Expert Intelligence: Theory of the Missing Facet

Abstract

This article sheds light on various less-explored areas, such as knowledge, intelligence, expertise, knowledge representation, skill acquisition and intelligent systems. It also proposes a missing facet, namely, Expert Intelligence (EI). Artificial Intelligence (AI) based systems such as expert systems and decision support systems were meant to substitute the expertise of human experts. However, in reality, these so-called intelligent systems are used as an aid for decision-making or only as a second choice of opinion in the absence of an expert. During the design of an intelligent system, a knowledge engineer encodes the knowledge of a domain expert into the system. The design and architecture of the system is meant to manipulate on the knowledge of the domain expert but his intelligence is neither acquired nor manifested. Furthermore, poor knowledge acquisition and knowledge representation schemes penalize the performance of these systems. Intelligent systems require more of an experts intelligence rather than his knowledge. Expert Intelligence attempts to bridge this gap. The notion of this article is not to provide an experimental analysis; the principle contribution of this work includes the dogma of Expert Intelligence and future directions for a paradigm-shift from knowledge-based AI approach to an intelligence-based EI approach.