使AI辅助声明可独立质疑：出版权威与可证伪出版记录协议
Making AI-Assisted Claims Independently Challengeable: Publication Authority and a Protocol for Falsifiable Publication Records
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中文总结 AI 辅助
针对AI辅助声明权威性来源不清的问题，提出出版权威概念及PAC-2026协议，通过六项义务和原子出版转换实现可证伪的出版记录，经实验验证其内部一致性与有界安全性。
中文摘要 AI 辅助
当证据、分析、人类授权、呈现方式和更正历史指向不同状态时，AI辅助声明可能显得具有权威性。溯源、认证和透明度揭示了历史，但单独来看并未规定本文所考察的出版转换。我们将出版权威发展为一种精确状态、不可转让、一次性使用的出版能力，并在PAC-2026（出版问责演算）中实例化，这是一个机器可读的AIJIM协议候选方案。我们评估了其第四个有界语义冻结（SF-4），这是一种为可替换绑定设计的固定配置文件规范。六项义务管辖证据、运行与工件、测量披露、授权、表面对应和生命周期连续性。每项义务产生一个目标绑定见证、局部反例或局部不可验证性；没有任何一项可以补偿另一项。只有一份全新的、完整通过所有检查的记录才能推导出由一次原子出版转换消耗的许可。我们使用了身份向量、对抗性案例、有限模型和历史实现。十个模型探索了110,764个安全可达状态；76个不安全配置产生了预期的违规或观察者反模型。通过其对应检查的读者表面不能授权出版，除非接受的记录承认该表面。SF-4将证据视野与验证时间分离，并拒绝真实但因果无效的授权。一个历史前驱路径重现了17个冻结的授权-后继结果。随后一次内部、实例盲测的已知案例类别匹配了所有183个评分预期；同主机包执行重现了其240个存档观察结果。结果支持内部一致性、有界安全性、故障敏感性和有限可构造性，但不支持事实真实性、一般细化、盲互操作性、现场有效性或标准状态。
英文摘要
AI-assisted claims can appear authoritative when evidence, analysis, human authorization, presentation, and correction history refer to different states. Provenance, attestation, and transparency expose history but alone do not specify the publication transition examined here. We develop Publication Authority as an exact-state, non-transferable, single-use publication capability and instantiate it in PAC-2026 (Publication-Accountability Calculus), a machine-readable AIJIM Protocol candidate. We evaluate its fourth bounded semantic freeze (SF-4), a fixed-profile specification designed for replaceable bindings. Six obligations govern evidence, runs and artifacts, measurement disclosure, authorization, surface correspondence, and lifecycle continuity. Each yields a target-bound witness, localized counterexample, or localized unverifiability; none can compensate for another. Only a fresh, complete all-pass record derives the permit consumed by one atomic publication transition. We use identity vectors, adversarial cases, finite models, and historical implementations. Ten models explored 110,764 safe reachable states; 76 unsafe configurations produced the expected violation or observer countermodel. A reader surface passing its correspondence check cannot authorize publication unless the accepted record admits that surface. SF-4 separates evidence horizon from verification time and rejects an authentic but causally invalid authorization. A historical predecessor path reproduced 17 frozen authorization-successor outcomes. A later in-house, instance-blind test of known case classes matched all 183 scored expectations; same-host package execution reproduced its 240 archived observations. Results support internal coherence, bounded safety, fault sensitivity, and limited constructibility, but not factual truth, general refinement, blind interoperability, field efficacy, or standards status.
发表机构
- Data Science Institute, University of Technology Sydney（悉尼科技大学数据科学研究所）
- Global Big Data Technologies Centre, University of Technology Sydney（悉尼科技大学全球大数据技术中心）
- School of Computer Science, University of Technology Sydney（悉尼科技大学计算机科学学院）
机构由 AI 辅助整理，请以论文原文为准。
