Epistemic Compression and Symbolic Absence Rethinking the Human and the Political
Published:
Ιουν 7, 2026
Keywords:
Symbolic absence Epistemic compression Political subjectivity Human agency AI ethics
Abstract
This article looks at how AI systems create symbolic absence through epistemic compression—reducing complex meanings to measurable categories. It traces these patterns across language models, healthcare, and epistemic infrastructures, from semantic flattening to structural exclusion. These patterns are not technical flaws. Rather, they are systemic features that privilege computational legibility over interpretive richness. Epistemic compression strips away culturally situated meaning and reshapes political subjectivity. When symbolic richness gives way to statistical data, human agency weakens, and the political subject becomes a data point. Restoring symbolic integrity is not just an epistemic ideal. It is a condition for rethinking the human and the political in AI governance. The analysis offers a new lens for diagnosing symbolic absence and a roadmap for rethinking AI governance around symbolic integrity.
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Lutfi, R. (2026). Epistemic Compression and Symbolic Absence: Rethinking the Human and the Political. Dia-Noesis: A Journal of Philosophy, 19(1), 203–236. https://doi.org/10.12681/dia.45799
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