Jenn Wortman Vaughan

Senior Principal Research Manager

出版物

表示方法:

- 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
  
  ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2025) | November 2025
  
  Honorable Mention
  
  Preprint
- Position: To Make Text-to-Image Models that Work for Marginalized Communities, We Need New Measurement Practices for the Long Tail
  
  Nari Johnson, Hamna ., Deepthi Sudharsan, Theo Holroyd, Samantha Dalal, Siobhan Mackenzie Hall, Jennifer Wortman Vaughan, Daniela Massiceti, Cecily Morrison
  
  July 2025
  
  Preprint プロジェクト
- Examining the Expanding Role of Synthetic Data Throughout the AI Development Pipeline
  
  Shivani Kapania, Stephanie Ballard, Alex Kessler, Jennifer Wortman Vaughan
  
  8th ACM Conference on Fairness, Accountability, and Transparency (FAccT 2025) | June 2025
  
  Preprint
- Canvil: Designerly Adaptation for LLM-Powered User Experiences
  
  K. Feng, Q. Vera Liao, Ziang Xiao, Jennifer Wortman Vaughan, Amy Zhang, David W. McDonald
  
  CHI 2025 | April 2025
  
  DOI
- Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies
  
  Sunnie S. Y. Kim, Jennifer Wortman Vaughan, Q. Vera Liao, Tania Lombrozo, Olga Russakovsky
  
  CHI 2025 | April 2025
  
  Honorable Mention, CHI 2025
  
  Publication
- Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions
  
  Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan
  
  ToCHI | April 2025, 巻32(1)
  
  Publication
- Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alex Chouldechova, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  ICML 2025 | January 2025
  
  Publication
- Machine Unlearning Doesn’t Do What You Think: Lessons for Generative AI Policy, Research, and Practice
  
  A. F. Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alex Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, N. Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, A. Cyphert, Mark A. Lemley, danah boyd, Jennifer Wortman Vaughan, M. Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna Wallach, Nicolas Papernot, Katherine Lee
  
  NeurIPS 2025 | December 2024
  
  DOI Publication Publication
- Challenges in Human-Agent Communication
  
  Gagan Bansal, Jennifer Wortman Vaughan, Saleema Amershi, Eric Horvitz, Adam Fourney, Hussein Mozannar, Victor Dibia, Daniel S. Weld
  
  MSR-TR-2024-53 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクト
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクトプロジェクト
- Dimensions of Generative AI Evaluation Design
  
  Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
  
  November 2024
  
  Publication
- Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, Nick Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alex Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  November 2024
  
  Publication
- (De)Noise: Moderating the Inconsistency Between Human Decision-Makers
  
  Nina Grgić-Hlača, Junaid Ali, Krishna P. Gummadi, Jennifer Wortman Vaughan
  
  ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2024) | November 2024
  
  Publication
- “I’m Not Sure, But…”: Examining the Impact of Large Language Models’ Uncertainty Expression on User Reliance and Trust
  
  Sunnie S. Y. Kim, Q. Vera Liao, Mihaela Vorvoreanu, Stephanie Ballard, Jennifer Wortman Vaughan
  
  7th ACM Conference on Fairness, Accountability, and Transparency (FAccT 2024) | June 2024
  
  Publication プロジェクト
- The CLeAR Documentation Framework for AI Transparency: Recommendations for Practitioners & Context for Policymakers
  
  Kasia Chmielinski, Sarah Newman, Chris N. Kranzinger, Michael Hind, Jennifer Wortman Vaughan, Margaret Mitchell, Julia Stoyanovich, Angelina McMillan-Major, Emily McReynolds, Kathleen Esfahany, Mary L. Gray, Audrey Chang, Maui Hudson
  
  April 2024
  
  Publication プロジェクト
- Tinker, Tailor, Configure, Customize: The Articulation Work of Customizing AI Fairness Checklists
  
  Michael Madaio, Jingya Chen, Hanna Wallach, Jennifer Wortman Vaughan
  
  Computer-Supported Cooperative Work | April 2024
  
  Publication プロジェクト
- AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap
  
  Q. Vera Liao, Jennifer Wortman Vaughan
  
  Harvard Data Science Review | February 2024
  
  Publication プロジェクト
- Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations
  
  Valerie Chen, Q. Vera Liao, Jennifer Wortman Vaughan, Gagan Bansal
  
  Proc. ACM Hum.-Comput. Interact. | October 2023, 巻7
  
  Article 370
  
  PDF プロジェクト
- Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience
  
  Q. Vera Liao, Hariharan Subramonyam, Jennifer Wang, Jennifer Wortman Vaughan
  
  2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | April 2023
  
  PDF プロジェクト
- GAM Coach: Towards Interactive and User-Centered Algorithmic Recourse
  
  Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau
  
  2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | February 2023
  
  PDF プロジェクト
- Understanding Machine Learning Practitioners’ Data Documentation Perceptions, Needs, Challenges, and Desiderata
  
  Amy K. Heger, Liz B. Marquis, Mihaela Vorvoreanu, Hanna Wallach, Jennifer Wortman Vaughan
  
  2022 Conference on Computer Supported Cooperative Work | November 2022
  
  Publication プロジェクトプロジェクト
- Generation Probabilities are Not Enough: Improving Error Highlighting for AI Code Suggestions
  
  Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan
  
  NeurIPS Workshop on Human-Centered AI | October 2022
  
  Publication
- Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
  
  Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
  
  KDD 2022 | July 2022
  
  Publication プロジェクト
- REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research
  
  Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna Wallach, Jennifer Wortman Vaughan
  
  FAccT 2022 | May 2022
  
  DOI プロジェクト
- Assessing the Fairness of AI Systems: AI Practitioners’ Processes, Challenges, and Needs for Support
  
  Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna Wallach
  
  25th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2022) | February 2022
  
  Publication
- A Human-Centered Agenda for Intelligible Machine Learning
  
  Jennifer Wortman Vaughan, Hanna Wallach
  
  In Machines We Trust: Perspectives on Dependable AI | MIT Press による投稿 | 2021
  
  Author's Version プロジェクト
- GAM Changer: Editing Generalized Additive Models with Interactive Visualization
  
  Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
  
  2021 Neural Information Processing Systems | December 2021
  
  Publication Github
- Datasheets for Datasets
  
  Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford
  
  Communications of the ACM | December 2021, 巻64(12): pp. 86-92
  
  Publication プロジェクトプロジェクト
- Summarize with Caution: Comparing Global Feature Attributions
  
  Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna Wallach, Jennifer Wortman Vaughan
  
  Bulletin of the IEEE Computer Society Technical Committee on Data Engineering | December 2021
  
  Publication プロジェクト
- From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
  
  David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
  
  HCOMP 2021 | September 2021
  
  Publication プロジェクト
- Responsible computing during COVID-19 and beyond
  
  Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miro Dudík, Benjamin Fish, Mary L. Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, Marion Zepf
  
  Communications of the ACM | July 2021, 巻67(7): pp. 30-32
  
  https://doi.org/10.1145/3466612
  
  Publication
- Manipulating and Measuring Model Interpretability
  
  Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake Hofman, Jennifer Wortman Vaughan, Hanna Wallach
  
  CHI 2021 | May 2021
  
  Publication プロジェクト
- Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs
  
  Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, Duncan Wadsworth, Hanna Wallach
  
  AIES 2021 | May 2021
  
  Publication
- No-Regret and Incentive-Compatible Online Learning
  
  Rupert Freeman, David M. Pennock, Chara Podimata, Jennifer Wortman Vaughan
  
  ICML 2020 | July 2020
  
  Publication PDF
- A Human in the Loop is Not Enough: The Need for Human-Subject Experiments in Facial Recognition
  
  Forough Poursabzi-Sangdeh, Samira Samadi, Jennifer Wortman Vaughan, Hanna Wallach
  
  April 2020
  
  PDF
- Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning
  
  Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna Wallach, Jennifer Wortman Vaughan
  
  CHI 2020 | April 2020
  
  CHI 2020 Honorable Mention Award
  
  Publication Github プロジェクト
- Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI
  
  Michael Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach
  
  CHI Conference on Human Factors in Computing Systems | March 2020
  
  CHI 2020 Best Paper Award
  
  PDF プロジェクト
- Weight of Evidence as a Basis for Human-Oriented Explanations
  
  David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
  
  Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
  
  Publication
- Toward Fairness in AI for People with Disabilities: A Research Roadmap
  
  Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna Wallach, Meredith Ringel Morris
  
  ASSETS 2019 Workshop on AI Fairness for People with Disabilities | October 2019
  
  Publication 動画プロジェクト
- Improving fairness in machine learning systems: What do industry practitioners need?
  
