AI takes center stage at COP28 as experts debate tech's climate impact
Running AI is much more energy-intensive than other forms of computing, but as leaders gather for the COP28 global climate summit in Dubai, we know relatively little about AI's net impact on climate change.
Why it matters: Increasing adoption of AI may make it one of the biggest uses of energy globally — putting pressure on AI providers to measure and publish data on energy use and energy sources.
- A growing body of evidence suggests using AI to improve physical systems — from farming processes to supply chains and buildings — will allow us to avoid around 10% of today's emissions.
Driving the news: AI has been a top theme of COP28.
- The United Nations and Microsoft on Thursday announced an AI-powered climate data hub to track progress in reducing emissions because as Microsoft's Brad Smith said in a statement, "you can't fix what you can't measure."
The context: Other high-growth, high-emission parts of the global economy including civil aviation and commercial shipping have bowed to pressure to measure and reduce their carbon emissions — but there's no such plan on the table for AI or data centers more generally.
State of play: Overall data center energy consumption is growing despite impressive efficiency gains, according to the International Energy Agency — everything beyond that is a matter of dispute.
- While cloud computing and other data centers use about 1% of today's electricity, Britain's National Grid predicts data centers will consume just under 6% of U.K. electricity by 2030.
- Microsoft, Google and Nvidia are more optimistic.
- Global datacenter workloads increased by 9x between 2010 and 2020, according to Microsoft — but meeting that demand required only a 10% increase in electricity use.
- Google researchers say some papers grossly overestimated machine learning energy use, and that energy consumption of machine learning could soon plateau, and then shrink.
- Nvidia, which sells 95% of the graphics processing units (GPUs), also notes that GPUs are more energy efficient than other types of chips. The GPUs it will ship in 2023 will collectively consume barely 1/1000th of the energy consumed in the U.S. each year.
- AI models such as Mistral 7B and Meta's Llama 2 use up to 100 times less energy than OpenAI's GPT4, while Google DeepMind launched a product for the discovery of faster computer algorithms, which the company hopes will cut the amount of energy needed to run AI.
Flashback: A Dutch PhD student grabbed headlines in October, by concluding in a peer-reviewed paper that AI could use as much electricity as the Netherlands or Sweden by 2027. But this is just 0.5% of global energy consumption.
The other side: It's possible to run power-hungry AI systems without wrecking the planet.
- AI has been demonstrated to cut data center cooling costs by 40%, and big tech companies are some of the leading investors in clean energy — committed to zero carbon energy systems between 2030 and 2040.
- One of the early uses of AI in the energy sector has been to improve predictions around weather and energy supply and demand. The impacts include European energy provider E.ON reducing outages by around 30%, Google increasing the financial value of its wind power by 20% through synchronizing turbines and optimizing energy flows into the wider grid.
What they're saying: Evan Smith, CEO of supply chain company Altana, tells Axios that he uses AI to "make a physical system more efficient," and that even marginal gains across big supply chains means "you're pulling a massive lever on the climate equation."
What we're watching: The European Union will start requiring all but the smallest data centers on the continent to report emissions to meet new corporate sustainability reporting requirements.
- In California companies with annual revenues over $1 billion will have to report their emissions by 2026.
The bottom line: While companies are getting better at setting climate targets, lack of transparency around energy use and the absence of standardized reporting requirements from regulators means we're going to be debating AI's climate impact for years to come.