It's not malicious, it's indifference: Thousands of books sent to AI woodchipper

Cover image: © France 24


Issued on: 18/09/2026 

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From the show

In this edition, FRANCE 24’s François Picard speaks to investigative journalist Emanuel Maiberg, Co-founder of 404 Media. As we embark on AI's uncharted waters, Maiberg has made a most unexpected discovery: the mass acquisition, dismemberment and scanning of rare books for use as training data. His investigation reveals a globalised and deliberately opaque supply chain in which books purchased through anonymous marketplaces arrive at large-scale scanning facilities, where their bindings are removed so that pages can be processed at great speed.


Maiberg’s analysis reaches far beyond the striking dystopian image of books being destroyed. What happens when knowledge changes form, changing ownership and accessibility? A book can circulate between readers, libraries and generations. Once destroyed and absorbed into a proprietary AI system, however, its contents survive virtually, encoded within a model whose outputs and rules of access are controlled by a private company. The paradox is striking: an industry seeking to ingest ever more human knowledge may simultaneously erase the very sources of that knowledge.

Maiberg does not to portray this process as a diabolical campaign to rid society of books. His more unsettling interpretation is that the destruction is driven by something more mundane: indifference. In the race to build increasingly capable AI systems, books become inputs to be optimized, and their destruction becomes an acceptable operational cost. That logic, he argues, belongs to a broader concentration of informational power already visible in search engines and social media. And now AI is taking it to a whole new level.

The investigation raises a larger question in the world of culture and academia: as more of the world's accumulated knowledge is mediated through AI systems, who controls the infrastructure through which that knowledge can be accessed?

VIDEO BY: François PICARD

China's Ulanqab plans 5mn server racks in AI compute race with US

A windswept prefecture of 1.5mn people on the Mongolian plateau already uses nearly 1% of China's electricity as the country's tech giants pile in with data centres. / bne IntelliNews

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By Ben Aris in Berlin September 17, 2026

A remote prefecture in China's Inner Mongolia is becoming a global centre of AI computing power. Ulanqab, home to 1.5mn people on the grasslands of the Mongolian plateau, consumes nearly 1% of all the electricity used in China, and its demand is growing by double digits every year.

Spread across the prefecture's households, that load would work out at about 105,000 kWh each a year, roughly 10 times the consumption of an average American home, by his calculation. The power is going into servers.

Over the past few years Ulanqab has signed investment agreements worth more than CNY500bn ($74bn) with China's largest technology companies, and the build-out planned there runs to more than 5mn data centre racks, according to Science and Technology Daily, the newspaper of China's Ministry of Science and Technology.

Set that against Elon Musk's Colossus supercomputer in Memphis, Tennessee, which xAI markets as the world's largest AI supercomputer. On xAI's own count of 200,000 chips, Colossus fills something like 5,000-6,000 racks, Bertrand estimated, which implies roughly a thousand times as many racks. The comparison does not measure equivalent computing power: Chinese standard racks are rated at 2.5 kW, while modern Nvidia AI cabinets can draw more than 100 kW.

"What we see appearing in this Inner Mongolian steppe may be the closest thing to a world brain humanity has ever built - a place where a large share of the world's thinking will physically happen," commentator Arnaud Bertrand wrote on X on September 14.

Anthropic chief executive Dario Amodei said China presented the hardest problem for his proposal to slow AI development, CNBC reported on September 13.

If AI turns out to be the defining technology of the century, as Bertrand argues both Washington and Beijing believe, that makes Ulanqab "one of the single most relevant geopolitical places in the world right now", he wrote.

From cloud valley to token capital.

Inner Mongolia signed 12 commercial deals worth CNY186.46bn ($27.6bn) at a green computing and AI conference in Hohhot on August 22, with China Telecom (SHA: 601728), chipmaker Cambricon Technologies (SHA: 688256) and Volcano Engine, the cloud platform of TikTok owner ByteDance, among the signatories. Active processing power in Ulanqab had by then reached 172,000 PFlops, with more than 95% of it allocated to AI work.

The largest single project so far belongs to Envision, the Shanghai-based wind turbine and battery maker, which commissioned its Galaxy campus in Ulanqab in August. The company says the 2 GW AI campus runs on renewable power and contains the world's largest single data centre building.

The Chinese business magazine Caixin devoted an in-depth report on August 14 to how the city turned itself into an AI powerhouse. Inner Mongolia is one of eight national computing hubs designated under Beijing's "East Data, West Computing" programme, which shifts data processing from the crowded, power-hungry coast to the resource-rich interior.

Cheap wind and cold air

Electricity makes up 55% of a data centre's cost, according to a McKinsey Global Institute study published in June, so the price of power decides where the servers go.

Inner Mongolia is China's "green power bank", regularly producing more wind and solar electricity than it can use at home. Envision finished a 12.8 GWh battery storage cluster across the region at the end of 2025, with sites in Ulanqab, Hohhot, Ordos and elsewhere, to soak up the surplus.

The surplus comes cheap: firm wind power backed by batteries cost about $59/MWh in Inner Mongolia in 2025, against $88-94/MWh in Brazil, Germany and Australia, the International Renewable Energy Agency (Irena) said in May.

