Realigning AI technology towards the Sustainable Development Goals

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The rapid expansion of AI infrastructure is creating unprecedented challenges in energy consumption and electronic waste (e-waste) management. Data centres accounted for approximately 1.5% of global electricity consumption in 2024, with their energy demand projected to more than double by 2030⁴. Where electricity generation relies on fossil fuels, this growth compounds greenhouse-gas emissions and complicates decarbonization pathways, hindering progress towards SDG 13 (climate action). Under aggressive growth scenarios, e-waste from generative AI could increase by nearly three orders of magnitude between 2020 and 2030, reaching an estimated five million tonnes⁵. However, less than one quarter of e-waste is formally collected and recycled⁶. Informal practices such as open burning, landfilling and uncontrolled dumping release hazardous substances that contaminate soil, water and air, obstructing advances towards SDGs 12 (responsible consumption and production) and 15 (life on land).

AI technology can be used to effortlessly generate highly realistic but factually incorrect texts, images and videos at low cost, which blurs the boundary between truth and fabrication⁷. The resulting spread of misinformation and synthetic content remains difficult to regulate, and a critical risk is the collapse of public trust in authentic information, dissolving the shared factual foundation essential to SDGs 3 (good health and well-being) and 4 (quality education). This challenge is compounded by the opacity and limited explainability of black-box AI algorithms⁸. When biased outputs or false claims arise, inscrutable decision pathways make it nearly impossible to trace reasoning or assign accountability. This fundamentally threatens SDG 16 (peace, justice and strong institutions), which relies on effective, accountable, and transparent social operation and governance frameworks.

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References

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4. International Energy Agency. Energy and AI: World Energy Outlook Special Report (IEA, 2025).

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Acknowledgements

This study was jointly supported by National Natural Science Foundation of China (NSFC) (grant nos. 42230510; 42371253).

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Feng, R., Li, Z., Fu, B. et al. Realigning AI technology towards the Sustainable Development Goals.
Nat Mach Intell (2026). https://doi.org/10.1038/s42256-026-01271-3

• Version of record:14 July 2026

• DOI
  :https://doi.org/10.1038/s42256-026-01271-3