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SELECTED PUBLICATIONS

A complete list of my publications can be found on my Google Scholar page.

2026

  • Tang, N., Li, M., Winecoff, A., Madaio, M., Heidari, H.‡, Shen, H.‡
    Navigating Uncertainties: How GenAI Developers Document their Models on Open-Source Platforms.
    (CHI 2026). [PDF]
  • Qian, A., Yang, Z., Shaw, R., Suh, J., Dabbish, L., Shen, H.
    Worker Discretion Advised: Co-designing Risk Disclosure in Crowdsourced Responsible AI (RAI) Content Work.
    (CHI 2026). [PDF]
  • Xiao, Q., Hu, Q., Xiao, J., Cao, H., Shen, H.
    Can GenAI Move from Individual Use to Collaborative Work? Experiences, Challenges, and Opportunities of Coordinating GenAI into Collaborative Newswork.
    (CHI 2026). [PDF]
  • Wang, Q., Kim, J., Sharma, A., Lee, A., Forlizzi, J., Shen, H.
    Situated, Dynamic, and Subjective: Envisioning the Design of Theory-of-Mind-Enabled Everyday AI with Industry Practitioners.
    (CHI 2026). [PDF]
  • Hu, Q., Xiao, Q., Cao, H., Shen, H.
    When Your Boss Is an AI Bot: Exploring Opportunities and Risks of Manager Clone Agents in the Future Workplace.
    (CHI 2026). [PDF]
  • Peng, C.†, Chai, M.†, Mo, G., Raman, N., Tang, N., Pagdon, S., Swarbrick, M., Jones, N., Fang, F., Shen, H.
    Large Language Models in Peer-Run Community Behavioral Health Services: Understanding Peer Specialists and Service Users’ Perspectives on Opportunities, Risks, and Mitigation Strategies.
    (CHI 2026). [PDF]
  • Shi, Y., Xiao, Q., Hu, Q., Shen, H., Shen, H.
    The Siren Song of LLMs: How Users Perceive and Respond to Dark Patterns in Large Language Models.
    (CHI 2026). [PDF]
  • Xiao, R., Xiao, Q., Hou, X., Moletsane, P., Li, H., Shen, H., Stamper, J.
    Do Teachers Dream of GenAI Widening Educational (In)equality? Envisioning the Future of K-12 GenAI Education from Global Teachers’ Perspectives.
    (CHI 2026). [PDF]
  • Qian, A., Shaw, R., Dabbish, L., Suh, J., Shen, H.
    Locating Risk: Task Designers and the Challenge of Risk Disclosure in RAI Content Work.
    (CSCW 2026). [PDF]
  • Kim, J., Yu, M., Zhi, J., Milani, S., Cheng, J., Fan, X., Shen, H.‡, Forlizzi, J.‡
    Content Creation with Generative AI: How Do Creators Responsibly Use Generative AI Tools?
    (CSCW 2026). [PDF]
  • Mo, G., Raman, N., Chai, M., Peng, C., Pagdon, S., Jones, N., Shen, H., Swarbrick, M., Fang, F.
    PeerCoPilot: A Language Model-Powered Assistant for Behavioral Health Organizations.
    (IAAI 2026). [PDF]

2025

  • Li, M., Bickerstech, W., Tang, N., Cranor, L., Hong, J., Shen, H.‡, Heidari, H.‡
    A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents.
    (AIES 2025). [PDF]
  • Xiao, S., Zou, H., Zhang, A., Kumar, D., Shen, H., Hong, J., Eslami, M.
    What Comes After Harm? Mapping Reparative Actions in AI through Justice Frameworks.
    (AIES 2025). [PDF]
  • Han, E., Zhang, A., Zhu, H., Shen, H., Liang, P., Hsieh, J.
    POET: Supporting Prompting Creativity and Personalization with Automated Expansion of Text-to-Image Generation.
    (UIST 2025). [PDF]
  • Wu, Y.†, Zhang, R.†, Liu, S., He, M., Hong, A., Northup, J., Kainaroi, C., Fang, F., Shen, H.
    Navigating Security and Privacy Threats in Homeless Social Service Provision.
    (USENIX Security 2025). [PDF]
  • Cheng, J., Ghate, K., Hua, W., Wang, W., Shen, H., Fang, F.
    REALM: A Dataset of Real-World LLM Use Cases.
    (ACL Findings 2025). [PDF]
  • Eslami, M., Fox, S., Shen, H., Fan, B., Lin, Y-R., Farzan, R., Schwanke, B.
    From Margins to the Table: Charting the Potential for Public Participatory Governance of Algorithmic Decision Making.
    (FAccT 2025). [PDF]
  • Fan, X., Xiao, Q., Zhou, X., Pei, J., Sap, M., Lu, Z., Shen, H.
    User-Driven Value Alignment: Understanding Users’ Perceptions and Strategies for Addressing Biased and Discriminatory Statements in AI Companions.
    (CHI 2025). [PDF]
  • Kapania, S.†, Wang, R.†, Li, T., Li, T., Shen, H.
    “I'm Categorizing LLM as a Productivity Tool”: Examining Ethics of LLM Use in HCI Research Practices.
    (CSCW 2025). [PDF]
  • Zhang, A., Amores, J., Shen, H., Czerwinski, M., Gray, M., Suh, J.
    AURA: Amplifying Understanding, Resilience, and Awareness for Responsible AI Content Work.
    (CSCW 2025). [PDF]
  • Sum, C., Zhi, J., Cook, A., Cooper, P., Lozano, A., Johnson, T.J., Perez, H., Ghani, R., Skirpan, M., Eslami, M., Shen, H., Fox, S.
    “You’re in a Ferrari. I’m Waiting for the Bus”: Confronting Tensions in Community-University Partnerships.
    (CSCW 2025). [PDF]

