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Article In: Humans, Machines, and Embedded Translation
Edited by Sandra L. Halverson and Jean Nitzke
[Translation, Cognition & Behavior 8:2] 2025

Prompting as thinking

Understanding the decisions made by translators in AI-assisted translation

ORCiD logo with link | The Chinese University of Hong Kong
This content is being prepared for publication; it may be subject to changes.
Abstract
This paper assesses AI-assisted translation by viewing prompting as an externalisation of cognitive processes during translator-AI interaction. More than mere technical inputs, prompts serve as authentic written traces behind the identification of problems by translators and their resultant solutions. This approach differs from traditional think-aloud methods by offering explicit access to decision-making. Using screen recordings and think-aloud protocols, the study observes seven trainee translators working on English-to-Chinese translation tasks using ChatGPT. The paper analyses three critical decision points: (1) when outputs are accepted, (2) factors triggering prompt engineering, and (3) criteria leading translators to stop prompting. Findings provide evidence-based insights for developing translator AI competence and inform a pedagogical framework that highlights the visibility of prompting processes, thereby enhancing translator education in the AI era. [125 words]
Article outline
  • 1.Introduction
  • 2.Literature review
    • 2.1Prompt engineering for translation-related tasks
    • 2.2Prompting as information seeking
    • 2.3Understanding prompting as a cognitive process
  • 3.Research design
    • 3.1Data
    • 3.2Analytical framework
  • 4.Results and discussion
    • 4.1Conditions for desired outputs
    • 4.2Triggers for prompt engineering
    • 4.3Decision to stop prompting
      • 4.3.1Efficiency optimisation stopping
      • 4.3.2Goal achievement stopping
      • 4.3.3Capability limitation stopping
    • 4.4Pedagogical implications
    • 4.5Limitations
  • 5.Conclusion
  • Author queries
  • References
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