提出参与式AI生命周期，让边缘群体共同塑造算法全链条。
Co-Producing AI: Toward an Augmented, Participatory Lifecycle
- 构建五阶段协同流程：共定义、共设计、共实施、共部署、共维护。
- 强调多元协作与权力共享，以减少算法对弱势群体的伤害。
- 适合关注伦理治理与包容性AI的研究者和实践者。
尽管已采取多种措施缓解人工智能算法固有的风险与偏见，这些算法仍可能对文化边缘群体造成不成比例的影响。为应对这些问题，已有研究提出伦理准则和技术手段以促进算法公平。本文基于设计正义、扩展学习理论及近期关于参与式AI的实证研究，主张要减轻此类危害，需从根本上重构AI生产流程。新的流程应聚焦协同生产、多样性、公平性、包容性（DEI）及跨学科合作。我们提出一个由五个相互关联阶段组成的增强型AI生命周期：共定义、共设计、共实施、共部署与共维护。该模型源自四场跨学科工作坊，核心理念是分布式权威与迭代知识交流。最后，我们将该生命周期与多个主流伦理框架关联，并指出未来在推广参与式治理方面亟待解决的关键研究问题。
原文摘要 · Abstract (English)
Despite efforts to mitigate the inherent risks and biases of artificial intelligence (AI) algorithms, these algorithms can disproportionately impact culturally marginalized groups. A range of approaches has been proposed to address or reduce these risks, including the development of ethical guidelines and principles for responsible AI, as well as technical solutions that promote algorithmic fairness. Drawing on design justice, expansive learning theory, and recent empirical work on participatory AI, we argue that mitigating these harms requires a fundamental re-architecture of the AI production pipeline. This re-design should center co-production, diversity, equity, inclusion (DEI), and multidisciplinary collaboration. We introduce an augmented AI lifecycle consisting of five interconnected phases: co-framing, co-design, co-implementation, co-deployment, and co-maintenance. The lifecycle is informed by four multidisciplinary workshops and grounded in themes of distributed authority and iterative knowledge exchange. Finally, we relate the proposed lifecycle to several leading ethical frameworks and outline key research questions that remain for scaling participatory governance.
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