Potential futures for the IPCC’s approach to artificial intelligence

During the first six assessment cycles of the Intergovernmental Panel on Climate Change (IPCC), generative artificial intelligence (AI) tools were not widely available. This has rapidly changed. The IPCC will need to make choices about how to use artificial intelligence powered applications in literature identification, literature assessment, and communicating the contents of the report. These are not merely technical decisions, but sociopolitical challenges, as the IPCC has a social function of creating a shared basis of reality for addressing climate change. To explore these challenges, this paper describes four scenarios of potential AI development: rapid adoption of AI agents, perceptions of superior AI reliability, caution among the research community, and public backlash to AI. If the IPCC can navigate these emergent challenges, there is an opportunity for it to serve as a learning opportunity for other institutions grappling with how to do scientific assessment in a world with generative AI. Developments in generative Artificial Intelligence and society’s perception of its safety shape four distinct scenarios of genAI use, from fast adoption to public backlash, that will shape socio-political challenges for the Intergovernmental Panel on Climate Change.

Authors

Institutions

Publication Details

Journal
Communications Earth & Environment
Published
2026-04-27
DOI
https://doi.org/10.1038/s43247-026-03514-y
Primary Topic
Climate Change Communication and Perception
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Potential futures for the IPCC’s approach to artificial intelligence

Oliver Geden, Holly Jean Buck, Shinichiro Asayama, Alaa Al Khourdajie
Communications Earth & Environment
Climate Change Communication and Perception
article

Potential futures for the IPCC’s approach to artificial intelligence

Oliver Geden, Holly Jean Buck, Shinichiro Asayama, Alaa Al Khourdajie
article en

Abstract

During the first six assessment cycles of the Intergovernmental Panel on Climate Change (IPCC), generative artificial intelligence (AI) tools were not widely available. This has rapidly changed. The IPCC will need to make choices about how to use artificial intelligence powered applications in literature identification, literature assessment, and communicating the contents of the report. These are not merely technical decisions, but sociopolitical challenges, as the IPCC has a social function of creating a shared basis of reality for addressing climate change. To explore these challenges, this paper describes four scenarios of potential AI development: rapid adoption of AI agents, perceptions of superior AI reliability, caution among the research community, and public backlash to AI. If the IPCC can navigate these emergent challenges, there is an opportunity for it to serve as a learning opportunity for other institutions grappling with how to do scientific assessment in a world with generative AI. Developments in generative Artificial Intelligence and society’s perception of its safety shape four distinct scenarios of genAI use, from fast adoption to public backlash, that will shape socio-political challenges for the Intergovernmental Panel on Climate Change.

Communications Earth & EnvironmentVol. 7(1)
Stiftung Wissenschaft und Politik, German Institute for International and Security Affairs (DE), International Institute for Applied Systems Analysis (AT), National Institute for Environmental Studies (JP), Imperial College London (GB), University at Buffalo, State University of New York (US)
HORIZON EUROPE Framework Programme
Climate action
Openalex Percentile: Top 9%
Climate Change Communication and Perception
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.