The tech industry's claims that artificial intelligence can help mitigate climate change have been met with skepticism by experts, who argue that these assertions are often based on flawed assumptions and a lack of concrete evidence. According to a recent report, the industry's tactics can be seen as "diversionary" and amount to "greenwashing," as they conflate traditional artificial intelligence with energy-hungry technologies such as generative AI and large language models.
The report, commissioned by nonprofits including Beyond Fossil Fuels and Climate Action Against Disinformation, analyzed 154 statements from tech companies and found that most claims about AI's climate benefits referred to machine learning, rather than the energy-intensive technologies driving the sector's growth. Ketan Joshi, an energy analyst and author of the report, likened the industry's approach to fossil fuel companies advertising their modest investments in solar panels and overstating the potential of carbon capture.
Joshi's report argues that the tech industry has misleadingly presented climate solutions and carbon pollution as a package deal by "muddling" types of AI. This has led to a lack of transparency and accountability, with most claims lacking evidence or relying on weak forms of evidence that have not been independently verified. As Sasha Luccioni, AI and climate lead at Hugging Face, noted, "When we talk about AI that's relatively bad for the planet, it's mostly generative AI and large language models."
The Problem with Green Claims
The analysis found that only 26% of green claims cited published academic research, while 36% did not cite evidence at all. One of the earliest examples identified in the report was a widespread claim that AI could help mitigate 5-10% of global greenhouse gas emissions by 2030. However, this figure, which Google repeated as recently as April last year, came from a report it commissioned from BCG, a consulting firm, which cited a blog post it wrote in 2021 that attributed the figure to its "experience with clients."
Datacentres, which consume just 1% of the world's electricity, are projected to account for at least 20% of the rich world's growth in electricity demand to the end of the decade, according to the IEA. The energy consumption of complex functions such as video generation and deep research has troubled some energy researchers, who are concerned about the speed and scale of its growth. As Joshi noted, "The false coupling of a big problem and a small solution serves as a distraction from the very preventable harms being done through unrestricted datacentre expansion."
Expert Analysis
Luccioni, who has pushed the industry to be more transparent about its carbon footprint, said that the report added nuance to a debate that often lumped very different applications together. "When we talk about AI that's 'good' for the planet, it's often predictive models, extractive models, or old-school AI models," she noted. However, even traditional AI's green claims tended to rely on weak forms of evidence that had not been independently verified.
A spokesperson for Google said that the company's estimated emissions reductions were based on a robust substantiation process grounded in the best available science. However, Microsoft declined to comment, and the IEA did not respond to requests for comment. As Joshi argued, the discourse around AI's climate benefits needs to be "brought back to reality," and the industry must be held accountable for its claims and actions.
The Way Forward
The report's findings highlight the need for greater transparency and accountability in the tech industry's climate claims. As the world grapples with the challenges of climate change, it is essential to separate fact from fiction and to ensure that the industry's assertions are based on concrete evidence. By doing so, we can work towards a more sustainable future, one that is grounded in reality rather than greenwashing tactics.
