从协议到证据：服务于公共利益的AI的有限主张
From Protocols to Evidence: Bounded Claims for AI in Service of the Common Good
- University of Notre Dame（圣母大学）
- LUISS Guido Carli University（路易斯大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出断裂测试和RISE AI架构，区分证据受限部署与测量受限治理，以实现基于证据的有限AI主张，服务公共利益。
AI中文摘要：
人工智能不仅仅是制造了一个治理问题。它还能揭示机构在哪些方面未能提供响应性、归属感、关怀和问责。一旦部署，AI便成为对这些状况的干预。它可以修复、加剧、替代或掩盖其所遇到的失败。因此，负责任的AI必须同时评估系统及其引入的制度性断裂。从原则到协议的转变已经在进行中。欧盟《人工智能法案》、NIST AI RMF、ISO/IEC 42001以及保证实践将承诺转化为角色、要求、记录、监督和评估。更困难的问题是这些协议实际上确立了什么，它们未触及谁的权力，以及测量必须在何处停止。教皇利奥十四世的《Magnifica Humanitas》提供了一个更广泛的道德框架，以尊严、技术权力和公共利益为中心。基于该框架，我们开发了一个断裂测试，将制度基线与系统评估联系起来。我们区分了证据受限的部署（将主张限制在实际评估过的内容上）与测量受限的治理（记录有利证据无法推翻的约束）。在这些限制内，RISE AI提供了一种架构，用于就责任、包容性、安全性和赋权做出有限的、基于证据的主张。负责任的AI需要更好的工程、制度修复以及持续的道德和政治判断。
英文摘要：
Claims that Artificial Intelligence systems improve decisions, broaden access, reduce harm, or empower users can exceed what their evaluation establishes. Predictive performance alone does not establish safety, the presence of oversight does not establish meaningful control, and faster task completion does not establish understanding or choice. Evaluation must account for unreliable outputs and uneven performance, but also for overreliance, weakened recourse, and displaced human expertise. The harder questions are what the evidence warrants, which relations of power remain unexamined, and where measurement must stop. Assessing improvement requires examining what institutions value and the conditions AI is asked to address. AI is both revelation and intervention. Its use can reveal unmet human needs and assumptions about what matters. Once deployed, it can repair, compound, substitute for, or conceal existing failures. We develop a rupture test that evaluates deployment against explicit human and non-AI baselines. Drawing on Pope Leo XIV's Magnifica Humanitas, we examine dignity and the common good alongside questions of who owns AI infrastructure and who controls its use. These commitments shape judgments about improvement; evidence alone cannot establish moral or political legitimacy. We distinguish evidence-bounded deployment, which limits claims to what has been evaluated, from measurement-bounded governance, which records constraints that favorable evidence cannot override. RISE AI provides an evidence architecture for making bounded claims about Responsibility, Inclusivity, Safety, and Empowerment. It records what is claimed, who answers for it, what evidence supports it, and what would require the claim to be qualified, revised, or withdrawn.
