English

Improving International Climate Policy via Mutually Conditional Binding Commitments

Computers and Society 2023-07-27 v1 Artificial Intelligence

Abstract

The Paris Agreement, considered a significant milestone in climate negotiations, has faced challenges in effectively addressing climate change due to the unconditional nature of most Nationally Determined Contributions (NDCs). This has resulted in a prevalence of free-riding behavior among major polluters and a lack of concrete conditionality in NDCs. To address this issue, we propose the implementation of a decentralized, bottom-up approach called the Conditional Commitment Mechanism. This mechanism, inspired by the National Popular Vote Interstate Compact, offers flexibility and incentives for early adopters, aiming to formalize conditional cooperation in international climate policy. In this paper, we provide an overview of the mechanism, its performance in the AI4ClimateCooperation challenge, and discuss potential real-world implementation aspects. Prior knowledge of the climate mitigation collective action problem, basic economic principles, and game theory concepts are assumed.

Cite

@article{arxiv.2307.14267,
  title  = {Improving International Climate Policy via Mutually Conditional Binding Commitments},
  author = {Jobst Heitzig and Jörg Oechssler and Christoph Pröschel and Niranjana Ragavan and Yat Long Lo},
  journal= {arXiv preprint arXiv:2307.14267},
  year   = {2023}
}

Comments

Presented at AI For Global Climate Cooperation Competition, 2023 (arXiv:cs/2307.06951)

R2 v1 2026-06-28T11:40:50.789Z