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This chapter explores the challenge of building global consensus on AI risk management through a multi-dimensional governance lens. Anchored in the NIST AI Risk Management Framework, it proposes a unified analytical structure to assess AI's dual potential to exacerbate or mitigate risks across four key domains—climate and energy, water systems, Biodiversity & Waste Management, and society. Emphasizing transparency, accountability, and inclusivity, the chapter advocates for coordinated international efforts to develop common standards, institutional mechanisms, and participatory processes. It also proposes the creation of an UN-led AI Risk Council to facilitate global alignment and concludes with actionable recommendations aimed at advancing sustainable, ethical, and evidence-based AI governance in support of human well-being.

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Consensus Building in AI Risk Management: Approaches to Global Cooperation

  • 章节

  • 发表日期：

    2026年

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  • Shen Qu,
  • Qi Zhou,
  • Jin Lin,
  • Yiyi Cao,
  • Yifan Song,
  • Yawen Ben,
  • Liyuan Lei,
  • Fengming Zhang,
  • Qiang Huang

摘要

This chapter explores the challenge of building global consensus on AI risk management through a multi-dimensional governance lens. Anchored in the NIST AI Risk Management Framework, it proposes a unified analytical structure to assess AI's dual potential to exacerbate or mitigate risks across four key domains—climate and energy, water systems, Biodiversity & Waste Management, and society. Emphasizing transparency, accountability, and inclusivity, the chapter advocates for coordinated international efforts to develop common standards, institutional mechanisms, and participatory processes. It also proposes the creation of an UN-led AI Risk Council to facilitate global alignment and concludes with actionable recommendations aimed at advancing sustainable, ethical, and evidence-based AI governance in support of human well-being.