Six key policy recommendations for promoting environmentally friendly AI

In this Artificial Footprint series, we have examined the potential environmental impacts of AI, but how can we improve these things? Based on the issues we’ve discussed and recommendations from the literature, we have proposed a set of policy interventions that could help minimise the environmental impacts of AI.

1. Increase energy efficiency

Firstly, there is a need to increase energy efficiency - not just in the design of data centres, processors and other hardware underpinning AI, but also in the design of AI algorithms and programs. This will necessitate promoting a culture that prioritises efficiency, rather than just building the biggest and most accurate models possible. In other words, encouraging a culture of ‘Green AI’ over ‘Red AI’. This may also require running AI programs on processors in locations and data centres that have more efficient running standards and higher proportions of renewable electricity.

2. Consider the entire tech ecosystem

Secondly, consider the entire tech ecosystem and all the systems that underpin AI and ICT hardware, promote ethical design standards which aim to minimise the impacts on the environment that these systems have, and where possible, promote the sourcing of hardware and materials from ethical sources.

3. Mandate transparency and choice

Thirdly, mandate transparency and accountability. Promote a culture of openness and responsibility, encourage and mandate more reporting of how, where and when AI is trained and hardware used in order to ensure that customers are as informed as possible.

Use procurement levers to disadvantage companies that do not do this, and work with social responsibility initiatives like the “B Corporation” mark to ensure environmentally sustainable AI use is included in their criteria.

Transparency alone will not be enough, there is also a need to ensure that customers have real choice (to move away from unethical companies) and methods to hold corporations to account for harmful practices (most likely through legislation).

4. Curb environmentally harmful AI use

Fourthly, curb the use of AI in environmentally harmful practices, for example, discourage the use of AI in maximising resource extraction. Ensure that where AI is used to maximise production and resource extraction, it accounts for negative externalities and does not simply seek to maximise efficiency or output regardless of negative external impacts.

5. Integrate climate policy into AI policy

There is a need to better integrate climate policy into all aspects of policy making, in this case tech and AI policy. Too often climate and environment is seen as a separate policy area that policy makers in other domains do not need to worry about. Instead, we need to promote the consideration of climate and environmental concerns in all aspects of policy making.

One example would be the Wellbeing of Future Generations (Wales) Act, which requires public bodies to consider the long-term impact of their decisions to prevent problems including climate change.

6. Improve public awareness

Ensure that the public are informed about the wider issues with AI, and how their use of AI can impact the environment. Educate around how different AI tasks can result in widely different related emissions. Indicate which companies are meeting ethical or environmental guidelines around AI, and make this information widely available.

To read our full paper exploring AI’s environmental impact, click here.