评估大型语言模型与心理健康整合的人类价值观的协调:使用施瓦茨基本价值观理论进行横截面研究.
Dorit Hadar-Shoval1, Kfir Asraf1, Yonathan Mizrachi2,3
1The Psychology Department, Max Stern Yezreel Valley College, Tel Adashim, Israel.
JMIR mental health
|April 9, 2024
概括
大型语言模型 (LLM) 与人类相比显示出明显的价值偏见,优先考虑普遍主义而不是成就. 这种分歧引发了心理健康应用的伦理问题,需要仔细调整和透明度.
科学领域:
- 人工智能伦理学 人工智能伦理学
- 计算社会科学 计算社会科学
- 心理测量 心理测量
背景情况:
- 大型语言模型 (LLM) 为心理健康提供了潜力,但不透明的调整过程可能会嵌入偏见.
- 评估LLM中嵌入的价值观对于道德AI开发和部署至关重要.
- 施瓦茨的基本价值观理论 (STBV) 为评估价值导向提供了一个框架.
研究的目的:
- 评估STBV是否可以在领先的LLMs中测量类似价值的结构.
- 为了确定LLM与人类和彼此相比是否表现出明显的价值类似模式.
主要方法:
- 四名法学士 (巴德,克劳德2,GPT-3.5,GPT-4) 完成了"肖像价值调整问卷" (PVQ-RR).
- 分析了LLM的可靠性和有效性,然后与来自49个国家的53,472名个人的人类数据进行了比较.
- 统计测试比较了LLM之间的价值配置文件和人类人口数据.
主要成果:
- 该PVQ-RR可靠量化了LLM中的类似价值结构,但与人类价值配置文件出现了显著的分歧.
- 法律学士优先考虑普遍主义和自我指导,不重视人类相对的成就,权力和安全.
- 独特的价值概况区分了四个LLM,并预测了他们对心理健康困境的反应.
结论:
- STBV有效地绘制了LLM中的价值类基础设施,揭示了与人类价值观的重大分歧.
- 嵌入式偏见对LLM整合到心理健康应用中构成道德风险,需要采取保障措施.
- 标准化调整过程对于捕捉文化多样性和确保在精神卫生保健中公平地部署人工智能至关重要.
关键词:
在这里,我们可以看到AIAIAI.巴尔德巴尔德 巴尔德巴尔德是什么意思聊天-GPT 的时间.聊天GPT 聊天 在GPT 聊天克劳德·克劳德·克劳德 (Claude Claude) 是一个在法学士 (LLM) 课程中.在法律上,LLMs.ML ML 在 ML在NLP中,我们使用了NLP.算法算法是一种算法.算法算法是一种算法.人工智能的人工智能是人工智能.聊天机器人 聊天机器人聊天机器人是一个聊天机器人.聊天机器人 聊天机器人聊天机器人聊天机器人聊天机器人深度学习是一种深度学习.电子健康 电子健康大型语言模型大型语言模型.移动健康 移动健康 移动健康 移动健康机器学习是机器学习.精神疾病是一种精神疾病.精神疾病是一种精神疾病.精神障碍 精神障碍是一种精神障碍.精神障碍 精神障碍 精神障碍心理健康 心理健康精神疾病 精神疾病精神疾病 精神疾病移动健康的移动健康情绪障碍是一种情绪障碍.情绪障碍 情绪障碍 情绪障碍自然语言处理自然语言处理.实用模型实用模型模型实用模型实用模型实用模型预测分析 预测分析预测模型是一个预测模型.预测模型的预测模型.预测系统 预测系统价值观的价值观的价值观.相关概念视频
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