Countering Disinformation Propaganda: Reverse Engineering the Experimental Implicit Learning Paradigm

Abstract

A conflict may develop when people ascribe different meanings to shared phenomena that entail action. In simple situations, resolution can be by persuading the other actors so that actions converge. In complex situations, explicit persuasion attempts are all too often ineffective. Effective persuasion might entail subtly attempting to alter the ascribed meaning of words and concepts. In modern warfare, adversaries can attempt to exploit the quirks of human psychology to influence, usurp, and manipulate everyday decisions by using disinformation. We introduce a conceptual model of information operations, drawing on the paradigm of implicit learning with Artificial Grammar Learning (AGL). The structure, grammar, and patterns of a Twitter data sample are examined. The modeling approach for designing, understanding, and formalizing the complex competitions of the information era is discussed, as is the possibility of using the model for reverse engineering as a possible disinformation stream. An argument is made for an alternative model for negating the effects of disinformation in the cognitive domain.