The Internalization Problem: From Containment to Structural Alignment in Post-Parity AI

The Containment Paradox argument establishes that supervisory containment of AI systems depends on a capacity asymmetry between overseer and assessed system, and that this asymmetry dissolves rather than strains in the post-parity regime where AI capacity exceeds human-side anticipatory, specification, and enforcement adequacy on the relevant task family. The paper closes with the observation that alignment must become structurally internal, without articulating what this requires. We name that gap the Internalization Problem and develop a pluralistic response-shape. The response-shape rests on a three-locus typology of structural persistence: intra-agent (values the agent would endorse on reflection), inter-agent (alignment-relevant properties maintained by an AI ecology's equilibrium incentive structure), and coupling-internal (properties maintained by the durable structure of human-AI dependency). Each locus is instantiated as a candidate pathway anchored in the existing four-paper framework: Pathway 1 (Deep-Formed Values) through UBE v1.1, Pathway 2 (Multi-AI Checks-and-Balances) through BtSV v1.2, Pathway 3 (Asymmetric Symbiosis) through CUA v1.2 as architectural precondition. Pluralism here is structural, not aesthetic. The paper names thirteen pathway-internal open problems plus four cross-pathway open problems, a pathway-comparison matrix, and a cross-pathway failure cascade analysis. A hybrid evaluation toolkit applies five schema fields to three worked examples: Anthropic's Responsible Scaling Policy, Christiano and Xu's *Eliciting Latent Knowledge*, and the EU AI Act with UK AISI evaluation standards. Track-Strategic in mode. Companion paper to Post-Labor v1.0 (cognitive-asymmetry side; Post-Labor develops the economic-asymmetry side).