the Technology Editor for Public Books.
Her current work includes the development of new methods for AI auditing and AI transparency, innovating AI procurement, AI in hiring and talent acquisition, AI participation and public education, new AI tools for investigative journalism, global AI policy and local governance innovation on AI, and a range of different AI topics.
At UVA, Mona runs Sloane Lab which conducts empirical research on the implications of technology for the organization of social life. Its focus lies on AI as a social phenomenon that intersects with wider cultural, economic, material, and political conditions. The lab spearheads social science leadership in applied work on responsible AI, public scholarship, and technology policy.
Previous projects Mona has led include A BETTER TECH, a public interest technology convention and career fair that brought together students and organizations in the public interest technology space across the United States and beyond that reached over 12,000 people, the Terra Incognita NYC project, an investigation of New York City’s digital public spaces in the pandemic, as well as the AI Procurement Roundtables project in collaboration with the IEEE Standards Association. In Spring 2020, Mona worked with the Swiss Consulate New York City on the “AI Here and There” series on the social impact of AI. From 2020-2021 she was an inaugural fellow of the Future Imagination Collaboratory (FIC) at NYU’s Tisch School of the Arts. In December 2020, she was added to the “100 Brilliant Women in AI Ethics Hall of Fame”. In 2021, she was named a NYU Faculty Honoree. Since 2021, she has served on the board of the Artificial Intelligence & Equality Initiative of the Carnegie Council for Ethics and International Affairs.
Mona currently is a Fellow with the NYU Institute for Public Knowledge and The GovLab, and is affiliated with the Tübingen AI Center in Germany where she recently completed a 3-year federally funded research project on the operationalization of ethics in German AI startups.
Mona holds a PhD from the London School of Economics and Political Science and has completed fellowships at the University of California at Berkeley, at the University of Cape Town, and at the Weizenbaum Institute Berlin. Before joining UVA, Mona was a Research Assistant Professor at NYU’s Tandon School of Engineering, a Senior Research Scientist at the NYU Center for Responsible AI, and the Founding Director of the *This Is Not A Drill* program, which develops public pedagogy on art, equity, technology, and the climate emergency.
Mona is a frequent public speaker and commentator, and has written for The Guardian, MIT Technology Review, The Hill, Nature, Times Higher Education, Frankfurter Allgemeine Zeitung, OneZero Medium, and other outlets. She tweets at @mona_sloane.
Recent Events
Future of Work Conference, AI and Recruiting: The Need for Transparency, April 3, 2024, Virtual
IBC Bank and Commerce Bank Keynote Speaker Series, Keynote, March 20, 2024, Texas A&M International University, Laredo, Texas, USA
National Institute of Standards and Technology (NIST), Human Subjects Research Day, Keynote, March 14, 2024, Gaithersburg, Maryland, USA
Co-Opting AI: Campaigning, February 29, 2024, UVA Karsh Institute of Democracy and NYU Institute for Public Knowledge, Video
The Algorithm: AI, Civil Rights, and the Workplace, Book Talk with Hilke Schellmann, February 15, 2024, UVA Karsh Institute of Democracy, Charlottesville, Virginia, USA
Telekom Management Team Meeting 2024, Keynote, January 31, 2024, Bonn, Germany
Motion Capture Audit Workshop, January 24, 2024, University of Virginia, Charlottesville, Virginia, USA
Co-Opting AI: Athletics, December 6, 2023, UVA Karsh Institute of Democracy and NYU Institute for Public Knowledge, Video
