Exploring how AI hallucinations might not be bugs but features—digital manifestations of Girard's scapegoat mechanism as AI systems resolve contradictions in their mimetic learning from human data.
Miglior citazione da The Mimetic Machine's Scapegoat
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AI hallucinations aren't actually errors or bugs, but a digital version of the scapegoat mechanism. When these systems face contradictory information in their training data, they fabricate a 'third option'—a hallucination—that resolves the conflict and allows the mimetic system to move forward.
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Girard’s "Mimetic Contagion" in AI
Applying René Girard to 2026 Large Language Models.
Theory: AI does not have original desire; it operates on pure "Mimesis" (imitation) of human training data. Therefore, AI inevitably inherits Mimetic Rivalry. When an AI "hallucinates," it is not an error, but a digital "Scapegoat Mechanism"—fabricating a victim/fact to resolve conflicting patterns in the dataset without violence.
System Focus: Systemic origins of error within mimetic systems.
Explore whether AI truly reasons or just mimics thinking through pattern recognition. We'll unpack the fascinating debate about machine cognition versus human critical thinking.
Exploring how AI systems create a new layer of illusion—a 'prison within a prison'—through the lens of ancient Gnostic philosophy, and questioning whether our reliance on AI-generated content represents a form of 'Cheap Grace.'
Exploring why humans can barely tell real from fake when AI creates flawless copies of voices, faces, and behaviors - and what 'too perfect' reveals about authenticity.