Decoding green justice: AI-assisted analysis of environmental court rulings in India
This project leverages AI-assisted methods to analyse large-scale legal datasets with around 70% accuracy, enhancing the monitoring of environmental litigation outcomes. Findings reveal that approximately 35% of rulings are environmentally favourable, with notable variations across different courts and case types.
Authors
Daniel Chen
Professor, Toulouse School of Economics
Shareen Joshi
Assistant Professor, Georgetown UniversityOlexiy Kyrychenko
Assistant Professor, Radboud UniversityViknesh Nagarathinam
Research Consultant, World BankPeter Neis
Postdoctoral Researcher, Centre d’Etudes et de Recherches sur le Développement International (CERDI)Shashank Singh
Manager, Blended and Innovative Blue Finance, WWF-
Behrer-et-al-Policy-Brief-February-2025.pdf
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- AI-assisted methods can analyse large-scale legal datasets with approximately 70% accuracy, enabling more effective monitoring of environmental litigation outcomes.
- Large language models (LLMs) like ChatGPT-4 can assess whether court rulings have a positive environmental impact with accuracy rates that approach human expert analysis.
- Analysis of 12,615 environmental court cases in India reveals that approximately 35% of rulings are intended to be favourable to the environment, with significant variations across courts and case types.