Department of Psychology and Neuroscience, Temple University, Weiss Hall, 1701 N. 13th St, Philadelphia, PA, 19122, USA.
Sci Rep. 2024 Oct 29;14(1):25989. doi: 10.1038/s41598-024-76218-y.
Artificial intelligence (AI) models can produce output that closely mimics human-generated content. We examined individual differences in the human ability to differentiate human- from AI-generated texts, exploring relationships with fluid intelligence, executive functioning, empathy, and digital habits. Overall, participants exhibited better than chance text discrimination, with substantial variation across individuals. Fluid intelligence strongly predicted differences in the ability to distinguish human from AI, but executive functioning and empathy did not. Meanwhile, heavier smartphone and social media use predicted misattribution of AI content (mistaking it for human). Determinations about the origin of encountered content also affected sharing preferences, with those who were better able to distinguish human from AI indicating a lower likelihood of sharing AI content online. Word-level differences in linguistic composition of the texts did not meaningfully influence participants' judgements. These findings inform our understanding of how individual difference factors may shape the course of human interactions with AI-generated information.
人工智能（AI）模型可以生成与人类生成内容极为相似的输出。我们考察了人类区分人工和 AI 生成文本的个体差异，探索了与流体智力、执行功能、同理心和数字习惯的关系。总的来说，参与者在文本区分方面表现出了高于随机水平的能力，个体之间存在很大差异。流体智力强烈预测了人类与 AI 之间区分能力的差异，但执行功能和同理心没有。同时，智能手机和社交媒体的使用频率越高，就越容易将 AI 内容误认为是人类生成的（将 AI 内容误认为是人类）。对遇到的内容来源的判断也会影响分享偏好，那些能够更好地区分人类和 AI 的人表示不太可能在网上分享 AI 内容。文本在语言组成上的词汇差异并没有对参与者的判断产生有意义的影响。这些发现为我们理解个体差异因素如何影响人类与 AI 生成信息的交互提供了信息。
