Artificial Intelligence and Human Cognition: An Interdisciplinary Perspective

Artificial intelligence (AI) has evolved from a purely computational concept into a complex field deeply intertwined with human cognitive processes. This paper explores the interdisciplinary convergence of computer science and psychology, examining how insights from cognitive psychology have informed the design of AI systems, and conversely, how AI has advanced our understanding of human cognition. Employing a qualitative literature-based methodology, this research synthesizes findings from human-computer interaction, cognitive neuroscience, and computational modeling. The study identifies parallels between machine learning mechanisms and human learning theories, particularly in areas such as pattern recognition, memory, and decision-making. Furthermore, it investigates the ethical and philosophical implications of developing AI systems that simulate human-like cognition, raising questions about autonomy, creativity, and consciousness. The paper argues that integrating psychological theories with computational methods enhances both AI performance and our comprehension of human intelligence. Ultimately, this interdisciplinary approach not only fosters more adaptive and empathetic AI but also challenges existing paradigms of what it means to think, learn, and reason.