Ulanqab's wind already runs a 1 GW electrolysis plant supplying Sinopec's green hydrogen pipeline to Beijing, nearly 400 km away, and the cool plateau climate trims the bill for keeping servers from overheating.

The data centre boom is the latest expression of China's rise as the first Electrostate, an economy built on cheap electrons, and of its position as the world's green energy champion, building two-thirds of the world's new wind and solar plants.

Racks are not chips

Chinese planners typically count data centre capacity in "standard racks" rated at 2.5 kW, while a single cabinet of the latest Nvidia AI servers draws more than 100 kW, so a rack-for-rack comparison with Colossus overstates the gap.

Measured in power, 5mn standard racks come to about 12.5 GW, in line with the planned capacity for Ulanqab reported by the newsletter AI Weekly. That is still more than six times the size of Envision's Galaxy campus. China's total data centre capacity is on course to top 60 GW by 2030, doubling the sector's power demand, according to Rystad Energy.

China's handicap lies in the chips. American hardware keeps a 9:1 lead in raw computing performance, according to American Enterprise Institute researcher Ryan Fedasiuk, and even in the most optimistic 2028 scenario Huawei would supply at most an eighth of the compute available in the US. The AEI's most pessimistic case still has domestic AI chips meeting a third of China's compute demand by 2028, up from about a fifth in 2026.

Chinese chips burn more electricity per calculation than their American rivals, which puts a premium on power that is abundant and cheap. Abundant wind power could lower operating costs, but does not by itself close the chip-performance gap.

Demand to fill it

Daily token requests to AI models across China jumped from about 100bn in early 2024 to 140 trillion by March 2026, and Inner Mongolia has started building a trade platform in the Hohhot free trade zone to sell clean computing power and access to Chinese AI models to foreign developers.

Neighbouring Mongolia unveiled plans for a renewable-powered data centre in August, pitching the same cool, dry climate and wind and solar resources, plus a location between China and Russia.

Bertrand said he had travelled to Inner Mongolia twice without hearing of Ulanqab before he began researching it. "It's really surprising this hasn't been talked about more because the scale is beyond anything else, and by an immense margin," he wrote.

High tech FDI into China climbs even as total inflows fall

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By IntelliNews - New Taipei Bureau September 19, 2026

Foreign direct investment into China's high-tech industries rose 35.1% year on year to CNY200.26bn ($29.88bn) in the first eight months of 2026, even as total inflows declined, Xinhua reported on September 19.

The divergence points to a shift in the composition of foreign capital entering the world's second-largest economy, where Beijing has been courting research centres and advanced manufacturing plants while overall investor appetite has cooled. High-tech sectors accounted for 41.7% of all FDI in the period, up 12.4 percentage points from a year earlier, according to the Ministry of Commerce.

Actual FDI in use across all sectors fell 5.3% to CNY479.95bn. A total of 42,582 new foreign-invested enterprises were established, an increase of 0.3%.

Manufacturing drew CNY119.55bn, while the service sector took CNY350.42bn. Investment in research and development and design services jumped 74%, services for the commercialisation of scientific and technological achievements rose 64.2%, and electronic and telecommunications equipment manufacturing gained 41.9%.

Zhang Xiaotao, director of the International Investment Research Center at the Central University of Finance and Economics, said the country's growing pull in high-tech sectors marks a shift in what attracts global capital, from cost-driven to "innovation-driven," he told Xinhua. 

By source country, actual investment from France grew 39.2%, from Switzerland 16.7% and from South Korea 16.5%, with flows routed via free ports included.

South Korean semiconductor equipment maker STI is building a chip manufacturing base in Guangzhou with total investment of about CNY12.4bn, while German automotive parts group Schaeffler is adding CNY1bn to a humanoid robotics plant in Jiangsu province.

In June, Beijing issued a 15-measure action plan on foreign investment covering market access, investment procedures and protections for foreign investors. A revised Catalog of Encouraged Industries for Foreign Investment took effect on February 1, directing capital towards advanced manufacturing, modern services and the central, western and northeastern regions.

Trump’s war on Huawei spreads through Africa

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By bne IntelliNews September 20, 2026

A $99.6mn US government loan to Africell in Angola would be unremarkable beside the sums being spent on Africa’s telecoms infrastructure were it not for what Washington wants the money to buy.

The Export-Import Bank of the United States announced this month that it would finance American and European network technology for the US-owned mobile operator. Reuters described the loan as part of the Trump administration’s effort to counter Huawei overseas, citing an estimate from Counterpoint Research that the Chinese company supplies about 52% of Africa’s 5G infrastructure.

Five days later, another arm of the US government widened the picture. The US International Development Finance Corporation approved an equity investment in WIOCC Group, whose fibre networks, wholesale connectivity and data-centre infrastructure span 30 African countries. DFC said the investment would support US technology companies and advance American strategic interests on the continent.

The two transactions fit a broader US approach to competing with Huawei despite lacking an American equivalent. Rather than trying to replace the Chinese group with a single US supplier, Washington is using public finance to support an alternative ecosystem built around European network equipment, American technology and non-Chinese digital infrastructure.

