"What is Your Envisioned Future?": Toward Human-AI Enrichment in Data Work of Asthma Care
Zhaoyuan Su, Lu He, Sunit P. Jariwala, Kai Zheng, Yunan Chen
摘要
Patient-generated health data (PGHD) is crucial for healthcare providers' decision making, as it complements clinical data by providing a more holistic view of patients' daily conditions. We interviewed 20 healthcare providers in asthma care to envision future technologies to support their PGHD use. We found that healthcare providers want future artificial intelligence (AI) systems to enhance their ability to treat patients by analyzing PGHD for profiling risk and predicting deterioration. Despite the potential benefits of AI, providers perceived various challenges of AI use with PGHD, including AI-driven data inequity, added burden, lack of trust toward AI, and fear of being replaced by AI. Clinicians wished for a future of co-dependent human-AI collaboration, where AI will help them to improve their clinical practice. In turn, healthcare providers can improve AI systems by making AI outputs more trustworthy and humane. Through the lens of data feminism, we discuss the importance of considering context and aligning the complex human infrastructure before designing or deploying PGHD-based AI systems in clinical settings. We highlight the opportunity to design for human-AI enrichment, where humans and AI not only partner with each other for improved performance, but also enrich each other to enhance each other's work overtime.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
引用它的顶会 Paper5
- Evaluating the Experience of LGBTQ+ People Using Large Language Model Based Chatbots for Mental Health SupportZilin Ma, Yiyang Mei, Yinru Long, Zhaoyuan Su 等CHI 2024 · 被引用 70 次
- Beyond the Waiting Room: Patient's Perspectives on the Conversational Nuances of Pre-Consultation ChatbotsBrenna Li, Ofek Gross, Noah Crampton, Mamta Kapoor 等CHI 2024 · 被引用 37 次
- A Systematic Literature Review of Infrastructure Studies in SIGCHIYao Lyu, Jie Cai, John M. CarrollCSCW 2025 · 被引用 19 次
- A Systematic Literature Review on Equity and Technology in HCI and Fairness: Navigating the Complexities and Nuances of Equity ResearchSeyun Kim, Yuanchen Bai, Haiyi Zhu, Motahhare EslamiCSCW 2025 · 被引用 14 次
- Understanding Collaboration between Professional Designers and Decision-making AI: A Case Study in the WorkplaceNami Ogawa, Yuki Okafuji, Yuji Hatada, Jun BabaCSCW 2025 · 被引用 3 次
相关 Paper
- Using Data to Approach the Unknown: Patients? and Healthcare Providers? Data Practices in Fertility ChallengesMayara Costa Figueiredo, H. Irene Su, Yunan ChenCSCW 2020 · 被引用 27 次
- Promise or Peril? Exploring Black Adults' Perspectives on the Use of Artificial Intelligence in Health ContextsAndrea G. Parker, Laura M. Vardoulakis, Christina N. HarringtonCHI 2026 · 被引用 1 次
- Uncertainty and Risk at the Point of Care: Implications of Patient-Generated ECGs and Algorithmic Interpretations for Clinical Decision MakingRachel Keys, Aisling Ann O'Kane, Paul Marshall, Graham StuartCHI 2026 · 被引用 1 次
- Patients Waiting for Cues: Information Asymmetries and Challenges in Sharing Patient-Generated Data in the ClinicChi Young Oh, Yuhan Luo, Beth St. Jean, Eun Kyoung ChoeCSCW 2022 · 被引用 20 次
- Healthcare AI Treatment Decision Support: Design Principles to Enhance Clinician Adoption and TrustEleanor R. Burgess, Ivana Jankovic, Melissa Austin, Nancy Cai 等CHI 2023 · 被引用 65 次
