Not only a lack of right definitions: Arguments for a shift in information-processing paradigm

TL;DR

This paper critiques the vague definitions in machine consciousness and intelligence research, highlighting the need for clearer concepts and proposing remedies to improve research clarity and progress.

Contribution

It identifies the lack of precise definitions as a key issue and suggests a paradigm shift towards more rigorous conceptual foundations in the field.

Findings

Current research suffers from ill-defined notions of cognition and intelligence.

Vague concepts hinder progress and goal setting in machine consciousness.

Proposes remedies to clarify and improve research practices.

Abstract

Machine Consciousness and Machine Intelligence are not simply new buzzwords that occupy our imagination. Over the last decades, we witness an unprecedented rise in attempts to create machines with human-like features and capabilities. However, despite widespread sympathy and abundant funding, progress in these enterprises is far from being satisfactory. The reasons for this are twofold: First, the notions of cognition and intelligence (usually borrowed from human behavior studies) are notoriously blurred and ill-defined, and second, the basic concepts underpinning the whole discourse are by themselves either undefined or defined very vaguely. That leads to improper and inadequate research goals determination, which I will illustrate with some examples drawn from recent documents issued by DARPA and the European Commission. On the other hand, I would like to propose some remedies that, I hope, would improve the current state-of-the-art disgrace.