Mutually Assured Deregulation makes voluntary AI governance structurally untenable because each actor's restraint creates competitive disadvantage, converting the governance game from cooperation to prisoner's dilemma

Abiri's Mutually Assured Deregulation framework formalizes what has been empirically observed across 20+ governance events: the 'Regulation Sacrifice' view held by policymakers since ~2022 creates a prisoner's dilemma where states minimize regulatory constraints to outrun adversaries (China/US) to frontier capabilities. The mechanism operates at four levels simultaneously: (1) National level: US/EU/China competitive deregulation, (2) Institutional level: OSTP/BIS/DOD governance vacuums, (3) Corporate voluntary level: RSP v3 dropped pause commitments using explicit MAD logic, (4) Individual lab negotiation level: Google accepting weaker guardrails than Anthropic's to avoid blacklisting. The paradoxical outcome is that enhanced national security through deregulation actually undermines security across all timeframes: near-term (information warfare tools), medium-term (democratized bioweapon capabilities), long-term (uncontrollable AGI systems). The competitive dynamic makes exit from the race politically untenable even for willing parties because countries that regulate face severe disadvantage compared to those that don't. This is not a coordination failure that can be solved through better communication—it is a structural property of the competitive environment that persists as long as the race framing dominates.

Extending Evidence

Source: Sharma resignation, Semafor/BISI reporting, Feb 9 2026

Sharma's February 9 resignation preceded both RSP v3.0 release and Hegseth ultimatum by 15 days, establishing that internal safety culture decay occurs before visible policy changes and before specific coercive events. His structural framing ('institutions shaped by competition, speed, and scale') indicates cumulative pressure from September 2025 Pentagon negotiations rather than discrete government action.