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20132024
most citedPreventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

381 citations · 1.4k across the 100 of their papers we have counts for

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5 papers · 1 filter

cs.HC2022★ 74 cited

Imagining new futures beyond predictive systems in child welfare: A qualitative study with impacted stakeholders

Logan Stapleton, Min Hun Lee, Diana Qing +5

Child welfare agencies across the United States are turning to data-driven predictive technologies (commonly called predictive analytics) which use government administrative data t…

cs.HC2022★ 96 cited

Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits

Wesley Hanwen Deng, Manish Nagireddy, Michelle Seng Ah Lee +4

Recent years have seen the development of many open-source ML fairness toolkits aimed at helping ML practitioners assess and address unfairness in their systems. However, there has…

cs.HC2022★ 1 cited

Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support

Anna Kawakami, Venkatesh Sivaraman, Hao-Fei Cheng +7

AI-based decision support tools (ADS) are increasingly used to augment human decision-making in high-stakes, social contexts. As public sector agencies begin to adopt ADS, it is cr…

cs.HC2021★ 54 cited

Soliciting Stakeholders' Fairness Notions in Child Maltreatment Predictive Systems

Hao-Fei Cheng, Logan Stapleton, Ruiqi Wang +4

Recent work in fair machine learning has proposed dozens of technical definitions of algorithmic fairness and methods for enforcing these definitions. However, we still lack an und…

cs.HC2019★ 5 cited

Keeping Designers in the Loop: Communicating Inherent Algorithmic Trade-offs Across Multiple Objectives

Bowen Yu, Ye Yuan, Loren Terveen +3

Artificial intelligence algorithms have been used to enhance a wide variety of products and services, including assisting human decision making in high-stakes contexts. However, th…