인공지능 번역과 이해의 해석학: 『바벨 이후』(1975)의 상호성과 윤리 재고
AI translation and the hermeneutics of understanding: Reconsidering reciprocity and ethics after After Babel
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This study revisits George Steiner’s After Babel(1975) to evaluate translation in the age of artificial intelligence(AI). Using Steiner’s hermeneutic motion—trust, invasion, incorporation, and reciprocity—the research examines how understanding is reshaped when translation is produced by AI systems. Paul Ricoeur’s linguistic hospitality and Antoine Berman’s ethics of alterity provide an ethical lens for assessing AI translation. Three passages from Floridi’s The Logic of Information(2019) were analyzed through a qualitative comparison of human, AI(DeepL and ChatGPT), and post-edited translations. Results show that AI can mimic the structural stages of hermeneutic motion but cannot realize reciprocity, which requires intentional and ethical engagement. Human translation maintains this reciprocity, and post-editing partially restores it. The study concludes that AI’s limitations stem from systemic constraints rather than linguistic factors. Translation in the AI era must therefore be redefined as an ethical practice of meaning restoration.
Abstract
This study revisits George Steiner’s After Babel(1975) to evaluate translation in the age of artificial intelligence(AI). Using Steiner’s hermeneutic motion—trust, invasion, incorporation, and reciprocity—the research examines how understanding is reshaped when translation is produced by AI systems. Paul Ricoeur’s linguistic hospitality and Antoine Berman’s ethics of alterity provide an ethical lens for assessing AI translation. Three passages from Floridi’s The Logic of Information(2019) were analyzed through a qualitative comparison of human, AI(DeepL and ChatGPT), and post-edited translations. Results show that AI can mimic the structural stages of hermeneutic motion but cannot realize reciprocity, which requires intentional and ethical engagement. Human translation maintains this reciprocity, and post-editing partially restores it. The study concludes that AI’s limitations stem from systemic constraints rather than linguistic factors. Translation in the AI era must therefore be redefined as an ethical practice of meaning restoration.