Hong Shen
Orcid: 0000-0002-5364-3718Affiliations:
- Carnegie Mellon University, Pittsburgh, PA, USA
According to our database1,
Hong Shen
authored at least 22 papers
between 2020 and 2024.
Collaborative distances:
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Bibliography
2024
Minion: A Technology Probe for Resolving Value Conflicts through Expert-Driven and User-Driven Strategies in AI Companion Applications.
CoRR, 2024
User-Driven Value Alignment: Understanding Users' Perceptions and Strategies for Addressing Biased and Discriminatory Statements in AI Companions.
CoRR, 2024
PATIENT-Ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals.
CoRR, 2024
"I'm categorizing LLM as a productivity tool": Examining ethics of LLM use in HCI research practices.
CoRR, 2024
Proceedings of the ACM on Web Conference 2024, 2024
AI Failure Cards: Understanding and Supporting Grassroots Efforts to Mitigate AI Failures in Homeless Services.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024
PATIENT-ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
2023
Shaping the Emerging Norms of Using Large Language Models in Social Computing Research.
Proceedings of the Computer Supported Cooperative Work and Social Computing, 2023
Participation and Division of Labor in User-Driven Algorithm Audits: How Do Everyday Users Work together to Surface Algorithmic Harms?
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023
Understanding Frontline Workers' and Unhoused Individuals' Perspectives on AI Used in Homeless Services.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023
Understanding Practices, Challenges, and Opportunities for User-Engaged Algorithm Auditing in Industry Practice.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023
2022
Understanding Practices, Challenges, and Opportunities for User-Driven Algorithm Auditing in Industry Practice.
CoRR, 2022
"Public(s)-in-the-Loop": Facilitating Deliberation of Algorithmic Decisions in Contentious Public Policy Domains.
CoRR, 2022
The Model Card Authoring Toolkit: Toward Community-centered, Deliberation-driven AI Design.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022
Toward User-Driven Algorithm Auditing: Investigating users' strategies for uncovering harmful algorithmic behavior.
Proceedings of the CHI '22: CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA, 29 April 2022, 2022
2021
Lean Privacy Review: Collecting Users' Privacy Concerns of Data Practices at a Low Cost.
ACM Trans. Comput. Hum. Interact., 2021
Everyday Algorithm Auditing: Understanding the Power of Everyday Users in Surfacing Harmful Algorithmic Behaviors.
Proc. ACM Hum. Comput. Interact., 2021
Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning through Deliberation.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021
More Kawaii than a Real-Person Live Streamer: Understanding How the Otaku Community Engages with and Perceives Virtual YouTubers.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021
2020
Designing Alternative Representations of Confusion Matrices to Support Non-Expert Public Understanding of Algorithm Performance.
Proc. ACM Hum. Comput. Interact., 2020
'I Can't Even Buy Apples If I Don't Use Mobile Pay?': When Mobile Payments Become Infrastructural in China.
Proc. ACM Hum. Comput. Interact., 2020