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Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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Algorithmic Warfare in the Iran Conflict: AI-Driven Decision Compression, the Erosion of Human Oversight, and Accountability Gaps in Contemporary Military Operations

Authors: Tsotniashvili, Zaza;

Algorithmic Warfare in the Iran Conflict: AI-Driven Decision Compression, the Erosion of Human Oversight, and Accountability Gaps in Contemporary Military Operations

Abstract

Introduction/Background: The joint United States–Israeli military offensive against Iran commencing on February 28, 2026, Operation Epic Fury/Operation Roaring Lion, produced an unprecedented operational tempo: nearly 900 strikes within the first twelve hours. What made this possible was not merely superior firepower but the deep integration of artificial intelligence (AI) into every phase of the kill chain. The Iran conflict has thus emerged as the first large-scale armed confrontation in which AI functioned not as a supporting analytical tool but as a core operational component of military decision-making, compressing targeting cycles from days to minutes and systematically marginalizing substantive human deliberation. Methods: This article employs a critical analytical framework drawing on OSINT-based investigative reporting on Operation Epic Fury, the academic literature on AI-enabled military targeting, documented AI deployments in prior conflicts (Gaza, Ukraine), emerging scholarship on the Iran-Israeli confrontation, international humanitarian law, and analysis of corporate governance tensions between leading AI developers and defense establishments. Results: The Iran conflict demonstrates three interlocking phenomena: first, AI-driven decision compression that reduced multi-day planning cycles to hours; second, the structural transformation of human oversight into a performative 'rubber stamp' - a formal authorization with no substantive deliberative content; and third, the collapse of corporate AI ethics under competitive military procurement pressure, illustrated most sharply by the simultaneous events of February 28, 2026, when Anthropic was blacklisted by the Pentagon for refusing to remove constraints on autonomous weapons, while its model was already embedded in Iran strike operations and OpenAI immediately assumed its defense contracts. Conclusions: Current governance frameworks are structurally inadequate to address the accountability gaps created by AI-assisted targeting. The Iran conflict has rendered urgent the development of binding international instruments that operationalize meaningful human control not as a nominal designation but as an enforceable behavioral standard, anchored in minimum deliberative time requirements and technical transparency mandates for AI-DSS used in lethal force decisions.

Keywords

artificial intelligence; Iran conflict; Operation Epic Fury; autonomous weapons; decision compression; kill chain; rubber-stamping; human oversight; international humanitarian law; algorithmic warfare; Anthropic; Project Maven

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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