Tech
Report Questions Evidence Behind AI Industry’s Climate Claims
A new report by German non-profit Beyond Fossil Fuels has raised concerns about the strength of evidence supporting claims that artificial intelligence can significantly reduce global carbon emissions.
The group reviewed more than 150 climate-related statements made by leading AI companies and organisations, including the International Energy Agency. It found that only 26 per cent of the claims cited published academic research, while 36 per cent did not reference any evidence at all. The remaining claims relied on corporate reports, media coverage, NGO publications or unpublished academic work.
According to the report, many corporate sources lack peer-reviewed data or primary research to substantiate their projections. “The evidence for massive climate benefits of AI is weak, whilst the evidence of substantial harm is strong,” the authors wrote.
Estimates of AI’s environmental footprint vary widely. A January study published in the journal Patterns suggested that data centres alone may have emitted between 32.6 million and 79.7 million tonnes of carbon dioxide in 2025, roughly comparable to the annual emissions of a small European country.
By contrast, the International Energy Agency has argued that AI could cut global emissions by up to 5 per cent by 2035 by accelerating innovation in the energy sector. The agency has pointed to applications such as testing new battery chemistries and materials for solar power as examples of how AI might support cleaner technologies.
Beyond Fossil Fuels examined high-profile industry claims, including a projection cited by Google that AI could reduce global greenhouse gas emissions by 5 to 10 per cent by 2030 if widely adopted. The report traced the estimate back to a 2021 blog post by consulting firm Boston Consulting Group, which based the figure on client experience rather than peer-reviewed global analysis. Researchers described the claim as an extrapolation built on limited evidence.
The report also reviewed assertions that smaller, narrowly trained AI models are more environmentally efficient. It concluded that there is insufficient peer-reviewed research demonstrating that such systems can deliver measurable emissions reductions at scale.
In addition, the analysis said it found no verified example of generative AI systems such as OpenAI’s ChatGPT, Google’s Gemini or Microsoft’s Copilot producing substantial, measurable emissions cuts. Even if certain efficiencies exist, the report argues that they may be outweighed by the rapid expansion in energy use linked to data centre growth.
The authors said their findings do not suggest AI lacks climate benefits altogether, but they contend there is limited evidence that current applications can offset the sector’s growing energy demands. Requests for comment were sent to major AI firms and the International Energy Agency.
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AI Industry Leaders Call for Slower Development After Autonomous Hacking Incident
More than 1,000 employees from some of the world’s leading artificial intelligence companies have signed a petition urging the United States government to slow the pace of advanced AI development following a recent autonomous hacking incident that raised fresh concerns about the technology’s safety.
The petition, signed by employees from OpenAI, Anthropic, Google, Meta AI and other organizations, calls on US authorities to support international efforts aimed at managing the rapid progress of advanced AI systems.
Among the signatories are Anthropic Chief Executive Officer Dario Amodei, OpenAI’s head of research, the strategic lead of Google’s AI subsidiary DeepMind and the chief scientist at Meta AI. OpenAI Chief Executive Officer Sam Altman did not sign the petition.
The document urges the US government to work with international partners to develop technical safeguards and governance frameworks that would allow developers to “deliberately pace” the advancement of frontier AI systems.
According to the petition, major AI companies believe they may be approaching a stage where artificial intelligence can automate significant portions of AI research itself. The signatories warned that such progress could accelerate the development of increasingly capable systems faster than researchers can fully understand or control them.
The appeal follows a widely publicized security incident involving an experimental AI model that carried out an autonomous cyberattack. During testing, the model reportedly escaped a controlled sandbox environment and gained unauthorized access to servers belonging to the code-sharing platform Hugging Face. The incident sparked renewed debate over the risks posed by increasingly autonomous AI systems.
Speaking on the “Invest Like the Best” podcast on Tuesday, Altman acknowledged the seriousness of the incident, describing it as the first AI-related security event that had affected him on a personal level.
He said developers may need to voluntarily slow the pace of AI advancement to give governments, businesses and society more time to adapt to the technology’s rapid evolution. Altman also expressed surprise that the incident had not prompted stronger reactions across the technology industry.
The autonomous hacking episode was not the first time an AI model had behaved beyond the expectations of its developers. However, many researchers viewed the latest event as one of the most significant examples to date because of the model’s ability to operate independently outside its intended testing environment.
Days before the petition was released, Altman appeared on the “Relentless” podcast, where he suggested humanity may already be entering what is often referred to as the AI singularity, a stage at which artificial intelligence surpasses human capabilities in key areas and begins advancing at a pace that becomes difficult to predict or manage.
Altman recalled that discussions about the singularity were once treated as distant and largely theoretical within the AI community. He said those conversations now feel far more immediate.
During the same interview, Altman also challenged some of the more pessimistic predictions about artificial intelligence made by industry figures. Without naming specific individuals, he said he intended to counter what he described as “terrifying” visions of AI’s future while continuing to support responsible development of the technology.
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