When Abel Kills Cain: What Machine Translation Cannot Capture
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Abstract
The article aims at identifying what, from a structural point of view, AI based automatic translators cannot fully capture. It focuses on the machine's mistakes, in order to try to explain its causes. The biblical story of Caïn and Abel has been chosen because of its rich interpretive and critical tradition, but also because of its semantic difficulty. The investigation begins with the observation, for the translation of this text, of the language pairs and interfaces offered by the best known machine translation services (Google Translate, DeepL). A typology of the most frequent translation errors is then established. Finally, contemporary translations are compared, in order to underline the unique contribution of each. In conclusion, the article suggests a revision of translation theory and, corArtificial Intelligence, Translation, Limitations, Interpretation, Comparison, Unicityelatively, a reformulation of its technology concerning cultural texts.
