基于语言的人工智能建模的人格特征和病理从生活叙事采访
Joshua R Oltmanns1, Ritik Khandelwal2, Jerry Ma2
1Department of Psychological & Brain Sciences, Washington University in St. Louis.
Journal of psychopathology and clinical science
|September 29, 2025
概括
人工智能 (AI) 使用自然语言从生活叙事中模拟人格. 基于语言的AI显示出对人格评估和改进人格障碍模型的希望.
科学领域:
- 计算语言学计算语言学
- 心理评估 心理评估 心理评估
- 在行为科学中的人工智能
背景情况:
- 人格和人格病理学模型需要改进.
- 自然语言处理 (NLP) 为人格评估提供了新的方法.
- 现有的人格评估方法可能耗时且主观.
研究的目的:
- 从生活叙事采访中使用自然语言建模个性和个性病理.
- 开发和验证人工智能驱动的语言模型用于人格评估.
- 探索AI在改进人格障碍 (PD) 框架中的实用性.
主要方法:
- 训练和测试语言模型 (RoBERTa,BERTopic,语言调查和单词计数) 在1,409名老年人的转录生活叙事上.
- 根据既有的人格指标 (NEO-PI-R,DSM-IV人格结构面试) 和多方法标准验证的语言模型.
- 利用RoBERTa参数的微调进行人格预测.
主要成果:
- 精心调整的罗伯塔模型预测了人格得分,相关性高于r = .40,表明效果大小.
- 生活叙事语言更有效地映射到五因素模型领域,而不是DSMPD类别.
- 对于将语言映射到边界人格病理学方面,发现了适度的支持.
结论:
- 基于语言的AI具有很大的潜力,可以完善人格和人格障碍的概念框架.
- 人工智能驱动的人格评估可以在研究和临床环境中提供自动预测.
- 多方法验证支持使用语言模型进行人格评估.
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