THE COGNITIVE REVOLUTION AS THE INTELLECTUAL FRAMEWORK FOR ESTABLISHING THE THEORETICAL FOUNDATIONS OF ARTIFICIAL INTELLIGENCE

Abstract

This paper examines the cognitive revolution as the intellectual framework that enabled the theoretical foundations of AI. Tracing the decline of behaviorism and the rise of internalist models in psychology and philosophy of mind, the study highlights how the information-processing metaphor and the formalization of mental representations provided the conceptual tools for early symbolic AI. The discussion follows the transition from symbolic to connectionist models, emphasizing the significance of parallel distributed processing and deep learning architectures in overcoming the limitations of classical AI. Special attention is given to the role of linguistics, functionalism, and the symbol-grounding problem in shaping both the possibilities and boundaries of machine intelligence. The paper also addresses the ethical and conceptual challenges posed by contemporary AI, including issues of transparency, autonomy, and the „black box“ problem. Ultimately, the cognitive revolution is presented not merely as a historical context but as the enduring intellectual framework that continues to define and challenge our understanding of AI, cognition, and the nature of intelligent systems.