Solon Barocas

According to our database, Solon Barocas authored at least 57 papers between 2010 and 2025.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2025

Bridging Prediction and Intervention Problems in Social Systems.

Lydia T. Liu, Inioluwa Deborah Raji, Angela Zhou, Luke Guerdan, Jessica Hullman, Daniel Malinsky, Bryan Wilder, Simone Zhang, Hammaad Adam, Amanda Coston, Benjamin Laufer, Ezinne Nwankwo, Michael Zanger-Tishler, Eli Ben-Michael, Solon Barocas, Avi Feller, Marissa Gerchick, Talia Gillis, Shion Guha, Daniel E. Ho, Lily Hu, Kosuke Imai, Sayash Kapoor, Joshua Loftus, Razieh Nabi, Arvind Narayanan, Ben Recht, Juan Carlos Perdomo, Matthew J. Salganik, Mark P. Sendak, Alexander Tolbert, Berk Ustun, Suresh Venkatasubramanian, Angelina Wang, Ashia Wilson

CoRR, July, 2025

Distinguishing Predictive and Generative AI in Regulation.

Jennifer Wang, Andrew D. Selbst, Solon Barocas, Suresh Venkatasubramanian

CoRR, June, 2025

Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor.

Alexandra Olteanu, Su Lin Blodgett, Agathe Balayn, Angelina Wang, Fernando Diaz, Flávio du Pin Calmon, Margaret Mitchell, Michael D. Ekstrand, Reuben Binns, Solon Barocas

CoRR, June, 2025

Validating LLM-as-a-Judge Systems in the Absence of Gold Labels.

Luke Guerdan, Solon Barocas, Kenneth Holstein, Hanna M. Wallach, Zhiwei Steven Wu, Alexandra Chouldechova

CoRR, March, 2025

AI Automatons: AI Systems Intended to Imitate Humans.

Alexandra Olteanu, Solon Barocas, Su Lin Blodgett, Lisa Egede, Alicia DeVrio, Myra Cheng

CoRR, March, 2025

Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge.

Hanna M. Wallach, Meera A. Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alexandra Chouldechova, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nicholas Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs

CoRR, February, 2025

Supporting Industry Computing Researchers in Assessing, Articulating, and Addressing the Potential Negative Societal Impact of Their Work.

Wesley Hanwen Deng, Solon Barocas, Jennifer Wortman Vaughan

Proc. ACM Hum. Comput. Interact., 2025

Designing Algorithmic Delegates: the Role of Indistinguishability in Human-AI Handoff.

Sophie Greenwood, Karen Levy, Solon Barocas, Hoda Heidari, Jon M. Kleinberg

Proceedings of the 26th ACM Conference on Economics and Computation, 2025

Measuring Machine Learning Harms from Stereotypes Requires Understanding Who Is Harmed by Which Errors in What Ways.

Angelina Wang, Xuechunzi Bai, Solon Barocas, Su Lin Blodgett

Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025

Disclosure without Engagement: An Empirical Review of Positionality Statements at FAccT.

Hope Schroeder, Akshansh Pareek, Solon Barocas

Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025

What Constitutes a Less Discriminatory Algorithm?

Benjamin Laufer, Manish Raghavan, Solon Barocas

Proceedings of the 2025 Symposium on Computer Science and Law, 2025

Understanding the LLM-ification of CHI: Unpacking the Impact of LLMs at CHI through a Systematic Literature Review.

Rock Yuren Pang, Hope Schroeder, Kynnedy Simone Smith, Solon Barocas, Ziang Xiao, Emily Tseng, Danielle Bragg

Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, 2025

2024

Fundamental Limits in the Search for Less Discriminatory Algorithms - and How to Avoid Them.

Benjamin Laufer, Manisch Raghavan, Solon Barocas

CoRR, 2024

Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice.

A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, Nicole Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando A. Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, Amy Cyphert, Mark A. Lemley, danah boyd, Jennifer Wortman Vaughan, Miles Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna M. Wallach, Nicolas Papernot, Katherine Lee

CoRR, 2024

A Shared Standard for Valid Measurement of Generative AI Systems' Capabilities, Risks, and Impacts.

Alexandra Chouldechova, Chad Atalla, Solon Barocas, A. Feder Cooper, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Nicholas Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Matthew Vogel, Hannah Washington, Hanna M. Wallach

CoRR, 2024

A Framework for Evaluating LLMs Under Task Indeterminacy.

Luke Guerdan, Hanna M. Wallach, Solon Barocas, Alexandra Chouldechova

CoRR, 2024

Dimensions of Generative AI Evaluation Design.

P. Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alexandra Chouldechova, Hanna M. Wallach

CoRR, 2024

Evaluating Generative AI Systems is a Social Science Measurement Challenge.

Hanna M. Wallach, Meera A. Desai, Nicholas Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alexandra Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs

CoRR, 2024

The Legal Duty to Search for Less Discriminatory Algorithms.

Emily Black, Logan Koepke, Pauline Kim, Solon Barocas, Mingwei Hsu

CoRR, 2024

Measuring machine learning harms from stereotypes: requires understanding who is being harmed by which errors in what ways.

Angelina Wang, Xuechunzi Bai, Solon Barocas, Su Lin Blodgett

CoRR, 2024

On the Actionability of Outcome Prediction.

Lydia T. Liu, Solon Barocas, Jon M. Kleinberg, Karen Levy

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification.

A. Feder Cooper, Katherine Lee, Madiha Zahrah Choksi, Solon Barocas, Christopher De Sa, James Grimmelmann, Jon M. Kleinberg, Siddhartha Sen, Baobao Zhang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Variance, Self-Consistency, and Arbitrariness in Fair Classification.

