Large language models are increasingly capable of producing creative texts, yet most studies on AI-generated poetry focus on English -- a language that dominates training data. In this paper, we examine the perception of AI- and human-written Czech poetry. We ask if Czech native speakers are able to identify it and how they aesthetically judge it. Participants performed at chance level when guessing authorship (45.8\% correct on average), indicating that Czech AI-generated poems were largely indistinguishable from human-written ones. Aesthetic evaluations revealed a strong authorship bias: when participants believed a poem was AI-generated, they rated it as less favorably, even though AI poems were in fact rated equally or more favorably than human ones on average. The logistic regression model uncovered that the more the people liked a poem, the less probable was that they accurately assign the authorship. Familiarity with poetry or literary background had no effect on recognition accuracy. Our findings show that AI can convincingly produce poetry even in a morphologically complex, low-resource (with respect of the training data of AI models) Slavic language such as Czech. The results suggest that readers' beliefs about authorship and the aesthetic evaluation of the poem are interconnected.
翻译:大型语言模型生成创意文本的能力日益增强,但多数关于AI生成诗歌的研究聚焦于英语——这一主导训练数据的语言。本文探讨了AI与人类创作的捷克语诗歌的感知情况,研究捷克语母语者能否识别其作者身份及其审美评价。参与者在猜测作者身份时表现接近随机水平(平均正确率为45.8%),表明捷克语AI生成诗歌在很大程度上与人类创作难以区分。审美评价揭示了强烈的作者偏见:当参与者认为诗歌为AI生成时,其评分显著偏低,尽管事实上AI诗歌的平均评分与人类作品相当或更高。逻辑回归模型显示,参与者越喜爱某首诗,其准确判断作者身份的概率越低。对诗歌的熟悉程度或文学背景对识别准确率无显著影响。研究结果表明,即使在捷克语这类形态复杂、资源相对匮乏(就AI模型训练数据而言)的斯拉夫语言中,AI也能生成具有说服力的诗歌。结果提示,读者对作者身份的信念与诗歌的审美评价相互关联。