Here’s what the world can do about that.
UN Environment Programme
Originally posted 21 Sept 24
There are high hopes that artificial intelligence (AI) can help tackle some of the world’s biggest environmental emergencies. Among other things, the technology is already being used to map the destructive dredging of sand and chart emissions of methane, a potent greenhouse gas.
But when it comes to the environment, there is a negative side to the explosion of AI and its associated infrastructure, according to a growing body of research. The proliferating data centres that house AI servers produce electronic waste. They are large consumers of water, which is becoming scarce in many places. They rely on critical minerals and rare elements, which are often mined unsustainably. And they use massive amounts of electricity, spurring the emission of planet-warming greenhouse gases.
“There is still much we don’t know about the environmental impact of AI but some of the data we do have is concerning,” said Golestan (Sally) Radwan, the Chief Digital Officer of the United Nations Environment Programme (UNEP). “We need to make sure the net effect of AI on the planet is positive before we deploy the technology at scale.”
This week, UNEP released an issue note that explores AI’s environmental footprint and considers how the technology can be rolled out sustainably. It follows a major UNEP report, Navigating New Horizons, which also examined AI’s promise and perils. Here’s what those publications found.
Here are some thoughts:
The article discusses the significant environmental impact of artificial intelligence (AI) technologies and proposes solutions to mitigate these effects. AI systems, particularly those requiring substantial computational power, consume vast amounts of energy, often sourced from non-renewable resources, contributing to carbon emissions. Data centers, which host AI operations, also demand considerable energy and water for cooling. Moreover, the production of AI hardware, such as GPUs and servers, involves the extraction of rare earth metals, leading to environmental damage, and the disposal of this hardware contributes to electronic waste.
The article likely suggests several strategies to address these issues, including the development of energy-efficient AI algorithms and hardware, the use of renewable energy sources to power data centers, and the implementation of sustainable practices in hardware production and disposal. It may also advocate for policies that regulate the environmental impact of AI technologies.
Stakeholders, including governments, corporations, and researchers, are probably emphasized as crucial players in creating sustainable AI ecosystems. The importance of public awareness and consumer pressure in driving the industry towards greener practices is likely highlighted as well.
From an ethical standpoint, the article underscores the responsibility of AI developers and companies to minimize environmental harm, balancing technological progress with ecological sustainability. It raises concerns about intergenerational equity, urging sustainable practices to protect the planet for future generations. Corporate accountability is another key ethical consideration, emphasizing the need for tech companies to prioritize environmental sustainability. The role of policy and governance is also stressed, with a call for regulatory frameworks to ensure ethical AI development. Lastly, the article likely emphasizes the moral duty of consumers to demand and be informed about greener AI technologies.