NeurIPS 2021 Workshop Explores Machine Learning's Role in Fighting Climate Change
A dedicated NeurIPS workshop examines how artificial intelligence can help reduce greenhouse gas emissions and aid climate adaptation, while cautioning against viewing tech as a silver bullet.
The NeurIPS 2021 workshop on tackling climate change with machine learning gathers researchers and practitioners to explore how AI assists in reducing greenhouse gas emissions and helping society adapt to environmental shifts. The organizers emphasize that while machine learning is not a silver bullet, it serves as an invaluable tool for addressing this complex global challenge through both theoretical advances and real-world technology deployment.
A standout moment of the digital event features an invited talk by MIT Institute Professor Daron Acemoglu, who challenges the overly optimistic view that AI alone solves the climate crisis. He presents evidence that AI usage in US businesses often drives inequality and wage reduction rather than delivering broad environmental benefits, arguing that significant carbon taxes and direct investments in green technologies remain essential.
Acemoglu points out that although renewable energy advances respond well to subsidies and fossil fuel pricing, this progress currently slows down. He further notes a lack of evidence that big tech companies lead the charge against climate change, suggesting instead that large energy companies frequently undermine the transition to renewable power sources.