  Ken Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miro Dudík, Hanna Wallach
  
  2019 ACM CHI Conference on Human Factors in Computing Systems | June 2019
  
  Publication
- Truthful Aggregation of Budget Proposals
  
  Rupert Freeman, David Pennock, Dominik Peters, Jennifer Wortman Vaughan
  
  Twentieth ACM Conference on Economics and Computation | June 2019
  
  Publication
- Using Search Queries to Understand Health Information Needs in Africa
  
  Rediet Abebe, Shawndra Hill, Jennifer Wortman Vaughan, Peter M. Small, H. Andrew Schwartz
  
  Proceedings of the International AAAI Conference on Web and Social Media | June 2019
  
  Publication
- Understanding the Effect of Accuracy on Trust in Machine Learning Models
  
  Ming Yin, Jennifer Wortman Vaughan, Hanna Wallach
  
  CHI 2019 | May 2019
  
  Honorable Mention Award at CHI 2019
  
  PDF
- Understanding the Effect of Accuracy on Trust in Machine Learning Models
  
  Ming Ying, Jennifer Wortman Vaughan, Hanna Wallach
  
  2019 ACM CHI Conference on Human Factors in Computing Systems | May 2019
  
  Honorable Mention Award at CHI 2019
  
  Publication プロジェクト
- The Disparate Effects of Strategic Manipulation
  
  Lily Hu, Nicole Immorlica, Jennifer Wortman Vaughan
  
  2nd ACM Conference on Fairness, Accountability, and Transparency | January 2019
  
  Publication
- An Equivalence Between Wagering and Fair-Division Mechanisms
  
  Rupert Freeman, David Pennock, Jennifer Wortman Vaughan
  
  AAAI 2019 | January 2019
  
  Publication
- Group Fairness for Indivisible Goods Allocation
  
  Vincent Conitzer, Rupert Freeman, Nisarg Shah, Jennifer Wortman Vaughan
  
  AAAI 2019 | January 2019
  
  PDF
- Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets
  
  Hoda Heidari, Sebastien Lahaie, David Pennock, Jennifer Wortman Vaughan
  
  ACM Transactions on Economics and Computation (TEAC) - Special Issue on EC'15 | November 2018, 巻6(3–4)
  
  Publication
- Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research
  
  Jennifer Wortman Vaughan
  
  JMLR | September 2018, 巻18(193): pp. 1-46
  
  Publication
- Incentive-Compatible Forecasting Competitions
  
  Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David Pennock, Andreas Krause
  
  Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018) | April 2018
  
  Publication
- The Externalities of Exploration and How Data Diversity Helps Exploitation
  
  Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
  
  31st Annual Conference on Learning Theory | February 2018
  
  Publication
- Oracle-Efficient Learning and Auction Design
  
  Miro Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
  
  Proceedings of the 58th Annual Symposium on Foundations of Computer Science (FOCS), 2017. | October 2017
  
  Publication Publication
- The Double Clinching Auction for Wagering
  
  Rupert Freeman, David Pennock, Jennifer Wortman Vaughan
  
  EC'17, Cambridge, Massachusetts, USA | June 2017
  
  Publication Publication Publication
- A Decomposition of Forecast Error in Prediction Markets
  
  Miro Dudík, Sébastien Lahaie, Ryan Rogers, Jennifer Wortman Vaughan
  
  31st Conference on Neural Information Processing Systems (NIPS 2017) | February 2017
  
  公開日
- Mathematical Foundations for Social Computing
  
  Yiling Chen, Arpita Ghosh, Michael Kearns, Tim Roughgarden, Jennifer Wortman Vaughan
  
  Communications of the ACM | December 2016, 巻59(12): pp. 102-108
  
  Publication PDF
- The Communication Network Within the Crowd
  
  Ming Yin, Mary L. Gray, Siddharth Suri, Jennifer Wortman Vaughan
  
  25th International World Wide Web Conference (WWW) 2016 | April 2016
  
  Publication PDF
- The Possibilities and Limitations of Private Prediction Markets
  
  Rachel Cummings, David Pennock, Jennifer Wortman Vaughan
  
  17th ACM Conference on Economics and Computation (EC 2016) | April 2016
  
  Publication
- Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
  
  Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  Journal of Artificial Intelligence Research | February 2016, 巻55
  
  Publication
- Bounded Rationality in Wagering Mechanisms
  
  David Pennock, Vasilis Syrgkanis, Jennifer Wortman Vaughan
  
  32nd Conference on Uncertainty in Artificial Intelligence | January 2016
  
  Publication
- Belief Aggregation with Automated Market Makers
  
  Rajiv Sethi, Jennifer Wortman Vaughan
  
  Computational Economics | June 2015
  
  Publication
- Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets
  
  Hoda Heidari, Sébastien Lahaie, David Pennock, Jennifer Wortman Vaughan
  
  June 2015
  
  公開日公開日プロジェクト
- Incentivizing High Quality Crowdwork
  
  Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan
  
  Twenty-Fourth International World Wide Web Conference | May 2015
  
  Publication
- Market Making with Decreasing Utility for Information
  
  Miroslav Dudík, Rafael Frongillo, Jennifer Wortman Vaughan
  
  30th Conference on Uncertainty in Artificial Intelligence | July 2014
  
  Publication プロジェクト
- Removing Arbitrage from Wagering Mechanisms
  
  Yiling Chen, Nikhil Devanur, David Pennock, Jennifer Wortman Vaughan
  
  Fifteenth ACM Conference on Economics and Computation | June 2014
  
  Publication プロジェクト
- An Axiomatic Characterization of Wagering Mechanisms
  
  Jennifer Wortman Vaughan, Yiling Chen, Daniel Reeves, David Pennock, Nicolas S. Lambert, John Langford, Yoav Shoham
  
  Journal of Economic Theory | March 2014, 巻156: pp. 389-416
  
  Publication プロジェクト
- A General Volume-Parameterized Market Making Framework
  
  Jacob Abernethy, Rafael Frongillo, Xiaolong Li, Jennifer Wortman Vaughan
  
  ACM Conference on Electronic Commerce | January 2014
  
  Publication プロジェクト
- Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
  
  Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  15th ACM Conf. on Economics and Computation (EC) | January 2014
  
  Publication プロジェクト
- Online Decision Making in Crowdsourcing Markets: Theoretical Challenges
  
  Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  ACM SIGecom Exchanges | December 2013, 巻12(2): pp. 4-23
  
  Position paper and survey.
  
  Publication プロジェクト
- Computational social science and social computing
  
  Winter Mason, Jennifer Wortman Vaughan, Hanna Wallach
  
  Mach Learn | November 2013, 巻95: pp. 257-260
  
  Publication DOI
- Adaptive Task Assignment for Crowdsourced Classification
  
  Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan
  
  30th International Conference on Machine Learning (ICML) | May 2013
  
  Publication
- An Axiomatic Characterization of Adaptive-Liquidity Market Makers
  
  Xiaolong Li, Jennifer Wortman Vaughan
  
  Fourteenth ACM Conference on Electronic Commerce (EC) | May 2013
  
  Publication プロジェクト
- Efficient Market Making via Convex Optimization, and a Connection to Online Learning
  
  Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
  
  ACM Transactions on Economics and Computation | May 2013, 巻1
  
  Publication プロジェクト
- Cost Function Market Makers for Measurable Spaces
  
  Yiling Chen, Michael Ruberry, Jennifer Wortman Vaughan
  
  Fourteenth ACM Conference on Electronic Commerce (EC) | January 2013
  
  Publication プロジェクト
- Designing Informative Securities
  
  Yiling Chen, Mike Ruberry, Jennifer Wortman Vaughan
  
  28th Conference on Uncertainty in Artificial Intelligence (UAI) | January 2012
  
  Publication プロジェクト
- Online Task Assignment in Crowdsourcing Markets
  
  Chien-Ju Ho, Jennifer Wortman Vaughan
  
  Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI) | January 2012
  
  Publication
- An Optimization-Based Framework for Automated Market-Making
  
  Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
  
  Twelfth ACM Conference on Electronic Commerce (EC) | January 2011
  
  Publication プロジェクト

- 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
  
  ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2025) | November 2025
  
  Honorable Mention
  
  Preprint
- Position: To Make Text-to-Image Models that Work for Marginalized Communities, We Need New Measurement Practices for the Long Tail
  
  Nari Johnson, Hamna ., Deepthi Sudharsan, Theo Holroyd, Samantha Dalal, Siobhan Mackenzie Hall, Jennifer Wortman Vaughan, Daniela Massiceti, Cecily Morrison
  
  July 2025
  
  Preprint プロジェクト
- Examining the Expanding Role of Synthetic Data Throughout the AI Development Pipeline
  
  Shivani Kapania, Stephanie Ballard, Alex Kessler, Jennifer Wortman Vaughan
  
  8th ACM Conference on Fairness, Accountability, and Transparency (FAccT 2025) | June 2025
  
