把信任看作关系而非功能，用非洲集体哲学构建更公平的AI
Beyond Abstract Compliance: Operationalising trust in AI as a moral relationship
- 将信任视为动态关系，强调参与和互敬
- 通过社区全程参与逐步建立信任
- 适合关注AI伦理与社会公平的研究者
主流方法如欧盟《可信AI框架》将信任视为可设计、评估与治理的属性，但忽视了信任的主观性、文化嵌入性和关系本质。本文提出扩展的信任原则，融入常规开发流程，将信任视为包含透明度与相互尊重的动态、历时性关系。借鉴关系伦理及非洲集体主义哲学，强调包容性、参与式过程与长期社区关系的重要性。在AI全生命周期中持续引入社区参与，可逐步建立有意义的信任关系，推动更具公平性与情境敏感性的AI系统。文中以医疗与教育领域的两个应用场景为例，说明基于非洲关系伦理的信任赋能原则如何落地实施。
原文摘要 · Abstract (English)
Dominant approaches, e.g. the EU's "Trustworthy AI framework", treat trust as a property that can be designed for, evaluated, and governed according to normative and technical criteria. They do not address how trust is subjectively cultivated and experienced, culturally embedded, and inherently relational. This paper proposes some expanded principles for trust in AI that can be incorporated into common development methods and frame trust as a dynamic, temporal relationship, which involves transparency and mutual respect. We draw on relational ethics and, in particular, African communitarian philosophies, to foreground the nuances of inclusive, participatory processes and long-term relationships with communities. Involving communities throughout the AI lifecycle can foster meaningful relationships with AI design and development teams that incrementally build trust and promote more equitable and context-sensitive AI systems. We illustrate how trust-enabling principles based on African relational ethics can be operationalised, using two use-cases for AI: healthcare and education.
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