Cognitive Offloading in the Age of Artificial Intelligence: A Systematic Review of Human Thinking Ability
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Abstract
Background: The increasing integration of artificial intelligence (AI) into everyday activities has accelerated the use of cognitive offloading, whereby individuals rely on external technologies to support memory, reasoning, and problem-solving. This systematic review aimed to synthesize current evidence on the effects of AI-assisted cognitive offloading on human thinking abilities, with particular attention to cognitive decline, cognitive restructuring, and cognitive enhancement. Methods: This review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A systematic search of Google Scholar, Scopus, and Web of Science identified peer-reviewed empirical studies, systematic reviews, meta-analyses, and theoretical papers published between 2014 and 2024. Eligible studies examined AI-assisted cognitive offloading or AI-supported cognition and reported outcomes related to memory, critical thinking, attention, or problem-solving. Studies unrelated to AI, lacking cognitive outcomes, or published in languages other than English were excluded. Data were synthesized using thematic analysis across four cognitive domains: memory retention, critical thinking, attentional control, and problem-solving. Results: The evidence indicates a dual-effect pattern. Frequent reliance on AI was associated with reduced independent recall, increased dependence on external systems, and lower engagement in effortful reasoning, supporting concerns regarding digital amnesia. Conversely, AI reduced extraneous cognitive load, enabling users to devote greater cognitive resources to higher-order processes such as analysis, evaluation, and creativity. These effects varied according to task complexity, user expertise, and the extent of AI use. Conclusion: AI-assisted cognitive offloading reshapes rather than uniformly diminishes or enhances human cognition. Longitudinal studies are needed to distinguish temporary cognitive adaptation from lasting cognitive change. The findings have important implications for education, digital literacy, and the human-centered design of AI technologies.
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