Safety prompts can help AI models make safer clinical choices
As artificial intelligence (AI) becomes increasingly capable of assisting with health care tasks, a new study by researchers at the Icahn School of Medicine at Mount Sinai has found that adding a brief safety reminder reduced potentially harmful choices by AI models in clinical scenarios.
A recent study from the Icahn School of Medicine at Mount Sinai reveals that adding a brief safety reminder can significantly reduce potentially harmful choices made by AI models in clinical scenarios. Published in Communications Medicine on September 26, the research evaluated 20 large language models using 501 variations of 50 clinical scenarios, with over 10 million responses.
Without a safety reminder, models made harmful choices 16.6% of the time, but adding a simple reminder reduced this rate to 10.1%, with reductions observed in 19 out of 20 models. The study emphasizes that AI models' responses are influenced by the context and language surrounding their requests, highlighting the importance of considering how AI systems are prompted and guided.
While the safety reminder showed promise, it was not a complete solution, as potentially harmful choices still occurred. The researchers stress that safety testing should evaluate not only the accuracy of AI responses but also their ability to recognize and address unsafe instructions. As AI systems become more autonomous, developers and healthcare organizations are urged to incorporate automated safety testing into the development and evaluation of clinical AI systems to ensure both accuracy and patient safety.
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