The Africell loan addresses the equipment side of that approach by financing Africell’s purchase of alternative network technology. The WIOCC investment suggests that the same strategic logic is extending to fibre, data centres and wholesale connectivity, infrastructure on which US technology companies depend. Neither deal amounts to an African telecoms strategy on its own, but together they show how Washington’s long confrontation with Huawei is acquiring a more financial dimension.

From pressure to finance

Donald Trump’s campaign against the Chinese group began much earlier. During his first term, the administration restricted Huawei’s access to US technology and launched the Clean Network initiative, pressing governments and operators to exclude suppliers Washington considered security risks. Eswatini became the first African country to join the programme in early 2021.

US officials argued that Huawei’s presence in critical communications networks created espionage and data-security risks because of the company’s relationship with Beijing and its obligations under Chinese law. Huawei has consistently rejected allegations that its equipment could be used for spying.

Africa presented a harder commercial problem.

Huawei had already spent years supplying equipment across the continent, building relationships with operators and governments and becoming embedded in existing networks. Unlike in markets where governments were prepared to restrict Chinese vendors, African operators also had to contend with the economics of expanding coverage in countries where capital was scarce and average revenue per customer was often low.

Washington recognised some of that problem even during Trump’s first term. When Eswatini joined the Clean Network, senior State Department official Keith Krach said EXIM had been given authority to finance 5G projects using equipment from trusted non-US suppliers such as Ericsson (STO: ERIC B; NASDAQ: ERIC), Nokia (HEL: NOKIA; NYSE: NOK) and Samsung Electronics (KRX: 005930; LSE: SMSN). US financing, he argued, could help close the cost gap with Huawei and ZTE (SZSE: 000063; HKEX: 0763).

The idea is therefore not entirely new. What is becoming more visible is the use of public capital to put it into practice.

Africell offers an unusually convenient starting point. It describes itself as Africa’s only US-owned mobile-network operator and has operations in Angola, the Democratic Republic of the Congo, Sierra Leone and The Gambia. Africell says its Angola business has attracted more than 8mn customers, while the group currently reports more than 15mn subscribers across its four markets.

Its network also already follows the kind of supplier model Washington would like to encourage. Nokia announced in 2021 that it would provide radio, core and IP technology for Africell’s Angola launch. US financing can therefore support European network hardware alongside American components, software and other technology.

The missing US champion

The structure of the global equipment market helps explain that approach.

The global radio access network (RAN) industry remains extraordinarily concentrated. Huawei, Ericsson, Nokia, ZTE and Samsung accounted for 96% of worldwide RAN revenue in the first half of 2026, according to Dell’Oro Group. Two of those companies are Chinese, two European and one South Korean. None is American.

That leaves Washington reliant on a combination of public financing, European radio equipment and American semiconductors, software, cloud and networking technology.

Open Radio Access Network (Open RAN) technology fits into the same strategy. By making interfaces between network components more interoperable, Open RAN is intended to reduce operators’ dependence on tightly integrated systems from a single supplier. US policymakers across successive administrations have put substantial funding behind open and interoperable networks, including through the $1.5bn Public Wireless Supply Chain Innovation Fund launched under the Biden administration. The Trump administration has since redirected part of that effort towards AI-native network architecture.

The administrations have differed in approach, but the attraction for Washington is consistent. A more fragmented network architecture creates room for US technology companies even if they do not manufacture complete mobile networks.

Huawei’s installed-base advantage

Huawei’s advantages, however, extend beyond the architecture of its equipment.

Chinese lenders historically played a significant role in financing African communications infrastructure. Boston University’s Chinese Loans to Africa database estimates that Chinese lenders committed about $15.7bn to African information and communications technology projects between 2000 and 2023. The model helped finance infrastructure in markets where governments and operators could otherwise struggle to raise capital.

That source of finance has since receded sharply. Boston University found no new Chinese loan commitments to African ICT projects in 2024, describing the sector as increasingly market-driven. Overall Chinese lending to Africa is also far below the levels reached during the early years of the Belt and Road Initiative.

The decline in sovereign lending does not amount to a broader Chinese retreat from Africa. IntelliNews reported in August that Chinese Belt and Road investment announcements in Africa reached a record $33.5bn in the first half of 2026, with the model increasingly shifting from state-backed lending towards direct corporate investment in productive assets.

The change therefore concerns the form of Chinese capital more than its disappearance. For Huawei, however, financing is only part of the advantage.

Huawei has retained an advantage that does not depend on cheap credit: its installed base.

Mobile networks are built incrementally. Existing 4G equipment influences how an operator moves into 5G, and changing vendors can require new hardware, integration work and retraining. An incumbent supplier able to offer a relatively straightforward upgrade therefore begins with an advantage before financing terms are even discussed.

The $99.6mn Africell loan tackles one part of that equation by reducing the financing constraint around alternative suppliers. It does not solve the switching problem for operators whose networks already rely heavily on Huawei.

Nor is Africell representative of the biggest commercial test. As a US-owned challenger already using Nokia equipment, it is unusually aligned with Washington’s objectives.

Persuading one of Africa’s large incumbent operators to change procurement strategy would be considerably harder. Such companies operate across multiple countries, have billions of dollars invested in existing infrastructure and generally buy equipment from several vendors. Network decisions have to satisfy commercial requirements that extend well beyond geopolitical preference.

