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 The remaining claims relied on corporate reports, media coverage, NGO publications or unpublished academic work.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.
Tech
Meta Apps Collect More User Data Than Other Big Tech, Study Finds
Meta’s apps collect more types of user data on average than applications from other major technology companies, according to research by cybersecurity and privacy company Surfshark.
The study analysed 171 apps available through Apple’s App Store that were developed by Meta, Google, Microsoft, Apple and Amazon. Researchers examined the types of information identified in each app’s privacy disclosures across 35 data categories.
Meta ranked highest, with its apps collecting an average of 25 out of 35 possible data types. Surfshark said this was more than three times the average recorded for some other major technology companies.
The categories examined included information such as browsing history, precise location, purchase details and other personal data that applications can collect or associate with users.
Seven of the apps identified among the most data-intensive were owned by Meta. They included Facebook, Messenger and Meta AI, as well as Meta Horizon, Meta Ads Manager, Meta Business Suite and Forum.
The findings put Meta well ahead of the other companies included in the analysis.
Google apps collected an average of 17 data types, according to Surfshark, while Amazon collected 12. Microsoft averaged eight types and Apple seven.
The research focuses on the number of data categories associated with each application rather than the volume of individual records collected from users. It also reflects information disclosed by developers through App Store privacy labels, which can vary according to how companies classify and report their data practices.
Meta operates some of the world’s most widely used digital platforms, including Facebook, Instagram, Messenger and WhatsApp. Its services rely heavily on advertising and personalised experiences, making user information an important part of its business model.
The findings are likely to renew questions about how much personal information consumers share when using popular social media and technology services.
Privacy concerns have increased as technology companies expand their use of artificial intelligence, targeted advertising and personalised recommendations. AI-powered applications can require access to additional information depending on their features and how users interact with them.
Surfshark’s analysis does not by itself establish whether any company has violated privacy laws or whether the data collected is used improperly. The number of data categories listed by an app also does not necessarily indicate how much information a particular user contributes.
However, the research highlights the differences in data collection practices among major technology companies.
The findings could encourage users to review application privacy settings and the information requested by apps before installing or continuing to use them.
As regulators and consumers place greater scrutiny on digital privacy, technology companies face increasing pressure to explain clearly what information they collect, why it is needed and how long it is retained.
Tech
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