人类更偏好人写的文本，哪怕两者实际一样。
Human Bias in the Face of AI: Examining Human Judgment Against Text Labeled as AI Generated
- 三组实验对比人写与AI写文本的感知差异
- 盲测时无法区分文本，但标签影响偏好超30%
- 适合关注人机协作与认知偏见的研究者
随着AI文本生成技术的发展，人们对AI内容的信任仍受超出准确性的偏见制约。本研究通过三组实验（文本重写、新闻摘要、说服性写作）探究人类对标注为AI或人类生成内容的感知差异。在盲测中，评估者无法区分两类文本，却显著偏好标注为‘人类生成’的内容，偏好度超过30%。即使标签被故意调换，该偏好模式依然存在。这一人类对AI的系统性偏见具有广泛的社会与认知影响，导致对AI表现的低估。研究揭示了人类判断在人机交互中的局限性，为改善创意领域中的人机协作提供了基础。
原文摘要 · Abstract (English)
As AI advances in text generation, human trust in AI generated content remains constrained by biases that go beyond concerns of accuracy. This study explores how bias shapes the perception of AI versus human generated content. Through three experiments involving text rephrasing, news article summarization, and persuasive writing, we investigated how human raters respond to labeled and unlabeled content. While the raters could not differentiate the two types of texts in the blind test, they overwhelmingly favored content labeled as "Human Generated," over those labeled "AI Generated," by a preference score of over 30%. We observed the same pattern even when the labels were deliberately swapped. This human bias against AI has broader societal and cognitive implications, as it undervalues AI performance. This study highlights the limitations of human judgment in interacting with AI and offers a foundation for improving human-AI collaboration, especially in creative fields.
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