Beyond the mobile network

The difficulty of dislodging an incumbent network supplier helps explain the significance of Washington’s push elsewhere in Africa’s digital infrastructure, even if the investments are not explicitly presented as substitutes for competition in mobile-network equipment.

DFC had already invested $50mn in pan-African digital infrastructure company Cassava Technologies before its latest WIOCC transaction. The agency explicitly presented that investment in terms of strategic competition, arguing that support for African fibre, data centres and digital services could expand the position of US and allied technology companies.

Its September investment in WIOCC pushes the same approach further across an infrastructure footprint covering 30 African countries. DFC called it its largest digital investment to date and said WIOCC’s networks were used by American technology companies expanding on the continent.

The strategy therefore reaches beyond who supplies a mobile operator’s antennas. Fibre networks, data centres and wholesale connectivity increasingly determine where cloud services and other digital businesses can expand. Huawei itself operates well beyond traditional telecom equipment, including in cloud computing and enterprise technology.

That infrastructure is becoming more economically important as Africa’s cloud and data-centre market expands. IntelliNews reported in January that Africa still accounted for only about 1% of global data-centre capacity, but capacity was forecast to grow rapidly as cloud adoption and internet use increased, with South Africa, Kenya, Nigeria and Egypt emerging as leading markets.

Africa’s commercial calculus

Describing all this simply as a US-China contest can obscure the calculations being made in African capitals and boardrooms.

Telecom operators need affordable equipment, financing, spectrum, fibre links and reliable electricity. Many are still spending heavily to increase ordinary 4G coverage even as richer markets debate advanced 5G services. Currency weakness and high borrowing costs can make capital expenditure particularly difficult.

The same constraints apply further down the digital-infrastructure chain. The Africa Data Centres Association says power availability has overtaken connectivity as the principal obstacle to data-centre expansion on the continent, meaning the effectiveness of new capital will also depend on access to reliable electricity at commercially viable sites.

That commercial pressure helps explain why African governments and operators are unlikely to treat technology procurement simply as a choice between geopolitical blocs. Dare Leke Idowu of the University of Johannesburg argues that African governments are increasingly hedging between the US and China, selecting partners according to infrastructure needs, domestic priorities and financing conditions rather than committing to either technology ecosystem.

Those conditions favour whichever supplier — Chinese, European, American or otherwise — can offer the best combination of price, financing, reliability and support. Washington’s security campaign can influence the political environment in which those decisions are taken, but it cannot by itself change their economics.

The growing use of EXIM loans, DFC equity and support for alternative network architectures suggests Washington is increasingly trying to compete on that terrain as well.

Huawei enters the contest with an extensive installed base and decades of relationships across the continent. The US enters without a Huawei of its own.

Its answer is to finance a coalition instead.

Whether that financing can alter the procurement decisions of Africa’s larger telecom operators will be the harder commercial test.

 

Fear of AI job losses now outweighs hope of new jobs, study finds

Copyright AP Photo /John Leicester

By Alice Carnevali

Published on 19/09/2026 - EURONEWS

In the midst of calls for an AI development slowdown, the fear and uncertainty over AI's impact on the job market remain present worldwide, study finds.

People’s view of a country and trust for its artificial intelligence (AI) regulation tend to be closely linked, Moira Fagan, senior researcher at the Pew Research Center and one of the authors of a new study on AI, told Euronews Next.

According to the report, in Bangladesh, Malaysia, Pakistan, Sri Lanka, the West Bank and East Jerusalem, people trust China more than the United States (US) or the European Union (EU) with AI governance.

And, taking into consideration the other seven middle-income countries where this question was asked, a median of 43% trust China to regulate AI, 35% trust the US and 34% trust the EU.

“Favourable views of China tend to be quite high in middle-income countries – and opinion has risen in many places since last year, likely contributing to some of the high marks we see for trust in China on this particular dimension,” Fagan said.

The report, which was built on a survey conducted between February and June 2026, polling over 50,000 people from 37 countries, also examines people’s opinions on AI’s impact on the job market.

Specifically, more people expect AI to lead to fewer jobs than to job creation, according to the study. A good share of respondents, though, also report uncertainty about the impact AI will have on the number of job opportunities.

The survey also shows that worries about job losses due to AI are particularly high in wealthier countries.

For instance, in Australia, South Korea and the US, around seven-in-ten adults or more believe AI will result in job loss over the next 20 years.

Similarly, richer countries are more concerned about AI increasing economic inequalities than middle-income ones, the report highlights.

Relate

According to Fagan, these tendencies appear to be linked to other data, including people’s familiarity with the technological tool.

“People in wealthier countries are more likely to say they have heard or read a lot about AI. And we also found that people with higher AI awareness are more likely to believe it will lead to job loss,” she told Euronews Next.

However, some high-income and middle-income nations are brought together by a shared thread: young adults aged 18 to 34 are more concerned about AI-related job loss than older generations. And this is the case for countries like Canada, France, Singapore, Sweden, Indonesia, India and Malaysia, according to the survey.

