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Human or machine? Do source beliefs shape cognitive bias in post-editing?
1School of Foreign Languages, Lanzhou Jiaotong University, Lanzhou, Gansu, China.
Frontiers in Psychology
|May 8, 2026
Summary
Translator perceptions of AI translation bias evaluation and post-editing behavior. Even when quality is equal, believing a text is AI-generated leads to more revisions and lower trust.
Area of Science:
- Cognitive Psychology
- Translation Studies
- Human-AI Interaction
Background:
- Artificial intelligence (AI) translation is increasingly used in professional and educational settings.
- Translator perceptions of machine vs. human translation may influence their behavior.
- Cognitive bias can affect how translators evaluate and revise texts.
Purpose of the Study:
- To investigate the role of cognitive bias in post-editing.
- To examine how beliefs about translation sources (human or AI) affect evaluation and revision.
- To understand how perceived source identity influences linguistic judgment and editing.
Main Methods:
- A between-subjects experiment with 60 Translation and Interpreting master students.
- Experimental group received mislabeled texts (human as AI, AI as human).
- Control group received accurately labeled texts.
- Participants evaluated translations on fidelity, fluency, and completeness, and performed post-editing.
Main Results:
- Perceived AI labels led to lower trust and increased post-editing intensity.
- Heightened error sensitivity and more conservative quality ratings were observed for perceived AI texts.
- Decisions were driven by perceived source identity rather than objective translation quality.
Conclusions:
- A subtle language-related cognitive bias exists, where perceived source influences judgment.
- Findings provide empirical insights into human-AI interaction in translation.
- Offers pedagogical implications for critical post-editing literacy and inclusive AI attitudes.
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