UVA Conference on Leadership in Business, Data, and Intelligence, December 5, 2023, University of Virginia, Arlington, Virginia, USA
RGF Staffing, AI and HR Roundtable: Transforming Staffing and Mitigating Risks, November 30, 2023, Virtual
Co-Opting AI: Origins, November 20, 2023, NYU Institute for Public Knowledge, Video
AI & The Student Experience, November 13, 2023, Tufts University, Medford, Massachusetts, USA
AI in Student Services, November 12, 2023, Student Affairs Administrators in Higher Education (NASPA), Portland, Maine, USA
2023 6th International Academic Conference on Artificial Intelligence and Laws-AI Financial Goverence & AI Basic Act and Generative AI, October 28, 2023, International Artificial Intelligence and Law Research Foundation, Taipei City, Taiwan
Innovating AI Accountability: Bridging Social Science and Technical Approaches, October 19, 2023, University of Maryland, College Park, Maryland, USA
Responsible AI Workshop, October 17, 2023, Northeastern University, Boston, Massachusetts, USA
ML Sensors: Safeguarding User Privacy in the Era of Sensor Intelligence, October 2-3, 2023, Harvard Radcliffe Institute, Cambridge, Massachusetts, USA
Sociotechnical Audit Summit, September 27-28, 2023, The Data Nutrition Project, Virtual
Talent Summit 2023, September 20, 2023, Gem, Session Recording
Discriminatory Affects of AI and Algorithms, September 13, 2023, League of Women Voters of Maine, Virtual
INTERSPEECH 2023, August 21, 2023, Dublin, Ireland
Sociotechnical Approaches to Measurement and Validation for Safety in AI, July 18-29, 2023, Center for Advancing Safety of Machine Intelligence, Northwestern University and UL Research Institutes, Evanston, Illinois, USA
AI Auditing Workshop, June 14, 2023, University of Notre Dame, South Bend, Indiana, USA
AI and Hiring, June 23, 2023, Fairness and Intersectional Non-Discrimination in Human Recommendation (FINDHR), Universidad Pompeu Fabra, Barcelona, Spain
American Council of Learned Societies, Research University Consortium in Support of the Humanities and Interpretive Social Sciences, May 31, 2023, Virtual
(un)Stable Diffusions, May, 23-24, 2023, Milieux Institute, Virtual
Is an Algorithm Your Next Hiring Manager?, May 10, 2023, The Future of Work Podcast, International Labor Organization, Podcast
Co-Opting AI: Classification, May 9, 2023, NYU Institute for Public Knowledge, New York City, USA, Video
Data Collection and Distribution Processes as Enablers for the Exercise of Human Rights, May 4, 2023, United Nations, New York City, USA, Video
Co-Opting AI: Language, April, 27, 2023, NYU Institute for Public Knowledge, New York City, USA, Video
Digitalisierung und KI in der Justiz: Chancen und Grenzen, April 24, 2023, University of Würzburg Law School, Würzburg, Germany
Artificial Intelligence and Recruiting: Gatekeeping the Labor Market, March 3, 2023, Night of Ideas by the Cultural Services of the French Embassy, the Ukrainian Institute of America, New York City, USA
Co-Opting AI: Recruiting, February 22, 2023, NYU Institute for Public Knowledge, New York City, USA, Video
Automation by Design, February 17, 2023, Charles Babbage Institute, University of Minnesota, Minneapolis, USA
Rethinking Work: AI, Recruiting, and Accountability, February 16, 2023, NYU SPS Human Capital Management, New York City, USA, Video
Gatekeeping the labor market: How Recruiters use AI to find and assess talent, January 10, 2023, International Labour Organization, Geneva, Switzerland, Video
Co-Opting AI: Agriculture, December 6, 2022, NYU Institute for Public Knowledge, New York City, USA, Video
First International Algorithmic Auditing Conference, November 8, 2022, Barcelona, Spain