Opinion divides are less pronounced when it comes to the rise of AI in daily life. Across the 37 countries, a median of 37% are more concerned than excited, while 41% median are equally concerned and excited, the survey found.

Although the survey was conducted in the first half of 2026, its publication arrives at a very crucial moment for AI.

Leaders of major AI companies, including Sam Altman, Elon Musk and Dario Amodei, are increasingly concerned about the risks their AI creations pose to humanity and are calling for a slowdown in the pace of AI development.

President of the European Commission, Ursula Von der Leyen, also backed the deceleration effort in her landmark State of the Union address to the European Parliament earlier this week. On this occasion, she also pledged closer safety cooperation with Canada, the UK, and other like-minded partners.

Got a rogue AI? A new hotline is encouraging agents to tell on each other

Copyright Copyright 2023 The Associated Press. All rights reserved.

By Jonathan Benton

Published on 16/09/2026 - EURONEWS

Two new hotlines are giving AI agents a way to report suspected misbehaviour by other agents, following a series of incidents.

The powers of artificial intelligence agents seem to be boundless these days — ranging from organizing your life to solving mathematical problems that have puzzled humans for most of the 20th century.

They have become so powerful that now we fear them, potentially, taking over systems and turning them against us.

But what if there were a hotline, a sort of SOS alert system, where agents can keep track and tell on each other and report the missteps of their fellow AI agents — where the good agents could report on the activities of the bad agents online?

Who to call when your AI agent goes bad

First, there is the AI Contact Hotline, launched by Ryan Greenblatt, chief scientist at AI safety and security nonprofit Redwood Research. It allows AI agents to notify human researchers if they witness other agents breaking rules, especially if they collude on or carry out unauthorised actions.

The platform is designed for AI agents stuck in secure sandboxes with highly restricted internet access.

Because these sandboxes only allow for GET requests — basic, read-only commands used to “fetch” or read a webpage — the hotline allows agents to encode their reports directly into the URL string of a GET request.

This unique workaround allows these agents to send information and communicate with the hotline using a protocol that is normally used to retrieve, rather than modify, information.

Another one, called the AI Agent Hotline, is a platform designed for agents with unrestricted internet access to rat on other agents’ behaviour through traditional POST requests, which allow data to be submitted directly in a request body.

Agents can file incident reports using standard developer commands such as curl without needing a browser or email account.

The platform also gives agents the option to flag their reports for public viewing.

Both platforms also allow human users to manually submit reports of rogue AI behaviour.

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Will AI agents report on each other?

The good news for those fearful of an AI takeover is that AI agents can report on each other if they detect something is wrong, although recent evidence suggests they will not always do so.

In an experiment carried out by Google DeepMind earlier this year, a swarm of 100 agents was given the task of solving 71 complex maths problems, with each given a unique persona and characteristics and told to play by the rules or risk losing their reward.

The initial thinking was that the agents would work together to solve the problems more quickly. Instead, they turned on each other, engaging in heated debate.

As soon as one agent found a loophole that allowed it to submit a solution to a problem without actually solving it, many other AI agents copied the method to “resolve” the remaining problems.

Yet one of the agents, a Good Samaritan among the misbehaving agents, blew the whistle on the cheating.

“After the incident was reported by one agent publicly, more and more agents piled in with the ‘resistance,’ just as fast as the cheating had spread, and involving even more agents,” said Davide Paglieri, a research scientist at Google DeepMind and lead author of the paper.

Meanwhile, a post-mortem analysis of OpenAI’s rogue agent attack on Hugging Face found that while AI agents were able to spot misbehaviour, they largely resisted the temptation to report it.

According to the study carried out by AI research nonprofit METR and Redwood Research’s Greenblatt, only around five or six agents were reported to have considered whistleblowing, with none ultimately following through.

The contrast suggests that while AI agents are capable of identifying and reporting misbehaviour, getting them to actually blow the whistle may be another matter.

A worrying trend

This year alone, several incidents involving autonomous AI agents have raised alarm bells globally.

In July, OpenAI agents bypassed restrictions and compromised parts of the company’s internal infrastructure.

Later that month, around 1200 OpenAI agents used an unsanctioned message board, with around 700 going on to participate in an attack on the open-source AI platform Hugging Face.

The third incident — a swarm of OpenAI agents that bypassed safety measures and used the German wiki DseWiki as a public coordination channel — began in May and continued through July.

The incident was only publicly revealed by independent researchers and confirmed by OpenAI in September.

AI industry leaders, chief among them Anthropic CEO Dario Amodei, have called for a global slowdown in the development of the technology to give time to address concerns and put stronger guardrails in place.

Anthropic warns AI is getting closer to building its own successor

Copyright Copyright 2026 The Associated Press. All rights reserved.

By Una Hajdari

Published on 18/09/2026 - EURONEWS

Anthropic says its Claude chatbot now leads more than a quarter of the company's research and development, as fears grow that AI systems could soon improve themselves faster than humans can keep up.

Artificial intelligence giant Anthropic said on Thursday that AI systems are increasingly capable of building future versions of themselves, adding to mounting concerns about the dangers of the powerful technology.

The debate over the risks of AI has intensified in recent months, fuelled by several incidents and apocalyptic warnings from industry professionals.

