| Improving human-AI partnerships in child welfare: understanding worker practices, challenges, and desires for algorithmic decision support A Kawakami, V Sivaraman, HF Cheng, L Stapleton, Y Cheng, D Qing, ... Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems …, 2022 | 101 | 2022 |
| An algorithmic framework for fairness elicitation C Jung, M Kearns, S Neel, A Roth, L Stapleton, ZS Wu arXiv preprint arXiv:1905.10660, 2019 | 99* | 2019 |
| How child welfare workers reduce racial disparities in algorithmic decisions HF Cheng, L Stapleton, A Kawakami, V Sivaraman, Y Cheng, D Qing, ... Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems …, 2022 | 67 | 2022 |
| Soliciting stakeholders’ fairness notions in child maltreatment predictive systems HF Cheng, L Stapleton, R Wang, P Bullock, A Chouldechova, ZSS Wu, ... Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021 | 67 | 2021 |
| Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders L Stapleton, MH Lee, D Qing, M Wright, A Chouldechova, K Holstein, ... Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 54 | 2022 |
| “Why Do I Care What’s Similar?” Probing Challenges in AI-Assisted Child Welfare Decision-Making through Worker-AI Interface Design Concepts A Kawakami, V Sivaraman, L Stapleton, HF Cheng, A Perer, ZS Wu, ... Proceedings of the 2022 ACM Designing Interactive Systems Conference, 454-470, 2022 | 40 | 2022 |
| Strategic instrumental variable regression: Recovering causal relationships from strategic responses K Harris, DDT Ngo, L Stapleton, H Heidari, S Wu International Conference on Machine Learning, 8502-8522, 2022 | 26 | 2022 |
| Seeing seeds beyond weeds: Green teaming generative ai for beneficial uses L Stapleton, J Taylor, S Fox, T Wu, H Zhu arXiv preprint arXiv:2306.03097, 2023 | 13 | 2023 |
| A sandbox tool to bias (stress)-test fairness algorithms NJ Akpinar, M Nagireddy, L Stapleton, HF Cheng, H Zhu, S Wu, H Heidari arXiv preprint arXiv:2204.10233, 2022 | 12 | 2022 |
| Who has an interest in “Public Interest Technology”?: Critical questions for working with local governments & impacted communities L Stapleton, D Saxena, A Kawakami, T Nguyen, A Ammitzbøll Flügge, ... Companion Publication of the 2022 Conference on Computer Supported …, 2022 | 8 | 2022 |
| Incentivizing compliance with algorithmic instruments DDT Ngo, L Stapleton, V Syrgkanis, S Wu International Conference on Machine Learning, 8045-8055, 2021 | 7* | 2021 |
| Community-driven AI: Empowering people through responsible data-driven decision-making R Wan, A Alvarado Garcia, D Saxena, C Vajiac, A Kawakami, L Stapleton, ... Companion Publication of the 2023 Conference on Computer Supported …, 2023 | 5 | 2023 |
| " If This Person is Suicidal, What Do I Do?": Designing Computational Approaches to Help Online Volunteers Respond to Suicidality L Stapleton, S Liu, C Liu, I Hong, S Chancellor, RE Kraut, H Zhu Proceedings of the CHI Conference on Human Factors in Computing Systems, 1-21, 2024 | 2 | 2024 |
| Extended Analysis of" How Child Welfare Workers Reduce Racial Disparities in Algorithmic Decisions" L Stapleton, HF Cheng, A Kawakami, V Sivaraman, Y Cheng, D Qing, ... arXiv preprint arXiv:2204.13872, 2022 | 2 | 2022 |
| Animals, machines, and moral responsibility in a built environment L Stapleton | 2 | 2018 |
| Data Agency Theory: A Precise Theory of Justice for AI Applications L Ajmani, L Stapleton, M Houtti, S Chancellor The 2024 ACM Conference on Fairness, Accountability, and Transparency, 631-641, 2024 | 1 | 2024 |
| Advancing a Consent-Forward Paradigm for Digital Mental Health Data SR Pendse, L Stapleton, N Kumar, M De Choudhury, S Chancellor arXiv preprint arXiv:2404.14548, 2024 | | 2024 |
| 2nd Symposium on Foundations of Responsible Computing (FORC 2021) A Ganesh, J Zhao, C Jung, M Kearns, S Neel, A Roth, L Stapleton, ZS Wu, ... Schloss Dagstuhl-Leibniz-Zentrum für Informatik GmbH, 2021 | | 2021 |
