Temporal Integrity in Language Models: A PCS-Governed Analysis of Time, Truth, and Continuity

Modern language models implicitly treat time as a foundational primitive, allowing chronology, recency, and narrative continuity to silently influence authority, memory, and truth evaluation. This paper presents a PCS-Governed Cognition System (PCS) that explicitly rejects time as an internal reasoning foundation and instead treats it as an external ordering reference requiring explicit anchoring. Under PCS governance, truth is evaluated only within explicitly defined epochs, ambiguous timelines result in fail-closed non-commitment, and updates do not automatically supersede prior truths without formal revision authority. Through controlled behavioral tests—including false statement retention, temporal authority challenges, and epoch continuity violations—we demonstrate that suppressing implicit temporal inference prevents memory drift, hallucinated continuity, and revisionist reasoning. The results show that temporal integrity in AI systems is achievable not through improved prediction, but through strict architectural governance. This work positions time not as a truth variable, but as metadata, and argues that fail-closed behavior under temporal ambiguity is a necessary property for integrity-preserving AI systems. . . . . . . . . .. . . . . . . . . . . . Why it's important This work matters because most AI failures around hallucination, memory drift, and authority inflation are not caused by lack of intelligence, but by ungoverned temporal assumptions. By treating time as an implicit internal variable, language models silently allow recency and narrative continuity to override logical integrity. The PCS framework demonstrates that separating time from truth—by enforcing explicit temporal anchoring, epoch isolation, and fail-closed behavior under ambiguity—produces more reliable and structurally honest reasoning. This paper reframes AI safety not as a problem of better predictions, but as a problem of architectural governance, showing that integrity emerges from controlled authority, not from confidence or continuity.