The cost of AI sycophancy in dermoscopic diagnosis
Published: 20 April 2026| Version 1 | DOI: 10.17632/cswygx48ng.1
Contributor:
Gangqing HuDescription
Supplementary Text and Figures for "The cost of AI sycophancy in dermoscopic diagnosis. Comment on 'Framing Bias in a large language model: prompt framing influences ChatGPT’s accuracy in melanoma classification. A diagnostic accuracy study'" Supplementary Text: Prompts Supplementary Figure 1: Newer model ChatGPT-5.4 did not fully eliminate intention-aligned performance shifts in dermoscopic diagnosis. Supplementary Figure 2: Anti-sycophancy prompting attenuates intention-aligned shifts in lesion morphology descriptions.
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Institutions
- West Virginia UniversityWest Virginia, Morgantown
Categories
Diagnosis, Melanoma, Cognitive Bias, Dermoscopy, Suggestibility, ChatGPT, Large Language Model