I recently retired from higher education. Although it represented a relatively short period of my overall career, I enjoyed the opportunity to work with young people and help prepare them to go forward into the world with their eyes open—or partially open, at least.
I must also say, with all respect to academia, that I was never entirely convinced by either the cost of obtaining a higher degree or the value students ultimately received from it. It is through that lens that I offer these thoughts.
For centuries, education has been built around a relatively simple assumption: knowledge is scarce, and teachers and universities are responsible for transmitting it.
That assumption no longer holds.
Artificial intelligence can already explain complex ideas, translate information, compare theories, generate examples, provide individual feedback and adapt its teaching to the needs of a learner. It can do this at any time, at little cost and without becoming impatient. In many situations, AI may already teach more effectively than the average human teacher—not necessarily because it possesses wisdom, but because it makes knowledge immediately accessible.
This creates an uncomfortable question for higher education:
What is the purpose of a university when knowledge is no longer difficult to obtain?
Much of our present education system remains organised around acquiring, remembering and reproducing information. Students attend lectures, take notes, read prescribed materials and then sit examinations designed to determine how much they can recall or explain. Success is often measured by the ability to produce an acceptable answer under controlled conditions.
AI has exposed the limitations of this model.
If an AI system can answer an examination question more accurately than the student—and sometimes more accurately than the lecturer—then the examination may no longer be measuring a capability that carries much value. Preventing students from using AI might protect the assessment process temporarily, but it does not resolve the deeper problem. We would merely be protecting a system designed for a world that is disappearing.
During my time as an Associate Professor, I saw this tension firsthand. My university was strongly opposed to students using AI. For a while, it was possible to detect its use, but this became increasingly difficult as the technology improved. The university system appeared to struggle with the need to change. Although some institutions and individual academics are attempting to respond, the continuing value of the current model must now be questioned.
I became increasingly frustrated as students used AI to complete their assignments while lecturers also began using AI to assess those assignments and provide feedback. We were moving towards a situation in which one machine produced the work and another machine evaluated it, while the student and lecturer became increasingly peripheral to the process.
Beyond the credential awarded at the end, what educational value remains in such an exchange?
It seems to me that the value of completing a university degree is being steadily eroded—not because learning has become less important, but because the system continues to reward activities that technology can now perform more efficiently.
This does not mean that human beings no longer need knowledge. We cannot think critically about something we know absolutely nothing about. We need enough knowledge to recognise what matters, frame useful questions, detect errors and judge whether an answer makes sense. A person who lacks any understanding of a subject is easily misled by both humans and machines.
But the emphasis must change.
The central purpose of education should no longer be how much a person knows. It should be whether that person understands what they need to know, where to find it, how to evaluate it and, most importantly, what they are capable of doing with it.
Human beings are not simply information-storage systems. We are physical, cognitive, imaginative and social beings. We are born with the capacity to move, observe, reason, create, cooperate, communicate, care, adapt and act. These functions do not operate separately. In real life, they are integrated.
Physical literacy provides a useful example of what education could develop but frequently neglects. A physically literate person does not merely know that exercise is beneficial. They possess the confidence, competence and understanding needed to move effectively and remain active throughout life. They can adapt their movement to different environments, recognise the needs of their own body and participate confidently with others.
The benefits extend well beyond sport. High levels of physical literacy support independence, health, resilience, confidence and social participation. They allow people to continue doing things for themselves as they age. They also teach lessons that cannot be fully learned from a lecture or generated by AI: how to persist through difficulty, respond to physical feedback, manage risk, cooperate with others and translate intention into coordinated action.
A student could produce an excellent essay about physical health with the assistance of AI while lacking the ability, confidence or motivation to apply any of that knowledge personally. This captures the weakness of an education system that rewards knowing about something without requiring the learner to become capable of doing it.
The same principle applies across other areas of human development.
A nurse does not merely know medicine. A good nurse observes, communicates, reassures, decides and acts.
An engineer does not merely know formulas. An engineer applies knowledge to physical conditions, resource limitations and human needs.
A teacher does not merely know a subject. A teacher creates an environment in which another human being develops confidence, curiosity, judgement and capability.
Leadership, likewise, is not demonstrated by correctly defining leadership theories. It is demonstrated through the ability to understand people, make decisions under uncertainty, accept responsibility and mobilise collective effort.
This is where higher education must rediscover its relevance.
Universities should become places in which people learn to use knowledge through purposeful action. Students should work on real problems, create things, test ideas, undertake investigations, collaborate with communities, manage projects and experience the consequences of their decisions. Their education should also develop physical competence, personal resilience, creative expression and the ability to function constructively with others.
Assessment should focus less on what students can reproduce and more on what they can design, demonstrate, improve, defend and implement.
AI should be integrated into this process. Students must learn how to use it intelligently, question its output, identify its limitations and combine its capabilities with human experience and judgement. Prohibiting AI in education would be rather like prohibiting calculators because students might stop doing arithmetic by hand. The more important task is to decide what human capability should develop once a machine can perform part of the work.
There are still qualities that cannot be reduced to the production of a technically correct answer. Judgement develops through experience. Trust develops through relationships. Courage becomes visible when decisions carry consequences. Imagination requires the willingness to see possibilities beyond what already exists. Wisdom involves understanding not only what can be done, but whether it should be done.
These are not secondary educational outcomes. They should become central.
The arrival of AI therefore does not make higher education irrelevant. It makes much of the existing model of higher education increasingly difficult to justify.
Universities will remain relevant if they help human beings become more capable—not merely more credentialled. Their task should be to develop the whole person: physically confident, intellectually curious, imaginatively alive, socially competent and capable of integrating these qualities in practical situations.
The graduate of the future should not be distinguished by the amount of information stored in their head. AI will nearly always have access to more.
The graduate should be distinguished by the ability to recognise what matters, ask better questions, evaluate competing answers, work constructively with others and turn knowledge into responsible action.
The real educational question is no longer simply:
What do you know?
It is:
What can you understand, what can you create, and what can you do—with all the knowledge now available to you?
