PHENOMENAL AND ACCESS CONSCIOUSNESS AND THE "HARD" PROBLEM: A VIEW FROM THE DESIGNER STANCE

Abstract

This paper is an attempt to summarise and justify critical comments I have been making over several decades about research on by philosophers, scientists and engineers. This includes (a) explaining why concept of phenomenal (P-C), in sense defined by Ned Block, is semantically flawed and unsuitable as a target for scientific research or machine modelling, whereas something like concept of access (A-C) with which it is often contrasted refers to phenomena that can be described and explained within a future scientific theory, and (b) explaining why hard is a bogus problem, because of its dependence on P-C concept. It is compared with another bogus problem, the 'hard' problem of spatial identity introduced as part of a tutorial on semantically flawed concepts. Different types of semantic flaw and conceptual confusion not normally studied outside analytical philosophy are distinguished. The semantic flaws of zombie argument, closely allied with P-C concept are also explained. These topics are related both to evolution of human and animal minds and brains and to requirements for human-like robots. The diversity of phenomena related to concept consciousness as ordinarily used makes it a polymorphic concept, partly analogous to concepts like efficient, sensitive, and impediment all of which need extra information to be provided before they can be applied to anything, and then criteria of applicability differ. As a result there cannot be one explanation of consciousness, one set of neural associates of consciousness, one explanation for evolution of consciousness, nor one machine model of consciousness. We need many of each. I present a way of making progress based on what McCarthy called the designer stance, using facts about running virtual machines, without which current computers obviously could not work. I suggest same is true of biological minds, because biological evolution long ago discovered a need for something like virtual machinery for self-monitoring and self-extending information-processing systems, and produced far more sophisticated versions than human engineers have so far achieved.