The increased representation of non-binary characters in audiovisual media is societally crucial, yet non-binary language (e.g., pronouns) offers new challenges for translators. In Dutch, the acceptability of pronoun strategies for non-binary reference is debated and evolving. Machine translation (MT) is increasingly being used in audiovisual translation, yet its potential for translation in gender-sensitive contexts is understudied. In this paper, we compare three pronoun translation strategies (two human-produced, one MT) for rendering the English non-binary pronoun they into Dutch in an audiovisual context, using a fragment from the Netflix show Sex Education. We explore general acceptability of these strategies and compare this to audience perceptions after viewing subtitled fragments employing a specific strategy. The results support findings from earlier work on non-binary pronouns in Dutch and indicate that the MT-generated translations were perceived as the least suitable.