TEMPORAL AI CASCADE (TAC)

This paper introduces Temporal AI Cascade (TAC) as a new theoretical framework for understanding how artificial intelligence embeds itself in the temporal gap between systemic crisis and critical response, actively widening that gap through cascade reproduction. Drawing on live observational material generated on 20 May 2026. Simultaneous news events comprising the UK Climate Change Committee's recommendation for maximum workplace temperature legislation and the World Health Organization's declared public health emergency of international concern for the Ebola Bundibugyo outbreak in the Democratic Republic of Congo and Uganda. This paper develops TAC through a conversation-as-methodology approach, pattern-matching both events against the existing Systemic Negative Panic (SNP) framework [1] and identifying where SNP requires significant theoretical extension. Three interlocking mechanisms are named and analysed: the SNP loop itself; repair language as a specific discursive technology that lubricates rather than interrupts systemic contraction; and TAC as the condition in which AI-accelerated cascade reproduction renders existing epistemological frameworks; particularly Haraway's situated knowledges [2], Hui's cosmotechnics [3], and Kafer's crip futurity [4] insufficient for the speed and depth of the crisis conditions they are asked to address. The paper introduces the V1 threshold as a structural analogy for the point of no return in crisis response. The most critical theoretical gap in existing literature concerns not the decision point itself but the epistemological condition of the operator after V1: airborne, neurochemically flooded, running degraded cognition through a checklist that has a gap in it. The paper identifies this post-V1 condition as the site where Temporal AI Cascade is both most active and most theoretically unaddressed. The paper is offered as a working document; its irresolution is methodological.