从拉玛到语言:提示工程使通用人工智能能够像专家心理学家一样对叙事进行评分
Barry Dauphin1, Caleb Siefert2
1Department of Psychology, University of Detroit-Mercy, Detroit, MI, United States.
Frontiers in artificial intelligence
|February 21, 2025
概括
人工智能 (AI) 可以使用专家精细的提示可靠地对叙事进行评分. 这种AI在心理学中的应用显著减少了临床医生和研究人员对叙事评估工具的负担,例如社会认知和对象关系尺度 - 全球评分方法 (SCORS-G).
科学领域:
- 心理学 心理学 心理学
- 人工智能的人工智能
- 计算语言学 计算语言学
背景情况:
- 人工智能 (AI) 在心理学中提供了潜在的应用,特别是在耗时的叙事-人格评估中.
- 当前人工智能模型对于叙事评估等复杂任务的复杂性仍然不清楚,这对减少临床医生和研究人员负担构成了挑战.
研究的目的:
- 探索专家精细的提示是否使人工智能聊天机器人能够使用社会认知和对象关系尺度 - 全球评分方法 (SCORS-G) 可靠地评分叙事.
主要方法:
- 专家通过详细的SCORS-G培训材料审查和与Llama-2-70b的系统互动来完善提示.
- 这些精细的提示在AI聊天机器人ChatGPT-4和CLAUDE-2-100k上进行了测试,以确定叙事评级的准确性和可靠性.
主要成果:
- 专家精细的提示使聊天机器人能够在全球层面可靠地评价叙述,精度在子尺度上有所不同.
- 通过平均化聊天机器人评级,提高了全球和子规模评分的可靠性. 专家精制的提示在评级机构之间的可靠性和与黄金标准评级的一致性方面表现优于基本提示.
结论:
- 人工智能利用专家精细的提示,可以显著减少与SCORS-G.等叙事评级系统相关的时间和资源负担.
- 研究结果支持AI在心理评估中的实用性,对未来的研究和临床实践产生影响.
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