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A Conceptual Framework for Identifying Risks of AI Integration in Higher Education

by Asma Ali Mosa Eltharif, Reem Ali Salem Abdalla
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 18
Year of Publication: 2025
Authors: Asma Ali Mosa Eltharif, Reem Ali Salem Abdalla
10.5120/ijca2025925258

Asma Ali Mosa Eltharif, Reem Ali Salem Abdalla . A Conceptual Framework for Identifying Risks of AI Integration in Higher Education. International Journal of Computer Applications. 187, 18 ( Jul 2025), 39-50. DOI=10.5120/ijca2025925258

@article{ 10.5120/ijca2025925258,
author = { Asma Ali Mosa Eltharif, Reem Ali Salem Abdalla },
title = { A Conceptual Framework for Identifying Risks of AI Integration in Higher Education },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2025 },
volume = { 187 },
number = { 18 },
month = { Jul },
year = { 2025 },
issn = { 0975-8887 },
pages = { 39-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number18/a-conceptual-framework-for-identifying-risks-of-ai-integration-in-higher-education/ },
doi = { 10.5120/ijca2025925258 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-07-09T01:07:36.643802+05:30
%A Asma Ali Mosa Eltharif
%A Reem Ali Salem Abdalla
%T A Conceptual Framework for Identifying Risks of AI Integration in Higher Education
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 18
%P 39-50
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The integration of Artificial Intelligence (AI) into Higher Education (HE) presents a dual-edged sword, offering transformative potential while introducing significant risks. This paper synthesizes existing literature to examine the multifaceted challenges associated with AI adoption in academic settings, including threats to academic integrity, algorithmic biases, data privacy concerns, and the erosion of critical human skills. This paper proposes the HE AI Risk Ecology (HE-AIRE) model, a conceptual framework that categorizes these risks into four interconnected layers: pedagogical, technological-ethical, institutional-operational, and socioeconomic-cultural. By highlighting systemic interdependencies, the model underscores the need for holistic strategies to mitigate risks while harnessing AI's benefits. The study calls for robust ethical frameworks, equitable implementation, and proactive policy interventions to ensure AI aligns with the core values of HE.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Intelligence (AI) Higher Education (HE) Risks Ethical Frameworks Technology in Education.

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