A. Feder Cooper, Solon Barocas, Christopher De Sa, Siddhartha Sen

CoRR, 2023

Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints.

Jamelle Watson-Daniels, Solon Barocas, Jake M. Hofman, Alexandra Chouldechova

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy.

Angelina Wang, Sayash Kapoor, Solon Barocas, Arvind Narayanan

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Informational Diversity and Affinity Bias in Team Growth Dynamics.

Hoda Heidari, Solon Barocas, Jon M. Kleinberg, Karen Levy

Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

Taxonomizing and Measuring Representational Harms: A Look at Image Tagging.

Jared Katzman, Angelina Wang, Morgan Klaus Scheuerman, Su Lin Blodgett, Kristen Laird, Hanna M. Wallach, Solon Barocas

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

On modeling human perceptions of allocation policies with uncertain outcomes.

Hoda Heidari, Solon Barocas, Jon M. Kleinberg, Karen Levy

SIGecom Exch., July, 2022

An Uncommon Task: Participatory Design in Legal AI.

Fernando A. Delgado, Solon Barocas, Karen Levy

Proc. ACM Hum. Comput. Interact., 2022

Measuring Representational Harms in Image Captioning.

Angelina Wang, Solon Barocas, Kristen Laird, Hanna M. Wallach

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research.

Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna M. Wallach, Jennifer Wortman Vaughan

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Model Multiplicity: Opportunities, Concerns, and Solutions.

Emily Black, Manish Raghavan, Solon Barocas

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Disentangling the Components of Ethical Research in Machine Learning.

Carolyn Ashurst, Solon Barocas, Rosie Campbell, Deborah Raji

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Mimetic Models: Ethical Implications of AI that Acts Like You.

Reid McIlroy-Young, Jon M. Kleinberg, Siddhartha Sen, Solon Barocas, Ashton Anderson

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021

Responsible computing during COVID-19 and beyond.

Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miroslav Dudík, Benjamin Fish, Mary L. Gray, Brent J. Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach, Marion Zepf

Commun. ACM, 2021

Better Together?: How Externalities of Size Complicate Notions of Solidarity and Actuarial Fairness.

Kate Donahue, Solon Barocas

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Algorithmic Auditing and Social Justice: Lessons from the History of Audit Studies.

Briana Vecchione, Karen Levy, Solon Barocas

Proceedings of the EAAMO 2021: ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, Virtual Event, USA, October 5, 2021

Computer Vision and Conflicting Values: Describing People with Automated Alt Text.

Margot J. Hanley, Solon Barocas, Karen Levy, Shiri Azenkot, Helen Nissenbaum

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs.

Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

Mitigating bias in algorithmic hiring: evaluating claims and practices.

Manish Raghavan, Solon Barocas, Jon M. Kleinberg, Karen Levy

Proceedings of the FAT* '20: Conference on Fairness, 2020

The meaning and measurement of bias: lessons from natural language processing.

Abigail Z. Jacobs, Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach

Proceedings of the FAT* '20: Conference on Fairness, 2020

The hidden assumptions behind counterfactual explanations and principal reasons.

Solon Barocas, Andrew D. Selbst, Manish Raghavan

Proceedings of the FAT* '20: Conference on Fairness, 2020

When not to design, build, or deploy.

Solon Barocas, Asia J. Biega, Benjamin Fish, Jedrzej Niklas, Luke Stark

Proceedings of the FAT* '20: Conference on Fairness, 2020

Roles for computing in social change.

Rediet Abebe, Solon Barocas, Jon M. Kleinberg, Karen Levy, Manish Raghavan, David G. Robinson

Proceedings of the FAT* '20: Conference on Fairness, 2020

Language (Technology) is Power: A Critical Survey of "Bias" in NLP.

Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Mitigating Bias in Algorithmic Employment Screening: Evaluating Claims and Practices.

Manish Raghavan, Solon Barocas, Jon M. Kleinberg, Karen Levy

CoRR, 2019

Problem Formulation and Fairness.

Samir Passi, Solon Barocas

Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

2018

Debiasing Desire: Addressing Bias & Discrimination on Intimate Platforms.

Jevan A. Hutson, Jessie G. Taft, Solon Barocas, Karen Levy

Proc. ACM Hum. Comput. Interact., 2018

2017

Ten simple rules for responsible big data research.

Matthew Zook, Solon Barocas, danah boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara König, Jacob Metcalf, Arvind Narayanan, Alondra Nelson, Frank Pasquale

PLoS Comput. Biol., 2017

Big Data, Data Science, and Civil Rights.

Solon Barocas, Elizabeth Bradley, Vasant G. Honavar, Foster J. Provost

CoRR, 2017

Engaging the ethics of data science in practice.

Solon Barocas, danah boyd

Commun. ACM, 2017

Social and Technical Trade-Offs in Data Science.

Solon Barocas, danah boyd, Sorelle A. Friedler, Hanna M. Wallach

Big Data, 2017

2016

WSDM 2016 Workshop on the Ethics of Online Experimentation.

Fernando Diaz, Solon Barocas

Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

2014

Big data's end run around procedural privacy protections.

Solon Barocas, Helen Nissenbaum

Commun. ACM, 2014

2012

A Critical Look at Decentralized Personal Data Architectures

Arvind Narayanan, Vincent Toubiana, Solon Barocas, Helen Nissenbaum, Dan Boneh

CoRR, 2012

The price of precision: voter microtargeting and its potential harms to the democratic process.

Solon Barocas

Proceedings of the first edition workshop on Politics, elections and data, 2012

2010

Adnostic: Privacy Preserving Targeted Advertising.

Vincent Toubiana, Arvind Narayanan, Dan Boneh, Helen Nissenbaum, Solon Barocas

Proceedings of the Network and Distributed System Security Symposium, 2010