  Preprint
- Canvil: Designerly Adaptation for LLM-Powered User Experiences
  
  K. Feng, Q. Vera Liao, Ziang Xiao, Jennifer Wortman Vaughan, Amy Zhang, David W. McDonald
  
  CHI 2025 | April 2025
  
  DOI
- Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies
  
  Sunnie S. Y. Kim, Jennifer Wortman Vaughan, Q. Vera Liao, Tania Lombrozo, Olga Russakovsky
  
  CHI 2025 | April 2025
  
  Honorable Mention, CHI 2025
  
  Publication
- Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions
  
  Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan
  
  ToCHI | April 2025, 巻32(1)
  
  Publication
- Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alex Chouldechova, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  ICML 2025 | January 2025
  
  Publication
- Machine Unlearning Doesn’t Do What You Think: Lessons for Generative AI Policy, Research, and Practice
  
  A. F. Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alex Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, N. Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, A. Cyphert, Mark A. Lemley, danah boyd, Jennifer Wortman Vaughan, M. Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna Wallach, Nicolas Papernot, Katherine Lee
  
  NeurIPS 2025 | December 2024
  
  DOI Publication Publication
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクトプロジェクト
- Challenges in Human-Agent Communication
  
  Gagan Bansal, Jennifer Wortman Vaughan, Saleema Amershi, Eric Horvitz, Adam Fourney, Hussein Mozannar, Victor Dibia, Daniel S. Weld
  
  MSR-TR-2024-53 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクト
- Dimensions of Generative AI Evaluation Design
  
  Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
  
  November 2024
  
  Publication
- Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, Nick Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alex Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  November 2024
  
  Publication
- (De)Noise: Moderating the Inconsistency Between Human Decision-Makers
  
  Nina Grgić-Hlača, Junaid Ali, Krishna P. Gummadi, Jennifer Wortman Vaughan
  
  ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2024) | November 2024
  
  Publication
- “I’m Not Sure, But…”: Examining the Impact of Large Language Models’ Uncertainty Expression on User Reliance and Trust
  
  Sunnie S. Y. Kim, Q. Vera Liao, Mihaela Vorvoreanu, Stephanie Ballard, Jennifer Wortman Vaughan
  
  7th ACM Conference on Fairness, Accountability, and Transparency (FAccT 2024) | June 2024
  
  Publication プロジェクト
- The CLeAR Documentation Framework for AI Transparency: Recommendations for Practitioners & Context for Policymakers
  
  Kasia Chmielinski, Sarah Newman, Chris N. Kranzinger, Michael Hind, Jennifer Wortman Vaughan, Margaret Mitchell, Julia Stoyanovich, Angelina McMillan-Major, Emily McReynolds, Kathleen Esfahany, Mary L. Gray, Audrey Chang, Maui Hudson
  
  April 2024
  
  Publication プロジェクト
- Tinker, Tailor, Configure, Customize: The Articulation Work of Customizing AI Fairness Checklists
  
  Michael Madaio, Jingya Chen, Hanna Wallach, Jennifer Wortman Vaughan
  
  Computer-Supported Cooperative Work | April 2024
  
  Publication プロジェクト
- AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap
  
  Q. Vera Liao, Jennifer Wortman Vaughan
  
  Harvard Data Science Review | February 2024
  
  Publication プロジェクト
- Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations
  
  Valerie Chen, Q. Vera Liao, Jennifer Wortman Vaughan, Gagan Bansal
  
  Proc. ACM Hum.-Comput. Interact. | October 2023, 巻7
  
  Article 370
  
  PDF プロジェクト
- Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience
  
  Q. Vera Liao, Hariharan Subramonyam, Jennifer Wang, Jennifer Wortman Vaughan
  
  2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | April 2023
  
  PDF プロジェクト
- GAM Coach: Towards Interactive and User-Centered Algorithmic Recourse
  
  Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau
  
  2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | February 2023
  
  PDF プロジェクト
- Understanding Machine Learning Practitioners’ Data Documentation Perceptions, Needs, Challenges, and Desiderata
  
  Amy K. Heger, Liz B. Marquis, Mihaela Vorvoreanu, Hanna Wallach, Jennifer Wortman Vaughan
  
  2022 Conference on Computer Supported Cooperative Work | November 2022
  
  Publication プロジェクトプロジェクト
- Generation Probabilities are Not Enough: Improving Error Highlighting for AI Code Suggestions
  
  Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan
  
  NeurIPS Workshop on Human-Centered AI | October 2022
  
  Publication
- Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
  
  Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
  
  KDD 2022 | July 2022
  
  Publication プロジェクト
- REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research
  
  Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna Wallach, Jennifer Wortman Vaughan
  
  FAccT 2022 | May 2022
  
  DOI プロジェクト
- Assessing the Fairness of AI Systems: AI Practitioners’ Processes, Challenges, and Needs for Support
  
  Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna Wallach
  
  25th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2022) | February 2022
  
  Publication
- A Human-Centered Agenda for Intelligible Machine Learning
  
  Jennifer Wortman Vaughan, Hanna Wallach
  
  In Machines We Trust: Perspectives on Dependable AI | MIT Press による投稿 | 2021
  
  Author's Version プロジェクト
- GAM Changer: Editing Generalized Additive Models with Interactive Visualization
  
  Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
  
  2021 Neural Information Processing Systems | December 2021
  
  Publication Github
- Summarize with Caution: Comparing Global Feature Attributions
  
  Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna Wallach, Jennifer Wortman Vaughan
  
  Bulletin of the IEEE Computer Society Technical Committee on Data Engineering | December 2021
  
  Publication プロジェクト
- Datasheets for Datasets
  
  Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford
  
  Communications of the ACM | December 2021, 巻64(12): pp. 86-92
  
  Publication プロジェクトプロジェクト
- From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
  
  David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
  
  HCOMP 2021 | September 2021
  
  Publication プロジェクト
- Responsible computing during COVID-19 and beyond
  
  Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miro Dudík, Benjamin Fish, Mary L. Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, Marion Zepf
  
  Communications of the ACM | July 2021, 巻67(7): pp. 30-32
  
  https://doi.org/10.1145/3466612
  
  Publication
- Manipulating and Measuring Model Interpretability
  
  Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake Hofman, Jennifer Wortman Vaughan, Hanna Wallach
  
  CHI 2021 | May 2021
  
  Publication プロジェクト
- Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs
  
  Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, Duncan Wadsworth, Hanna Wallach
  
  AIES 2021 | May 2021
  
  Publication
- No-Regret and Incentive-Compatible Online Learning
  
  Rupert Freeman, David M. Pennock, Chara Podimata, Jennifer Wortman Vaughan
  
  ICML 2020 | July 2020
  
  Publication PDF
- A Human in the Loop is Not Enough: The Need for Human-Subject Experiments in Facial Recognition
  
  Forough Poursabzi-Sangdeh, Samira Samadi, Jennifer Wortman Vaughan, Hanna Wallach
  
  April 2020
  
  PDF
- Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning
  
  Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna Wallach, Jennifer Wortman Vaughan
  
  CHI 2020 | April 2020
  
  CHI 2020 Honorable Mention Award
  
  Publication Github プロジェクト
- Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI
  
  Michael Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach
  
  CHI Conference on Human Factors in Computing Systems | March 2020
  
  CHI 2020 Best Paper Award
  
  PDF プロジェクト
- Weight of Evidence as a Basis for Human-Oriented Explanations
  
  David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
  
  Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
  
  Publication
- Toward Fairness in AI for People with Disabilities: A Research Roadmap
  
  Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna Wallach, Meredith Ringel Morris
  
  ASSETS 2019 Workshop on AI Fairness for People with Disabilities | October 2019
  
  Publication 動画プロジェクト
- Truthful Aggregation of Budget Proposals
  
  Rupert Freeman, David Pennock, Dominik Peters, Jennifer Wortman Vaughan
  
  Twentieth ACM Conference on Economics and Computation | June 2019
  
  Publication
- Improving fairness in machine learning systems: What do industry practitioners need?
  
