Common errors in Generative AI systems used for knowledge extraction in the climate action domain
Year: 2024
Type: article
Abstract: Large Language Models (LLMs) and, more specifically, the Generative Pre-Trained Transformers (GPT) can help stakeholders in climate action to explore digital knowledge bases, extract and utilize climate action knowledge in sustainable manner. However, LLMs are "probabilistic models of knowledge bases" that excel at generating convincing texts but cannot be entirely relied upon due to the probabilistic nature of the information produced. This brief report illustrates the problem space by shedding some light on the issues of incomplete answers, hallucinations, and misinformation threats.
Source: Open Research Europe
Authors: Denis Havlik, Marcelo Rita Pias
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $841
Award: G5457987452
OpenAlex ID: W4403448927