LSE: Public lectures and events Harnessing AI: safeguarding high-integrity data for climate action
Jun 24, 2025
Sylvan Lutz, a researcher focused on automating net-zero assessments, joins John Cardoso Silva, an AI and social science expert, along with Amy Fisher, a director at Moir AI, and David McNeil, a VP of climate research. Melissa Chapman, an environmental policy professor, rounds out the panel. They explore how AI can transform climate action through high-quality data while warning against the risks of misinformation and greenwashing. The discussion emphasizes the need for responsible AI development, transparency, and community consent to navigate these challenges effectively.
AI Snips
Chapters
Transcript
Episode notes
AI's Environmental Trade-offs
- AI's environmental impact can be high but manageable with responsible energy sourcing.
- Its potential emissions reductions in sectors like power and agriculture could significantly outweigh these costs.
Human Oversight Is Essential
- Humans must critically oversee AI assessments to ensure data quality.
- Analysts should verify at every step to catch errors and understand AI's data use.
Environmental AI Bias and Responsibility
- Responsible environmental data science requires transparency, accountability, and bias awareness.
- AI can propagate and omit biases, especially impacting marginalized communities in climate data.