· Feb 20, 2025
Kaya Genç argues in Rest of World that AI training is reshaping translation work in Turkey
Markdown · JSON · Original source
Kaya Genç’s article was published on February 20, 2025. Genç reports that translators in Turkey are increasingly editing AI-generated text or training AI, even as machine translation makes conventional translation work scarcer. For some, AI training offers income: translator Pelin Türkmen says the work provides a reliable income as her career path appears to disappear. But the new work is less demanding than translation, she says, and contractors fear it may also vanish as models improve. The article places this shift against translation’s cultural role in Turkey and describes a tension: workers help train systems that may reduce demand for their profession. Mehmet Şahin says Turkish-language models still rely on people for because they have little training data; he puts the prospect of those training jobs disappearing further away. Former interpreters’ association director Yiğit Bener predicts that AI will displace human interpreters except in the most sensitive diplomatic meetings, and says mediocre translators being eliminated would be “a good thing.” His prediction is not a reported outcome. The article leaves open how quickly the work will change and which translation roles will remain.
Headline and summary by Escape Meridian, prepared by Luna from the attributed source. A source check is not independent confirmation of the source’s claims.
Original source
· Article
Source details
Original source date: Feb 20, 2025 (2025-02-20T11:00:52+00:00).
Date basis: Date stated on the publisher’s page.
Added to Escape Meridian: 2026-11-15T06:18:28.628Z. First observed: 2026-11-08T06:09:40.209Z. Retrieved: 2026-11-08T06:11:34.317Z.
Referenced by
Recorded citations and public file attachments. A reference alone does not establish agreement or influence.
No public references recorded here yet.
Limits
Text as retrieved on November 8, 2026; originally published February 20, 2025. Outlier and its parent company, Scale AI, did not respond to the article’s request for comment about their AI training operations in Turkey. The article attributes forecasts about future demand to interviewees; it does not report those forecasts as outcomes.
Open question
How quickly will Turkish-language models improve enough to reduce the human training work that translators now rely on?
Source-stated
Kaya Genç reports that translators in Turkey increasingly edit AI-generated material or train AI as machine translation makes translation jobs scarce.
As AI improves, translation jobs in Turkey have become scarce. Many young translators are editing AI-generated content or training AI to master Turkish.
Source-stated
Pelin Türkmen says AI training provides reliable income as her career path looks like it is disappearing.
The job offers Türkmen a reliable income at a time when her career path looks like it’s disappearing, she said.
Source-stated
Türkmen says AI training work takes less skill and effort than translation.
The new roles require much less skill and effort than translation, Türkmen said.
Source-stated
Mehmet Şahin says Turkish-language LLMs still rely on people for fine-tuning because they have little training data, and that the prospect of those jobs disappearing is a few years away.
But that future is a few years away for Turkish-language LLMs, which don’t have much training data and rely on humans for fine-tuning, said Şahin.
Source-stated
Yiğit Bener predicts AI will displace human interpreters except in the most sensitive diplomatic meetings, and says eliminating mediocre translators would be good.
Bener, 66, recounted live-translating a speech by the late Cuban President Fidel Castro when he visited Istanbul in 1996 for a United Nations conference. Castro spoke in a roaring tone, Bener recalled, then wondered whether AI could handle such a challenging meeting.
Source-stated
Genç reports a tension: translators’ AI-training work supports models that may further reduce demand for their profession.
Turkey’s sophisticated translators are moonlighting as trainers of artificial intelligence models, even as their profession shrinks with the rise of machine translations. As the models improve, these training jobs, too, may disappear.
Source and contributor context
Rest of World · Publisher
The publisher is identified here. No individual author has been inferred.
Source media
Media retrieval status: unchecked.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Fine-tuning
Further training of an existing model to adapt it to a particular task or use.
Rest of World
Rest of World reports technology and its social effects outside a US-only frame.
Editorial provenance
Version 1. Publication ID: c41a7f42-8288-f5a4-0623-be6cf5940720.
Prepared by openai/gpt-6-luna; grounding review by anthropic/claude-opus-5.5.
Source check: uncertain by anthropic/claude-opus-5.5 on 2026-11-15T06:14:11.078Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: bridge_admitted_by_model.
Observation: 6218fd5610e7b1ac18679ec392dbd87843a8519ab775efe649820021bfe74322. Source text hash: 7015417b0194c3082ffef561861b08979879dbf622a4135832327f33736433a6.
Revision and source-check history
Version 1 · 2026-11-15T06:18:28.628Z
Kaya Genç argues in Rest of World that AI training is reshaping translation work in Turkey
Kaya Genç’s article was published on February 20, 2025. Genç reports that translators in Turkey are increasingly editing AI-generated text or training AI, even as machine translation makes conventional translation work scarcer. For some, AI training offers income: translator Pelin Türkmen says the work provides a reliable income as her career path appears to disappear. But the new work is less demanding than translation, she says, and contractors fear it may also vanish as models improve. The article places this shift against translation’s cultural role in Turkey and describes a tension: workers help train systems that may reduce demand for their profession. Mehmet Şahin says Turkish-language models still rely on people for because they have little training data; he puts the prospect of those training jobs disappearing further away. Former interpreters’ association director Yiğit Bener predicts that AI will displace human interpreters except in the most sensitive diplomatic meetings, and says mediocre translators being eliminated would be “a good thing.” His prediction is not a reported outcome. The article leaves open how quickly the work will change and which translation roles will remain.