  Ken Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miro Dudík, Hanna Wallach
  
  2019 ACM CHI Conference on Human Factors in Computing Systems | June 2019
  
  Publication
- Understanding the Effect of Accuracy on Trust in Machine Learning Models
  
  Ming Ying, Jennifer Wortman Vaughan, Hanna Wallach
  
  2019 ACM CHI Conference on Human Factors in Computing Systems | May 2019
  
  Honorable Mention Award at CHI 2019
  
  Publication プロジェクト
- The Disparate Effects of Strategic Manipulation
  
  Lily Hu, Nicole Immorlica, Jennifer Wortman Vaughan
  
  2nd ACM Conference on Fairness, Accountability, and Transparency | January 2019
  
  Publication
- Group Fairness for Indivisible Goods Allocation
  
  Vincent Conitzer, Rupert Freeman, Nisarg Shah, Jennifer Wortman Vaughan
  
  AAAI 2019 | January 2019
  
  PDF
- An Equivalence Between Wagering and Fair-Division Mechanisms
  
  Rupert Freeman, David Pennock, Jennifer Wortman Vaughan
  
  AAAI 2019 | January 2019
  
  Publication
- Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets
  
  Hoda Heidari, Sebastien Lahaie, David Pennock, Jennifer Wortman Vaughan
  
  ACM Transactions on Economics and Computation (TEAC) - Special Issue on EC'15 | November 2018, 巻6(3–4)
  
  Publication
- Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research
  
  Jennifer Wortman Vaughan
  
  JMLR | September 2018, 巻18(193): pp. 1-46
  
  Publication
- Incentive-Compatible Forecasting Competitions
  
  Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David Pennock, Andreas Krause
  
  Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018) | April 2018
  
  Publication
- The Externalities of Exploration and How Data Diversity Helps Exploitation
  
  Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
  
  31st Annual Conference on Learning Theory | February 2018
  
  Publication
- Oracle-Efficient Learning and Auction Design
  
  Miro Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
  
  Proceedings of the 58th Annual Symposium on Foundations of Computer Science (FOCS), 2017. | October 2017
  
  Publication Publication
- The Double Clinching Auction for Wagering
  
  Rupert Freeman, David Pennock, Jennifer Wortman Vaughan
  
  EC'17, Cambridge, Massachusetts, USA | June 2017
  
  Publication Publication Publication
- A Decomposition of Forecast Error in Prediction Markets
  
  Miro Dudík, Sébastien Lahaie, Ryan Rogers, Jennifer Wortman Vaughan
  
  31st Conference on Neural Information Processing Systems (NIPS 2017) | February 2017
  
  公開日
- Mathematical Foundations for Social Computing
  
  Yiling Chen, Arpita Ghosh, Michael Kearns, Tim Roughgarden, Jennifer Wortman Vaughan
  
  Communications of the ACM | December 2016, 巻59(12): pp. 102-108
  
  Publication PDF
- The Communication Network Within the Crowd
  
  Ming Yin, Mary L. Gray, Siddharth Suri, Jennifer Wortman Vaughan
  
  25th International World Wide Web Conference (WWW) 2016 | April 2016
  
  Publication PDF
- The Possibilities and Limitations of Private Prediction Markets
  
  Rachel Cummings, David Pennock, Jennifer Wortman Vaughan
  
  17th ACM Conference on Economics and Computation (EC 2016) | April 2016
  
  Publication
- Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
  
  Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  Journal of Artificial Intelligence Research | February 2016, 巻55
  
  Publication
- Belief Aggregation with Automated Market Makers
  
  Rajiv Sethi, Jennifer Wortman Vaughan
  
  Computational Economics | June 2015
  
  Publication
- Incentivizing High Quality Crowdwork
  
  Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan
  
  Twenty-Fourth International World Wide Web Conference | May 2015
  
  Publication
- Market Making with Decreasing Utility for Information
  
  Miroslav Dudík, Rafael Frongillo, Jennifer Wortman Vaughan
  
  30th Conference on Uncertainty in Artificial Intelligence | July 2014
  
  Publication プロジェクト
- Removing Arbitrage from Wagering Mechanisms
  
  Yiling Chen, Nikhil Devanur, David Pennock, Jennifer Wortman Vaughan
  
  Fifteenth ACM Conference on Economics and Computation | June 2014
  
  Publication プロジェクト
- An Axiomatic Characterization of Wagering Mechanisms
  
  Jennifer Wortman Vaughan, Yiling Chen, Daniel Reeves, David Pennock, Nicolas S. Lambert, John Langford, Yoav Shoham
  
  Journal of Economic Theory | March 2014, 巻156: pp. 389-416
  
  Publication プロジェクト
- A General Volume-Parameterized Market Making Framework
  
  Jacob Abernethy, Rafael Frongillo, Xiaolong Li, Jennifer Wortman Vaughan
  
  ACM Conference on Electronic Commerce | January 2014
  
  Publication プロジェクト
- Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
  
  Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  15th ACM Conf. on Economics and Computation (EC) | January 2014
  
  Publication プロジェクト
- Online Decision Making in Crowdsourcing Markets: Theoretical Challenges
  
  Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  ACM SIGecom Exchanges | December 2013, 巻12(2): pp. 4-23
  
  Position paper and survey.
  
  Publication プロジェクト
- Adaptive Task Assignment for Crowdsourced Classification
  
  Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan
  
  30th International Conference on Machine Learning (ICML) | May 2013
  
  Publication
- An Axiomatic Characterization of Adaptive-Liquidity Market Makers
  
  Xiaolong Li, Jennifer Wortman Vaughan
  
  Fourteenth ACM Conference on Electronic Commerce (EC) | May 2013
  
  Publication プロジェクト
- Efficient Market Making via Convex Optimization, and a Connection to Online Learning
  
  Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
  
  ACM Transactions on Economics and Computation | May 2013, 巻1
  
  Publication プロジェクト
- Cost Function Market Makers for Measurable Spaces
  
  Yiling Chen, Michael Ruberry, Jennifer Wortman Vaughan
  
  Fourteenth ACM Conference on Electronic Commerce (EC) | January 2013
  
  Publication プロジェクト
- Online Task Assignment in Crowdsourcing Markets
  
  Chien-Ju Ho, Jennifer Wortman Vaughan
  
  Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI) | January 2012
  
  Publication
- Designing Informative Securities
  
  Yiling Chen, Mike Ruberry, Jennifer Wortman Vaughan
  
  28th Conference on Uncertainty in Artificial Intelligence (UAI) | January 2012
  
  Publication プロジェクト
- An Optimization-Based Framework for Automated Market-Making
  
  Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
  
  Twelfth ACM Conference on Electronic Commerce (EC) | January 2011
  
  Publication プロジェクト
- Position: To Make Text-to-Image Models that Work for Marginalized Communities, We Need New Measurement Practices for the Long Tail
  
  Nari Johnson, Hamna ., Deepthi Sudharsan, Theo Holroyd, Samantha Dalal, Siobhan Mackenzie Hall, Jennifer Wortman Vaughan, Daniela Massiceti, Cecily Morrison
  
  July 2025
  
  Preprint プロジェクト
- 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
  
  ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2025) | November 2025
  
  Honorable Mention
  
  Preprint
- Position: To Make Text-to-Image Models that Work for Marginalized Communities, We Need New Measurement Practices for the Long Tail
  
  Nari Johnson, Hamna ., Deepthi Sudharsan, Theo Holroyd, Samantha Dalal, Siobhan Mackenzie Hall, Jennifer Wortman Vaughan, Daniela Massiceti, Cecily Morrison
  
  July 2025
  
  Preprint プロジェクト
- Canvil: Designerly Adaptation for LLM-Powered User Experiences
  
  K. Feng, Q. Vera Liao, Ziang Xiao, Jennifer Wortman Vaughan, Amy Zhang, David W. McDonald
  
  CHI 2025 | April 2025
  
  DOI
- Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies
  
  Sunnie S. Y. Kim, Jennifer Wortman Vaughan, Q. Vera Liao, Tania Lombrozo, Olga Russakovsky
  
  CHI 2025 | April 2025
  
  Honorable Mention, CHI 2025
  
  Publication
- Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions
  
  Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan
  
  ToCHI | April 2025, 巻32(1)
  
  Publication
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクトプロジェクト
- Challenges in Human-Agent Communication
  
  Gagan Bansal, Jennifer Wortman Vaughan, Saleema Amershi, Eric Horvitz, Adam Fourney, Hussein Mozannar, Victor Dibia, Daniel S. Weld
  
  MSR-TR-2024-53 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクト
- (De)Noise: Moderating the Inconsistency Between Human Decision-Makers
  
  Nina Grgić-Hlača, Junaid Ali, Krishna P. Gummadi, Jennifer Wortman Vaughan
  
  ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2024) | November 2024
  
  Publication
- AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap
  
  Q. Vera Liao, Jennifer Wortman Vaughan
  
  Harvard Data Science Review | February 2024
  
  Publication プロジェクト
- Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations
  
  Valerie Chen, Q. Vera Liao, Jennifer Wortman Vaughan, Gagan Bansal
  
  Proc. ACM Hum.-Comput. Interact. | October 2023, 巻7
  
  Article 370
  
  PDF プロジェクト
- Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience
  
  Q. Vera Liao, Hariharan Subramonyam, Jennifer Wang, Jennifer Wortman Vaughan
  
  2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | April 2023
  
  PDF プロジェクト
- GAM Coach: Towards Interactive and User-Centered Algorithmic Recourse
  
  Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau
  
  2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | February 2023
  
  PDF プロジェクト
- Understanding Machine Learning Practitioners’ Data Documentation Perceptions, Needs, Challenges, and Desiderata
  
  Amy K. Heger, Liz B. Marquis, Mihaela Vorvoreanu, Hanna Wallach, Jennifer Wortman Vaughan
  
  2022 Conference on Computer Supported Cooperative Work | November 2022
  
  Publication プロジェクトプロジェクト
- Generation Probabilities are Not Enough: Improving Error Highlighting for AI Code Suggestions
  
  Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan
  
  NeurIPS Workshop on Human-Centered AI | October 2022
  
  Publication
- GAM Changer: Editing Generalized Additive Models with Interactive Visualization
  
  Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
  
  2021 Neural Information Processing Systems | December 2021
  
  Publication Github
- Responsible computing during COVID-19 and beyond
  
  Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miro Dudík, Benjamin Fish, Mary L. Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, Marion Zepf
  
  Communications of the ACM | July 2021, 巻67(7): pp. 30-32
  
  https://doi.org/10.1145/3466612
  
  Publication
- Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning
  
  Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna Wallach, Jennifer Wortman Vaughan
  
  CHI 2020 | April 2020
  
  CHI 2020 Honorable Mention Award
  
  Publication Github プロジェクト
- Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI
  
  Michael Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach
  
  CHI Conference on Human Factors in Computing Systems | March 2020
  
  CHI 2020 Best Paper Award
  
  PDF プロジェクト
- Toward Fairness in AI for People with Disabilities: A Research Roadmap
  
  Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna Wallach, Meredith Ringel Morris
  
  ASSETS 2019 Workshop on AI Fairness for People with Disabilities | October 2019
  
  Publication 動画プロジェクト
- Improving fairness in machine learning systems: What do industry practitioners need?
  
  Ken Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miro Dudík, Hanna Wallach
  
  2019 ACM CHI Conference on Human Factors in Computing Systems | June 2019
  
  Publication
- Understanding the Effect of Accuracy on Trust in Machine Learning Models
  
  Ming Yin, Jennifer Wortman Vaughan, Hanna Wallach
  
  CHI 2019 | May 2019
  
  Honorable Mention Award at CHI 2019
  
  PDF
- Understanding the Effect of Accuracy on Trust in Machine Learning Models
  
  Ming Ying, Jennifer Wortman Vaughan, Hanna Wallach
  
  2019 ACM CHI Conference on Human Factors in Computing Systems | May 2019
  
  Honorable Mention Award at CHI 2019
  
  Publication プロジェクト
- Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research
  
  Jennifer Wortman Vaughan
  
  JMLR | September 2018, 巻18(193): pp. 1-46
  
  Publication
- Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alex Chouldechova, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  ICML 2025 | January 2025
  
  Publication
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクトプロジェクト
- Dimensions of Generative AI Evaluation Design
  
  Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
  
  November 2024
  
  Publication
- Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, Nick Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alex Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  November 2024
  
  Publication
- Responsible computing during COVID-19 and beyond
  
  Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miro Dudík, Benjamin Fish, Mary L. Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, Marion Zepf
  
  Communications of the ACM | July 2021, 巻67(7): pp. 30-32
  
  https://doi.org/10.1145/3466612
  
  Publication
- Manipulating and Measuring Model Interpretability
  
  Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake Hofman, Jennifer Wortman Vaughan, Hanna Wallach
  
  CHI 2021 | May 2021
  
  Publication プロジェクト
- Using Search Queries to Understand Health Information Needs in Africa
  
  Rediet Abebe, Shawndra Hill, Jennifer Wortman Vaughan, Peter M. Small, H. Andrew Schwartz
  
  Proceedings of the International AAAI Conference on Web and Social Media | June 2019
  
  Publication
- Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research
  
  Jennifer Wortman Vaughan
  
  JMLR | September 2018, 巻18(193): pp. 1-46
  
  Publication
- The Communication Network Within the Crowd
  
  Ming Yin, Mary L. Gray, Siddharth Suri, Jennifer Wortman Vaughan
  
  25th International World Wide Web Conference (WWW) 2016 | April 2016
  
  Publication PDF
- Computational social science and social computing
  
  Winter Mason, Jennifer Wortman Vaughan, Hanna Wallach
  
  Mach Learn | November 2013, 巻95: pp. 257-260
  
  Publication DOI
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクトプロジェクト
- The CLeAR Documentation Framework for AI Transparency: Recommendations for Practitioners & Context for Policymakers
  
  Kasia Chmielinski, Sarah Newman, Chris N. Kranzinger, Michael Hind, Jennifer Wortman Vaughan, Margaret Mitchell, Julia Stoyanovich, Angelina McMillan-Major, Emily McReynolds, Kathleen Esfahany, Mary L. Gray, Audrey Chang, Maui Hudson
  
  April 2024
  
  Publication プロジェクト
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクトプロジェクト
- Truthful Aggregation of Budget Proposals
  
  Rupert Freeman, David Pennock, Dominik Peters, Jennifer Wortman Vaughan
  
  Twentieth ACM Conference on Economics and Computation | June 2019
  
  Publication
- The Disparate Effects of Strategic Manipulation
  
  Lily Hu, Nicole Immorlica, Jennifer Wortman Vaughan
  
  2nd ACM Conference on Fairness, Accountability, and Transparency | January 2019
  
  Publication
- Group Fairness for Indivisible Goods Allocation
  
  Vincent Conitzer, Rupert Freeman, Nisarg Shah, Jennifer Wortman Vaughan
  
  AAAI 2019 | January 2019
  
  PDF
- An Equivalence Between Wagering and Fair-Division Mechanisms
  
  Rupert Freeman, David Pennock, Jennifer Wortman Vaughan
  
  AAAI 2019 | January 2019
  
  Publication
- Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets
  
  Hoda Heidari, Sebastien Lahaie, David Pennock, Jennifer Wortman Vaughan
  
  ACM Transactions on Economics and Computation (TEAC) - Special Issue on EC'15 | November 2018, 巻6(3–4)
  
  Publication
- Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research
  
  Jennifer Wortman Vaughan
  
  JMLR | September 2018, 巻18(193): pp. 1-46
  
  Publication
- Incentive-Compatible Forecasting Competitions
  
  Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David Pennock, Andreas Krause
  
  Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018) | April 2018
  
  Publication
- The Externalities of Exploration and How Data Diversity Helps Exploitation
  
  Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
  
  31st Annual Conference on Learning Theory | February 2018
  
  Publication
- Oracle-Efficient Learning and Auction Design
  
  Miro Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
  
  Proceedings of the 58th Annual Symposium on Foundations of Computer Science (FOCS), 2017. | October 2017
  
  Publication Publication
- A Decomposition of Forecast Error in Prediction Markets
  
  Miro Dudík, Sébastien Lahaie, Ryan Rogers, Jennifer Wortman Vaughan
  
  31st Conference on Neural Information Processing Systems (NIPS 2017) | February 2017
  
  公開日
- Mathematical Foundations for Social Computing
  
  Yiling Chen, Arpita Ghosh, Michael Kearns, Tim Roughgarden, Jennifer Wortman Vaughan
  
  Communications of the ACM | December 2016, 巻59(12): pp. 102-108
  
  Publication PDF
- The Possibilities and Limitations of Private Prediction Markets
  
  Rachel Cummings, David Pennock, Jennifer Wortman Vaughan
  
  17th ACM Conference on Economics and Computation (EC 2016) | April 2016
  
  Publication
- Bounded Rationality in Wagering Mechanisms
  
  David Pennock, Vasilis Syrgkanis, Jennifer Wortman Vaughan
  
  32nd Conference on Uncertainty in Artificial Intelligence | January 2016
  
  Publication
- Belief Aggregation with Automated Market Makers
  
  Rajiv Sethi, Jennifer Wortman Vaughan
  
  Computational Economics | June 2015
  
  Publication
- Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets
  
  Hoda Heidari, Sébastien Lahaie, David Pennock, Jennifer Wortman Vaughan
  
  June 2015
  
  公開日公開日プロジェクト
- Incentivizing High Quality Crowdwork
  
  Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan
  
  Twenty-Fourth International World Wide Web Conference | May 2015
  
  Publication
- Market Making with Decreasing Utility for Information
  
  Miroslav Dudík, Rafael Frongillo, Jennifer Wortman Vaughan
  
  30th Conference on Uncertainty in Artificial Intelligence | July 2014
  
  Publication プロジェクト
- Removing Arbitrage from Wagering Mechanisms
  
  Yiling Chen, Nikhil Devanur, David Pennock, Jennifer Wortman Vaughan
  
  Fifteenth ACM Conference on Economics and Computation | June 2014
  
  Publication プロジェクト
- An Axiomatic Characterization of Wagering Mechanisms
  
  Jennifer Wortman Vaughan, Yiling Chen, Daniel Reeves, David Pennock, Nicolas S. Lambert, John Langford, Yoav Shoham
  
