Haiyi Zhu

Stapleton, L. ., Lee, M. H., Qing, D. ., Wright, M. ., Chouldechova, A. ., Holstein, K. ., … Zhu, H. . (2022). Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders. In 2022 ACM Conference on Fairness, Accountability, and Transparency (p. 16). http://doi.org/10.1145/3531146.3533177

Yao, Z. ., Yang, D. ., Levine, J. M., Low, C. A., Smith, T. ., Zhu, H. ., & Kraut, R. E. (2021). Join, Stay or Go?: A Closer Look at Members’ Life Cycles in Online Health Communities. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW1), 22. http://doi.org/10.1145/3449245

Yao, Z. ., Weden, S. ., Emerlyn, L. ., Zhu, H. ., & Kraut, R. E. (2021). Together But Alone: Atomization and Peer Support among Gig Workers. In Proceedings of the ACM on Human-Computer Interaction (Vol. 5). http://doi.org/10.1145/3479535

Cheng, H.-F. ., Stapleton, L. ., Kawakami, A. ., Sivaraman, V. ., Cheng, Y. ., Qing, D. ., … Zhu, H. . (2022). How Child Welfare Workers Reduce Racial Disparities in Algorithmic Decisions. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (p. 22). http://doi.org/10.1145/3491102.3501831

Kawakami, A. ., Sivaraman, V. ., Cheng, H.-F. ., Stapleton, L. ., Cheng, Y. ., Qing, D. ., … Holstein, K. . (2022). Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (p. 18). http://doi.org/10.1145/3491102.3517439

Hsieh, J. ., Hong, Y. ., Burtch, G. ., & Zhu, H. . (2022). A Little Too Personal: Effects of Standardization versus Personalization on Job Acquisition, Work Completion, and Revenue for Online Freelancers. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (p. 11). http://doi.org/10.1145/3491102.3517546

Kawakami, A. ., Sivaraman, V. ., Stapleton, L. ., Cheng, H.-F. ., Perer, A. ., Wu, Z. S., … Holstein, K. . (2022). “Why Do I Care What’s Similar?” Probing Challenges in AI-Assisted Child Welfare Decision-Making through Worker-AI Interface Design Concepts. In Designing Interactive Systems Conference (p. 17). http://doi.org/10.1145/3532106.3533556

Shen, H. ., Wang, L. ., Deng, W. H., Brusse, C. ., Velgersdijk, R. ., & Zhu, H. . (2022). The Model Card Authoring Toolkit: Toward Community-centered, Deliberation-driven AI Design. In 2022 ACM Conference on Fairness, Accountability, and Transparency (p. 12). http://doi.org/10.1145/3531146.3533110

Deng, W. H., Nagireddy, M. ., Lee, M. S., Singh, J. ., Wu, Z. S., Holstein, K. ., & Zhu, H. . (2022). Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits. In 2022 ACM Conference on Fairness, Accountability, and Transparency (p. 12). http://doi.org/10.1145/3531146.3533113

Wang, L. ., & Zhu, H. . (2022). How are ML-Based Online Content Moderation Systems Actually Used? Studying Community Size, Local Activity, and Disparate Treatment. In 2022 ACM Conference on Fairness, Accountability, and Transparency (p. 15). http://doi.org/10.1145/3531146.3533147