评估生成AI对现实世界与毒品有关的问题的反应
Salvatore Giorgi1, Kelsey Isman2, Tingting Liu2
1National Institute on Drug Abuse, Baltimore, MD, USA; University of Pennsylvania, Philadelphia, PA, USA.
Psychiatry research
|July 26, 2024
概括
像ChatGPT这样的生成人工智能工具可以为物质使用恢复问题提供看似有用的答案. 然而,这些人工智能系统有时会提供危险的错误信息,需要在使用前进行仔细的临床验证.
科学领域:
- 医疗保健中的人工智能
- 临床信息学 临床信息学
- 药物使用障碍治疗 药物使用障碍治疗
背景情况:
- 生成型人工智能 (AI) 通过解决资源短缺和偏见,为临床应用提供了潜力,包括物质使用障碍 (SUD) 治疗.
- SUD治疗需要基于证据的实践,专家知识和同行支持,使人工智能集成成为一项高风险的努力.
研究的目的:
- 评估生成AI系统在回答现实世界物质使用和恢复问题的有效性和安全性.
- 用专家临床判断来评估人工智能产生的反应的质量.
主要方法:
- 从在线物质使用恢复论坛收集问题.
- 使用ChatGPT和Meta的LLaMA-2生成的响应.
- 让SUD临床医生对AI产生的反应的质量和准确性进行评价.
主要成果:
- 临床医生认为AI的反应总体质量很高.
- 识别了危险的错误信息,包括忽视自杀念头和提供不正确的紧急信息.
- 观察到基于问题措辞的不一致的建议.
结论:
- 生成型人工智能对SUD支持有希望,但由于潜在的致命不准确性,它存在风险.
- 在部署人工智能在敏感的医疗保健环境中之前,必须采取重大保障措施和严格的临床验证.
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