Literarisches Übersetzen im KI-Zeitalter: Überlegungen zu einer nachhaltigen Markttransformation

Abstract Although it is less technologized than other language services, (partial) automation has also been witnessed in literary translation. Since 2017, neural machine translation (NMT) systems such as DeepL and, subsequently, large language models (LLMs) such as ChatGPT have been drastically changing, if not revolutionizing, the language industry. LLMs have larger context windows than NMT systems and allow for translations to be adapted to various reception situations. For instance, a text can be simultaneously translated and stylistically raised or lowered, and its literary form can be adapted in the target language. LLMs can also be useful for translating neologisms and other playful or creative textual elements. Despite the advantages of AI-based translation processes, some AI critics want literary translation to remain the sole preserve of humans. They speak of the impending destruction of the literary industry, a sensitive ecosystem, or of human creativity being connected to the desire to answer profound questions, which only humans are capable of, in the process of intellectual debate. Taking account of these conflicting positions, this contribution suggests that artificial intelligence can only transform literary translation in a sustainable way if humans are placed at the center of translation-relevant technological advancements.

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Publication Details

Journal
Lebende Sprachen
Published
2025-04-01
DOI
https://doi.org/10.1515/les-2025-0019
Citations
1
Primary Topic
Linguistic research and analysis
Type
article
Field-Weighted Citation Impact
10.42
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article

Literarisches Übersetzen im KI-Zeitalter: Überlegungen zu einer nachhaltigen Markttransformation

Katharina Walter
1 citations
Lebende Sprachen
Linguistic research and analysis
10.42
article

Literarisches Übersetzen im KI-Zeitalter: Überlegungen zu einer nachhaltigen Markttransformation

Katharina Walter
article en
1 citations

Abstract

Abstract Although it is less technologized than other language services, (partial) automation has also been witnessed in literary translation. Since 2017, neural machine translation (NMT) systems such as DeepL and, subsequently, large language models (LLMs) such as ChatGPT have been drastically changing, if not revolutionizing, the language industry. LLMs have larger context windows than NMT systems and allow for translations to be adapted to various reception situations. For instance, a text can be simultaneously translated and stylistically raised or lowered, and its literary form can be adapted in the target language. LLMs can also be useful for translating neologisms and other playful or creative textual elements. Despite the advantages of AI-based translation processes, some AI critics want literary translation to remain the sole preserve of humans. They speak of the impending destruction of the literary industry, a sensitive ecosystem, or of human creativity being connected to the desire to answer profound questions, which only humans are capable of, in the process of intellectual debate. Taking account of these conflicting positions, this contribution suggests that artificial intelligence can only transform literary translation in a sustainable way if humans are placed at the center of translation-relevant technological advancements.

Lebende SprachenVol. 70(1)
Universität Innsbruck (AT)
Openalex Percentile: Top 4%
Linguistic research and analysis
10.42
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Literarisches Übersetzen im KI-Zeitalter: Überlegungen zu einer nachhaltigen Markttransformation — Katharina Walter · Lebende Sprachen (2025) | TGRS Research Map | TGRS