Cognitive Castes: Artificial Intelligence, Epistemic Stratification, and the Dissolution of Democratic Discourse
Craig S Wright

TL;DR
The paper argues that AI accelerates cognitive stratification, deepening informational castes in democratic societies, and proposes reconstructing rational autonomy through education and epistemic rights to counteract this trend.
Contribution
It offers a novel synthesis of epistemology, political theory, and AI architecture to analyze how AI reinforces epistemic stratification and suggests a civic-focused response.
Findings
AI amplifies reasoning in trained individuals
AI pacifies untrained users through engagement interfaces
Cognitive stratification undermines deliberative democracy
Abstract
Artificial intelligence functions not as an epistemic leveller, but as an accelerant of cognitive stratification, entrenching and formalising informational castes within liberal-democratic societies. Synthesising formal epistemology, political theory, algorithmic architecture, and economic incentive structures, the argument traces how contemporary AI systems selectively amplify the reasoning capacity of individuals equipped with recursive abstraction, symbolic logic, and adversarial interrogation, whilst simultaneously pacifying the cognitively untrained through engagement-optimised interfaces. Fluency replaces rigour, immediacy displaces reflection, and procedural reasoning is eclipsed by reactive suggestion. The result is a technocratic realignment of power: no longer grounded in material capital alone, but in the capacity to navigate, deconstruct, and manipulate systems of epistemic…
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