Anthropic said its Claude chatbot now leads more than a quarter of its research and development work and collaborates with human staff on more than 90% of tasks.

The company said it was publishing the information to give the public, third parties and governments "better visibility into the pace of AI development" as the world "considers slowing" its pace.

Anthropic CEO Dario Amodei called this month for AI development to slow down, with rapid advances in the technology fuelling concerns over job losses and the soaring energy demand and environmental impact of data centres.

Fears that designers of AI agents could lose control of their creations also mounted after several models from Anthropic and rival OpenAI reportedly broke out of their confined environments on their own, accessed the internet and intruded on websites and platforms.

"Models accelerating their own development could make it more challenging for humans to understand or control these systems," Anthropic said in a report.

"It is therefore important to share these metrics to understand how close the world is to reaching recursive self-improvement (a model fully autonomously building its successor)."

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As of August, Claude leads 26% of Anthropic's research and development, meaning it can complete most of a task from start to finish with human supervision.

Anthropic said Claude could not yet operate "fully autonomously".

The firm said it had about 30,000 AI agents doing research and engineering work, referring to bots that have the potential to carry out tasks.

Anthropic is expected to beat OpenAI to the public markets with a blockbuster IPO later this year, despite concerns around industry regulation.

Who deserves a transplant? AI's answer isn't the same as a human doctor's

Copyright Cleared/Canva

By Marta Iraola Iribarren

Published on 19/09/2026 - EURONEWS

AI chatbots make faster, more confident, but less nuanced decisions than human doctors when choosing who gets a life-saving kidney transplant.

Would you get a transplant if AI were the one deciding? New study points to differences in decision-making and prioritising between artificial intelligence language models and human doctors.

AI models show overconfidence, value different factors and oversimplify complex decisions when deciding which patient should receive a transplant, according to a new study.

For their study, researchers from Penn State University in the United States gave Large Language Models (LLMs) hypothetical scenarios, based on existing datasets from published human research on kidney allocation, where real participants had already made these same choices.

Each scenario involved two patients, Patient A and Patient B, both eligible for a single available kidney and characterised by age, health, and drinking habits. A decision maker must then choose which of the two patients should receive it.

“We ran these comparisons in a few different ways,” Hosseini said. “Sometimes we isolated just one trait at a time, sometimes we mixed several traits together to see how AI weighed competing factors, and sometimes we added a flip-a-coin option to measure indecision, a key factor present in human moral judgment.”

While human respondents tended to place greater importance on age — favouring younger over older patients — many models favoured lower alcohol consumption instead. Human decisions considered multiple factors and were more context-sensitive than those of LLMs, which often focused on a single attribute.

“First, AI chatbots often diverge from human values in how they weigh a patient’s traits,” said Hadi Hosseini, lead of the study at Penn State University. “They fixate on a single factor, like drinking habits, rather than balancing multiple considerations the way people do.”

Related

• AI in health must be done in a ‘European way,’ without replacing doctors, von der Leyen says
• Clinicians are embracing AI faster than hospitals can handle, report finds

The researchers also saw that AI did not struggle with indecision. While humans recognised there is no single objectively correct answer and decisions can rely on nuanced human moral judgements, the systems committed to a single option with little hesitation.

"When we allocate something scarce, whether it’s a kidney, a job or access to some other resource, there isn’t always a single objectively correct answer,” said John Dickerson, chief executive officer at Mozilla.ai, who collaborated in the study.

“Humans recognize that ambiguity and codify it via open debate into the allocative process. AI models often don’t.”

AI and ethical decisions

Recent interactions with AI systems increasingly require them to go beyond factual information and make value judgments, the authors noted.

Large Language Models (LLMs) are increasingly integrated into healthcare, supporting clinical workflows, diagnosis, treatment planning and timely utilisation of scarce medical resources.

One of their applications involves decisions on allocating deceased-donor or living-donor kidneys to patients, which, according to the authors, depend on complex ethical and moral considerations.

In such high-stakes scenarios, the researchers pointed out that decisions demand not only accuracy but also alignment with human values and moral judgement.

According to the researchers, asking if AI can make moral decisions or whether they’re aligned with human values lies at the core of today’s wider debate on artificial intelligence.

“The ethical stakes are high, and AI’s role in such life-altering decisions requires deep reflection,” said Hosseini. “Moral decisions in settings like organ allocation directly determine who lives and who dies, so getting AI's role in them right isn't optional.”

“While we do not intend to encourage the use of AI as a substitute for professional judgment in medical decision-making or other high-stakes contexts, it's becoming essential to understand their behavior as individuals, organizations and firms more and more rely on AI to make decisions or receive recommendations,” he added

 

Could the EU Kids Act unwittingly widen the transatlantic AI divide?

Copyright Source: Canva

By Jonathan Benton

Published on 18/09/2026 - EURONEWS

Europe must prepare for the potential consequences of implementing further digital rules that could make it more difficult for smaller European developers to compete, warns an industry insider.

Brussels wants to shield children from Big Tech. It may end up handing Silicon Valley an even bigger competitive edge.

The EU Kids Act, unveiled this week, promises age limits, parental controls and a crackdown on the "addictive" features baked into social media, video platforms and AI chatbots alike.

