By Ruby Lister
AI systems are the latest and greatest tools that technology companies praise as the next best way to fight climate change. Here’s how it works: first, the technology company sells an AI system to a corporation. Then, the AI system further automates the corporation, making its system run more effectively. This results in the corporation improving its energy efficiency and reducing its overall emissions.
Undoubtedly, this is a promising pathway toward sustainability and efficiency. AI systems can be adopted by virtually every sector, including energy, agriculture, and transportation. As outlined by Forbes, AI could help mitigate climate change through emission reduction and removal. Furthermore, it could increase resilience through hazard forecasting and exposure management. This could create a transparent and adaptive corporate landscape, leading to renewed confidence in ESG principles. This viewpoint is widely accepted, and according to a 2022 BCG Climate AI Survey Report, 87% of private and public sector CEOs believe AI is essential in the fight against climate change.
A prevalent example is a recent partnership between Microsoft and Suncor Energy Inc. to produce “Suncor 4.0,” a plan to transform the oilsands giant’s carbon footprint using Microsoft’s cloud computing, big data, and machine learning. The partnership has the potential to not only reduce Suncor’s emissions but also improve safety, reduce operating costs, and streamline profit generation. Suncor is optimistic that the use of AI will have widespread benefits: “Digital technologies will be a means to draw superior insights from data and will open new ways to drive improved economic, social and environmental performance.”
However, despite the extensive approval of AI systems for climate change, there is a growing base of scholars, companies, and citizens who believe using AI systems to fight corporations’ emissions could exacerbate climate change issues. In the case of the Microsoft and Suncor deal, the improved efficiency of the oilsands giant would increase extracting productivity, resulting in increased natural resource depletion and greenhouse gas emissions. This is only the tip of the iceberg. The production and application of AI systems are enormous sources of environmental pollution within themselves. For example, “the carbon footprint of training a single big language model is equal to around 300,000 kg of carbon dioxide emissions. This is equivalent to 125 round-trip flights between New York and Beijing.” And, of course, the increased adoption of AI systems could result in the digitization of entire job sectors, offsetting the livelihoods of citizens.
In conclusion, AI systems could play a dual role in the fight against climate change. While there are clear short-term benefits for a corporation’s efficiency and resilience, there are long-term issues in creating and using AI systems on environmental, economic, and social levels. To truly align with ESG principles, every cost of an AI system during both its creation and use must be accounted for.
References:
Sources
- https://www.forbes.com/sites/markminevich/2022/07/08/how-to-fight-climate-change-using-ai/?sh=214db10e2a83
- https://financialpost.com/commodities/energy/suncor-strikes-deal-with-microsoft-for-digital-transformation-in-first-for-the-oilsands
- https://www.jwnenergy.com/article/2019/11/13/suncor-strategic-alliance-microsoft-azure-become-p/