生成性AI中的文化趋势
Jackson G Lu1, Lesley Luyang Song2,3, Lu Doris Zhang4
1MIT Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA. lu18@mit.edu.
Nature human behaviour
|June 20, 2025
概括
在文化文本上训练的生成人工智能 (AI) 模型在不同语言中显示出不同的文化偏见. 这些AI文化趋势影响社会取向和认知风格,影响广告等现实应用.
科学领域:
- 人工智能的人工智能
- 文化心理学 文化心理学
- 计算语言学 计算语言学
背景情况:
- 生成型人工智能模型在庞大的文本数据集上进行训练,这些数据集本质上包含文化信息.
- 文化心理学研究了社会取向和认知风格在不同文化之间如何变化.
- 了解AI的文化趋势对于其道德和有效的部署至关重要.
研究的目的:
- 调查生成性AI模型在处理不同人类语言时是否表现出文化倾向.
- 在语言和文化背景下分析AI的社会取向和认知风格.
- 探索AI的文化偏见对现实世界的影响和潜在的缓解策略.
主要方法:
- 分析GPT模型对标准化心理测量的反应,用中文和英语进行分析.
- 使用ERNIE复制发现,这是中国著名的生成AI模型.
- 在不同语言中对人工智能产生的文化导向广告进行评估.
主要成果:
- 与英语相比,GPT在中文表现出更相互依存的社会取向和整体的认知风格.
- 这些文化趋势在ERNIE模型中得到复制.
- 人工智能驱动的广告建议显示了相应的文化偏见,有利于在中国背景下相互依赖的方向.
结论:
- 在文化文本上训练的生成人工智能模型继承并展示这些文化趋势.
- 人工智能的文化偏见体现在社会取向,认知风格和实际应用中.
- 文化提示可能会调节这些AI文化趋势,建议减轻偏见的途径.
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