Cognition and understanding in deep learning

Abstract

Deep learning makes it possible to recognize patterns, play games, process and translate sentences, or do other works by learning from examples. It sometimes outperforms humans for some specific problems. Then, there naturally arises a fundamental question how different are the ways of information processing in deep learning and humans. To answer this question, we recapitulate the history of AI and deep learning shortly. We then show that deep learning generates very high-dimensional experimental formulae of interpolation and extrapolation. Humans do similar, but after finding the experimental formulae, they search for the reasons why such formulae work well. Humans search for fundamental principles underlying phenomena in the environment whereas deep learning does not. Humans cognize and understand the world they live in with consciousness. Furthermore, humans have a mind. Humans have obtained mind and consciousness through a long history of evolution, which deep learning does not. What is the role of mind and consciousness for cognition and understanding? The human brain has an excellent ability of prediction (as well as other animals), which is fundamental for surviving in the severe environment. However, humans have developed the ability of postdiction, which reviews the action plan based on a prediction before execution by integrating various pieces of evidence. This is an important function of consciousness, which deep learning does not have.