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Mona Sloane
Sloane Lab

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Mona Sloane
Sloane Lab

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Sloane Lab


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 Technology
Editor for Public Books.

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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 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
responsible 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, Frankfurter Allgemeine
Zeitung, OneZero Medium, and other outlets. She tweets at @mona_sloane.

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CONTACT

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

Short CV

Google Scholar




UPCOMING EVENTS

Responsible AI Workshop, October 17, 2023, Northeastern University, Boston,
Massachusetts, USA

Innovating AI Accountability: Bridging Social Science and Technical Approaches,
October 19, University of Maryland, College Park, Maryland, 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


RECENT EVENTS

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, 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

Co-Opting AI: Origins, May, 23, 2023, NYU Institute for Public Knowledge, New
York City, USA

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 


KEY PUBLICATIONS

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

Center for Advancing Safety of Machine Intelligence (2023): ‘Measuring Safety in
Artificial Intelligence: ‘Positionality Matters’. In: CASMI, August 2023. Link

Milieux Institute for Arts, Culture, and Technology (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

Copyright © 2023 Mona Sloane

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