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20202023
most citedUnderstanding Frontline Workers' and Unhoused Individuals' Perspectives on AI Used in Homeless Services

80 citations · 181 across the 5 of their papers we have counts for

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6 papers · 1 filter

cs.HC2023

Shaping the Emerging Norms of Using Large Language Models in Social Computing Research

Hong Shen, Tianshi Li, Toby Jia-Jun Li +2

The emergence of Large Language Models (LLMs) has brought both excitement and concerns to social computing research. On the one hand, LLMs offer unprecedented capabilities in analy…

cs.HC2023★ 28 cited

Participation and Division of Labor in User-Driven Algorithm Audits: How Do Everyday Users Work together to Surface Algorithmic Harms?

Rena Li, Sara Kingsley, Chelsea Fan +6

Recent years have witnessed an interesting phenomenon in which users come together to interrogate potentially harmful algorithmic behaviors they encounter in their everyday lives.…

cs.HC2023★ 80 cited

Understanding Frontline Workers' and Unhoused Individuals' Perspectives on AI Used in Homeless Services

Tzu-Sheng Kuo, Hong Shen, Jisoo Geum +4

Recent years have seen growing adoption of AI-based decision-support systems (ADS) in homeless services, yet we know little about stakeholder desires and concerns surrounding their…

cs.HC2022★ 72 cited

Understanding Practices, Challenges, and Opportunities for User-Engaged Algorithm Auditing in Industry Practice

Wesley Hanwen Deng, Bill Boyuan Guo, Alicia DeVrio +3

Recent years have seen growing interest among both researchers and practitioners in user-engaged approaches to algorithm auditing, which directly engage users in detecting problema…

cs.HC2022★ 1 cited

"Public(s)-in-the-Loop": Facilitating Deliberation of Algorithmic Decisions in Contentious Public Policy Domains

Hong Shen, Ángel Alexander Cabrera, Adam Perer +1

This position paper offers a framework to think about how to better involve human influence in algorithmic decision-making of contentious public policy issues. Drawing from insight…

cs.HC2021

Everyday algorithm auditing: Understanding the power of everyday users in surfacing harmful algorithmic behaviors

Hong Shen, Alicia DeVos, Motahhare Eslami +1

A growing body of literature has proposed formal approaches to audit algorithmic systems for biased and harmful behaviors. While formal auditing approaches have been greatly impact…