Examining University Obsolescence Claims in the Conversational AI Era

Abstract

Background: Higher education is at a crossroads with artificial intelligence, in particular, large language models such as ChatGPT, providing new opportunities to customize learning on demand. The latest developments, including the increased connectivity between chat AI and online platforms including Coursera, have raised concerns as to whether conventional universities will be able to survive. These applications promise seamless curriculum development, interactive video classes, voice responsive tutors, and high-tech instructions using visual and metaphorical explanations and all this is made immediately and cheaply.

Objectives: This review analyzes critically the argument that colleges will become obsolete in few years due to the use of AI-based learning. It also assesses the practical capacity of the existing AI education tools, quantifies their real and possible impact on universities, identifies gaps between the promises and delivery of technology, and considers the numerous roles that universities fulfill beyond merely passing knowledge.

Methodology: The methodology adopted in the study is a narrative review with technology assessment models. The researchers checked regarding journals and databases, namely, ERIC, Scopus, Web of Science, and Google Scholar that included articles published since 2018. Peer-reviewed articles, technical reports, policy documents, and credible industry analysis were searched. The keywords included AI in higher education, personalised learning technologies, ChatGPT education, the university disruption, online learning platforms, and so on.

Key Findings: There were four major themes. To begin with, the existing AI systems are not only powerful but also have obvious limitations. Second, their performance in instruction is yet to be compared with the conventional practices. Third, universities offer a rich variety of services in addition to teaching including research support and community building. Fourth, economic and social effects of possible disruption are complicated. Although AI enhances content delivery and tutoring, it lacks critical-thinking, collaboration, credential credibility, research, and fair-access. Overall, there is an indication of transition to hybrid models, as opposed to the total substitutes of institutions.

Conclusion: The relationship of AI with higher education is also transformative rather than destructive. Although universities need to change and evolve AI in a way that is considerate, it has not been empirically proven that few years will lead to complete obsolescence. The future research must be directed to study long-term learning, equity, the most effective ways to employ AI in teaching, and institutional change strategies. The collaboration between policymakers, teachers and technologists need to come together to ensure that educational evolution enhances, and not diminishes accessibility, quality and benefit to the society.