Wallach, Hanna

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

Language (Technology) is Power: A Critical Survey of “Bias” in NLP

Blodgett, S. L., Barocas, S., Daumé III, H., & Wallach, H. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Ethics and Social Impacts of AINatural Language Processing Techniques

Cited by 1,050

Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need?

Holstein, K., Wortman Vaughan, J., Daumé, H., Dudik, M., & Wallach, H. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 777

Manipulating and Measuring Model Interpretability

Poursabzi-Sangdeh, F., Goldstein, D. G., Hofman, J. M., Wortman Vaughan, J. W., & Wallach, H. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

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

Cited by 728

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

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

Kaur, H., Nori, H., Jenkins, S., Caruana, R., Wallach, H., & Wortman Vaughan, J. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Explainable Artificial Intelligence (XAI)Data Visualization and Analytics

Cited by 564

Understanding the Effect of Accuracy on Trust in Machine Learning Models

Yin, M., Wortman Vaughan, J., & Wallach, H. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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

Cited by 527

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

Madaio, M. A., Stark, L., Wortman Vaughan, J., & Wallach, H. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 436

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

Madaio, M., Egede, L., Subramonyam, H., Wortman Vaughan, J., & Wallach, H. (2022) · Proceedings of the ACM on Human-Computer Interaction

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 156

Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets

Blodgett, S. L., Lopez, G., Olteanu, A., Sim, R., & Wallach, H. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Ethics and Social Impacts of AITopic Modeling

Cited by 147

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

Measuring Representational Harms in Image Captioning

Wang, A., Barocas, S., Laird, K., & Wallach, H. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 40

Taxonomizing and Measuring Representational Harms: A Look at Image Tagging

Katzman, J., Wang, A., Scheuerman, M., Blodgett, S. L., Laird, K., Wallach, H., & Barocas, S. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 32

FairPrism: Evaluating Fairness-Related Harms in Text Generation

Fleisig, E., Amstutz, A., Atalla, C., Blodgett, S. L., Daumé III, H., Olteanu, A., Sheng, E., Vann, D., & Wallach, H. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Ethics and Social Impacts of AIHate Speech and Cyberbullying Detection

Cited by 14

Taxonomizing Representational Harms using Speech Act Theory

Corvi, E., Washington, H., Reed, S., Atalla, C., Chouldechova, A., Dow, P. A., Garcia-Gathright, J., Pangakis, N. J., Sheng, E., Vann, D., et al. (2025) · Findings of the Association for Computational Linguistics: ACL 2025

Ethics and Social Impacts of AIHate Speech and Cyberbullying Detection

Cited by 6

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