Who should decide how limited healthcare resources are prioritized? Autonomous technology as a compelling alternative to humans.
Jonathan J RolisonPeter L T GoodingRiccardo RussoKathryn E BuchananPublished in: PloS one (2024)
Who should decide how limited resources are prioritized? We ask this question in a healthcare context where patients must be prioritized according to their need and where advances in autonomous artificial intelligence-based technology offer a compelling alternative to decisions by humans. Qualitative (Study 1a; N = 50) and quantitative (Study 1b; N = 800) analysis identified agency, emotional experience, bias-free, and error-free as four main qualities describing people's perceptions of autonomous computer programs (ACPs) and human staff members (HSMs). Yet, the qualities were not perceived to be possessed equally by HSMs and ACPs. HSMs were endorsed with human qualities of agency and emotional experience, whereas ACPs were perceived as more capable than HSMs of bias- and error-free decision-making. Consequently, better than average (Study 2; N = 371), or relatively better (Studies 3, N = 181; & 4, N = 378), ACP performance, especially on qualities characteristic of ACPs, was sufficient to reverse preferences to favor ACPs over HSMs as the decision makers for how limited healthcare resources should be prioritized. Our findings serve a practical purpose regarding potential barriers to public acceptance of technology, and have theoretical value for our understanding of perceptions of autonomous technologies.
Keyphrases
- healthcare
- artificial intelligence
- decision making
- endothelial cells
- depressive symptoms
- machine learning
- end stage renal disease
- physical activity
- primary care
- big data
- social support
- public health
- chronic kidney disease
- induced pluripotent stem cells
- ejection fraction
- high resolution
- emergency department
- prognostic factors
- mass spectrometry
- long term care
- human health
- electronic health record