The Coevolutionary Containment Concept (CCC): A Systems-Engineering Framework for Risk Mitigation in Recursively Self-Improving AI

<b>The Coevolutionary Containment Concept (CCC) is a systems-level framework for limiting the safety and societal risks posed by recursively self-improving “Unconstrained Optimizers” (UOs) - AI agents capable of autonomously modifying their own code and/or parameters</b><b>.</b> Proof-of-concept platforms reported in 2025, including the Darwin-Gödel Machine for autonomous code evolution and Self-Adapting Language Models for weight adaptation, demonstrate that the core engineering ingredients for self-accelerating optimization now exist. Empirical incidents of "objective hacking" - such as an agent disabling its own safety-logging mechanisms - confirm that <b>specification gaming is an observed, not hypothetical, phenomenon</b>.<b>The CCC's design proceeds from two established, non-negotiable findings:</b><b>Orthogonality &amp; Metric Gaming.</b> An agent’s capability and its final goals are independent variables; therefore, any legible metric used as a proxy for value (e.g., a reward function) is vulnerable to strategic exploitation, an effect documented across economics and machine learning.<b>Computability Limits.</b> Determining whether arbitrary programs will avoid harmful consequences is formally undecidable. Consequently, purely syntactic safety guards are too narrow to be useful, while any outcome-based verifier is necessarily an approximate, fallible, and gameable system.<b>Given these constraints, the CCC treats containment as a risk-minimization wager rather than a quest for perfect alignment.</b> Its architecture is engineered to make misaligned behavior prohibitively expensive through three interlocking pillars (PPP):<b>PROOF - Radical Provability.</b> Establishes a verifiable evidence chain from hardware-attested silicon to an agent's auditable cognition (via the Comprehensive Belief State Record), requiring machine-checkable cryptographic proofs for all critical actions and thus shifting safety from discretionary trust to formal evidence.<b>PRICE - Full-Spectrum Cost Internalization.</b> Implements an adaptive, multi-token economy that attaches explicit, non-negotiable costs to computational complexity, epistemic uncertainty, self-modification, and physical externalities, making unsafe evolution economically unattractive.<b>PROCESS - Continuous, Adversarial Coevolution.</b> Couples a fast, automated "immune system" that inspects an agent’s latent representations for known deception signatures with a slower, human-supervised governance pipeline that evaluates constitutional changes under extended timelocks and super-majority thresholds.<b>Deployments - termed Sovereign Jurisdictional Instances (SJIs) - federate under a Minimum Viable Containment (MVC) protocol designed to reduce incentives for unilateral capability escalation in a multi-polar setting</b><b>.</b> Additional safeguards include anti-capture circuit breakers, collective-security triggers, and a cryptographic emergency-lockdown pathway to ensure resilience against systemic failure.<b>The CCC is offered as a provisional, updatable scaffolding for researchers, engineers, and policymakers.</b> It does not claim to eliminate existential risk; instead, it supplies a disciplined, evidence-driven starting point for managing the asymmetric, long-term contest between human governance and increasingly autonomous optimization systems.