Universities should not be adopting AI to automate their own absurdities ...Middle East

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The promises AI offers higher education are familiar: an increase in efficiency as a consequence of less administration, more teaching coverage, better feedback and smarter assessment. But introducing artificial intelligence (AI) systems in an attempt to fix these problems is not the answer. If anything, AI systems will magnify and speed up the bureaucracy that is driving universities' decline.

The danger is not that AI will destroy universities but that universities will use AI to preserve the very processes that make them dysfunctional. If this happens, we might see faculty spending less time on research, less time on teaching, and more time on activities that do not directly contribute to the production of knowledge and education of students.

In essence, faculty become the human interface between incompatible platforms, spending their time reconciling grades and chasing missing evidence rather than teaching. While this example pertains to U.K. universities, the trend to expand the administrative staff extends to North America. AI simply introduces a new opportunity to increase administration.

At least one possible outcome is that universities will create AI-use policies, require module-level AI statements, mandate disclosure forms, introduce approved-tool lists and establish review committees. Faculty will be asked to redesign assessments, monitor suspected misuse, document their decisions, complete training, and explain their approach to students. Much of this labor will be invisible. It will appear not as a new job title but as an additional expectation attached to teaching.

This creates a familiar pattern: responsibility without authority. Faculty are expected to make consequential judgments about academic integrity, fairness, privacy and assessment validity. But they do not control procurement, system design, institutional policy or disciplinary procedures. When something goes wrong, the academic is exposed; when the system works, the institution claims the credit.

One possible outcome is that universities will encourage the development of faculty AI avatars and cut hours and employment. The institution will then justify hiring more ‪—‬ not fewer ‪—‬ compliance and "educational enhancement" staff to manage and maintain these AI avatars, negating the idea of efficiency and cost savings. In this scenario, bureaucracy will expand to manage the problems created by its own expansion while undercutting quality for the students who are paying high tuition fees. One might need to hire staff for oversight of these avatars, administrators and lawyers to manage licensing agreements, quality control staff in case things go wrong, and IT teams for integrating them into learning platforms and websites.

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There is an alternative to the administrative tasks. AI should be governed by a simple institutional rule: no new compliance requirement without the removal of an equivalent existing burden. If a university requires assessment redesign to accommodate AI, or the introduction of new technology, it should provide protected time, technical support and a single integrated platform. If it expects faculty to manage AI use, it must give them clear institutional backing rather than leaving them to improvise. And critically, it should show how the technology makes work more efficient before rolling it out across the board.

If they cannot, the outcome will be an educational system that looks progressively sophisticated while becoming increasingly hollow ‪—‬ full of monitoring, low on trust; rich in measuring, poor in teaching; obsessed with compliance, indifferent to the people who make education possible; overly procedural sans intellectual life. It will become an audited theater of learning not worth students' time.

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