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Human–AI literary translation: Who takes the lead, and what do they follow?

  • The Journal of Translation Studies
  • Abbr : JTS
  • 2026, 27(3), pp.257~291
  • DOI : 10.15749/jts.2026.27.3.009
  • Publisher : The Korean Association for Translation Studies
  • Research Area : Humanities > Interpretation and Translation Studies
  • Received : August 15, 2026
  • Accepted : September 15, 2026
  • Published : September 30, 2026

Sun, Young-hwa ORD ID 1

1한국외국어대학교

Accredited

ABSTRACT

This study examines human–generative AI collaboration in literary translation education through the concept of interpretive agency. Interpretive agency refers to the relative influence of a particular participant’s perspectives, understandings, and strategies on determining and adjusting the direction of interpretation and translation during human–AI interaction. To explore how interpretive agency is formed and transformed, this study analyzed an English–Korean poetry translation activity involving 49 students enrolled in a literary translation course at a university-level translation program. Before engaging in human–AI collaborative translation, learners were asked to articulate their interpretive intent toward the source text, and their subsequent interactions with AI were analyzed. The findings identified three recurring patterns in the exercise of interpretive agency: critical regulation, exploratory adjustment, and conformist acceptance. These patterns did not represent stable learner traits; rather, they shifted according to learners’ perceptions of AI’s role, attention to the source text, the specificity of their interpretive intent, and engagement with AI-generated interpretive frames. This study reconceptualizes translation competence in the GenAI era not merely as the ability to produce high-quality outputs, but as the capacity to exercise interpretive judgment and direct translation decisions in interaction with AI. It highlights the implications for literary translation education, emphasizing the importance of strengthening learners’ source-based interpretive judgment, explicit formulation of interpretive intent, critical and reflective engagement with AI, and the ability to exercise interpretive agency flexibly in human–AI collaborative translation.

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