THE GAP: A Neutral Layer Standard for Irreversible Digital Decisions

This paper introduces THE GAP Framework, an open standard that defines a neutral layer for AI systems encountering irreversible decision contexts and thought-loop behaviors. As AI-generated advice increasingly carries legal liability—confirmed by cases including Garcia v. Character Technologies (2024), Raine v. OpenAI (2025), Moffatt v. Air Canada (2024), and Krafton v. Unknown Worlds (2026)—AI providers face a structural dilemma: giving advice creates liability, withholding advice abandons the user, and internalizing pause mechanisms transfers design liability to the provider. THE GAP resolves this trilemma by specifying an external, independent neutral layer that AI systems can enumerate—not recommend—when they detect relevant contexts. The framework defines two parallel context systems: the Universal Decision Irreversibility Architecture (UDIA), a machine-readable taxonomy of 82 decision contexts organized into 6 irreversibility layers for critical-point situations; and the Wandering-State Context Architecture (WSCA), a three-facet classification of thought-loop behaviors for spiral float situations. The GAP-NLP-1.0 protocol standardizes neutral layer enumeration. Two first implementations are presented: Notsure (critical-point neutral layer, serving UDIA contexts) and THEGREY (wandering-type neutral layer, serving WSCA contexts). The open specification, including 18-language context mappings for both systems, is released under CC BY 4.0 at https://github.com/thegap-framework/thegap-framework.