Published 2026-04-24 | Version v1.0
Working PaperOpenPublished

Beyond Theater Effects

Perception-Driven Escalation and Loss-of-Control Thresholds in AI-Mediated Conflict

Description

This working paper examines how AI-enabled information systems transform escalation dynamics by shifting conflict transmission from material interaction to perception-driven amplification. Grounded in the Multi-Layer Coupled Complexity Model (MCCM), it develops a mechanism-based account of theater effects, narrative amplification, perception–impact decoupling, and loss-of-control threshold (LoCT) compression across high-information conflict environments.

Abstract

This paper examines how artificial intelligence (AI) transforms escalation dynamics by shifting the primary transmission mechanism of conflict from material interaction to perception-driven amplification. Within the Multi-Layer Coupled Complexity Model (MCCM) framework, narrative systems operate as nonlinear multipliers that enable low-cost actions to generate disproportionate systemic effects. The study develops a mechanism-based account of theater effects and validates it across multiple conflict environments. It shows that perception–impact decoupling and loss-of-control threshold (LoCT) compression can emerge under conditions of high information density, even in the absence of major kinetic change. The findings suggest that escalation is no longer governed primarily by force, but by the interaction of information, perception, and institutional dynamics. Escalation should therefore be understood as a coupled system process rather than a linear function of material change.

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Keywords

  • Artificial Intelligence
  • AI-mediated conflict
  • Escalation dynamics
  • Narrative amplification
  • Information warfare
  • Perception–impact decoupling
  • Loss-of-Control Threshold
  • LoCT
  • Systemic risk
  • MCCM framework
  • Theater effects
  • Information System Amplification Index
  • ISAI
  • Decision friction
  • High-pressure systemic equilibrium
  • Conflict systems
  • Strategic signaling
  • Institutional instability
  • EPINOVA

Subjects

  • Artificial intelligence governance
  • Conflict studies
  • International security
  • Strategic studies
  • Information warfare
  • Narrative systems
  • Complex systems
  • Political risk
  • Threshold dynamics
  • Decision-making under uncertainty
  • Public policy

Recommended citation

Wu, Shaoyuan. (2026). Beyond Theater Effects: Perception-Driven Escalation and Loss-of-Control Thresholds in AI-Mediated Conflict (EPINOVA Working Paper No. EPINOVA–WP–A–2026–02). Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.5281/zenodo.19734514. DOI: To be assigned after Crossref membership approval.

APA citation

Wu, S. (2026). Beyond theater effects: Perception-driven escalation and loss-of-control thresholds in AI-mediated conflict (EPINOVA Working Paper No. EPINOVA–WP–A–2026–02). Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.5281/zenodo.19734514. DOI: To be assigned after Crossref membership approval.

Alternate identifiers

SchemeIdentifierDescription
DOIhttps://doi.org/10.5281/zenodo.19734514Zenodo DOI landing page
Local identifierEPINOVA–WP–A–2026–02EPINOVA Working Paper A-Series publication number

Related works

RelationIdentifierTypeDescription
IsSupplementedByhttps://github.com/EPINOVALLC/EPINOVA-ResearchRepositorySupplementary EPINOVA research repository and structural archive
Referenceshttps://doi.org/10.5281/zenodo.19139977Working PaperReferenced EPINOVA working paper on systemic escalation theory and the loss-of-control threshold
Referenceshttps://doi.org/10.5281/zenodo.19550886Policy BriefReferenced EPINOVA policy brief on the MCCM v2.0+ framework
Referenceshttps://doi.org/10.5281/zenodo.19645873Policy BriefReferenced EPINOVA policy brief on high-pressure systemic equilibrium in the U.S.–Israel–Iran conflict
Referenceshttps://doi.org/10.5281/zenodo.19118195Working PaperReferenced EPINOVA working paper on threshold competition and loss-of-control dynamics
Referenceshttps://doi.org/10.1162/isec_a_00351Journal articleSource cited for weaponized interdependence and networked coercion
Referenceshttps://doi.org/10.1038/nature12047Journal articleSource cited for globally networked risk and systemic response
Referenceshttps://doi.org/10.9776/14308Conference paperSource cited for misinformation dynamics and platform-amplified rumor propagation

References

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  14. Wu, S. (2026b). From cost monitoring to systemic escalation assessment: The MCCM v2.0+ framework (Policy Brief No. EPINOVA–2026–PB–29). Global AI Governance and Policy Research Center, EPINOVA LLC. https://doi.org/10.5281/zenodo.19550886
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