Alan Turing and the "Hard" and "Easy" Problem of Cognition: Doing and Feeling

TL;DR

This paper discusses the distinction between the 'easy' problem of explaining cognitive abilities and the 'hard' problem of explaining consciousness and feeling, highlighting limitations of computational models and the necessity of sensory-motor grounding.

Contribution

It analyzes the limitations of Turing's approach and Searle's critique, emphasizing the complexity of explaining subjective experience beyond computational and sensory-motor models.

Findings

Computational models alone cannot explain consciousness.

Sensory-motor grounding is necessary but not sufficient for feeling.

The 'hard' problem of cognition remains largely unsolved.

Abstract

The "easy" problem of cognitive science is explaining how and why we can do what we can do. The "hard" problem is explaining how and why we feel. Turing's methodology for cognitive science (the Turing Test) is based on doing: Design a model that can do anything a human can do, indistinguishably from a human, to a human, and you have explained cognition. Searle has shown that the successful model cannot be solely computational. Sensory-motor robotic capacities are necessary to ground some, at least, of the model's words, in what the robot can do with the things in the world that the words are about. But even grounding is not enough to guarantee that -- nor to explain how and why -- the model feels (if it does). That problem is much harder to solve (and perhaps insoluble).