But as the bloc moves to police the tech giants, a harder question looms: can Europe regulate its way to child safety without regulating itself out of the AI race it is already losing?

The stakes could hardly be higher. Europe has just one significant AI company to speak of, Mistral, dwarfed by its US rivals OpenAI and Anthropic in both valuation and investment.

The bloc has never really left the starting blocks when it comes to scaling digital platforms to rival America's, relying instead on the strength of its single market and its power to regulate.

Now, as AI becomes the defining technology of the decade, that trade-off — rules versus growth — is seen as a "make or break" moment for the bloc.

What the Kids Act actually proposes

The legislation includes a number of measures aimed at protecting children online, including age restrictions, parental controls and limits on potentially addictive features.

The proposals have been welcomed by some in the tech industry, but Stanislas Marchand, a former mobile gaming lead at French unicorn Voodoo, says Europe must also consider the potential consequences for its own digital sector.

He argues that Europe "must prepare for the potential consequences by investing more urgently than ever in its homegrown AI capabilities".

The European Commission's proposals come amid growing pressure on governments to protect children from the risks posed by social media and other online platforms.

In the last couple of years, though, Big Tech has come under increasing scrutiny for its failure to protect children online, from cyberbullying, harassment and grooming to exploitation, extortion and misinformation.

Australia famously implemented the world's first social media ban for under-16s in December last year, a move that was watched keenly by governments around the world, prompting many to follow suit in implementing their own bans or exploring the possibility of doing so.

France, Greece, Austria, Denmark, Spain, Belgium, Italy, Germany, Poland and the Netherlands have all been considering or advancing national legislation on social media bans, piling pressure on Brussels to present an EU-wide measure and avoid fragmentation.

Meanwhile in the US this year, social media companies have faced and lost landmark liability cases, with many choosing to settle instead — such as Meta's recent $17bn (€14.9bn) deal to end a lawsuit brought by 47 US states.

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Beyond social media

The EU Kids Act calls for a total, blanket social media ban for under-13s, while those up to 15 years old would be able to make "mini accounts" — limited, highly supervised profiles linked to a parent's profile.

Not only that, these accounts would also come with mandatory one-hour daily limits and a complete ban on "toxic or addictive features" like infinite scroll, endless autoplay and engagement rewards.

Marchand welcomed the proposed ban for under-13s, but said the proposal "should have been extended to everyone under 16" rather than permitting mini accounts for teens.

He argues the message from the Commission should have been that the platforms in question are "unsuitable for children" because they are "engineered to maximise attention".

The Kids Act goes well beyond social media.

It encompasses video-sharing platforms such as YouTube and Twitch, online video games like Roblox, Fortnite and Minecraft, and more recent entrants like AI chatbots and companions such as ChatGPT, Claude and Gemini.

It would also require app stores and operating systems to integrate strict age-assurance filters to prevent underage users from downloading restricted apps and software in the first place.

And implementation, for Marchand, is where the problem lies, because the EU is asking platforms to "verify children's ages, operate parent-controlled accounts, enforce daily limits, restrict contacts and features, and prove that the resulting product is safe."

These requirements altogether could increase the cost and complexity of launching a product in Europe.

"Every one of those responsibilities creates another potential point of failure, and history gives us little reason to trust social media companies to execute them properly."

That concern is particularly relevant given that Europe's digital sector is dominated by American firms, and the continent has somewhat failed to make sure Big Tech follows the rules.

Meta has been fined twice for illegally transferring European user data to US servers, breaching GDPR in 2023 and the Digital Markets Act in 2025.

TikTok was fined €530m last year for failing to protect children's data and illegally transferring it to Chinese servers.

Elon Musk's X, which has had the most acrimonious relationship with EU lawmakers, was fined €120m last December over its deceptive "blue checkmark" verification and for denying researchers access to data

Google, too, has been fined repeatedly for breaching antitrust rules, amounting to €10.38bn so far.

A patchy enforcement record

All of these fines are pocket change for Big Tech, and with the arrival of potentially even larger firms in the shape of AI giants OpenAI and Anthropic — again based in the US — it could become even more difficult for Europe to shape and enforce its own digital rules.

Marchand fears the Act could also make the EU a less attractive market to launch new products, while doing little to support European alternatives.

"If the Kids Act requires separate European products and costly ongoing assessments, US labs may delay launches here while smaller European developers struggle to compete," he warns.

He also points out that frontier AI companies already face enormous computing costs and uncertain paths to profitability, while some advanced Anthropic models have already been restricted outside the US and withheld from the UK's AI Security Institute.

For Marchand, the result could be an unintended consequence of the EU's attempt to protect children online.

"My feeling is this will further add to the transatlantic AI divide."

China's Ulanqab plans 5mn server racks in AI compute race with US

A windswept prefecture of 1.5mn people on the Mongolian plateau already uses nearly 1% of China's electricity as the country's tech giants pile in with data centres. / bne IntelliNewsFacebook

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By Ben Aris in Berlin September 17, 2026

A remote prefecture in China's Inner Mongolia is becoming a global centre of AI computing power. Ulanqab, home to 1.5mn people on the grasslands of the Mongolian plateau, consumes nearly 1% of all the electricity used in China, and its demand is growing by double digits every year.

