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  Responsibility under uncertainty: which climate decisions matter most?

Botta, N., Brede, N., Crucifix, M., Ionescu, C., Jansson, P., Li, Z., Martínez-Montero, M., Richter, T. (2023): Responsibility under uncertainty: which climate decisions matter most? - Environmental Modeling and Assessment, 28, 337-365.
https://doi.org/10.1007/s10666-022-09867-w

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 Creators:
Botta, Nicola1, Author              
Brede, Nuria1, Author              
Crucifix, Michel 2, Author
Ionescu, Cezar 2, Author
Jansson, Patrik 2, Author
Li, Zheng 2, Author
Martínez-Montero, Marina2, Author
Richter, Tim 2, Author
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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Free keywords: -
 Abstract: We propose a new method for estimating how much decisions under monadic uncertainty matter. The method is generic and suitable for measuring responsibility in finite horizon sequential decision processes. It fulfills “fairness” requirements and three natural conditions for responsibility measures: agency, avoidance and causal relevance. We apply the method to study how much decisions matter in a stylized greenhouse gas emissions process in which a decision maker repeatedly faces two options: start a “green” transition to a decarbonized society or further delay such a transition. We account for the fact that climate decisions are rarely implemented with certainty and that their consequences on the climate and on the global economy are uncertain. We discover that a “moral” approach towards decision making — doing the right thing even though the probability of success becomes increasingly small — is rational over a wide range of uncertainties.

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Language(s): eng - English
 Dates: 2022-10-232023-02-022023-06
 Publication Status: Finally published
 Pages: 29
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Attribution
Research topic keyword: Climate Policy
Research topic keyword: Policy Advice
Model / method: Decision Theory
Model / method: Open Source Software
Model / method: Quantitative Methods
OATYPE: Hybrid - DEAL Springer Nature
DOI: 10.1007/s10666-022-09867-w
 Degree: -

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Project name : TiPES
Grant ID : 820970
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Environmental Modeling and Assessment
Source Genre: Journal, SCI, Scopus, p3
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Publ. Info: -
Pages: - Volume / Issue: 28 Sequence Number: - Start / End Page: 337 - 365 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals126
Publisher: Springer