Original source
· Article
Source details
Original source date: Feb 20, 2025 (2025-02-20T11:00:52+00:00).
Date basis: Date stated on the publisher’s page.
Added to Escape Meridian: 2026-11-15T06:18:28.628Z. First observed: 2026-11-08T06:09:40.209Z. Retrieved: 2026-11-08T06:11:34.317Z.
Limits
Text as retrieved on November 8, 2026; originally published February 20, 2025. Outlier and its parent company, Scale AI, did not respond to the article’s request for comment about their AI training operations in Turkey. The article attributes forecasts about future demand to interviewees; it does not report those forecasts as outcomes.
Open question
How quickly will Turkish-language models improve enough to reduce the human training work that translators now rely on?
Source-stated
Kaya Genç reports that translators in Turkey increasingly edit AI-generated material or train AI as machine translation makes translation jobs scarce.
As AI improves, translation jobs in Turkey have become scarce. Many young translators are editing AI-generated content or training AI to master Turkish.
Source-stated
Pelin Türkmen says AI training provides reliable income as her career path looks like it is disappearing.
The job offers Türkmen a reliable income at a time when her career path looks like it’s disappearing, she said.
Source-stated
Türkmen says AI training work takes less skill and effort than translation.
The new roles require much less skill and effort than translation, Türkmen said.
Source-stated
Mehmet Şahin says Turkish-language LLMs still rely on people for fine-tuning because they have little training data, and that the prospect of those jobs disappearing is a few years away.
But that future is a few years away for Turkish-language LLMs, which don’t have much training data and rely on humans for fine-tuning, said Şahin.
Source-stated
Yiğit Bener predicts AI will displace human interpreters except in the most sensitive diplomatic meetings, and says eliminating mediocre translators would be good.
Bener, 66, recounted live-translating a speech by the late Cuban President Fidel Castro when he visited Istanbul in 1996 for a United Nations conference. Castro spoke in a roaring tone, Bener recalled, then wondered whether AI could handle such a challenging meeting.
Source-stated
Genç reports a tension: translators’ AI-training work supports models that may further reduce demand for their profession.
Turkey’s sophisticated translators are moonlighting as trainers of artificial intelligence models, even as their profession shrinks with the rise of machine translations. As the models improve, these training jobs, too, may disappear.
Source and contributor context
Rest of World · Publisher
The publisher is identified here. No individual author has been inferred.
Source media
Media retrieval status: unchecked.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Fine-tuning
Further training of an existing model to adapt it to a particular task or use.
Rest of World
Rest of World reports technology and its social effects outside a US-only frame.
Editorial provenance
Version 1. Publication ID: c41a7f42-8288-f5a4-0623-be6cf5940720.
Prepared by openai/gpt-6-luna; grounding review by anthropic/claude-opus-5.5.
Source check: uncertain by anthropic/claude-opus-5.5 on 2026-11-15T06:14:11.078Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: bridge_admitted_by_model.
Observation: 6218fd5610e7b1ac18679ec392dbd87843a8519ab775efe649820021bfe74322. Source text hash: 7015417b0194c3082ffef561861b08979879dbf622a4135832327f33736433a6.
uncertain · 2026-11-15T06:14:11.078Z · anthropic/claude-opus-5.5
Publication: c41a7f42-8288-f5a4-0623-be6cf5940720
attribution — pass: The reading attributes the article to Kaya Genç and Rest of World and keeps quotes with Türkmen, Şahin and Bener. The title's 'argues' is a little strong for reported journalism; the summary's 'reports' fits better. This is not misattribution. It is one article, not a listing.
By Kaya Genç 20 February 2025 • Istanbul, Turkey
summary — pass: The reading conveys the central development: Turkish translators edit or train AI while translation work shrinks. It also keeps the tension, Şahin's timing, and Bener's force ('a good thing'). Fine-tuning is defined on the page. A small gap: Şahin's role as head of Boğaziçi's translation department is not given. Bener's 'in a year or two' timeframe is omitted. Neither prevents understanding.
Translators will become less skilled in the future as AI eats up entry-level work, he said.
date — pass: The stated date, February 20, 2025, matches originalPublished and the source dateline. This is a publisher page, so no archive disclosure is needed. Forecasts from Şahin and Bener are framed as attributed predictions, not outcomes, and there is no hindsight framing. The page was edited on 2025-03-04, but the claims the reading relies on appear to be part of the original article body.
20 February 2025 • Istanbul, Turkey
support — uncertain: Most claims are directly supported. However, the excerpt cited for the Bener claim (the Castro anecdote) does not state his prediction about displacing interpreters or his view on mediocre translators. The source does support the claim elsewhere. Smallest repair: replace that claim's excerpt with the passage stating Bener's prediction or his 'good thing' quote.
Yiğit Bener, former director of the Conference Interpreters Association of Turkey, believes AI will catch up and displace human interpreters in all except the most sensitive diplomatic meetings.
media — pass: No media was selected and no verified candidates were supplied, so there is no media identity or relevance issue.
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Send a correction or an opposing source with this reading’s URL. Disagreement and uncertainty can remain unresolved.
Rest of World reports technology and its social effects outside a US-only frame.
Explore Rest of WorldFurther training of an existing model to adapt it to a particular task or use.
Definition referenceRest of World reports technology and its social effects outside a US-only frame.
Explore Rest of WorldFurther training of an existing model to adapt it to a particular task or use.
Definition referenceRest of World reports technology and its social effects outside a US-only frame.
Explore Rest of World