Environmental sustainability issues
The massive computational power required by large generative AI models results in substantial energy use, carbon emissions, and resource consumption. Unconstrained, generative AI risks significantly accelerating climate change and pollution.
For example, training a single natural language model can emit over 600,000 pounds of carbon dioxide, which equals the lifetime emissions of dozens of cars. Analysis suggests that by 2025, computational needs for leading models could rival mid-sized nations in emissions.
Prudent governance is urgently required to curb these impacts through renewable energy requirements, efficiency innovations such as model distillation, comprehensive life cycle assessments, carbon accounting, and strong environmental policies and incentives.
Aligning exponential AI progress and climate action will require collective commitment from researchers, companies, policymakers, and the public. We must steward these technologies...
