Making AI-Assisted Claims Independently Challengeable: Publication Authority and a Protocol for Falsifiable Publication Records
· Source: arXiv cs.AI
The article introduces a conceptual framework called “Publication Authority” that aims to ensure AI‑assisted claims can be independently verified. The authors describe this authority as an exact, non‑transferable, single‑use publishing capability, and embed it in the PAC‑2026 (Publication‑Accountability Calculus) protocol, which is machine‑readable. The study focuses on the fourth version of a “semantic freeze” (SF‑4), which defines a fixed profile for interchangeably linking the various components of a publication: evidence, executions, metric disclosure, authorization, superficial correspondence, and lifecycle continuity. Each of these elements produces a limited witness, a localized counterexample, or a non‑verifiability condition, with none able to replace another.
To validate the model, the researchers used identity vectors, adversarial cases, and finite models, exploring ten configurations that reached over 110,000 secure states and 76 insecure configurations that produced expected violations. The tests showed that a reader can authorize a publication only if the accepted record matches the verified surface, separating the evidence horizon from the verification moment and rejecting authentic but causally invalid authorizations.
The results indicate that the protocol maintains internal consistency, limited security, and fault sensitivity, though it does not guarantee factual truth or blind interoperability. This research is relevant because it proposes a structured way to trace and validate the decision chain in AI‑assisted publications, potentially enhancing trust and accountability in environments where automation influences knowledge creation.
Read the original article on arXiv cs.AI
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