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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title ChatClimate: Grounding conversational AI in climate science
Organization Unit
Authors
  • Saeid Ashraf Vaghefi
  • Dominik Stammbach
  • Veruska Muccione
  • Julia Bingler
  • Jingwei Ni
  • Mathias Kraus
  • Simon Allen
  • Chiara Colesanti-Senni
  • Tobias Wekhof
  • Tobias Schimanski
  • Glen Gostlow
  • Tingyu Yu
  • Qian Wang
  • Nicolas Webersinke
  • Christian Huggel
  • Markus Leippold
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title Communications Earth & Environment
Publisher Nature Publishing Group
Geographical Reach international
ISSN 2662-4435
Volume 4
Page Range 480
Date 2023
Abstract Text Large Language Models have made remarkable progress in question-answering tasks, but challenges like hallucination and outdated information persist. These issues are especially critical in domains like climate change, where timely access to reliable information is vital. One solution is granting these models access to external, scientifically accurate sources to enhance their knowledge and reliability. Here, we enhance GPT-4 by providing access to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6), the most comprehensive, up-to-date, and reliable source in this domain (refer to the ’Data Availability’ section). We present our conversational AI prototype, available at www.chatclimate.ai, and demonstrate its ability to answer challenging questions in three different setups: (1) GPT-4, (2) ChatClimate, which relies exclusively on IPCC AR6 reports, and (3) Hybrid ChatClimate, which utilizes IPCC AR6 reports with in-house GPT-4 knowledge. The evaluation of answers by experts show that the hybrid ChatClimate AI assistant provide more accurate responses, highlighting the effectiveness of our solution.
Free access at DOI
Digital Object Identifier 10.1038/s43247-023-01084-x
Other Identification Number merlin-id:24243
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