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. She also serves as the co-chair of the National Academies of Sciences, Engineering, and Medicine (NASEM) project Human and Organizational Factors in AI Risk Management. Her book “Co-Opting AI: Society” is under contract with the University of California Press.

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Email: mona [dot] sloane [at] virginia [dot] edu

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📣 The paper 'The Cadaver in the Machine' about normative assumptions in motion capture technology has received Best Paper Honorable Mention at ACM CHI 2024! You can read the paper here.

👓 Check out the newest article in the Public Book Technology section, curated by Mona: ‘The “Diet Soda” of Data’ by Kim Gallon. Link

Upcoming Events

Co-Opting AI: Anatomy, November 7, 2024, UVA Karsh Institute of Democracy and NYU Institute for Public Knowledge, RSVP

Toward Public Interest Technology, November 8, 2024, Public Interest Technology University Network, University of Virginia, Charlottesville, Virginia, USA, RSVP

Co-Opting AI: Cars, December 4, 2024, UVA Karsh Institute of Democracy and NYU Institute for Public Knowledge, RSVP

Recent Events

Co-Opting AI: Architecture, October 28, 2024, UVA Karsh Institute of Democracy and NYU Institute for Public Knowledge, Video

Operationalizing Ethics into Online Safety and AI Research Workshop, White House Office of Science and Technology Policy, October 22, 2024, Washington D.C., USA

The Last Human Job Book Tour, October 16, 2024, NYU Institute for Public Knowledge, New York, USA

Co-Opting AI: Math, September 17, 2024, UVA Karsh Institute of Democracy and NYU Institute for Public Knowledge, Video

AI in Education Workshop, National Association for the Advancement of Colored People (NAACP) and Schott Foundation, August 22, 2024, Virtual

Data for Policy Conference, Paper Presentation ‘A systematic review of regulatory strategies and transparency mandates in AI regulation in Europe, the US, and Canada’, July 9-11, 2024, London, UK

Workshop on Human and Organizational Factors in AI Risk Management: Designing Paths Forward in AI Risk Management, Co-Chair, The National Academies of Sciences, Engineering, and Medicine, July 2, 2024, Washington D.C., USA

HCI International Conference 2024, Invited Tutorial Talk ‘AI’s Epistemology’, July 1, 2024, Washington D.C., USA

Workshop on Human and Organizational Factors in AI Risk Management: Safety in Context: Culture, Processes, and Frameworks, Co-Chair, The National Academies of Sciences, Engineering, and Medicine, June 26, 2024, Video

Workshop on Human and Organizational Factors in AI Risk Management: Evaluation, Testing, and Oversight, Co-Chair, The National Academies of Sciences, Engineering, and Medicine, June 20, 2024, Video

Workshop on Human and Organizational Factors in AI Risk Management: Broadening Stakeholder Participation, Co-Chair, The National Academies of Sciences, Engineering, and Medicine, June 11, 2024, Video

The Past, Present, and Future of Technology Policy, The John W. Kluge Center at the Library of Congress, Washington D.C., USA, June 6, 2024, Closed Door

AI and Recruiting, Federal Trade Commission, Washington D.C., USA, June 5, 2024, Closed Door

Co-Opting AI: Crime, April 18, 2024, UVA Karsh Institute of Democracy and NYU Institute for Public Knowledge, Video

Science Diplomacy Summit 2024, April 15-16, 2024, Johns Hopkins Bloomberg Center, Washington, D.C., USA

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

Harvey, E., Sandhaus, H., Jacbos, A.Z., Moss, E., Sloane, M. (2024): ‘The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology’. 2024 ACM CHI Conference on Human Factors in Computing Systems, May 2024. *Honorable Mention Best Paper Award* Link Video

Koenecke, A., Choi, A. S. G., Mei, K. X., Schellmann, H., Sloane, M. (2024): ’Careless Whisper: Speech-to-Text Hallucination Harms’. 2024 ACM Conference on Fairness, Accountability, and Transparency, June 2024. Link Video

Sloane, M., Moss, E., Danks, D. (2024): ‘Tackling “AI Hyping” in AI’, In: AI and Ethics, Volume 4, Issue 2, April 2024. Link

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

Edwards, B. (2024): ‘OpenAI’s Transcription Tool Hallucinates. Hospitals Are Using It Anyway’, In: Wired, October 2024. Link

Edwards, B. (2024): ‘Hospitals adopt error-prone AI transcription tools despite warnings’, In: Ars Technica, October 2024. Link

Burke, E. and Schellmann, H. (2024): ‘Researchers say an AI-powered transcription tool used in hospitals invents things no one ever said’, In: The Associated Press, October 2024. Link

Allen, C. (2024): ‘UVA Research Group Examining AI and Job Recruitment Expands’, In: UVA Data Science, August 2024. Link

Tech Ethics Lab (2024): ‘Research Project Outcomes: Mitigating Bias in Motion Capture Technology’, In: Tech Ethics Lab, July 2024. Link

Bang, K. (2024): ‘Is AI in Media Inevitable?’, In: Morning Wave in Busan, July 2024. Link

DailyAI (2024): ‘AI transcription tools generate harmful hallucinations’, In: DailyAI, May 2024. Link

Nyce, C. M. (2024): ‘You Don’t Have to Type Anymore’, In: The Atlantic, April 2024. Link

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