Faithful or Just Plausible? Evaluating the Faithfulness of Closed-Source LLMs in Medical Reasoning
#LLMs #medical reasoning #faithfulness #closed-source AI #healthcare AI #AI evaluation #transparency
📌 Key Takeaways
- Closed-source LLMs often produce plausible but unfaithful medical reasoning
- Study evaluates faithfulness of LLMs in medical contexts
- Findings highlight risks of relying on LLMs for critical medical decisions
- Calls for improved transparency and evaluation methods in AI healthcare
📖 Full Retelling
arXiv:2603.13988v1 Announce Type: new
Abstract: Closed-source large language models (LLMs), such as ChatGPT and Gemini, are increasingly consulted for medical advice, yet their explanations may appear plausible while failing to reflect the model's underlying reasoning process. This gap poses serious risks as patients and clinicians may trust coherent but misleading explanations. We conduct a systematic black-box evaluation of faithfulness in medical reasoning among three widely used closed-sour
🏷️ Themes
AI Ethics, Healthcare Technology
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Original Source
arXiv:2603.13988v1 Announce Type: new
Abstract: Closed-source large language models (LLMs), such as ChatGPT and Gemini, are increasingly consulted for medical advice, yet their explanations may appear plausible while failing to reflect the model's underlying reasoning process. This gap poses serious risks as patients and clinicians may trust coherent but misleading explanations. We conduct a systematic black-box evaluation of faithfulness in medical reasoning among three widely used closed-sour
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