arXiv:2608. 14074v1 Announce Type: new Abstract: AI agents increasingly act on external systems through standardized tool-calling protocols such as the Model Context Protocol (MCP), yet no infrastructure layer constrains their actions to what a principal has verifiably authorized: authorization logic lives in application code, is neither signed nor independently auditable, and the resulting logs lack evidentiary value.
By Giovanni Racioppi
arXiv:2607. 22953v1 Announce Type: new Abstract: Modern AI systems bring societal risks such as mass surveillance, extreme concentrations of power, and loss of user autonomy---calling into question a model where third-parties collect and control massive amounts of user data.
By Sourena Khanzadeh, Daniel Platnick, Marjan Alirezaie, Hossein Rahnama
arXiv:2609.22961v1 Announce Type: cross
Abstract: Agentic systems increasingly invoke tools, services, data, and other agents across organizational boundaries, yet a relying party cannot assess a del...
By Huafu Li, Jia Xia
arXiv:2601. 14271v2 Announce Type: replace Abstract: Shared accountability records are often used by parties who may never agree about causation, responsibility, or normative interpretation.
By Denise M. Case
The paper introduces Persona‑Execution Separation (PES), an architecture pattern that splits an LLM agent’s persona—its instructions, tone, and self‑presentation—from its execution—stateful, auditable work—by placing them in distinct trust domains linked through a governed contract bridge. PES allows the persona to evolve freely while keeping execution traceable, using mechanisms such as an approval matrix, data‑loss‑prevention exceptions, and continuous identity. A pilot implementation on a regulated digital‑employee platform demonstrated that PES successfully decouples persona drift from execution audit, preventing re‑validation or fingerprinting of hard‑asserted fields.
By Yisen Xi
arXiv:2601. 16152v2 Announce Type: replace-cross Abstract: Data systems increasingly operate under persistent legal, political, and analytic disagreement, where no single interpretive authority can be assumed.
By Denise M. Case
arXiv:2606. 04104v1 Announce Type: cross Abstract: Agent systems execute through runtimes with very different control points: local coding tools, framework SDKs, managed agent platforms, API gateways, and observer-only integrations.
By Zexun Wang
arXiv:2606. 11632v1 Announce Type: cross Abstract: Agentic infrastructure introduces a critical control-plane authorization problem: non-deterministic reasoning systems can propose high-stakes mutations to production resources, yet existing security mechanisms -- such as identity and access management (IAM), policy engines, consensus protocols, and audit logs -- either enforce static, context-unaware permissions or merely record actions post-execution.
By Jun He, Deying Yu
The Civilization Framework proposes a new way for AI systems to communicate by treating the entire civilization—one human sovereign, a persistent ledger, and interchangeable agents—as the addressable party, rather than individual agents. It introduces the Embassy Protocol, an asynchronous, carrier‑agnostic overlay that routes messages to a ledger endpoint where any online agent of the receiver can process them, with commitment state on both ledgers serving as the ground truth. The framework also identifies a temporal‑weight effect in AI‑to‑AI communication, demonstrates its impact in a preregistered experiment, and explores mitigation strategies such as instruction‑level provenance labeling and sealed‑answer accuracy equivalence.
whyItMatters":"The framework aims to reduce context loss and authority bias in AI interactions by grounding communication in a shared ledger and sovereign oversight, potentially improving reliability and accountability in multi‑agent systems."
By Guangjun Liu
arXiv:2607. 20729v1 Announce Type: cross Abstract: A record system declares when two records refer to the same entity, occurrence, scope, or rule.
By Denise M. Case
arXiv:2607. 25364v1 Announce Type: new Abstract: Tool-using agents expose structured calls but commonly attach free-form rationales.
By Genliang Zhu (Accentrust, Georgia Institute of Technology), Chu Wang (Accentrust, University of Illinois Urbana-Champaign)
arXiv:2603. 03971v3 Announce Type: replace-cross Abstract: Generative AI can convert uncertainty into authoritative-seeming verdicts, intensifying the hypersuasive force of automated speech and displacing the justificatory work on which democratic epistemic agency depends.
By Michael J\"ulich