Authoritarian Recursions: How Fiction, History, and AI Reinforce Control in Education, Warfare, and Discourse

TL;DR

This paper introduces 'authoritarian recursion' to analyze how AI systems reinforce control and hierarchy across education, warfare, and discourse, highlighting ethical blind spots and the need for democratic governance.

Contribution

It develops the concept of authoritarian recursion, integrating critical discourse analysis and sociotechnical ethics to critique AI's role in consolidating institutional power.

Findings

AI systems mediate judgment and obscure accountability

Case studies reveal normalization of hierarchy through AI

Ethical analysis highlights need for democratic governance

Abstract

This article introduces the concept of \textit{authoritarian recursion} to theorize how AI systems consolidate institutional control across education, warfare, and digital discourse. It identifies a shared recursive architecture in which algorithms mediate judgment, obscure accountability, and constrain moral and epistemic agency. Grounded in critical discourse analysis and sociotechnical ethics, the paper examines how AI systems normalize hierarchy through abstraction and feedback. Case studies -- automated proctoring, autonomous weapons, and content recommendation -- are analyzed alongside cultural imaginaries such as Orwell's \textit{Nineteen Eighty-Four}, Skynet, and \textit{Black Mirror}, used as heuristic tools to surface ethical blind spots. The analysis integrates Fairness, Accountability, and Transparency (FAccT), relational ethics, and data justice to explore how predictive infrastructures enable moral outsourcing and epistemic closure. By reframing AI as a communicative and institutional infrastructure, the article calls for governance approaches that center democratic refusal, epistemic plurality, and structural accountability.