# Definitively Identifying an Inherent Limitation to Actual Cognition

## TL;DR

This paper revises computability theory to identify a fundamental limitation that applies to real-world cognition, avoiding assumptions of infallibility and formal reasoning that are contradicted by empirical cognitive science data.

## Contribution

It introduces a novel methodology that redefines computability limits in a way applicable to human cognition without relying on unrealistic assumptions.

## Key findings

- The limitation applies to individual humans and groups.
- Empirical data contradicts assumptions of infallible reasoning.
- The new framework aligns computability theory with cognitive science evidence.

## Abstract

A century ago, discoveries of a serious kind of logical error made separately by several leading mathematicians led to acceptance of a sharply enhanced standard for rigor within what ultimately became the foundation for Computer Science. By 1931, Godel had obtained a definitive and remarkable result: an inherent limitation to that foundation. The resulting limitation is not applicable to actual human cognition, to even the smallest extent, unless both of these extremely brittle assumptions hold: humans are infallible reasoners and reason solely via formal inference rules. Both assumptions are contradicted by empirical data from well-known Cognitive Science experiments. This article investigates how a novel multi-part methodology recasts computability theory within Computer Science to obtain a definitive limitation whose application to human cognition avoids assumptions contradicting empirical data. The limitation applies to individual humans, to finite sets of humans, and more generally to any real-world entity.