专业译者难辨AI生成文本，关键线索是语义矛盾与句式突变。
Can professional translators identify machine-generated text?
- 69名译者现场判断三篇意大利语短文的作者来源。
- 16.2%的译者准确识别出AI文本，主要依赖语义断裂等客观特征。
- 多数人误判，常被语法正确性误导，反映对AI文本的偏好心理。
本研究调查无特殊训练的专业译者能否可靠识别由AI（ChatGPT-4o）生成的意大利语短篇小说。69名译者参与面对面实验，评估三篇匿名短文——两篇由ChatGPT-4o生成，一篇由真人撰写。每位参与者对每篇作品的AI生成可能性打分，并说明理由。整体平均结果不显著，但16.2%的译者成功区分出合成文本，表明其判断基于分析能力而非随机猜测。然而，几乎等量译者将真实文本误判为AI生成，常依赖主观感受而非客观指标，可能反映读者对AI文本的偏好。低突发性（burstiness）和叙事矛盾是最可靠的合成文本标志，意外的借词、语义移植及英语句法迁移亦被提及。相反，语法准确性与情感基调常导致误判。研究提示了合成文本在专业领域编辑中的角色与边界问题。
原文摘要 · Abstract (English)
This study investigates whether professional translators without prior specialized training can reliably identify short stories generated in Italian by artificial intelligence (AI). Sixty-nine translators took part in an in-person experiment, where they assessed three anonymized short stories - two written by ChatGPT-4o and one by a human author. For each story, participants rated the likelihood of AI authorship and provided justifications for their choices. While average results were inconclusive, a statistically significant subset (16.2%) successfully distinguished the synthetic texts from the human text, suggesting that their judgements were informed by analytical skill rather than chance. However, a nearly equal number misclassified the texts in the opposite direction, often relying on subjective impressions rather than objective markers, possibly reflecting a reader preference for AI-generated texts. Low burstiness and narrative contradiction emerged as the most reliable indicators of synthetic authorship, with unexpected calques, semantic loans and syntactic transfer from English also reported. In contrast, features such as grammatical accuracy and emotional tone frequently led to misclassification. These findings raise questions about the role and scope of synthetic-text editing in professional contexts.
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