Central Asian newsrooms put AI on a short leash

Tue, 13 Oct 2026 15:05:24 +0000

Editors at an OSCE conference in Bishkek said AI is speeding up translation, transcription and monitoring, but warned that human judgement remains essential as errors and language gaps threaten trust.

At a conference in Bishkek this month, editors and technology specialists from across Central Asia made a cautiously pragmatic case for artificial intelligence in the newsroom: useful for repetitive work, dangerous when treated as a substitute for judgement. The discussion formed part of the OSCE Central Asia Media Conference, which took place on 9-10 October and was framed by organisers around information integrity, media ethics and trust in the digital age.

The panel brought together Azat Seyitmuhammedov of Turkmenistan’s Arzuw News, Dina Maslova of Kyrgyzstan’s Kaktus Media, the Tajik digital rights specialist Khurshed Qurbonshoev, and the Kazakh lecturer Askhat Yerkimbay. Their examples suggested that AI is already embedded in regional editorial workflows, but in narrowly defined ways: translation, transcription, monitoring and content digestion, rather than final editorial decision-making.

Seyitmuhammedov described how a small four-person team uses a language-model plugin to process a large archive and turn fresh material from selected outlets and government sites into short summaries delivered to editors through Telegram. The system is designed to speed up the first pass, not to replace editorial scrutiny. According to his account, human checks remain essential for names, figures and factual detail, especially before English-language publication. The same principle applies to Kaktus Media, where Maslova said AI is helpful for transcribing interviews and, in some cases, translating between Russian and Kyrgyz, but still requires substantial human correction.

Maslova also drew a line between convenient automation and editorial risk. She said her newsroom uses AI sparingly for voiceovers and image generation because mistakes in place names, statistics or visual framing can quickly undermine credibility. Professional video editors still handle more complex work, while experiments with chatbots for advertising and accounting were not especially successful. Even where tools such as Gemini and Claude are used to compress long reads into social media formats, every headline and caption is checked by editors before publication.

Yerkimbay argued that the apparent efficiency gains of AI can be deceptive. In his view, journalists often spend extra time validating machine output, producing what he called an efficiency trap: work that looks faster on paper but still demands human oversight. He also pointed to the unequal performance of language models across the region’s languages, warning that low-resource languages remain more vulnerable to error than English or Russian. That imbalance, he suggested, risks deepening the digital divide unless newsrooms understand the limitations of the systems they adopt.

The panel’s broader message was not anti-technology, but anti-complacency. AI, the speakers said, should be reserved for routine and mechanical tasks so reporters can spend more time on reporting, interviewing and verification. Qurbonshoev stressed that audiences will continue to value distinctive human voice and reporting with genuine local texture, even as synthetic content becomes more common. Seyitmuhammedov was the most outspoken about structural change, predicting that some desk-based roles may disappear as automation improves. Yet he, too, drew a clear distinction between replaceable production work and original coverage in the field, which he said will still depend on reporters and camera crews. The consensus in Bishkek was that no newsroom can afford a simple yes-or-no policy on AI; each outlet must decide what can be automated, what must be checked and who remains answerable for the final product.

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Source: Noah Wire Services

AI is removing the training wheels from the first rung of the career ladder

Tue, 13 Oct 2026 08:08:11 +0000

As AI takes over routine tasks, employers are hiring fewer beginners or expecting them to contribute at a higher level , raising concerns about how the next generation will gain the experience to know when technology is wrong.

Artificial intelligence is quietly redrawing the first rungs of the career ladder, especially in sectors that once relied on large cohorts of graduates to handle repetitive tasks. At Catalyst, a London advertising agency, founder Tobias Green says one junior employee can now do the work that previously required several people, because AI now handles research, first-draft copy and data gathering while humans step in later to refine the output. What was once an apprenticeship in basic execution is increasingly becoming an exercise in supervision, prompting a wider debate about how new entrants are meant to learn if the easiest work disappears first.

The shift is not confined to advertising. Open University’s 2026 Business Barometer, which surveyed 1,500 business leaders in the UK, found that 51% said AI was changing how they hire, while 19% reported cutting entry-level recruitment, with 42% of those pointing to AI adoption as the reason. Gartner reported in July that 22% of chief human resources officers said automation had reduced entry-level hiring in their organisations, reinforcing the view that routine tasks are being stripped out of some junior roles before graduates ever reach them.

Yet the picture is not simply one of shrinkage. In a separate survey of 500 UK and Irish mid-market leaders by technology consultancy Klarus, 45% said AI was helping junior staff work faster and better, while almost a quarter said it was creating new roles and opportunities. IBM has also argued that entry-level work is being redefined rather than erased, with an emphasis on analysis, problem-solving and responsible AI use, alongside greater willingness to hire for learning agility and potential rather than a fixed job description. That suggests some employers are using AI less as a replacement for new hires than as a way to raise the baseline expectation for what juniors can contribute from day one.

The biggest change may be in software and other technical roles, where junior staff are increasingly expected to oversee systems rather than build everything from scratch. Sheila Flavell of FDM Group told CNBC that tools such as Claude Code and Codex are pushing developers towards managing both AI agents and colleagues, a shift that may make collaboration and oversight more valuable than narrow technical repetition. Similar thinking is appearing in recruitment more broadly: some employers are moving away from hiring graduates into rigid slots and instead look for transferable capabilities, such as critical thinking and adaptability, then decide where those people fit.

That strategy, however, carries a risk. Cheney Hamilton of Bloor argues that the menial tasks now being removed were never merely busywork; they were the means by which younger workers built judgement, learned to spot errors and absorbed the unwritten rules of corporate life. AI may allow a junior employee to produce more polished work, but it does not automatically teach the experience needed to know when that work is wrong. For employers, the challenge is no longer just how to use AI efficiently, but how to preserve enough exposure, repetition and responsibility for the next generation to become capable managers of the technology rather than passive users of it.

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Source: Noah Wire Services

Tomorrow's Publisher 2 People & Skills

Central Asian newsrooms put AI on a short leash

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AI is removing the training wheels from the first rung of the career ladder

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