https://www.nature.com/articles/d41586-024-02680-3
The recommendations
To achieve meaningful progress, it is essential that all stakeholders take proactive steps to ensure the sustainable growth of AI. The following recommendations provide some specific guidance to the variety of players involved.
Get developers involved. AI researchers and developers are at the core of innovation in this field. By considering sustainability throughout the development and deployment cycle, they can significantly reduce AI’s environmental impact from the outset. To make it standard practice to measure and publicly share the energy use of models (for example, in a ‘model card’ setting out information such as training data, evaluations of performance and metadata), it’s essential to get developers on board.
Drive the market towards sustainability. Enterprises and product developers play a crucial part in the deployment and commercial use of AI technologies. Whether creating a standalone product, enhancing existing software or adopting AI for internal business processes, these groups are often key decision makers in the AI value chain. By demanding energy-efficient models and setting procurement standards, they can drive the market towards sustainable solutions. For instance, they could set baseline expectations (such as requiring that models achieve at least two stars according to the AI Energy Star scheme) or support sustainable-AI legislation.
Disclose energy consumption. AI users are on the front lines, interacting with AI products in various applications. A preference for energy-efficient solutions could send a powerful market signal, encouraging developers and enterprises to prioritize sustainability. Users can nudge the industry in the right direction by opting for models that publicly disclose energy consumption. They can also use AI products more conscientiously, avoiding wasteful and unnecessary use.
Strengthen regulation and governance. Policymakers have the authority to treat sustainability as a mandatory criterion in AI development and deployment. With recent examples of legislation calling for AI impact transparency in the European Union and the United States, policymakers are already moving towards greater accountability. This can initially be voluntary, but eventually governments could regulate AI system deployment on the basis of the efficiency of the underlying models.
Regulators can adopt a bird’s-eye view, and their input will be crucial for creating global standards. It might also be important to establish independent authorities to track changes in AI energy consumption over time.
