Cognitive Offloading to Artificial Intelligence and Perceived Self-Efficacy

Tomasz J. Kowalczyk

Cognitive Offloading to Artificial Intelligence and Perceived Self-Efficacy

Author(s)	Dr. Tomasz J. Kowalczyk
Country	United States
Abstract	Artificial intelligence has become an increasingly accessible external cognitive resource for information retrieval, idea generation, summarization, problem solving, drafting, planning, and decision support. Its growing role in everyday knowledge work raises a significant psychological question: when individuals delegate cognitive operations to artificial intelligence, does the resulting reduction in mental effort strengthen their perceived capability or gradually weaken confidence in their ability to perform independently? This study examines the relationship between cognitive offloading to artificial intelligence and perceived self-efficacy through a simulation-based analytical design grounded in cognitive offloading theory and social cognitive theory. Rather than presenting synthetic observations as real participant data, the study constructs a reproducible hypothetical dataset of 360 cases to test a theoretically informed nonlinear model. AI cognitive offloading was modeled on a five-point continuum, while perceived self-efficacy represented confidence in independently understanding, evaluating, solving, and completing cognitively demanding tasks. The simulation also incorporated AI literacy as a control variable. Results produced a curvilinear pattern. Mean perceived self-efficacy increased from 3.44 among low-offloading cases to 3.76 under moderate offloading, before declining to 3.53 among high-offloading cases. Quadratic regression supported the simulated inverted-U relationship, with the negative squared offloading coefficient indicating that increasing delegation became progressively less beneficial after a moderate level. The findings support a distinction between supportive offloading, in which AI reduces peripheral cognitive burden while preserving human judgment, and substitutive offloading, in which AI begins to replace cognitively consequential processes required for mastery and confidence formation. The study therefore argues that the central psychological issue is not whether people use AI, but which cognitive operations they delegate, how frequently they verify AI outputs, and whether they retain opportunities for independent mastery. Implications are developed for higher education, professional learning, human–AI interface design, and future longitudinal research.
Keywords	artificial intelligence, cognitive offloading, perceived self-efficacy, generative AI, cognitive dependence, human–AI collaboration, metacognition, cognitive agency
Field	Engineering
Published In	Volume 4, Issue 1, January-February 2023
Published On	2023-01-19

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American Journal of Advanced Multidisciplinary Innovation and Research

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Cognitive Offloading to Artificial Intelligence and Perceived Self-Efficacy

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