Photo Credit: Adib Hussain on Unsplash (edited by Ashley Moniz)
Photo Credit: Adib Hussain on .
Ali Mesbahian is an IPilogue Writer and a 2L JD Candidate at Osgoode Hall Law School.
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The ever-growing reliance on artificial intelligence (AI) in our everyday life and industry is an undisputable condition of our time. Whether we speak of gaming, speech and facial recognition, smartphones, medical research, agriculture, trading and investment, cybersecurity, or resource extraction (and of course, much more)—few, if any, sectors fall outside the purview of AI. As with any emerging technology, as to whether AI is a “net good” are abundant. This brief article focuses on this issue with respect to AI’s environmental impact.
For starters, it is important to acknowledge AI’s potential in combatting climate change. Among other things, lead to better climate predictions, create virtual simulations that demonstrate what a given area would look like after the impacts of climate change, and help track the source of carbon emissions for regulation purposes.
On the other hand, AI requires infrastructure that consumes a great deal of energy. study conducted at the University of Massachusetts Amherst shed light on the enormous scale of this consumption: the energy required to train a single natural language processing (NLP) model leaves a carbon footprint of roughly 300,000 kg— (for a fascinating map on the human and environmental costs of AI, see ). Of more concern, “.” But what contributes to this increasing energy-intensive dynamic? Consider the following two points .
First, some researchers and academics have raised concerns about the AI community’s hyper-focus on their models’ accuracy and which come at the expense of cost and energy-efficiency considerations. Accordingly, calls are being made to research “ Ěýthat not only incorporates the energy consumption levels of a given AI model in its evaluative criteria, but also factors in the renewability of energy-sources and the extent to which a given model’s research results can be reproduced for future research.
Second, a 2020 , illustrates the close connection between tech and fossil-fuel industries. For instance, while Microsoft has vowed to become “carbon negative” by 2030 in order to counteract its contribution to environmental damage, it also offers AI capabilities to oil and gas companies such as ExxonMobil “in all phases of oil production.” Microsoft is not alone in signing these kinds of lucrative contracts; it’s joined by companies such as Amazon and Google. This casts huge doubt on the achievability and commitment of tech firms’ own climate goals. As was the case when , it is important for both civil society and insiders in the tech industry to pressure corporate executives to stop assisting the extractive activities of the fossil fuel industry and be more aggressive in reducing their own carbon footprints.
It is important to mention that the success of initiatives aiming to reduce the negative impacts of AI depend on the , both domestically and internationally. In this regard, I end with a hopeful starting point: Germany’s supreme constitutional court’s historic ruling in April 2021 that rendered the government’s climate goal to achieve carbon neutrality by 2050 as . The Court found that the government’s policy simply does not go far enough in protecting future generations from the catastrophes of climate change. As a result, the German government is in the process of bringing forward a —which undoubtedly bears regulatory implications for the tech industry.
To learn more about the relationship between artificial intelligence and the environment, check out next week’s , hosted by IP Osgoode and featuring a panel of leaders in the fields of AI and sustainability.