Right to History: A Sovereignty Kernel for Verifiable AI Agent Execution
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Abstract (arXiv)
AI agents increasingly act on behalf of humans, yet no existing system provides a tamper-evident, independently verifiable record of what they did. As regulations such as the EU AI Act begin mandating automatic logging for high-risk AI systems, this gap carries concrete consequences -- especially for agents running on personal hardware, where no centralized provider controls the log. Extending Floridi's informational rights framework from data about individuals to actions performed on their behalf, this paper proposes the Right to History: the principle that individuals are entitled to a complete, verifiable record of every AI agent action on their own hardware. The paper formalizes this principle through five system invariants with structured proof sketches, and implements it in PunkGo, a Rust sovereignty kernel that unifies RFC 6962 Merkle tree audit logs, capability-based isolation, energy-budget governance, and a human-approval mechanism. Adversarial testing confirms all five invariants hold. Performance evaluation shows sub-1.3 ms median action latency, ~400 actions/sec throughput, and 448-byte Merkle inclusion proofs at 10,000 log entries.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 12 of its 43 references that are in the map. First posted on arXiv 23 Feb 2026.
Builds on
12 of 43 references.
References · 12
- 2016The Off-Switch Gamecited by 97
- 2024AIOS: LLM Agent Operating Systemcited by 94
- 2018Hyperledger Fabric: A Distributed Operating System for Permissioned Blockchainscited by 48
- 2025Infrastructure for AI Agentscited by 40
- 2023LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent Ecosystemcited by 35
- 2025AgentBound: Securing Execution Boundaries of AI Agentscited by 20
- 2025Governance-as-a-Service: A Multi-Agent Framework for AI System Compliance and Policy Enforcementcited by 15
- 2026AgentCgroup: Understanding and Controlling OS Resources of AI Agentscited by 13
- 2026Agent Contracts: A Formal Framework for Resource-Bounded Autonomous AI Systemscited by 12
- 2026Sovereign Agents: Towards Infrastructural Sovereignty and Diffused Accountability in Decentralized AIcited by 6
- 2025The Oversight Game: Learning to Cooperatively Balance an AI Agent's Safety and Autonomycited by 3
- 2025Who Grants the Agent Power? Defending Against Instruction Injection via Task-Centric Access Controlcited by 1
Built on by
Citing papers per year: 2026: 7.
7 papers.
- 2026ProbeLogits: Kernel-Level LLM Inference Primitives for AI-Native Operating Systemscited by 2
- 2026CapSeal: Capability-Sealed Secret Mediation for Secure Agent Executioncited by 1
- 2026Notarized Agents: Receiver-Attested Confidential Receipts for AI Agent Actionscited by 0
- 2026Agent Economics: An Entropy-Controlled Pluralistic Alignment Framework for Preventing Artificial Hivemind in Autonomous Agentscited by 0
- 2026Behavioral Governance for Autonomous AI Agents: The AgentBound Frameworkcited by 0
- 2026The Civilization Framework: Sovereign-Anchored Communication Between Personal Multi-Agent Systemscited by 0
- 2026Janus: Evidence-Before-Effect Sagas and Offline-Verifiable Provenance for Agentic LLMscited by 0
- 2026Janus: Evidence-Before-Effect Sagas and Offline-Verifiable Provenance for Agentic LLMs29 Sep 2026
- 2026The Civilization Framework: Sovereign-Anchored Communication Between Personal Multi-Agent Systems3 Sep 2026
- 2026Behavioral Governance for Autonomous AI Agents: The AgentBound Framework29 Jun 2026
- 2026Agent Economics: An Entropy-Controlled Pluralistic Alignment Framework for Preventing Artificial Hivemind in Autonomous Agents8 Jun 2026
- 2026Notarized Agents: Receiver-Attested Confidential Receipts for AI Agent Actions2 Jun 2026
- 2026CapSeal: Capability-Sealed Secret Mediation for Secure Agent Execution18 Apr 2026
- 2026ProbeLogits: Kernel-Level LLM Inference Primitives for AI-Native Operating Systems13 Apr 2026