The Hegemonic Function of AI: Cognitive Sovereignty in the Age of Algorithmic Mediation

Abstract

This paper argues that artificial intelligence systems perform a hegemonic function in the Gramscian sense: they naturalize a particular arrangement of cognitive authority until alternatives become inconceivable. AI achieves its hegemonic effect not primarily through overt ideology but through cognitive architecture, making independent reasoning feel unnecessary rather than persuading us it should be abandoned. The mechanism is exceptionally efficient because convenience recruits its subjects as willing participants in their own cognitive displacement.

Drawing on peer-reviewed research in cognitive offloading, automation bias, and the generation effect, the paper argues that passive reliance on AI poses a measurable risk to the cognitive capacities on which professional judgment and democratic participation depend. A comparative review of major AI governance frameworks, including the EU AI Act, NIST AI Risk Management Framework, OECD AI Principles, and ISO/IEC 42001, reveals that, although some warn against over-reliance, none directly operationalizes the sustained risk of cognitive atrophy through AI dependency as a standalone governance category.

Distinguishing ideological from architectural hegemony, the paper identifies three vectors of cognitive capture (scope expansion, language drift, logic mutation) and a three-class hegemonic operation spanning professional users, governed populations, and legitimizing institutions. It then identifies a recursive consent loop—we are building instruments that erode the faculties required to govern them—that generalizes across cognitive domains in a way no prior technology has achieved, and proposes counter-hegemonic practices and governance structures designed to preserve cognitive sovereignty under conditions of AI saturation.

Keywords: artificial intelligence, cultural hegemony, Gramsci, cognitive sovereignty, automation bias, cognitive offloading, professional judgment, AI governance, consent loop, human oversight, professional deskilling

JEL Classification: K10, K40, O33, Z13