  Journal of Economic Theory | March 2014, 巻156: pp. 389-416
  
  Publication プロジェクト
- A General Volume-Parameterized Market Making Framework
  
  Jacob Abernethy, Rafael Frongillo, Xiaolong Li, Jennifer Wortman Vaughan
  
  ACM Conference on Electronic Commerce | January 2014
  
  Publication プロジェクト
- Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
  
  Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  15th ACM Conf. on Economics and Computation (EC) | January 2014
  
  Publication プロジェクト
- An Axiomatic Characterization of Adaptive-Liquidity Market Makers
  
  Xiaolong Li, Jennifer Wortman Vaughan
  
  Fourteenth ACM Conference on Electronic Commerce (EC) | May 2013
  
  Publication プロジェクト
- Efficient Market Making via Convex Optimization, and a Connection to Online Learning
  
  Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
  
  ACM Transactions on Economics and Computation | May 2013, 巻1
  
  Publication プロジェクト
- Cost Function Market Makers for Measurable Spaces
  
  Yiling Chen, Michael Ruberry, Jennifer Wortman Vaughan
  
  Fourteenth ACM Conference on Electronic Commerce (EC) | January 2013
  
  Publication プロジェクト
- Designing Informative Securities
  
  Yiling Chen, Mike Ruberry, Jennifer Wortman Vaughan
  
  28th Conference on Uncertainty in Artificial Intelligence (UAI) | January 2012
  
  Publication プロジェクト
- An Optimization-Based Framework for Automated Market-Making
  
  Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
  
  Twelfth ACM Conference on Electronic Commerce (EC) | January 2011
  
  Publication プロジェクト
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクトプロジェクト
- Toward Fairness in AI for People with Disabilities: A Research Roadmap
  
  Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna Wallach, Meredith Ringel Morris
  
  ASSETS 2019 Workshop on AI Fairness for People with Disabilities | October 2019
  
  Publication 動画プロジェクト
- The Externalities of Exploration and How Data Diversity Helps Exploitation
  
  Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
  
  31st Annual Conference on Learning Theory | February 2018
  
  Publication
- Oracle-Efficient Learning and Auction Design
  
  Miro Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
  
  Proceedings of the 58th Annual Symposium on Foundations of Computer Science (FOCS), 2017. | October 2017
  
  Publication Publication
- A Decomposition of Forecast Error in Prediction Markets
  
  Miro Dudík, Sébastien Lahaie, Ryan Rogers, Jennifer Wortman Vaughan
  
  31st Conference on Neural Information Processing Systems (NIPS 2017) | February 2017
  
  公開日
- Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
  
  Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  Journal of Artificial Intelligence Research | February 2016, 巻55
  
  Publication
- Bounded Rationality in Wagering Mechanisms
  
  David Pennock, Vasilis Syrgkanis, Jennifer Wortman Vaughan
  
  32nd Conference on Uncertainty in Artificial Intelligence | January 2016
  
  Publication
- A General Volume-Parameterized Market Making Framework
  
  Jacob Abernethy, Rafael Frongillo, Xiaolong Li, Jennifer Wortman Vaughan
  
  ACM Conference on Electronic Commerce | January 2014
  
  Publication プロジェクト
- Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
  
  Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  15th ACM Conf. on Economics and Computation (EC) | January 2014
  
  Publication プロジェクト
- Online Decision Making in Crowdsourcing Markets: Theoretical Challenges
  
  Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  ACM SIGecom Exchanges | December 2013, 巻12(2): pp. 4-23
  
  Position paper and survey.
  
  Publication プロジェクト
- Adaptive Task Assignment for Crowdsourced Classification
  
  Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan
  
  30th International Conference on Machine Learning (ICML) | May 2013
  
  Publication
- An Axiomatic Characterization of Adaptive-Liquidity Market Makers
  
  Xiaolong Li, Jennifer Wortman Vaughan
  
  Fourteenth ACM Conference on Electronic Commerce (EC) | May 2013
  
  Publication プロジェクト
- Efficient Market Making via Convex Optimization, and a Connection to Online Learning
  
  Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
  
  ACM Transactions on Economics and Computation | May 2013, 巻1
  
  Publication プロジェクト
- Cost Function Market Makers for Measurable Spaces
  
  Yiling Chen, Michael Ruberry, Jennifer Wortman Vaughan
  
  Fourteenth ACM Conference on Electronic Commerce (EC) | January 2013
  
  Publication プロジェクト
- Online Task Assignment in Crowdsourcing Markets
  
  Chien-Ju Ho, Jennifer Wortman Vaughan
  
  Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI) | January 2012
  
  Publication
- An Optimization-Based Framework for Automated Market-Making
  
  Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
  
  Twelfth ACM Conference on Electronic Commerce (EC) | January 2011
  
  Publication プロジェクト

- 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
  
  ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2025) | November 2025
  
  Honorable Mention
  
  Preprint
- Examining the Expanding Role of Synthetic Data Throughout the AI Development Pipeline
  
  Shivani Kapania, Stephanie Ballard, Alex Kessler, Jennifer Wortman Vaughan
  
  8th ACM Conference on Fairness, Accountability, and Transparency (FAccT 2025) | June 2025
  
  Preprint
- Canvil: Designerly Adaptation for LLM-Powered User Experiences
  
  K. Feng, Q. Vera Liao, Ziang Xiao, Jennifer Wortman Vaughan, Amy Zhang, David W. McDonald
  
  CHI 2025 | April 2025
  
  DOI
- Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies
  
  Sunnie S. Y. Kim, Jennifer Wortman Vaughan, Q. Vera Liao, Tania Lombrozo, Olga Russakovsky
  
  CHI 2025 | April 2025
  
  Honorable Mention, CHI 2025
  
  Publication
- Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alex Chouldechova, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nick Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  ICML 2025 | January 2025
  
  Publication
- Machine Unlearning Doesn’t Do What You Think: Lessons for Generative AI Policy, Research, and Practice
  
  A. F. Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alex Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, N. Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, A. Cyphert, Mark A. Lemley, danah boyd, Jennifer Wortman Vaughan, M. Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna Wallach, Nicolas Papernot, Katherine Lee
  
  NeurIPS 2025 | December 2024
  
  DOI Publication Publication
- (De)Noise: Moderating the Inconsistency Between Human Decision-Makers
  
  Nina Grgić-Hlača, Junaid Ali, Krishna P. Gummadi, Jennifer Wortman Vaughan
  
  ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2024) | November 2024
  
  Publication
- “I’m Not Sure, But…”: Examining the Impact of Large Language Models’ Uncertainty Expression on User Reliance and Trust
  
  Sunnie S. Y. Kim, Q. Vera Liao, Mihaela Vorvoreanu, Stephanie Ballard, Jennifer Wortman Vaughan
  
  7th ACM Conference on Fairness, Accountability, and Transparency (FAccT 2024) | June 2024
  
  Publication プロジェクト
- Tinker, Tailor, Configure, Customize: The Articulation Work of Customizing AI Fairness Checklists
  
  Michael Madaio, Jingya Chen, Hanna Wallach, Jennifer Wortman Vaughan
  
  Computer-Supported Cooperative Work | April 2024
  
  Publication プロジェクト
- Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience
  
  Q. Vera Liao, Hariharan Subramonyam, Jennifer Wang, Jennifer Wortman Vaughan
  
  2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | April 2023
  
  PDF プロジェクト
- GAM Coach: Towards Interactive and User-Centered Algorithmic Recourse
  
  Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau
  
  2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | February 2023
  
  PDF プロジェクト
- Understanding Machine Learning Practitioners’ Data Documentation Perceptions, Needs, Challenges, and Desiderata
  
  Amy K. Heger, Liz B. Marquis, Mihaela Vorvoreanu, Hanna Wallach, Jennifer Wortman Vaughan
  
  2022 Conference on Computer Supported Cooperative Work | November 2022
  
  Publication プロジェクトプロジェクト
- Generation Probabilities are Not Enough: Improving Error Highlighting for AI Code Suggestions
  
  Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan
  
  NeurIPS Workshop on Human-Centered AI | October 2022
  
  Publication
- Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
  
  Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
  
  KDD 2022 | July 2022
  
  Publication プロジェクト
- REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research
  
  Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna Wallach, Jennifer Wortman Vaughan
  
  FAccT 2022 | May 2022
  
  DOI プロジェクト
- Assessing the Fairness of AI Systems: AI Practitioners’ Processes, Challenges, and Needs for Support
  
  Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna Wallach
  
  25th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2022) | February 2022
  
  Publication
- GAM Changer: Editing Generalized Additive Models with Interactive Visualization
  
  Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
  
  2021 Neural Information Processing Systems | December 2021
  
  Publication Github
- From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
  
  David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
  
  HCOMP 2021 | September 2021
  
  Publication プロジェクト
- Manipulating and Measuring Model Interpretability
  
  Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake Hofman, Jennifer Wortman Vaughan, Hanna Wallach
  
  CHI 2021 | May 2021
  
  Publication プロジェクト
- Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs
  
  Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, Duncan Wadsworth, Hanna Wallach
  
  AIES 2021 | May 2021
  
  Publication
- No-Regret and Incentive-Compatible Online Learning
  
  Rupert Freeman, David M. Pennock, Chara Podimata, Jennifer Wortman Vaughan
  
  ICML 2020 | July 2020
  
  Publication PDF
- Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning
  
  Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna Wallach, Jennifer Wortman Vaughan
  
  CHI 2020 | April 2020
  
  CHI 2020 Honorable Mention Award
  
  Publication Github プロジェクト
- Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI
  
  Michael Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach
  
  CHI Conference on Human Factors in Computing Systems | March 2020
  
  CHI 2020 Best Paper Award
  
  PDF プロジェクト
- Weight of Evidence as a Basis for Human-Oriented Explanations
  
  David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
  
  Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
  
  Publication
- Toward Fairness in AI for People with Disabilities: A Research Roadmap
  
  Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna Wallach, Meredith Ringel Morris
  
  ASSETS 2019 Workshop on AI Fairness for People with Disabilities | October 2019
  
  Publication 動画プロジェクト
- Using Search Queries to Understand Health Information Needs in Africa
  
  Rediet Abebe, Shawndra Hill, Jennifer Wortman Vaughan, Peter M. Small, H. Andrew Schwartz
  
  Proceedings of the International AAAI Conference on Web and Social Media | June 2019
  
  Publication
- Truthful Aggregation of Budget Proposals
  
  Rupert Freeman, David Pennock, Dominik Peters, Jennifer Wortman Vaughan
  
  Twentieth ACM Conference on Economics and Computation | June 2019
  
  Publication
- Improving fairness in machine learning systems: What do industry practitioners need?
  
  Ken Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miro Dudík, Hanna Wallach
  
  2019 ACM CHI Conference on Human Factors in Computing Systems | June 2019
  
  Publication
- Understanding the Effect of Accuracy on Trust in Machine Learning Models
  
  Ming Yin, Jennifer Wortman Vaughan, Hanna Wallach
  
  CHI 2019 | May 2019
  
  Honorable Mention Award at CHI 2019
  
  PDF
- Understanding the Effect of Accuracy on Trust in Machine Learning Models
  
  Ming Ying, Jennifer Wortman Vaughan, Hanna Wallach
  
  2019 ACM CHI Conference on Human Factors in Computing Systems | May 2019
  
  Honorable Mention Award at CHI 2019
  
  Publication プロジェクト
- The Disparate Effects of Strategic Manipulation
  
  Lily Hu, Nicole Immorlica, Jennifer Wortman Vaughan
  
  2nd ACM Conference on Fairness, Accountability, and Transparency | January 2019
  
  Publication
- Group Fairness for Indivisible Goods Allocation
  
  Vincent Conitzer, Rupert Freeman, Nisarg Shah, Jennifer Wortman Vaughan
  
  AAAI 2019 | January 2019
  
  PDF
- An Equivalence Between Wagering and Fair-Division Mechanisms
  
  Rupert Freeman, David Pennock, Jennifer Wortman Vaughan
  
  AAAI 2019 | January 2019
  
  Publication
- Incentive-Compatible Forecasting Competitions
  
  Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David Pennock, Andreas Krause
  
  Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018) | April 2018
  
  Publication
- The Externalities of Exploration and How Data Diversity Helps Exploitation
  
  Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu
  
  31st Annual Conference on Learning Theory | February 2018
  
  Publication
- Oracle-Efficient Learning and Auction Design
  
  Miro Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
  
  Proceedings of the 58th Annual Symposium on Foundations of Computer Science (FOCS), 2017. | October 2017
  
  Publication Publication
- The Double Clinching Auction for Wagering
  
  Rupert Freeman, David Pennock, Jennifer Wortman Vaughan
  
  EC'17, Cambridge, Massachusetts, USA | June 2017
  
  Publication Publication Publication
- A Decomposition of Forecast Error in Prediction Markets
  
  Miro Dudík, Sébastien Lahaie, Ryan Rogers, Jennifer Wortman Vaughan
  
  31st Conference on Neural Information Processing Systems (NIPS 2017) | February 2017
  
  公開日
- The Communication Network Within the Crowd
  
  Ming Yin, Mary L. Gray, Siddharth Suri, Jennifer Wortman Vaughan
  
  25th International World Wide Web Conference (WWW) 2016 | April 2016
  
  Publication PDF
- The Possibilities and Limitations of Private Prediction Markets
  
  Rachel Cummings, David Pennock, Jennifer Wortman Vaughan
  
  17th ACM Conference on Economics and Computation (EC 2016) | April 2016
  
  Publication
- Bounded Rationality in Wagering Mechanisms
  
  David Pennock, Vasilis Syrgkanis, Jennifer Wortman Vaughan
  
  32nd Conference on Uncertainty in Artificial Intelligence | January 2016
  
  Publication
- Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets
  
  Hoda Heidari, Sébastien Lahaie, David Pennock, Jennifer Wortman Vaughan
  
  June 2015
  
  公開日公開日プロジェクト
- Incentivizing High Quality Crowdwork
  
  Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan
  
  Twenty-Fourth International World Wide Web Conference | May 2015
  
  Publication
- Market Making with Decreasing Utility for Information
  
  Miroslav Dudík, Rafael Frongillo, Jennifer Wortman Vaughan
  
  30th Conference on Uncertainty in Artificial Intelligence | July 2014
  
  Publication プロジェクト
- Removing Arbitrage from Wagering Mechanisms
  
  Yiling Chen, Nikhil Devanur, David Pennock, Jennifer Wortman Vaughan
  
  Fifteenth ACM Conference on Economics and Computation | June 2014
  
  Publication プロジェクト
- A General Volume-Parameterized Market Making Framework
  
  Jacob Abernethy, Rafael Frongillo, Xiaolong Li, Jennifer Wortman Vaughan
  
  ACM Conference on Electronic Commerce | January 2014
  
  Publication プロジェクト
- Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
  
  Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  15th ACM Conf. on Economics and Computation (EC) | January 2014
  
  Publication プロジェクト
- Adaptive Task Assignment for Crowdsourced Classification
  
  Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan
  
  30th International Conference on Machine Learning (ICML) | May 2013
  
  Publication
- An Axiomatic Characterization of Adaptive-Liquidity Market Makers
  
  Xiaolong Li, Jennifer Wortman Vaughan
  
  Fourteenth ACM Conference on Electronic Commerce (EC) | May 2013
  
  Publication プロジェクト
- Cost Function Market Makers for Measurable Spaces
  
  Yiling Chen, Michael Ruberry, Jennifer Wortman Vaughan
  
  Fourteenth ACM Conference on Electronic Commerce (EC) | January 2013
  
  Publication プロジェクト
- Online Task Assignment in Crowdsourcing Markets
  
  Chien-Ju Ho, Jennifer Wortman Vaughan
  
  Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI) | January 2012
  
  Publication
- Designing Informative Securities
  
  Yiling Chen, Mike Ruberry, Jennifer Wortman Vaughan
  
  28th Conference on Uncertainty in Artificial Intelligence (UAI) | January 2012
  
  Publication プロジェクト
- An Optimization-Based Framework for Automated Market-Making
  
  Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
  
  Twelfth ACM Conference on Electronic Commerce (EC) | January 2011
  
  Publication プロジェクト
- Position: To Make Text-to-Image Models that Work for Marginalized Communities, We Need New Measurement Practices for the Long Tail
  
  Nari Johnson, Hamna ., Deepthi Sudharsan, Theo Holroyd, Samantha Dalal, Siobhan Mackenzie Hall, Jennifer Wortman Vaughan, Daniela Massiceti, Cecily Morrison
  
  July 2025
  
  Preprint プロジェクト
- Dimensions of Generative AI Evaluation Design
  
  Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alex Chouldechova, Hanna Wallach
  
  November 2024
  
  Publication
- Evaluating Generative AI Systems is a Social Science Measurement Challenge
  
  Hanna Wallach, Meera Desai, Nick Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alex Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
  
  November 2024
  
  Publication
- The CLeAR Documentation Framework for AI Transparency: Recommendations for Practitioners & Context for Policymakers
  
