Hume in the Light of Bayes: Towards a Unified Cognitive Science of Human Nature

Abstract

David Hume hoped future advances would bring his nascent science of human nature nearer to perfection. He conjectured that since it is probable one operation and principle of the mind depends on another it might someday be possible to subsume all mental operations under one absolutely general and universal principle. I argue that the day Hume hoped for may now be upon us, as an increasing number of theorists suspect that predictive Bayesian models of cognitive architecture provide the best clue yet as to the shape of a unified theory of mind. A theory in which the manifold operations of perception, imagination, and belief formation may all be explained in terms of the same cognitive processes that implement causal inference. I show the fundamental mechanism behind such architectures, the notion of a generative model, comprises a functional analogue to Hume’s faculty of the imagination. I apply the ideas outlined to construct a theoretical model of speech perception which is able to explain perceptual illusions, such as phonemic restoration and Ganong effects as artifacts of Bayesian inference. If the unitary view spelled out in this paper is correct perception, action, understanding, and the imagination all co-emerge from the same neural and computational resources that implement error correction and causal inference. I thus conclude that predictive Bayesian models comprise a sound methodology with which to continue Hume’s project of constructing a genuinely unified cognitive science of human nature.