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

Dr. Ramzy Muorwel Matueny and Dr. Joseph Juma Nyamai
Additional contact information
Dr. Ramzy Muorwel Matueny: College of Health Sciences, Mount Kenya University, Thika Main Campus, Kenya
Dr. Joseph Juma Nyamai: College of Health Sciences, Mount Kenya University, Thika Main Campus, Kenya

International Journal of Research and Scientific Innovation, 2025, vol. 12, issue 5, 1725-1738

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.

Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.rsisinternational.org/journals/ijrsi/d ... ssue-5/1725-1738.pdf (application/pdf)
https://rsisinternational.org/journals/ijrsi/artic ... endency-among-users/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjc:journl:v:12:y:2025:i:5:p:1725-1738

Access Statistics for this article

International Journal of Research and Scientific Innovation is currently edited by Dr. Renu Malsaria

More articles in International Journal of Research and Scientific Innovation from International Journal of Research and Scientific Innovation (IJRSI)
Bibliographic data for series maintained by Dr. Renu Malsaria ().