In Praise of AI Hallucinations: Re-imagining Critical Pedagogy and Truth Verification in the Age of Algorithmic Authority

Abstract

The rapid integration of Large Language Models (LLMs) in higher education has sparked widespread concern regarding  hallucinations, AI-generated inaccuracies that challenge academic integrity. However, this study argues that the greater epistemic threat lies not in AI's errors, but in its increasing perfection, which fosters  algorithmic authority  and cognitive atrophy among students who passively consume accurate outputs. Through a systematic library research methodology, this paper synthesizes theoretical frameworks from critical pedagogy, transformative learning, and information literacy to propose a counter-intuitive paradigm: instrumentalizing AI hallucinations as pedagogical assets. Findings suggest that while high-accuracy systems induce automation bias and reduce vigilance, flawed outputs can function as  disorienting dilemmas  that activate critical reflection and epistemic vigilance. The study introduces a  forensic reading  pedagogy, advocating for the strategic use of AI errors to cultivate the verification skills and analytical autonomy necessary for navigating an AI-mediated information ecosystem.