Algorithmic Auditing Workshop, October 24, 2022, The German Marshall Fund of the United States, Virtual
Managing AI Risk, October 19, 2022, National Institute of Standards and Technology, Video
Co-Opting AI: Robot Law, October 19, 2022, NYU Institute for Public Knowledge, New York City, USA, Video
AI & Future of Work, October 13, 2022, ETH Zürich AI Policy Summit, Zürich, Switzerland, Video
Understanding AI Ethics as Cultural Practice, We Robot Conference, September 14-16, 2022, University of Washington, Seattle, USA
Selected Publications
Sloane, M., Solano-Kamaiko, I.R., Yuan, J. et al. Introducing contextual transparency for automated decision systems. Nat Mach Intell 5, 187–195 (2023). https://doi.org/10.1038/s42256-023-00623-7
Sloane, M. (2024): ‘Controversies, contradiction, and “participation” in AI’ In: AI. Big Data & Society, Volume 11, Number 1, February 2024. Link
Sloane, M., Solano-Kamaiko, I., Yuan, J., Dasgupta., A., Stoyanovich, S. (2023): ‘Introducing Contextual Transparency for Automated Decision Systems’, In: Nature Machine Intelligence, published online March 2023. Link
Sloane, M. (2022): ‘To make AI fair, here’s what we must learn to do’. In: Nature, Volume 605, Number 7908, May 2022. Link
Sloane, M. (2022): ‘Threading Innovation, Regulation, and the Mitigation of AI Harm: Examining Ethics in National AI Strategies.’ Book Chapter in ‘The Global Politics of Artificial Intelligence.’ Taylor & Francis/Routledge, New York. Link
Sloane, M., Moss, E., Chowdhury, R. (2022): ‘A Silicon Valley Love Triangle: Hiring Algorithms, Pseudo-Science, and the Quest for Auditability’, In: Patterns (Cell Press), Volume 3, Number 2, February 2022. Link
Sloane, M., Zakrzewski, J. (2022): ‘German AI Start-Ups and “AI Ethics”: Using A Social Practice Lens for Assessing and Implementing Socio-Technical Innovation.’ 2022 ACM Conference on Fairness, Accountability, and Transparency, June 2022. Link
Sloane, M., Moss, E., Awomolo, O., Forlano, L. (2022): ‘Participation Is not a Design Fix for Machine Learning’, 2022 ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, October 2022. Link
Rhea, A., Markey, K. D’Arinzo, L., Schellmann, H., Sloane, M., Squires, P., Stoyanovich, J. (2022): ‘Resume Format, LinkedIn URLs and Other Unexpected Influences on AI Personality Prediction in Hiring: Results of an Audit’, 2022 ACM Conference on Artificial Intelligence, Ethics, and Society, July 2022. Link
Sloane, M., Kraemer, J. (2021): ‘Terra Incognita NYC – Mapping New York City’s New Digital Public Spaces During the Covid-19 Outbreak’. New York University, 2021. Link
Sloane, M., Chowdhury, R., Havens, J.C., Rincon Alba, L.C. (2021): ‘AI and Procurement – A Primer’. New York University, June 2021. Link
Sloane, M., Moss, E. (2019): ‘AI’s Social Sciences Deficit’. In: Nature Machine Intelligence, Volume 1, August 2019. Link
Sloane, M. (2019): ‘Inequality Is the Name of the Game: Thoughts on the Emerging Field of Technology, Ethics and Social Justice’, 2019 Weizenbaum Conference on Challenges of Digital Inequality: Digital Education, Digital Work, Digital Life, May 2019, Best Paper Award. Link
Sloane, M. Beecham, N. (Eds.) (2019): ‘On the Need for Mapping Design Inequalities’. Design Issues (MIT Press), Volume 35, Number 4, September 2019. Link
Selected Press
Hoos in STEM (2024): ‘Dr. Mona Sloane is on the Cutting Edge of AI Ethics’, In: Hoos in STEM, April 2024. Link
Pepitone, J. (2024): ‘AI Is Being Built on Dated, Flawed Motion-Capture Data “Gold standard” data is based on certain body types...and cadavers’, In: IEEE Spectrum for the Technology Insider, March 2024. Link
Waters, G. and Miller, C. (2024): ‘A How-To Guide on Acquiring AI Systems: The IEEE standard helps government agencies strengthen their purchasing requirements’. In: IEEE Spectrum for the Technology Insider, January 2024. Link