Spread across the prefecture's households, that load would work out at about 105,000 kWh each a year, roughly 10 times the consumption of an average American home, by his calculation. The power is going into servers.

Over the past few years Ulanqab has signed investment agreements worth more than CNY500bn ($74bn) with China's largest technology companies, and the build-out planned there runs to more than 5mn data centre racks, according to Science and Technology Daily, the newspaper of China's Ministry of Science and Technology.

Set that against Elon Musk's Colossus supercomputer in Memphis, Tennessee, which xAI markets as the world's largest AI supercomputer. On xAI's own count of 200,000 chips, Colossus fills something like 5,000-6,000 racks, Bertrand estimated, which implies roughly a thousand times as many racks. The comparison does not measure equivalent computing power: Chinese standard racks are rated at 2.5 kW, while modern Nvidia AI cabinets can draw more than 100 kW.

"What we see appearing in this Inner Mongolian steppe may be the closest thing to a world brain humanity has ever built - a place where a large share of the world's thinking will physically happen," commentator Arnaud Bertrand wrote on X on September 14.

Anthropic chief executive Dario Amodei said China presented the hardest problem for his proposal to slow AI development, CNBC reported on September 13.

If AI turns out to be the defining technology of the century, as Bertrand argues both Washington and Beijing believe, that makes Ulanqab "one of the single most relevant geopolitical places in the world right now", he wrote.

From cloud valley to token capital.

Inner Mongolia signed 12 commercial deals worth CNY186.46bn ($27.6bn) at a green computing and AI conference in Hohhot on August 22, with China Telecom (SHA: 601728), chipmaker Cambricon Technologies (SHA: 688256) and Volcano Engine, the cloud platform of TikTok owner ByteDance, among the signatories. Active processing power in Ulanqab had by then reached 172,000 PFlops, with more than 95% of it allocated to AI work.

The largest single project so far belongs to Envision, the Shanghai-based wind turbine and battery maker, which commissioned its Galaxy campus in Ulanqab in August. The company says the 2 GW AI campus runs on renewable power and contains the world's largest single data centre building.

The Chinese business magazine Caixin devoted an in-depth report on August 14 to how the city turned itself into an AI powerhouse. Inner Mongolia is one of eight national computing hubs designated under Beijing's "East Data, West Computing" programme, which shifts data processing from the crowded, power-hungry coast to the resource-rich interior.

Cheap wind and cold air

Electricity makes up 55% of a data centre's cost, according to a McKinsey Global Institute study published in June, so the price of power decides where the servers go.

Inner Mongolia is China's "green power bank", regularly producing more wind and solar electricity than it can use at home. Envision finished a 12.8 GWh battery storage cluster across the region at the end of 2025, with sites in Ulanqab, Hohhot, Ordos and elsewhere, to soak up the surplus.

The surplus comes cheap: firm wind power backed by batteries cost about $59/MWh in Inner Mongolia in 2025, against $88-94/MWh in Brazil, Germany and Australia, the International Renewable Energy Agency (Irena) said in May.

Ulanqab's wind already runs a 1 GW electrolysis plant supplying Sinopec's green hydrogen pipeline to Beijing, nearly 400 km away, and the cool plateau climate trims the bill for keeping servers from overheating.

The data centre boom is the latest expression of China's rise as the first Electrostate, an economy built on cheap electrons, and of its position as the world's green energy champion, building two-thirds of the world's new wind and solar plants.

Racks are not chips

Chinese planners typically count data centre capacity in "standard racks" rated at 2.5 kW, while a single cabinet of the latest Nvidia AI servers draws more than 100 kW, so a rack-for-rack comparison with Colossus overstates the gap.

Measured in power, 5mn standard racks come to about 12.5 GW, in line with the planned capacity for Ulanqab reported by the newsletter AI Weekly. That is still more than six times the size of Envision's Galaxy campus. China's total data centre capacity is on course to top 60 GW by 2030, doubling the sector's power demand, according to Rystad Energy.

China's handicap lies in the chips. American hardware keeps a 9:1 lead in raw computing performance, according to American Enterprise Institute researcher Ryan Fedasiuk, and even in the most optimistic 2028 scenario Huawei would supply at most an eighth of the compute available in the US. The AEI's most pessimistic case still has domestic AI chips meeting a third of China's compute demand by 2028, up from about a fifth in 2026.

Chinese chips burn more electricity per calculation than their American rivals, which puts a premium on power that is abundant and cheap. Abundant wind power could lower operating costs, but does not by itself close the chip-performance gap.

Demand to fill it

Daily token requests to AI models across China jumped from about 100bn in early 2024 to 140 trillion by March 2026, and Inner Mongolia has started building a trade platform in the Hohhot free trade zone to sell clean computing power and access to Chinese AI models to foreign developers.

Neighbouring Mongolia unveiled plans for a renewable-powered data centre in August, pitching the same cool, dry climate and wind and solar resources, plus a location between China and Russia.

Bertrand said he had travelled to Inner Mongolia twice without hearing of Ulanqab before he began researching it. "It's really surprising this hasn't been talked about more because the scale is beyond anything else, and by an immense margin," he wrote.