Vaughan, Jennifer Wortman

A theory of learning from different domains

Ben-David, S., Blitzer, J., Crammer, K., Kulesza, A., Pereira, F., & Vaughan, J. W. (2010) · Machine Learning

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 3,515

Datasheets for Datasets

Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., Daumé, H., & Crawford, K. (2018) · arXiv

Research Data Management PracticesScientific Computing and Data Management

Cited by 2,474

Datasheets for datasets

Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., III, H. D., & Crawford, K. (2021) · Communications of the ACM

Research Data Management PracticesScientific Computing and Data Management

Cited by 2,469

Manipulating and Measuring Model Interpretability

Poursabzi-Sangdeh, F., Goldstein, D. G., Hofman, J. M., Vaughan, J. W., & Wallach, H. (2018) · arXiv

Explainable Artificial Intelligence (XAI)Human-Automation Interaction and Safety

Cited by 711

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

Liao, Q. V., & Vaughan, J. W. (2023) · arXiv

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 209

"I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust

Kim, S. S. Y., Liao, Q. V., Vorvoreanu, M., Ballard, S., & Vaughan, J. W. (2024) · The 2024 ACM Conference on Fairness Accountability and Transparency

Human-Automation Interaction and SafetyInformation Retrieval and Search Behavior

Cited by 147

Incentivizing High Quality Crowdwork

Ho, C.-J., Slivkins, A., Suri, S., & Vaughan, J. W. (2015) · Proceedings of the 24th International Conference on World Wide Web

Mobile Crowdsensing and CrowdsourcingExperimental Behavioral Economics Studies

Cited by 146

Toward fairness in AI for people with disabilities SBG@a research roadmap

Guo, A., Kamar, E., Vaughan, J. W., Wallach, H., & Morris, M. R. (2020) · ACM SIGACCESS Accessibility and Computing

Ethics and Social Impacts of AIDigital Accessibility for Disabilities

Cited by 128

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

Barocas, S., Guo, A., Kamar, E., Krones, J., Morris, M. R., Vaughan, J. W., Wadsworth, W. D., & Wallach, H. (2021) · Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 72

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

Kim, S. S. Y., Vaughan, J. W., Liao, Q. V., Lombrozo, T., & Russakovsky, O. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

Explainable Artificial Intelligence (XAI)Information Retrieval and Search Behavior

Cited by 58

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

Vasconcelos, H., Bansal, G., Fourney, A., Liao, Q. V., & Vaughan, J. W. (2023) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 23

Challenges in Human-Agent Communication

Bansal, G., Vaughan, J. W., Amershi, S., Horvitz, E., Fourney, A., Mozannar, H., Dibia, V., & Weld, D. S. (2024) · arXiv

Speech and dialogue systemsSocial Robot Interaction and HRI

Cited by 8

Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment

Beygelzimer, A., Dauphin, Y. N., Liang, P., & Vaughan, J. W. (2023) · arXiv

Academic Writing and PublishingPsychology Research and Bibliometrics

Cited by 2

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

Wallach, H., Desai, M., Cooper, A. F., Wang, A., Atalla, C., Barocas, S., Blodgett, S. L., Chouldechova, A., Corvi, E., Dow, P. A., et al. (2025) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence Applications

Cited by 1