责任型 AI 研究论文：超越原则与实践差距，将其视为情境化的认知与伦理实践
Beyond the principle-practice gap: Responsible AI as situated epistemic and ethical practice
AI 导读
arXiv 论文提出解释 AI 伦理原则难以落实的新框架，认为"原则与实践差距"并非单纯的执行或合规问题，而是源于机构与职业条件的差异。研究基于对反人口贩卖 AI 系统相关从业者（涵盖执法、商业、研究、幸存者支持领域）的 14 次半结构化访谈，梳理出感知、判断、情境化行动与社会技术物化四个环节。论文主张责任型 AI 治理需要专门的认知基础设施，使受影响社区的知识与潜在危害在设计中被接收并可行。
正文 · 原文
Abstract:Responsible AI scholarship has found that ethical principles are frequently not reflected in AI design and development. Conceptualised as a `gap' between principle and practice, this is framed as a problem of implementation, awareness or compliance, and by implication, a deficit of systems or individual behaviour. This paper sets out an alternative explanation. Drawing on fourteen semi-structured interviews with actors designing and governing AI-enabled anti-trafficking systems across law enforcement, commercial, research, and survivor-support contexts, it argues that such apparent gaps emerge from the varied and complex institutional and professional conditions through which actors come to recognise some issues, but not others, as ethical problems requiring action. We show that epistemic choices are intertwined with ethical judgements, and trace four interconnected moments---perception, judgement, situated action and socio-technical materialisation---through which concerns become intelligible, are weighed and acted upon, and are embedded in technical artefacts and governance arrangements. Actors often hold genuine ethical commitments, but these commitments are shaped by institutional logics and professional moral economies: some concerns are materialised, while others are narrowed, deferred or left unrealised. We show that ethical agency is exercised within and between competing constraints of profession, role, prior experience, and institutional settings. The paper argues that responsible AI governance requires purposeful and well-developed epistemic infrastructures that can cut across these constraints to establish institutional conditions through which the knowledge of affected communities and potential harms becomes receivable and actionable in design.
| Subjects: | Computers and Society (cs.CY); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2611.06709 [cs.CY] |
| (or arXiv:2611.06709v1 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2611.06709 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Thao Do-Ngoc Ms [view email]
[v1]
Wed, 4 Nov 2026 16:08:17 UTC (31 KB)
来源：arXiv cs.AI · arxiv.org