Illusion of Competence and Skill Degradation in Artificial Intelligence Dependency among Users

This conceptual review paper explores the emerging phenomenon of skill degradation in the context of increasing reliance on artificial intelligence (AI) within higher education and professional environments. As AI tools become integral to learning, writing, assessment, and decision-making processes, many users particularly students and instructors experience what has been termed the illusion of competence, a misleading perception of mastery created by AI-generated outputs that mask underlying cognitive deficits. Drawing on Cognitive Load Theory and Technological Dependency Theory, this paper examines how the offloading of intellectual effort to AI systems diminishes core human faculties such as memory retention, critical thinking, metacognitive awareness, creativity, and professional judgment. The analysis is structured across multiple dimensions, including the cognitive mechanisms of skill loss, real-world manifestations in academic and occupational settings, and the broader psychological and social consequences of overdependence. It highlights risks such as academic underperformance, reduced originality, erosion of self-efficacy, widening equity gaps, and the devaluation of human expertise. Ethical and pedagogical concerns such as fairness, transparency, data privacy, and faculty readiness are also addressed. The paper concludes with strategic recommendations for educational institutions, including the need for AI literacy training, faculty development, assessment reform, and policy frameworks that encourage responsible and critical engagement with AI technologies. Ultimately, the paper argues for a balanced, human-centered approach to AI integration, one that positions AI as a support system rather than a substitute for cognitive engagement, ensuring that technological advancement enhances rather than displaces the human capacity for deep, reflective learning.

Authors

Publication Details

Journal
International journal of research and scientific innovation
Published
2025-06-18
DOI
https://doi.org/10.51244/ijrsi.2025.120500163
Citations
3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.96
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article

Illusion of Competence and Skill Degradation in Artificial Intelligence Dependency among Users

Ramzy Muorwel Matueny, Joseph J. Nyamai
3 citations
International journal of research and scientific innovation
Artificial Intelligence in Healthcare and Education
1.96
article

Illusion of Competence and Skill Degradation in Artificial Intelligence Dependency among Users

Ramzy Muorwel Matueny, Joseph J. Nyamai
article en
3 citations

Abstract

This conceptual review paper explores the emerging phenomenon of skill degradation in the context of increasing reliance on artificial intelligence (AI) within higher education and professional environments. As AI tools become integral to learning, writing, assessment, and decision-making processes, many users particularly students and instructors experience what has been termed the illusion of competence, a misleading perception of mastery created by AI-generated outputs that mask underlying cognitive deficits. Drawing on Cognitive Load Theory and Technological Dependency Theory, this paper examines how the offloading of intellectual effort to AI systems diminishes core human faculties such as memory retention, critical thinking, metacognitive awareness, creativity, and professional judgment. The analysis is structured across multiple dimensions, including the cognitive mechanisms of skill loss, real-world manifestations in academic and occupational settings, and the broader psychological and social consequences of overdependence. It highlights risks such as academic underperformance, reduced originality, erosion of self-efficacy, widening equity gaps, and the devaluation of human expertise. Ethical and pedagogical concerns such as fairness, transparency, data privacy, and faculty readiness are also addressed. The paper concludes with strategic recommendations for educational institutions, including the need for AI literacy training, faculty development, assessment reform, and policy frameworks that encourage responsible and critical engagement with AI technologies. Ultimately, the paper argues for a balanced, human-centered approach to AI integration, one that positions AI as a support system rather than a substitute for cognitive engagement, ensuring that technological advancement enhances rather than displaces the human capacity for deep, reflective learning.

International journal of research and scientific innovationVol. XII(V)
Quality Education
Openalex Percentile: Top 11%
Artificial Intelligence in Healthcare and Education
1.96
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