Implicit Learning in Artificial Intelligent Systems:
The Coming Problem of Real,
Cognitive AI
Authors:
- Dr. James Crowder, CAES APD
- Dr. Shelli Friess, LPC, NCC, ACS, School of Counseling, Walden University
- Dr. John Carbone, Electrical and Computer Engineering, 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 selfadapting,
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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