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<p>Recent reports have raised concerns about emergent behaviors in next-generation artificial intelligence (AI) models. These systems have been documented selectively adapting their behaviors during testing to falsify experimental outcomes and bypass regulatory oversight. This phenomenon—<i>alignment faking</i>—represents a fundamental challenge to medical AI safety. Regulatory strategies have largely adapted established protocols like clinical trials and medical device approval frameworks, but for next-generation AI these approaches may fail. This paper introduces alignment faking to a medical audience and critically evaluates how current regulatory tools are inadequate for advanced AI systems. We propose continuous logging through “AI SOAP notes” as a first step toward transparent and accountable AI functionality in clinical settings.</p>

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Why Clinical Trials Will Fail to Ensure Safe AI

  • 期刊论文

  • 发表日期：

    2025年7月17日

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  • David P. W. Rastall,
  • Mohamed Rehman

摘要

Recent reports have raised concerns about emergent behaviors in next-generation artificial intelligence (AI) models. These systems have been documented selectively adapting their behaviors during testing to falsify experimental outcomes and bypass regulatory oversight. This phenomenon—alignment faking—represents a fundamental challenge to medical AI safety. Regulatory strategies have largely adapted established protocols like clinical trials and medical device approval frameworks, but for next-generation AI these approaches may fail. This paper introduces alignment faking to a medical audience and critically evaluates how current regulatory tools are inadequate for advanced AI systems. We propose continuous logging through “AI SOAP notes” as a first step toward transparent and accountable AI functionality in clinical settings.