2024

  • Kingsley, S.†, Zhi, J.†, Deng, W. H., Lee, J., Zhang, S., Eslami, M.‡, Holstein, K.‡, Hong, J.I.‡, Li, T.‡, Shen, H.‡.
    Investigating What Factors Influence Users' Detection of Harmful Algorithmic Bias and Discrimination.
    (HCOMP 2024). Best Paper Award 🏆 [PDF]
  • Tang, N., Zhi, J., Kuo, T., Kainaroi, C., Northup, J., Holstein, K., Zhu, H., Heidari, H., Shen, H.
    AI Failure Cards: Understanding and Supporting Grassroots Efforts to Mitigate AI Failures in Homeless Services.
    (FAccT 2024). [PDF]
  • Wang, R.†, Milani, S.†, Chiu, J., Eack, S., Labrum, T., Murphy, S., Jones, N., Hardy, K., Shen, H., Fang, F., Chen, Z.
    PATIENT-Ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals.
    (EMNLP 2024). Best Paper Award 🏆 at NeurIPS GenAI for Health Workshop [PDF]
  • Shi, R., Zhi, J., Zeng, S., Zhang, Z., Kapoor, A., Hudson, S., Shen, H., Fang, F.
    Predicting and Presenting Task Difficulty for Crowdsourcing Food Rescue Platforms.
    (WWW 2024). [PDF]

2023

  • Kuo, T.†, Shen, H.†, Geum, J. S., Jones, N., Hong, J.I., Zhu, H.‡, Holstein, K.‡.
    Understanding Frontline Workers’ and Unhoused Populations’ Perspectives on AI Used in Homeless Services.
    (CHI 2023). Best Paper Award 🏆 [PDF]
  • Deng, W. H., Guo, B., DeVos, A., Shen, H., Eslami, M.‡, Holstein, K.‡.
    Understanding Practices, Challenges, and Opportunities for User-driven Algorithm Auditing in Industry Practice.
    (CHI 2023). [PDF]
  • Li, R.†, Kingsley, S.†, Fan, C., Sinha, P., Wai, N., Lee, J., Shen, H., Eslami, M., Hong, J.I.
    Participation and Division of Labor in User-Driven Algorithm Audits: How Do Everyday Users Work Together to Surface Algorithmic Harms?
    (CHI 2023). [PDF]

2022

  • Shen, H., Wang, L., Deng, W., Ciell, Velgersdijk, R., Zhu, H.
    The Model Card Authoring Toolkit: Toward Community-Centered, Deliberation-Driven AI Design.
    (FAccT 2022). [PDF]
  • DeVos, A., Dhabalia, A., Shen, H., Holstein, K.‡, Eslami, M.‡.
    Towards User-Driven Algorithm Auditing: Investigating Users' Search and Sensemaking Strategies for Uncovering Harmful Algorithmic Behavior.
    (CHI 2022). [PDF]

2021

  • Shen, H.†, DeVos, A.†, Eslami, M.‡, Holstein, K.‡.
    Everyday Algorithm Auditing: Understanding the Power of Everyday Users in Surfacing Harmful Algorithmic Behaviors.
    (CSCW 2021). [PDF]
  • Jin, H., Shen, H., Jain, M., Kumar, S., Hong, J.I.
    Lean Privacy Review: Collecting Users’ Privacy Concerns of Data Practices at a Low Cost.
    (TOCHI 2021). [PDF]
  • Lu, Z., Shen, C., Li, J., Shen, H., Wigdor, D.
    More Kawaii Than a Real-Person Streamer: Understanding How Viewers Engage with and Perceive Virtual YouTubers.
    (CHI 2021). [PDF]
  • Shen, H., Deng, W., Chattopadhyay, A., Wu, S., Wang, X., Zhu, H.
    Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning Through Deliberation.
    (FAccT 2021). [PDF]

2020

  • Shen, H., Jin, H., Cabrera, A., Perer, A., Zhu, H., Hong, J.I.
    Designing Alternative Representations of Confusion Matrices to Support Non-Expert Public Understanding of Algorithm Performance.
    (CSCW 2020). [PDF]
  • Shen, H., Faklaris, C., Jin, H., Dabbish, L., Hong, J.I.
    “I Can’t Even Buy Apples If I Don't Use Mobile Pay?” When Mobile Payments Become Infrastructural in China.
    (CSCW 2020). [PDF]