Artificial Intelligence in Achieving Sustainable Development Goals
AI can support sustainable development but also poses risks, requiring regulation to ensure transparency, safety, and ethical standards.
AI & Environment Resource HubGovernance, accountability, equity, finance, and social context relevant to the collection; not necessarily an environmental impact study.
Browse all 522 resources →Counts reflect provisional metadata classification, not measured environmental impact. A record may belong to multiple topics.
Share of the 522 records in this view. Pathways can overlap; bars do not add to 100%.
Research papers and scholarly literature on impacts, applications, and methods.
AI can support sustainable development but also poses risks, requiring regulation to ensure transparency, safety, and ethical standards.
Organizations are reducing electricity-related carbon emissions by adjusting energy use based on carbon intensity data and securing renewable energy through power purchase agreements.
AI's growing energy demand worsens air quality, imposing significant public health costs, especially on disadvantaged communities, necessitating better reporting and mitigation strategies.
Integrating citizen science into AI can enhance sustainability efforts by addressing AI challenges like social bias while leveraging synergies for improved monitoring and progress toward sustainable development.
Missing metadata is a curation task, not evidence of absent research or activity. The Resource Hub does not currently contain a validated incident dataset, expert survey, or measurements of net environmental benefit.