arXiv:2501.17899cs.CYcs.AI2025-01ICML被引 8

主张普通人应参与AI发展与治理,推动集体数据所有权与透明设计。

The Right to AI

  • 将AI视为社会基础设施,倡导社区参与共建
  • 提出四层参与模型,应对生成式代理与文化差异挑战
  • 适合关注AI伦理、数字公平与公民参与的研究者

本文提出「AI权利」概念,主张个人与社群应在塑造其生活的AI系统发展中实现有意义的参与。受亨利·列斐伏尔「城市权」思想启发,本文将AI重新定义为社会基础设施,而非专家设计的产品。针对生成式代理、大规模数据提取及多元文化价值观带来的治理复杂性,论文强调草根参与方法可缓解偏见、提升社会响应性。指出数据具有社会生产属性,应由集体管理与拥有。基于雪莉·阿恩斯坦的公民参与阶梯理论,结合九个案例研究,构建了四层级的AI权利模型,用于定位当前范式并展望理想未来。提出包容性数据所有权、透明设计流程与利益相关方主导监督等建议。同时探讨市场主导与国家中心两种替代路径,认为参与式方法在技术效率与民主合法性间取得更优平衡。

原文摘要 · Abstract (English)

This paper proposes a Right to AI, which asserts that individuals and communities should meaningfully participate in the development and governance of the AI systems that shape their lives. Motivated by the increasing deployment of AI in critical domains and inspired by Henri Lefebvre's concept of the Right to the City, we reconceptualize AI as a societal infrastructure, rather than merely a product of expert design. In this paper, we critically evaluate how generative agents, large-scale data extraction, and diverse cultural values bring new complexities to AI oversight. The paper proposes that grassroots participatory methodologies can mitigate biased outcomes and enhance social responsiveness. It asserts that data is socially produced and should be managed and owned collectively. Drawing on Sherry Arnstein's Ladder of Citizen Participation and analyzing nine case studies, the paper develops a four-tier model for the Right to AI that situates the current paradigm and envisions an aspirational future. It proposes recommendations for inclusive data ownership, transparent design processes, and stakeholder-driven oversight. We also discuss market-led and state-centric alternatives and argue that participatory approaches offer a better balance between technical efficiency and democratic legitimacy.

AI治理数据所有权公民参与伦理框架

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