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AI and the environment: What are the pitfalls?

Artificial intelligence (AI) is an exciting and fast-changing technology. But it has a big CO2 footprint and is being used to boost activities that make climate change worse.

To carry out the tasks they’re supposed to, AI models need to process mountains of data. To learn to recognize an image of a car, for example, an algorithm will need to churn through millions of pictures of cars. Or in the case of ChatGPT, it’s fed colossal text databases from the internet to learn to handle human language.

This data crunching happens in data centers. It requires a lot of computing power and is energy-intensive. “The entire data center infrastructure and data submission networks account for 2-4% of global CO2 emissions,” says Anne Mollen, researcher at NGO Algorithmwatch. This is not only AI, but AI is a large part of that. That’s on a par with aviation industry emissions.

Beyond the “training” phase, more emissions are created when the model is applied in the real world, something that can happen billions of times a day, such as every time an online translator translates a word, or a chatbot answers a question. Mollen from Algorithmwatch says this application phase can potentially account for up to 90% of the emissions in the life cycle of an AI.

We need to consider the entire production chain and all the environmental problems that are connected to this chain… most notably energy consumption and emissions, but also material toxicity and electronic waste. Rather than building bigger and bigger AI models, as is the current trend, Mollen suggests companies could scale them down, use smaller data sets, and ensure the AI is trained on the most efficient hardware available.

Using data centers in regions that rely on renewable energy and don’t require vast amounts of water for cooling could also make a difference. Huge facilities in parts of the US, where fossil fuels make up a significant chunk of the energy mix, will produce more emissions than in Iceland, where geothermal power is a primary source of energy and lower temperatures make cooling servers easier.

Mollen notes that tech giants have a fairly good record of using renewable energy to power their operations. Google says its carbon footprint is zero, thanks to investment in offsets. It aims to be operating exclusively on carbon-free energy by 2030. Microsoft has pledged to be carbon-negative by 2030, using carbon capture and storage technologies, and Meta plans to reach net zero across its value chain by 2030.

But energy isn’t the only consideration. The huge amount of water data centers need to prevent their facilities from overheating has raised concerns in some water-stressed regions, such as Santiago, Chile.

The role of AI is only likely to become more significant in the future. And keeping up with such rapidly advancing technology will be a challenge. That’s why regulation is crucial to ensuring AI development is sustainable and doesn’t make emissions targets harder to reach.

Source: Deutsche Welle