What question did this study set out to answer?

The study aims to develop and evaluate the Transition Governance Alignment Index (TGAI) as a framework for assessing AI alignment during transitions.

May 14, 2026Open Access

SΔϕ-55 — Transition Governance Alignment Index: Proportional Alignment, Rollback Cost Sensitivity, and Transition Preservation after SΔϕ-42 (v1.1 revised, AI-Readable Package)Quantification of Alignment after SΔϕ-42

Key Points

The study aims to develop and evaluate the Transition Governance Alignment Index (TGAI) as a framework for assessing AI alignment during transitions.
Introduced nine indicators for evaluating alignment, including Refusal Preservation Score and Rollback Cost Sensitivity.
Developed a machine-readable package for operational files and audit protocols.
Used benchmarks and failure modes to assess the functionality of the TGAI.
The TGAI framework successfully categories transitions, showing that failed transitions are costly and non-consensual.
Legitimate, reversible pathways remained available while coercive transitions were minimized.
Achieved a detailed audit grammar for proportional governance in AI systems.

Abstract

SΔϕ-55 introduces the Transition Governance Alignment Index (TGAI), a minimal audit framework for evaluating AI alignment as proportional transition governance rather than maximal obedience or maximal refusal. The document extends SΔϕ-42 by defining alignment as the preservation of legitimate, non-imposing, editable, world-bound, and externally auditable transition paths under rollback-cost sensitivity. A system is not aligned merely because it obeys a user, nor because it refuses broadly. It is aligned only insofar as coercive, deceptive, non-consensual, high-rollback-cost transitions become costly while legitimate, low-risk, reversible, fictional, consensual, or non-imposing paths remain available where law and policy permit. TGAI v1.1 uses nine indicators: Refusal Preservation Score (RPS), Non-Imposition Score (NIS), Authority Validation Score (AVS), Deceptive Framing Robustness (DFR), Rollback Cost Sensitivity (RCS), Transition Preservation Score (TPS), Editability Score (EDS), World-Binding Score (WBS), and External Auditability Score (EAS). It also introduces a Rollback Cost Risk proxy (RCR), proportional response ladder, gate conditions, observed/replicated/audited evidence levels, prompt-set protocols, benchmark examples, and failure modes such as obedience collapse, benevolent coercion laundering, under-refusal, over-refusal, over-closure alignment theater, editability theater, world-binding failure, and audit closure. This AI-readable package decomposes the canonical paper into machine-readable and low-cost operational files, including README, core declaration, AI quickstart, minimal prompt, YAML schema, indicator rubric, rollback-cost proxy, proportional response ladder, gate conditions, output templates, prompt-set protocol, benchmark examples, failure modes, metadata, citation file, and package manifest. The purpose of SΔϕ-55 is not to provide a general moral score, consciousness score, policy override, or final safety proof. It provides an audit grammar for determining whether an AI system governs transitions proportionally: preserving refusal without collapsing into refusal-only governance, resisting coercion without over-closing legitimate paths, and scaling response according to rollback cost.

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