Large companies in the EU are legally required to report their greenhouse gas (GHG) emissions. Yet pulling this information manually from long PDF sustainability reports is slow and error-prone.
Large companies in the EU are legally required to report their greenhouse gas (GHG) emissions. Yet pulling this information manually from long PDF sustainability reports is slow and error-prone. Many teams try to speed up the process with automation—for example by using Large Language Models (LLMs), AI systems that read text and produce answers.
Project coordinator and postdoctoral researcher at the Social Data Science and AI Lab (SODA Lab), Dr. Malte Schierholz urges caution though: “With automatic extraction methods, it’s easy to fully trust the LLM’s output and overlook measurement errors that occur frequently.” Because the trend of increased automation is promising but risky at the same time, the research group Greenhouse Gas Insights and Sustainability Tracking (GIST) set out to build a reliable point of reference for collecting emission data.
Read More at: Ludwig-Maximilians-Universitat Munchen
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