Machine Translation Post-Editing (MTPE) is often sold as the ultimate solution for faster, cheaper translations.
Clients and agencies promise that combining AI speed with human oversight will boost productivity and maintain quality.
The translation industry quietly knows the truth: MTPE is not a productivity hack. It is a pressure tool — one that increases mental load, erodes quality, and may even drive the best talent out of the profession.
Why MTPE Often Slows Translators Down
Contrary to popular belief, MTPE does not automatically speed up workflows. Poor machine output can be riddled with errors, unnatural phrasing, and inconsistencies, forcing translators to spend more time correcting mistakes than they would translating from scratch.
- Studies show that the cognitive load of evaluating and fixing machine suggestions can be significant (Koehn & Germann, 2014; MDPI, 2021).
- Complex or ambiguous texts often generate MT errors that are subtle, difficult to detect, and mentally draining.
- Translators report that post-editing requires constant vigilance, leaving little room for creative or nuanced decisions.
Far from a shortcut, MTPE can increase mental fatigue and slow down even highly experienced translators.
The Hidden Danger: “Post-Editese”
Repeated exposure to machine-generated phrasing can subtly shape a translator’s own habits. This phenomenon, known as post-editese, occurs when translators unconsciously adopt the AI’s style and structures.
- Krings (2001) warned that consistent MT errors can normalize incorrect structures, making translators less critical of repeated mistakes.
- In creative or literary translation, research shows that post-edited texts often remain unnaturally close to the MT output, losing nuance, cultural sensitivity, and stylistic flair (JoSTrans, 2024; MDPI, 2021).
The result is a contamination of human skill, reducing the translator’s capacity to produce polished, natural translations.
MTPE as a Tool to Reduce Costs
MTPE also reflects a broader economic pressure: it is a way to push down rates and commoditize human labor.
- Clients increasingly demand low-cost post-editing rather than fully human translation, treating skilled translators as mere error-correctors (The Guardian, 2024).
- Translators report that MTPE assignments are repetitive, exhausting, and poorly compensated, creating a financial and mental burden.
- The worst outcome? Some of the industry’s most skilled and promising talent may leave the profession entirely, unable to sustain themselves under these conditions.
Quality Isn’t Guaranteed
Even with careful post-editing, MTPE cannot ensure high-quality translations:
- Machine errors can persist, particularly in technical, marketing, or literary content (ACL Anthology, 2014; arXiv, 2021).
- Fully human translations still outperform post-edited MT in style, clarity, and nuance.
- Relying on MTPE for high-stakes texts risks sacrificing accuracy and creativity for the illusion of efficiency.
Protecting Translator Skills and Quality
To prevent MTPE from undermining the profession:
- Use MT selectively. Only employ MT when the raw output meets a quality threshold.
- Invest in proper training. Translators need guidance on when to accept, revise, or reject machine suggestions.
- Compensate fairly. Acknowledge the cognitive effort and decision-making inherent in post-editing.
- Preserve creative work. Critical, nuanced, or stylistically complex content should remain fully human.
Conclusion
MTPE is often sold as a silver bullet, but the reality is stark: it can slow down translators, degrade quality, and threaten the profession’s best talent. Recognizing this hidden cost is essential. If we want to preserve human creativity, expertise, and fair working conditions, the industry must treat MTPE not as a universal solution, but as a carefully controlled tool, used wisely and ethicall