Water shortage fears as Government pursues AI growth – Prolific North

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Academics are urging the government to put the environment and sustainability at the centre of its AI revolution.

The new report from the Royal Academy of Engineering shows that Google and Microsoft have reported year-on-year increases how much water they use to cool down their data centres – some of which is coming from sources of drinking water.

In the Engineering Responsible AI: foundations for environmentally sustainable AI publication, the National Engineering Policy Centre says that data centres “can and should” be designed to use less water and critical raw materials, but that the government “must set the conditions for this” as the AI Opportunities Action Plan is rolled out.

“In recent years advances in AI systems and services has largely been driven by a race for size scale, demanding increasing amounts of computational power. As a result, AI systems and services are growing at a rate unparalleled by other high energy systems – and generally without much regard for resource efficiency. This is a dangerous trend, and we face a real risk that our development, deployment and use of AI could do irreparable damage to the environment,” said Professor Tom Rodden CBE FREng FRS FBCS, Pro-Vice-Chancellor of Research & Knowledge Exchange and Professor of Computing, University of Nottingham and Chair of the working group.

“To build systems and services that effectively use resource, we first need to effectively monitor their environmental cost. Once we have access to trustworthy data pertaining to their environmental impacts, and a sense for where these services and systems are needed, we can begin to effectively target efficiency in development, deployment, and use – and plan a sustainable AI future for the UK.”

In order to meet the government’s plans, new data centres will need to be built, but the report said that “reliable data is not currently available on how much resources these infrastructures consume.”

It added: “this impacts policymakers’ ability to understand and respond to environmental risks.”

“Engineering has a vital role in making AI more efficient and, in turn, more environmentally sustainable. Some of this will come from improvements to AI models and hardware, making them less energy intensive. But we must also ensure that the data centres housing AI’s computing power and storage are as sustainable as possible. That means prioritising renewable energy, minimising water use, and reducing carbon emissions—both directly and indirectly. Using low-carbon building materials is also essential,” added Dame Dawn Childs DBE FREng FICE FIMechE FRAeS, CEO of Pure Data Centres Group.

“Achieving this requires joined up thinking from the outset, particularly at the planning stage. As the UK government accelerates AI adoption—through AI Growth Zones and streamlined planning for data centres—sustainability must be a priority at every step.”

The Engineering Responsible AI outlines 5 steps to environmentally sustainable AI:

Expanding environmental reporting mandates
Providing information on environmental impacts of AI systems across the value chain, including AI compute, IT infrastructure, data and algorithms, interaction and use.
Setting environmental sustainability requirements for data centres
Reconsidering data collection, transmission, storage, and management practices
Leading the way with government investment

Last month Autotrader and Manchester Digital launched the first ever Digital and Technology Carbon Literacy Toolkit in partnership with The Carbon Literacy Project, as the digital and tech sectors come under growing pressure to reduce carbon emissions.

A similar, but mandatory call is being pushed here, so that data is available on energy consumption and sources, water consumption, withdrawal and sources, carbon emissions and e-waste recycling.

The report also wants environmental sustainability requirements for all data centres, including reducing the use of drinking water and moving to zero use for cooling.

“At the British Computer Society, we advocate the importance of achieving more with limited resources. Evidence shows that even when skilled AI developers have restricted access to computational resources, they can still create effective models,” said Alex Bardell FBCS, Founder of SDAdvocate and Chair of BCS’ Green IT Specialist Group.

“Our report has discussed optimising models for efficiency. Previous attempts to limit the drive toward increased computational power and larger models have faced significant resistance, with concerns that the UK may fall behind in the AI arena; this may not necessarily be true. It is crucial to reevaluate our approach to developing sustainable AI in the future.”

The publication was developed by the Royal Academy of Engineering in partnership with the Institution of Engineering and Technology and BCS, the Chartered Institute of IT, under the National Engineering Policy Centre (NEPC).