"Who is running it?" Towards Equitable AI Deployment in Home Care Work

要旨

We present a qualitative study that investigates the implications of current and near-future AI deployment for home care workers (HCWs), an overlooked group of frontline healthcare workers. Through interviews with 22 HCWs, care agency staff, and worker advocates, we find that HCWs do not understand how AI works, how their data can be used, or why AI systems might retain their information. HCWs are unaware that AI is already being utilized in their work, primarily via algorithmic shift-matching systems adopted by agencies. Participants detail the risks AI poses in sensitive care settings for HCWs, patients, and agencies, including threats to workers' autonomy and livelihoods, and express concerns that workers will be held accountable for AI mistakes, with the burden of proving AI's decisions incorrect falling on them. Considering these risks, participants advocate for new regulations and democratic governance structures that protect workers and control AI deployment in home care work.

著者
Ian René. Solano-Kamaiko
Cornell Tech, New York, New York, United States
Melissa Tan
Cornell Tech, New York, New York, United States
Joy Ming
Cornell, Ithaca, New York, United States
Ariel C. Avgar
Cornell University, Ithaca, New York, United States
Aditya Vashistha
Cornell University, Ithaca, New York, United States
Madeline Sterling
Weill Cornell Medicine, New York, New York, United States
Nicola Dell
Cornell Tech, New York, New York, United States
DOI

10.1145/3706598.3713850

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713850

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Better Work and Career

G414+G415
7 件の発表
2025-04-29 20:10:00
2025-04-29 21:40:00
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