Is Every Cognitive Phenomenon Computable?
Fernando Rodriguez-Vergara, Phil Husbands
Mathematics February 2, 2026 DOI: 10.3390/math14030535 via OpenAlex
Summary
AI-generated from the abstractThe Church–Turing thesis sets the limits of computability at Turing machines, leading some to argue that cognitive processes must also be bounded by such machines. Yet a strong intuition in cognitive science holds that mental phenomena like consciousness and agency transcend computational frameworks. This paper argues that the relationship between cognition and computation is a crucial, often overlooked issue that will shape future research in artificial life, cognitive science, and artificial intelligence.
Study at a glance
| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Keywords | Cognition Phenomenon Consciousness Relation database Limit mathematics |
| Key finding | The relationship between cognition and computation, often simplified in models, is argued to define the direction of future research in artificial life, cognitive science, and artificial intelligence. |
Abstract
According to the Church–Turing thesis, the limit of what is computable is bounded by Turing machines. Following from this, given that general computable functions formally describe the notion of recursive mechanisms, it is sometimes argued that every organismic process that specifies consistent cognitive responses should be both limited to Turing machine capabilities and amenable to formalization. There is, however, a deep intuitive conviction permeating contemporary cognitive science, according to which mental phenomena, such as consciousness and agency, cannot be explained by resorting to this kind of framework. In spite of some exceptions, the overall tacit assumption is that whatever the mind is, it exceeds the reach of what is described by notions of computability. This issue, namely the nature of the relation between cognition and computation, becomes particularly pertinent and increasingly more relevant as a possible source of better understanding the inner workings of the mind, as well as the limits of artificial implementations thereof. Moreover, although it is often overlooked or omitted so as to simplify our models, it will probably define, or so we argue, the direction of future research on artificial life, cognitive science, artificial intelligence, and related fields.