Levin, Ilya (2026) Navigational Epistemology: Toward a New Understanding of Knowledge in the Age of Generative AI. [Preprint]

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Abstract

Generative artificial intelligence represents a technology marked by a growing asymmetry between its capabilities and its conceptual understanding. While such systems exhibit performance comparable to human intelligence, they are still interpreted through frameworks derived from tools, collaboration, or statistical recombination. This paper argues that these frameworks share a key limitation: they treat the medium of generative AI as epistemologically neutral. In contrast, the paper identifies this medium as a high-dimensional geometric space whose properties differ fundamentally from the low-dimensional intuitions shaping traditional epistemology.

The analysis develops a framework of navigational epistemology. It begins with threshold logic and the perceptron as the boundary where symbolic computation transitions into geometric processing. It then shows how properties of high-dimensional spaces, including concentration of measure, near-orthogonality, and manifold structure, function as active conditions shaping knowledge.

The paper argues that generative AI operates through an indexical mode of signification, where meaning arises from positional relations within a learned manifold. This leads to the concept of navigational knowledge, a form of knowledge that is positional and enactive. This interaction gives rise to an emergent cognitive formation, the Third Entity, defined by the automation of tacit knowledge through geometric traversal. The paper concludes by proposing navigational thinking as an epistemic paradigm in which navigation precedes computation.

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Item Type:	Preprint
Creators:	Creators Email ORCID Levin, Ilya levini@hit.ac.il 0000-0002-0298-4547
Keywords:	navigational epistemology, generative AI, high-dimensional geometry, threshold logic, indexical signification, navigational knowledge, Vibe-Creation, Third Entity, navigational thinking
Subjects:	Specific Sciences > Mathematics > Epistemology Specific Sciences > Mathematics > Foundations Specific Sciences > Artificial Intelligence > Classical AI Specific Sciences > Computer Science General Issues > Technology General Issues > Theory Change
Depositing User:	Dr. Ilya Levin
Date Deposited:	09 Apr 2026 12:27
Last Modified:	09 Apr 2026 12:27
Item ID:	28970
Subjects:	Specific Sciences > Mathematics > Epistemology Specific Sciences > Mathematics > Foundations Specific Sciences > Artificial Intelligence > Classical AI Specific Sciences > Computer Science General Issues > Technology General Issues > Theory Change
Date:	9 April 2026
URI:	https://philsci-archive.pitt.edu/id/eprint/28970

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