在心理学研究中使用大型语言模型的危险和机遇
Suhaib Abdurahman1,2, Mohammad Atari3,4, Farzan Karimi-Malekabadi1,2
1Department of Psychology, University of Southern California, Los Angeles, CA 90089, USA.
PNAS nexus
|July 17, 2024
概括
大型语言模型 (LLM) 在心理学研究中具有潜力,但需要谨慎使用. 研究人员必须解决LLM的局限性和偏见,以确保包容性,可概括的科学发现.
科学领域:
- 心理学研究 心理学研究
- 人工智能的人工智能
- 计算社会科学 计算社会科学
背景情况:
- 大型语言模型 (LLM) 越来越多地被用于心理学研究应用.
- 人们担心,在不完全理解LLM的局限性和风险的情况下,人们不用批判地采用LLM,称为"GPTology".
- 现有的一般指导方针可能无法完全解决在心理背景下LLM使用的具体细微差别.
研究的目的:
- 调查心理研究中的LLMs当前的局限性,伦理含义和潜力.
- 在各种经验心理学研究中分析LLMs的具体影响.
- 倡导对LLMs在现场的负责任和方法上健全的整合.
主要方法:
- 审查目前的LLM能力和与心理学研究相关的局限性.
- 在心理学中使用LLM的经验研究分析.
- 伦理考虑和LLM应用的风险评估.
- 探索用于人工智能生成数据推断的透明和开放方法.
主要成果:
- 当用于心理学研究时,LLM存在重大限制和风险,特别是在全球心理多样性方面.
- 特别是在零射击环境中,将LLM视为通用文本分析解决方案是值得谨慎的.
- 法律法规的不透明性要求开发透明,开放的方法,以实现可靠和可重复的AI驱动推理.
结论:
- 承认LLM对文本注释和理解人类心理学等任务的实用性很重要.
- 多样化人类样本和扩大心理学方法论工具箱至关重要.
- 促进一个包容性,可普遍化的科学需要抵制均质化和过度依赖LLMs.
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