Editing synthetic text from generative artificial intelligence – two exploratory case studies

Abstract

As the use of generative artificial intelligence (GenAI) becomes more mainstream, an increasing number of authors may turn to this technology to write directly in a second language, bypassing traditional translation methods. Consequently, professional editors may have to develop new skills: shifting from correcting translation and non-native errors to editing AI-assisted texts. This study includes several stages: participant selection, text planning, prompt engineering, text generation and text editing. The recruited authors provided prompts for GPT-4 to generate texts, edited the output as they desired and then passed them on to professional editors for a final edit. All participants reported their experiences and described the nature of their interactions. The findings reveal that, while GenAI significantly improved the grammatical accuracy of the non-native English texts, it also introduced anomalies. In conclusion, although AI was useful in these two cases, it did not fully replace the human editors, and professional translators-with their language skills-may like to consider offering this additional service. The study also suggests that both authors and editors should be trained in synthetic-text editing to fully harness the benefits of AI-assisted writing, and that further research should be conducted with diverse texts and authors to generalize the findings.

Published in

Translating and the Computer 46: proceedings. Asling: International Society for Advancement in Language Technology, 18-20 November 2024; pp. 35‑46 (ISBN 978-2-9701733-2-8).

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