The Cognitive Cost of Artificial Intelligence: A Neurocognitive Review

Abstract

Artificial Intelligence was originally conceived as a tool for human ease, intended to enhance productivity and streamline complex tasks. However, recent trends suggest a shift from augmentation to a total "cognitive offloading," where humans increasingly outsource critical thinking and memory to AI. This review paper explores the hypothesis that this dependency is contributing to a reversal of the Flynn Effect. After reviewing neuroimaging data from fMRI and EEG studies, the paper identifies significant alterations in neuroplasticity and neural activity. A primary concern is the observed decline in hippocampal volume among individuals who over-rely on AI for routine and complex cognitive tasks. Because the brain follows a "use it or lose it" paradigm, bypassing "desirable difficulties" during information processing leads to a lack of deep memory encoding and weakened retention skills. This phenomenon, often termed "Digital Amnesia," suggests that our neural architecture is physically adapting to a state of passive retrieval rather than active synthesis. The paper concludes that while AI offers immense efficiency, we must develop a balanced Human-AI interaction model. By treating AI as a collaborative partner rather than a cognitive substitute, we can leverage technological speed while preserving the biological integrity and intellectual capacity of the human brain.