Artificial intelligence chain-of-thought reasoning in nuanced medical scenarios: mitigation of cognitive biases through model intransigence
Some biases persist in chain-of-thought reasoning LLMs, and models tend to produce intransigent recommendations. These findings highlight the role of clinicians to think broadly, respect diversity and remain vigilant when interpreting chain-of-thought reasoning artificial intelligence LLMs in nuanced medical decisions for patients.
Authors
- Donald A. Redelmeier (ORCID: https://orcid.org/0000-0003-4147-3544)
- Jonathan Wang (ORCID: https://orcid.org/0000-0003-4173-6594)
Institutions
- Sunnybrook Health Science Centre (CA)
- University of Toronto (CA)
- Health Sciences Centre (CA)
Publication Details
- Journal
- BMJ Quality & Safety
- Published
- 2025-11-24
- DOI
- https://doi.org/10.1136/bmjqs-2025-019299
- Primary Topic
- Clinical Reasoning and Diagnostic Skills
- Type
- article
- Field-Weighted Citation Impact
- 0.00