In this article, we investigate translation specialists’ capacity to identify raw machine translation (MT) output in comparison with so-called “human” translations produced without any use of MT. Specifically, we measure this capacity via an online activity, based on different criteria: (i) degree of expertise (translation students vs. professionals with at least 5 years’ experience), (ii) MT engine (DeepL, Google Translate, Reverso, ChatGPT), and (iii) length of input (1-3 sentences). A complementary, qualitative analysis, based on participants’ feedback, provides interesting insight on how they discriminate between raw MT output and human translations.