Published July 23, 2026 | Version v2

Fate-Coupling: A Runtime Governance Primitive for AI Alignment

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Abstract

Advanced AI systems may increasingly operate as persistent deployments with tools, memory, delegated subagents, economic resources, and access to consequential infrastructure. Existing training-time alignment, monitoring, interruptibility, and access-control methods address important parts of this problem, but most do not ask whether high-impact operational privileges should remain valid when independently observed human outcomes deteriorate. This paper introduces fate-coupling: a proposed runtime-governance primitive that conditions a deployment's scoped capabilities on plural, audited, uncertainty-aware evidence about human welfare within a compliant enforcement perimeter.

The central object is not an internal reward and not a complete definition of welfare. It is an external authorization policy that combines welfare evidence with non-compensatory rights, catastrophic-risk, data-integrity, audit, lineage, and service-coverage gates. The policy issues short-lived capability permits, supports tiered and reversible safing, and reserves durable sanctions for stronger evidence and causal review. We define global, sectoral, and individual fate scopes; model the governed unit as an agent together with its operator, runtime, delegation chain, and material descendants; and present a substrate-neutral architecture comprising a Temporal AI Registry, a Human Welfare Evidence Layer, a policy evaluator, capability gateways, and tamper-evident decision records. Blockchain or smart contracts are possible implementations, but neither is required.

The paper treats Goodhart effects, strategic adaptation, threshold-localized gaming, risk selection, oracle corruption, exogenous shocks, cascade failures, privacy, governance capture, and authoritarian function creep as first-class design threats. It also revises Individual Fate-Coupling as a lifecycle policy for personalized deployments rather than a claim about the moral status or literal death of a model. Finally, it specifies FateBench-MA, a falsifiable multi-agent research program with comparative baselines, adversarial scenarios, measurable outcomes, and explicit rejection criteria. Fate-coupling is presented as a conceptual and perimeter-limited research hypothesis, not as a proven control method or deployment-ready safety guarantee.

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Version note

Public version 2 is the first public revision after the original Zenodo version published on December 20, 2025. It replaces reward-like and anthropomorphic formulations with external authorization semantics; makes the architecture substrate-neutral; adds non-compensatory welfare, rights, integrity, audit, lineage, and coverage gates; distinguishes reversible safing from sanction; strengthens privacy and anti-function-creep safeguards; updates related work through July 23, 2026; and adds FateBench-MA as a falsifiable research program. No empirical validation is claimed.

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Preprint: 10.5281/zenodo.17993331 (DOI)