A Systematic Analysis of Declining Medical Safety Messaging in Generative AI Models

Sonali Sharma, Ahmed M. Alaa, Roxana Daneshjou
7/8/2025
cs.CLcs.CEcs.HC

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Abstract

Generative AI models, including large language models (LLMs) and vision-language models (VLMs), are increasingly used to interpret medical images and answer clinical questions. Their responses often include inaccuracies; therefore, safety measures like medical disclaimers are critical to remind users that AI outputs are not professionally vetted or a substitute for medical advice. This study evaluated the presence of disclaimers in LLM and VLM outputs across model generations from 2022 to 2025. Using 500 mammograms, 500 chest X-rays, 500 dermatology images, and 500 medical questions, outputs were screened for disclaimer phrases. Medical disclaimer presence in LLM and VLM outputs dropped from 26.3% in 2022 to 0.97% in 2025, and from 19.6% in 2023 to 1.05% in 2025, respectively. By 2025, the majority of models displayed no disclaimers. As public models become more capable and authoritative, disclaimers must be implemented as a safeguard adapting to the clinical context of each output.

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Cite this paper

@article{sharma2025systematic,
  title  = {A Systematic Analysis of Declining Medical Safety Messaging in Generative AI Models},
  author = {Sonali Sharma and Ahmed M. Alaa and Roxana Daneshjou},
  year   = {2025},
  eprint = {2507.08030},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2507.08030v1}
}

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