  Kasia Chmielinski, Sarah Newman, Chris N. Kranzinger, Michael Hind, Jennifer Wortman Vaughan, Margaret Mitchell, Julia Stoyanovich, Angelina McMillan-Major, Emily McReynolds, Kathleen Esfahany, Mary L. Gray, Audrey Chang, Maui Hudson
  
  April 2024
  
  Publication プロジェクト
- A Human in the Loop is Not Enough: The Need for Human-Subject Experiments in Facial Recognition
  
  Forough Poursabzi-Sangdeh, Samira Samadi, Jennifer Wortman Vaughan, Hanna Wallach
  
  April 2020
  
  PDF
- Microsoft New Future of Work Report 2024
  
  Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
  
  MSR-TR-2024-56 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクトプロジェクト
- Challenges in Human-Agent Communication
  
  Gagan Bansal, Jennifer Wortman Vaughan, Saleema Amershi, Eric Horvitz, Adam Fourney, Hussein Mozannar, Victor Dibia, Daniel S. Weld
  
  MSR-TR-2024-53 | December 2024
  
  Microsoft による投稿
  
  Publication プロジェクト
- Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions
  
  Helena Vasconcelos, Gagan Bansal, Adam Fourney, Q. Vera Liao, Jennifer Wortman Vaughan
  
  ToCHI | April 2025, 巻32(1)
  
  Publication
- AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap
  
  Q. Vera Liao, Jennifer Wortman Vaughan
  
  Harvard Data Science Review | February 2024
  
  Publication プロジェクト
- Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations
  
  Valerie Chen, Q. Vera Liao, Jennifer Wortman Vaughan, Gagan Bansal
  
  Proc. ACM Hum.-Comput. Interact. | October 2023, 巻7
  
  Article 370
  
  PDF プロジェクト
- Summarize with Caution: Comparing Global Feature Attributions
  
  Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna Wallach, Jennifer Wortman Vaughan
  
  Bulletin of the IEEE Computer Society Technical Committee on Data Engineering | December 2021
  
  Publication プロジェクト
- Datasheets for Datasets
  
  Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford
  
  Communications of the ACM | December 2021, 巻64(12): pp. 86-92
  
  Publication プロジェクトプロジェクト
- Responsible computing during COVID-19 and beyond
  
  Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miro Dudík, Benjamin Fish, Mary L. Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, Marion Zepf
  
  Communications of the ACM | July 2021, 巻67(7): pp. 30-32
  
  https://doi.org/10.1145/3466612
  
  Publication
- Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets
  
  Hoda Heidari, Sebastien Lahaie, David Pennock, Jennifer Wortman Vaughan
  
  ACM Transactions on Economics and Computation (TEAC) - Special Issue on EC'15 | November 2018, 巻6(3–4)
  
  Publication
- Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research
  
  Jennifer Wortman Vaughan
  
  JMLR | September 2018, 巻18(193): pp. 1-46
  
  Publication
- Mathematical Foundations for Social Computing
  
  Yiling Chen, Arpita Ghosh, Michael Kearns, Tim Roughgarden, Jennifer Wortman Vaughan
  
  Communications of the ACM | December 2016, 巻59(12): pp. 102-108
  
  Publication PDF
- Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems
  
  Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  Journal of Artificial Intelligence Research | February 2016, 巻55
  
  Publication
- Belief Aggregation with Automated Market Makers
  
  Rajiv Sethi, Jennifer Wortman Vaughan
  
  Computational Economics | June 2015
  
  Publication
- An Axiomatic Characterization of Wagering Mechanisms
  
  Jennifer Wortman Vaughan, Yiling Chen, Daniel Reeves, David Pennock, Nicolas S. Lambert, John Langford, Yoav Shoham
  
  Journal of Economic Theory | March 2014, 巻156: pp. 389-416
  
  Publication プロジェクト
- Online Decision Making in Crowdsourcing Markets: Theoretical Challenges
  
  Aleksandrs Slivkins, Jennifer Wortman Vaughan
  
  ACM SIGecom Exchanges | December 2013, 巻12(2): pp. 4-23
  
  Position paper and survey.
  
  Publication プロジェクト
- Computational social science and social computing
  
  Winter Mason, Jennifer Wortman Vaughan, Hanna Wallach
  
  Mach Learn | November 2013, 巻95: pp. 257-260
  
  Publication DOI
- Efficient Market Making via Convex Optimization, and a Connection to Online Learning
  
  Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
  
  ACM Transactions on Economics and Computation | May 2013, 巻1
  
  Publication プロジェクト
- A Human-Centered Agenda for Intelligible Machine Learning
  
  Jennifer Wortman Vaughan, Hanna Wallach
  
  In Machines We Trust: Perspectives on Dependable AI | MIT Press による投稿 | 2021
  
  Author's Version プロジェクト

Jenn Wortman Vaughan

出版物

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

Position: To Make Text-to-Image Models that Work for Marginalized Communities, We Need New Measurement Practices for the Long Tail

Examining the Expanding Role of Synthetic Data Throughout the AI Development Pipeline

Canvil: Designerly Adaptation for LLM-Powered User Experiences

Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies

Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions

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

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

Challenges in Human-Agent Communication

Microsoft New Future of Work Report 2024

Dimensions of Generative AI Evaluation Design

Evaluating Generative AI Systems is a Social Science Measurement Challenge

(De)Noise: Moderating the Inconsistency Between Human Decision-Makers

“I’m Not Sure, But…”: Examining the Impact of Large Language Models’ Uncertainty Expression on User Reliance and Trust

The CLeAR Documentation Framework for AI Transparency: Recommendations for Practitioners & Context for Policymakers

Tinker, Tailor, Configure, Customize: The Articulation Work of Customizing AI Fairness Checklists

AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap

Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations

Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience

GAM Coach: Towards Interactive and User-Centered Algorithmic Recourse

Understanding Machine Learning Practitioners’ Data Documentation Perceptions, Needs, Challenges, and Desiderata

Generation Probabilities are Not Enough: Improving Error Highlighting for AI Code Suggestions

Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values

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

Assessing the Fairness of AI Systems: AI Practitioners’ Processes, Challenges, and Needs for Support

A Human-Centered Agenda for Intelligible Machine Learning

GAM Changer: Editing Generalized Additive Models with Interactive Visualization

Datasheets for Datasets

Summarize with Caution: Comparing Global Feature Attributions

From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence

Responsible computing during COVID-19 and beyond

Manipulating and Measuring Model Interpretability

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

No-Regret and Incentive-Compatible Online Learning

A Human in the Loop is Not Enough: The Need for Human-Subject Experiments in Facial Recognition

Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning

Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI

Weight of Evidence as a Basis for Human-Oriented Explanations

Toward Fairness in AI for People with Disabilities: A Research Roadmap

Improving fairness in machine learning systems: What do industry practitioners need?

Truthful Aggregation of Budget Proposals

Using Search Queries to Understand Health Information Needs in Africa

Understanding the Effect of Accuracy on Trust in Machine Learning Models

Understanding the Effect of Accuracy on Trust in Machine Learning Models

The Disparate Effects of Strategic Manipulation

An Equivalence Between Wagering and Fair-Division Mechanisms

Group Fairness for Indivisible Goods Allocation

Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets

Making Better Use of the Crowd: How Crowdsourcing Can Advance Machine Learning Research

Incentive-Compatible Forecasting Competitions

The Externalities of Exploration and How Data Diversity Helps Exploitation

Oracle-Efficient Learning and Auction Design

The Double Clinching Auction for Wagering

A Decomposition of Forecast Error in Prediction Markets

Mathematical Foundations for Social Computing

The Communication Network Within the Crowd

The Possibilities and Limitations of Private Prediction Markets

Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems

Bounded Rationality in Wagering Mechanisms

Belief Aggregation with Automated Market Makers

Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets

Incentivizing High Quality Crowdwork

Market Making with Decreasing Utility for Information

Removing Arbitrage from Wagering Mechanisms

An Axiomatic Characterization of Wagering Mechanisms

A General Volume-Parameterized Market Making Framework

Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems

Online Decision Making in Crowdsourcing Markets: Theoretical Challenges

Computational social science and social computing

Adaptive Task Assignment for Crowdsourced Classification

An Axiomatic Characterization of Adaptive-Liquidity Market Makers

Efficient Market Making via Convex Optimization, and a Connection to Online Learning

Cost Function Market Makers for Measurable Spaces

Designing Informative Securities

Online Task Assignment in Crowdsourcing Markets

An Optimization-Based Framework for Automated Market-Making

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

Position: To Make Text-to-Image Models that Work for Marginalized Communities, We Need New Measurement Practices for the Long Tail