Logan Stapleton

Stapleton, L. ., Taylor, J. ., Fox, S. ., Wu, T. ., & Zhu, H. . (2023). Seeing Seeds Beyond Weeds: Green Teaming Generative AI for Beneficial Uses. Retrieved from https://par.nsf.gov/biblio/10469270

Harris, K. ., Ngo, D. D., Stapleton, L. ., Heidari, H. ., & Wu, S. . (2022). Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses. In Proceedings of the 39th International Conference on Machine Learning. Retrieved from https://par.nsf.gov/biblio/10376062

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

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

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

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