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Implicit Learning in Artificial Intelligent Systems: The Coming Problem of Real, Cognitive AI

Authors:
Dr. James Crowder, Systems Fellow, Colorado Engineering Inc.
Dr. Shelli Friess, LPC, NCC, ACS, School of Counseling, Walden University
Dr. John Carbone, Electrical and Computer Eng., Southern Methodist University

Abstract:
There has been much discussion and research over the last few decades on the differences between implicit and explicit learning and subsequently, the difference between explicit and implicit memories that result from implicit vs. explicit learning. Implicit learning differs from explicit learning in that implicit learning happens through unconscious acquisition of knowledge. Implicit learning represents a fundamental process in overall cognition, stemming from unconscious acquisition of knowledge and skills as a result of an entity interacting with its environment. One of the issues or consequences of implicit learning is the notion of how do we recognize that implicit learning has occurred, how will it affect the overall cognitive functions of the entity, and how do we measure and affect implicit learning within an entity? Here we discuss the notion of self adapting, cognitive, artificial intelligent entities and the notion of implicit learning within the artificial intelligent entity; how this will lead to implicit memories and how they might affect an overall artificial intelligent entity, for better or worse.

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Implicit Learning in Artificial Intelligent Systems: The Coming Problem of Real, Cognitive AI (94 downloads)