Artificial intelligence (AI) has many use cases, including tackling climate change challenges.
However, this technology is a significant carbon emitter and might find itself at odds with the environmental purposes it claims to solve, as its use exacerbates environmental greenhouse gas emissions. This technology seems to face a dualism: is it benefitting our planet or a dog chasing its own tail?
AI role 1: the green tool
In 2023, at the height of AI hype, many interesting examples of how AI can help solve sustainability challenges are emerging across various sectors. This technology can help with smart power grid design, developing low-emission infrastructure, and forecasting climate-related events.
In the automotive industry, AI can be used as an early warning system for sustainability within the supply chain. For example, in 2020, Porsche, Audi, and Volkswagen launched a pilot project using an intelligent algorithm that monitored supplier-related news from publicly available media and social networks in over 150 countries. The goal was to identify major sustainability risks such as environmental pollution, human rights abuses, and corruption.
Using the algorithm, when a sustainability risk is identified, brands are notified so that they can take action. The major advantage of intelligent sustainability in the automotive sector is the transparency across the supply chain, as AI facilitates complex data analysis and greatly speeds up the identification and screening process of risk assessment information in real time.
Another 2023’s case is easyJet which just introduced a collaborative initiative with Winnow, a commercial food waste solutions company, to utilise AI technology to minimise food waste in the kitchens of one of EasyJet Holiday’s hotels in the Canary Islands. This pilot program uses Winnow’s AI tools to detect and track food waste, and then store the collected data in the cloud. Eventually, the hotel receives detailed reports highlighting areas of waste, allowing them to make operational enhancements.
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By GlobalDataAI role 2: the resource demander
AI is one of the most energy-intensive technologies, largely contributing to greenhouse emissions. Indeed, training an AI model requires significant amounts of computational power, which in turn requires a significant amount of energy largely generated by fossil fuels. In 2019, researchers at the University of Massachusetts Amherst found that the carbon footprint of training a single large language model is equal to around 300,000kg of carbon dioxide emissions.
This figure is roughly equal to 125 round-trip flights between New York and Beijing, points out Payal Dhar in the university’s 2020 research paper ‘The carbon impact of artificial intelligence’. Again, a study from MIT Technology Review (2019) showed that the current cloud infrastructure has a greater impact than the entire aviation industry.
Benefits are in the balance
On top of this, the increasing demand for advanced AI technology weighs on our planet in terms of electronic waste, as it causes soil and water pollution, states the Global Research and Consulting Group Insights in its ‘The Environmental Impact of AI’ study.
The question at this point is whether the benefits of AI technology outweigh its drawbacks in terms of resource demand. Currently, the role that it plays in global warming is under scrutiny and no conclusive answers have been reached.
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