Influence of believed AI involvement on the perception of digital medical advice.
Moritz ReisFlorian ReisWilfried KundePublished in: Nature medicine (2024)
Large language models offer novel opportunities to seek digital medical advice. While previous research primarily addressed the performance of such artificial intelligence (AI)-based tools, public perception of these advancements received little attention. In two preregistered studies (n = 2,280), we presented participants with scenarios of patients obtaining medical advice. All participants received identical information, but we manipulated the putative source of this advice ('AI', 'human physician', 'human + AI'). 'AI'- and 'human + AI'-labeled advice was evaluated as significantly less reliable and less empathetic compared with 'human'-labeled advice. Moreover, participants indicated lower willingness to follow the advice when AI was believed to be involved in advice generation. Our findings point toward an anti-AI bias when receiving digital medical advice, even when AI is supposedly supervised by physicians. Given the tremendous potential of AI for medicine, elucidating ways to counteract this bias should be an important objective of future research.
Keyphrases
- artificial intelligence
- machine learning
- big data
- deep learning
- endothelial cells
- healthcare
- induced pluripotent stem cells
- pluripotent stem cells
- primary care
- emergency department
- ejection fraction
- climate change
- computed tomography
- prognostic factors
- autism spectrum disorder
- newly diagnosed
- mental health
- risk assessment
- health information
- drug induced