Designing medical artificial intelligence for in- and out-groups
作者：
Highlights：
• Medical artificial intelligence (AI) can deliver worldwide access to healthcare.
• In three studies, we addressed how designing medical AI varies between in- and out-groups.
• We examined how non-medical and medical people varies in designing medical AI for in- and out-groups.
• Out-group stereotype shapes the design of medical AI.
• This health inequity has implications for AI stakeholders and health researchers.
摘要
•Medical artificial intelligence (AI) can deliver worldwide access to healthcare.•In three studies, we addressed how designing medical AI varies between in- and out-groups.•We examined how non-medical and medical people varies in designing medical AI for in- and out-groups.•Out-group stereotype shapes the design of medical AI.•This health inequity has implications for AI stakeholders and health researchers.
论文关键词：Medical artificial intelligence design,Out-group homogeneity effect,Health inequity,Experiment
论文评审过程：Received 30 April 2020, Revised 11 June 2021, Accepted 20 June 2021, Available online 22 June 2021, Version of Record 30 June 2021.
论文官网地址：https://doi.org/10.1016/j.chb.2021.106929
