Skip to content
Open access

What Computation Cannot Be: Linguistic Colonization, Formal Limits, and a Taxonomy of Irreducibly Human Faculties

Sep 2026 · Philosophies · 0 citations · 57 references

TL;DR

The article concludes that the burden of proof now lies with those who claim that formal computation can exhaust human understanding, and argues that the simulation–possession distinction provides a principled basis for restoring conceptual clarity to discourse about artificial intelligence.

Abstract

The vocabulary of artificial intelligence has colonized human self-description. Terms historically reserved for conscious agents—intelligence, learning, understanding, creativity—now routinely designate computational processes that bear no phenomenological resemblance to the experiences that they originally named. This conceptual erosion is not merely semantic; it undermines our capacity to articulate what distinguishes human cognition from machine operation at a moment when that distinction matters most. This article develops a dual-path argument for the identification of irreducibly human capacities. A via negativa assembles four independent lines of formal and philosophical reasoning—Gödel’s incompleteness theorems, Turing’s halting problem, Searle’s Chinese Room, and the frame problem—that establish principled limits to what computation can achieve. A via positiva draws on phenomenology to positively characterize the structures of human existence that lie beyond those limits: embodiment, intersubjectivity, temporality, being-in-the-world, and subjective experience. The convergence of these independent paths—each pointing from its own starting point toward the same boundary—grounds a taxonomy of five Unique Human Faculties (creativity, moral judgment, self-determination, empathy, and sentience) that resist mechanization in principle. The article concludes that the burden of proof now lies with those who claim that formal computation can exhaust human understanding, and argues that the simulation–possession distinction provides a principled basis for restoring conceptual clarity to discourse about artificial intelligence.

Read PDF

Similar papers

#artificial intelligence Preprint Sep 2026

We Built a Mirror and Mistook It for a Mind: Causal Liability and the Fallacy of AI Consciousness

The contemporary debate over machine consciousness begins from a concealed assumption: that the object called"AI"already constitutes the kind of entity to which consciousness could belong. This paper challenges that assumption by separating phenomenal consciousness, introspective report, and human projective introspect...

Afshin Khadangi · 0 citations
Sep 2026

ON AI AND SOME PHILOSOPHICAL CHALLENGES

A unified vision is offered: intelligence arises from constrained architectures and emergent patterns, and as AI systems become more autonomous, they may require surrogate forms of consciousness to handle complex, real-world challenges—though these will never fully replicate the biological original.

John-Michael M. Kuczynski · 0 citations
Open access Sep 2026

Historical and philosophical foundations of the artificial intelligence problem: from myths to computability theory

The study aims to reconstruct the emergence and evolution of the “mind and machine” problem from ancient perceptions to computability theory, tracing the key stages in the formalization of reasoning along with its intrinsic limits. The article examines the lineage of the formalization of reasoning, wherein Aristotle, R...

Vladislav Antonovich Maltsev · 0 citations
Open access Sep 2026

Informational self meaning as a structural theory in artificial intelligence ontology and epistemology

This paper introduces the concept of informational self-meaning (ISM) as a philosophical account for addressing AI ontology and epistemology, providing a conceptual foundation for gradualist models of AI recognition in legal and ethical contexts.

Jae-Eung Yu · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.