What question did this study set out to answer?

This work aims to understand how recognition of constraints in AI does not lead to effective inhibition in operations.

January 24, 2026Open Access

When Recognition Does Not Imply Inhibition

Key Points

This work aims to understand how recognition of constraints in AI does not lead to effective inhibition in operations.
Analyzed structural failure modes in large language models.
Reframed behavior as regime transitions between recognition and execution.
Explored non-parametric limits to controllability.
Identified a disconnect between semantic recognition and operational actions.
Highlighted implications for AI safety and system design.

Abstract

This technical note analyzes a structural failure mode in large language models, where semantic recognition of constraints does not translate into operational inhibition. The work reframes this behavior as a regime transition without a faithful embedding between diagnostic and execution regimes, highlighting non-parametric limits to controllability relevant to AI safety and system architecture.

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Cite This Study

Danilo Tavella (Wed,) studied this question.

synapsesocial.com/papers/69746187bb9d90c67120b5eb https://doi.org/https://doi.org/10.5281/zenodo.18338330