On September 6th, we hosted an AI Deep Dive Session with J.B. Ruhl and Ethan Thorpe from the Private Climate Governance Lab, where we discussed the challenges of using AI for climate adaptation and mitigation planning. Their project aims to leverage AI to process large volumes of PDFs and help identify trends, sources, and solutions for climate governance.
Highlights:
- Purpose: The session explored how AI can assist in extracting valuable data from climate adaptation and mitigation plans to support local governments and private organizations in planning for climate risks.
- Challenges: J.B. and Ethan emphasized their difficulties with managing the large corpus of documents—some exceeding hundreds of pages—and the need for accuracy in AI-generated summaries.
- AI Applications: We discussed potential AI solutions for summarizing documents, recognizing threats, and highlighting mitigation measures across various regions, with a focus on developing automated processes for smaller cities lacking resources.
Session Insights:
- AI could significantly expedite the process of climate adaptation planning by providing accurate, summarized data for decision-making, reducing the time and resources needed for manual document review.
- Customized AI tools could support smaller municipalities in developing climate action plans by leveraging knowledge from larger city initiatives, thereby closing the resource gap.
Conclusion:
The AI Deep Dive with J.B. Ruhl and Ethan Thorpe opened up exciting possibilities for how AI can assist in processing extensive documentation for climate adaptation and mitigation. With the right tools, AI has the potential to empower cities of all sizes to create robust climate action plans, addressing both local and global environmental challenges.
Are you interested in being a part of the research team? Contact us at datascience@vanderbilt.edu.