<![CDATA[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.]]>
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