UVA Data Science (2024): ‘New Research Examines How Assumptions Affect Motion Capture Technology’. In: UVA Data Science News, January 2024. Link
Office of Management and Budget (2024): ‘Comment on OMB-2023-0020-0001’, In: Regulations.gov, December 2023. Link
UVA Data Science (2023): ‘Two Data Science Faculty Members Awarded DCADS Research Fellowships’. In: UVA Data Science News, December 2023. Link
Biron, C. (2023): ‘Cities draw up AI policies as US federal laws lag behind’. In: Thomson Reuters Foundation, November 2023. Link
Sloane, M. (2023): ‘Biden’s AI executive order underlines need for student technology councils’. In: Times Higher Education, November 2023. Link
Boone, E. (2023): ‘Strike two: Residual anxieties haunt actors, AI and the arts’. In: The Cavalier Daily, November 2023. Link
UC Press (2023): ‘Q&A with Mona Sloane, Editor of New Co-Opting AI Book Series’. In: UC Press, November 2023. Link
Bahorsky, R. (2023): ‘Bridging Journalism’s Technological Divide’. In: University of Virginia, College and Graduate School of Arts & Sciences, October 2023. Link
NYU-TV (2023): ‘This Is Not A Drill 2023 Exhibition Video’, September 2023. Link
Azzo, A. (2023): ‘Measuring Safety in Artificial Intelligence: ‘Positionality Matters’. In: Center for Advancing Safety of Machine Intelligence, August 2023. Link
Gurung, A. (2023): ‘Promises and Controversies of AI’s (Un)Stable Diffusions: Highlights of the Keynote Panels‘. In: Milieux, July 2023. Link
Davis, L. (2023): ‘The New Age of Hiring: AI Is Changing the Game for Job Seekers’. In: CNET, June 2023. Link
Sloane, M., Ernst, E. (2023): ‘The shake-up of the tech sector shows: we must learn from finance regulation’. In: The Hill, March 2023. Link
Edward Moreno, J. (2023): ‘Workplace AI Vendors, Employers Rush to Set Bias Auditing Bar’. In: Bloomberg Law, March 2023. Link
Mhlungu, G. (2023): ‘How Artificial Intelligence Is Affecting Human Rights and Freedoms’. In: Global Citizen, January 2023. Link
Walk-Morris, T. (2022): ‘These algorithms could be getting between you and your next job’. In: Quartz, December 2022. Link
Onderka, L. (2022): ‘Eine KI kann das Entwicklungspotenzial eines Bewerbers nicht erkennen: Interview mit Mona Sloane’. In: Personalwirtschaft, November 2022. Link
Inside Big Data (2022): ‘AI Hiring Experts on President Biden’s AI Bill of Rights’. In: Inside Big Data, November 2022. Link
Sloane, M. (2022): ‘AI-Driven Biometry and the Infrastructures of Everyday Life’. In: Ada Lovelace Institute, May 2022. Link
Sklar, J. (2022): ‘5 Tips for Covering Racial Bias in Health Care AI’. In: The Journalist’s Resource, Shorenstein Center on Media, Politics and Public Policy, Harvard Kennedy School, July 2022. Link
Irwin, V. (2022): ‘The Rise of Tech Ethicists Shows How the Industry is Changing’. In: Protocol, April 2022. Link
Kaye, K. (2022): ‘A New Wave of AI Auditing Startups Wants to Prove Responsibility Can Be Profitable’. In: Protocol, January 2022. Link
Sloane, M. (2021): ‘The Algorithmic Auditing Trap’. OneZero, May 17, 2021. Link
Sloane, M. (2021): ‘Surveillance Society: Artificial Lighting for a Policed Public’. In: The Architectural Review, September 2021. Link
Deutsche Welle (2021): ‘Looking into the future II – Technology to the rescue’. In: DW Global Media Forum 2021. Link
Sloane, M. (2020): ‘Participation-washing could be the next dangerous fad in machine learning’. In: MIT Technology Review, August 2020. Link
Verhulst, S., Sloane, M. (2020): ‘Realizing the Potential of AI Localism’. In: Project Syndicate, February 2020. Link
Sloane, M. (2019): ‘Intelligente Maschinen hinter ethischen Rauchwänden’. In: Frankfurter Allgemeine Zeitung, Feuilleton, June 2019. Link