By AFP -Agence France Presse
UK engineers warn of risks to the environment posed by artificial intelligence
Governments need to start acting on the environmental risks, including possible water shortages, posed by the development of artificial intelligence, a UK body that advises on engineering policy warned on Friday.
The National Engineering Policy Centre - made up of 42 institutions led by the Royal Academy of Engineering - highlighted the possible consequences of data centers that rely heavily on energy, water, and essential materials such as silicon.
“These rapidly growing resource demands could have far-reaching effects, such as creating competition for renewable energy or clean water,” said the NEPC in a report that recommended short-term measures by world governments to help provide sustainable AI.
This includes setting environmental sustainability requirements for data centers, which require significant amounts of water for cooling purposes.
“Artificial intelligence can be harnessed to accelerate progress towards net-zero carbon emissions and improvements in environmental sustainability,” the report noted.
However, the way AI systems and services are currently designed, built, and used imposes “demands on resources such as energy, water, and critical materials, which can create new environmental damage or exacerbate existing damage,” it added.
The report, entitled Engineering Responsible AI: foundations for environmentally sustainable AI, was drawn up after British Prime Minister Keir Starmer set out a vision to put the UK at the forefront of artificial intelligence development.
Britain currently has the third largest AI sector in the world, after the US and China.
In a warning to the UK and other countries, the chair of the report's working group said that “to create systems and services that use resources effectively, we first need to effectively monitor their environmental cost”.
Professor Tom Rodden added that “once we have access to reliable data regarding their environmental impacts... we can begin to effectively target efficiency in development, deployment and use - and plan for a sustainable future for AI.”
bcp/ajb/cw
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