AI透明度：治理合规还是利益相关者需求
SOURCE / arXiv cs.CY · AI Transparency: Governance Compliance or Stakeholder Requirements?
原文
AI Transparency: Governance Compliance or Stakeholder Requirements?
完整原文
arXiv:2606.30652v1 Announce Type: new Abstract: Transparency is increasingly mandated for public-sector AI systems, with organisations required to publish statements describing their AI use and oversight arrangements. However, the existence of such artefacts is often treated as equivalent to transparency itself, despite limited evidence that they proportionately serve relevant stakeholder groups. From a requirements engineering perspective, this raises a validation concern: compliance with mandated disclosure criteria does not necessarily ensure transparency adequacy for stakeholders with different levels of risk exposure, decision control, and involvement. This paper presents an empirical analysis of 92 publicly available AI transparency statements published by Australian Government agencies under the national AI governance mandate. We introduce the stakeholder Risk--Control--Involvement--Need (RCIN) framework to differentiate stakeholder classes according to their structural position and transparency needs. Using a structured rubric derived from the mandated criteria, we evaluate how both the mandate and published statements are calibrated to each stakeholder class. The findings show that while structural compliance is widespread, transparency calibration is uneven. Criteria serving high-control stakeholders are consistently realised, whereas criteria most critical for high-risk, low-control stakeholders are fewer and less substantively addressed. We conceptualise this as the Transparency Illusion: a condition in which transparency appears satisfied through compliant artefacts yet remains unevenly calibrated to stakeholders bearing the greatest exposure to AI-supported decisions. The study frames transparency as a stakeholder-calibrated validation problem, demonstrating that artefact-level compliance does not constitute requirements validation in this context.
归纳
该研究探讨了公共部门AI系统透明度要求中合规性与利益相关者需求之间的差距。通过分析澳大利亚政府机构根据国家AI治理授权发布的92份公开透明度声明，引入风险-控制-参与-需求（RCIN）框架，区分不同利益相关者类别及其透明度需求。评估发现，虽然结构性合规普遍存在，但透明度校准不均：服务于高控制利益相关者的标准得到一致实现，而对高风险、低控制利益相关者至关重要的标准较少且实质性不足。研究将这一现象概念化为“透明度幻觉”，即通过合规性文件看似满足透明度要求，但实际未均衡校准至受AI决策影响最大的群体。研究将透明度视为一个利益相关者校准的验证问题，表明文件层面的合规并不等同于需求验证。
点评
该研究揭示的“透明度幻觉”警示：仅满足文件层面的合规性要求，可能掩盖对高风险、低控制利益相关者实质知情权的侵害，构成监管形式主义风险。
法律视角点评
AI 生成 · 人工审核核心关切
该研究揭示的“透明度幻觉”警示：仅满足文件层面的合规性要求，可能掩盖对高风险、低控制利益相关者实质知情权的侵害，构成监管形式主义风险。
实务启示
中国法律人审查AI系统透明度时，应引入利益相关者分类校准机制，避免仅以形式合规替代对受影响群体的实质信息保障。