A Global Comparison of Schemas, Transparency, and Interoperability in Public-Sector AI Registers and Inventories· 全球公共部门 AI 登记制度对比
Artificial intelligence (AI) registers and inventories aim to make governmental AI visible, but their institutional scope, schemas, and reporting practices construct different representations of public-sector AI. We compare 8,368 records from country-specific and transnational inventories covering 72 countries. Across 23 harmonized fields, registers shared a descriptive core but rarely requested information about appeals, risks, legal bases, or external evaluation. We found that broad schemas often contained substantial missingness, schema similarity showed no significant patterned convergence, and multiple sources covering the same jurisdictions overlapped only selectively. Based on these findings, we synthesize a layered visibility framework that shows how register records reflect disclo
研究对比了72国公共部门AI登记制度的异同。
- 核心方法
- 对比分析8,368条记录，涵盖23个标准化字段，评估各国AI登记制度的范围、模式和报告实践。
- 适合谁读
- 研究者、政策制定者、公共部门管理者
- 要解决的问题
- 不同国家的公共部门AI登记制度在信息覆盖、透明度和互操作性方面存在较大差异，需要一个统一框架来评估。
- 关键实验
- 分析了8,368条记录，从72个国家的国家和跨国登记制度中提取数据。
- 主要贡献
- 提出了一种分层可见性框架，以更全面地理解公共部门AI登记制度的信息披露方式。
- 意义与局限
- 研究为优化公共部门AI治理提供了理论基础，但也指出现有登记制度存在信息缺失和有限的互操作性。