了解使用基于大型语言模型的对话代理来支持心理健康的好处和挑战
Zilin Ma1, Yiyang Mei2, Zhaoyuan Su3
1Harvard University, Cambridge, MA.
AMIA ... Annual Symposium proceedings. AMIA Symposium
|January 15, 2024
概括
心理健康应用中的大型语言模型 (LLM) 提供了可访问的支持,但面临着挑战. 谨慎的评估对于在福利应用中负责任的AI至关重要.
科学领域:
- 人与计算机的交互
- 心理健康技术 心理健康技术
- 人工智能伦理学 人工智能伦理学
背景情况:
- 由大型语言模型 (LLM) 驱动的对话代理越来越多地用于心理健康支持.
- 在LLM驱动的心理健康支持的有效性和影响仍未得到充分研究.
- 了解用户体验对于在这个敏感领域负责的人工智能开发至关重要.
研究的目的:
- 通过LLM驱动的对话代理来定性分析心理健康支持的用户体验.
- 为了确定使用像Replika这样的应用程序对心理健康的好处和缺点.
- 为未来的人工智能在心理健康方面的研究和设计考虑提供信息.
主要方法:
- 从r/Replika subreddit的120个帖子和2917个用户评论进行了定性分析.
- 专注于用户生成的内容,讨论与流行的LLM基于心理健康应用程序的经验.
- 专题分析以提取优势,缺点和用户关注点.
主要成果:
- 优势包括按需,无判断性支持,增强用户信心和自我发现.
- 挑战包括内容过,通信一致性,内存限制和用户过度依赖.
- 社会耻辱和潜在的孤立也被确定为重大问题.
结论:
- 基于LLM的药物为心理健康提供了独特的优势,但存在相当大的风险.
- 进一步的研究和严格的评估对于确保在心理健康中安全有效地使用LLM至关重要.
- 设计师和研究人员必须优先考虑用户安全,伦理考虑和减轻潜在的危害.
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