The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations
By Josh Cowls, Andreas Tsamados, Mariarosaria Taddeo, Luciano Floridi. Ai & Society, 2021
379 citations recorded by the source corpus.
In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based, and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment.
Subfields: Economics and Econometrics, Environmental Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/5f6baf6a7342715060c389e9e1c71d23398e0f72
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
Citations in the corpus
- Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation (2023, background): “Although they can be an effective tool to mitigate climate change [89, 90], greenhouse gases emitted by the computationally intensive training processes of complex AI-based systems can exacerbate existing social and ethical challenges linked to AI [91].”
- Aligning artificial intelligence with climate change mitigation (2022, neutral): “In terms of scope, our framework predominantly focuses on algorithm-related impacts, and omits impacts relating to data collection and management, ICT and digitalization more broadly 2,20,23–25 .”
- GPT (Generative Pre-Trained Transformer)— A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions (2023, background): “The models can optimize supply chains for decreased carbon emissions, minimized waste, and improved resource efficiency by assessing elements including transportation routes, packaging materials, and supplier practises [110].”
- Regulating ChatGPT and other Large Generative AI Models (2023, background): “While the carbon footprint of IT and AI is significant and steadily rising [50-54], and training of LGAIMs is particularly resource intensive [136], large models may ultimately create significantly fewer greenhouse gas emissions than their smaller brethren [136, p.”