Universities are asking the wrong questions as they attempt to adapt to the rise of generative artificial intelligence. They’re asking, “Should AI be banned? Should students disclose its use? How much AI use is acceptable? Are students abusing it? Should institutions use AI detection software?”
What they should explore instead is how to ensure that, in a world increasingly infused with AI, university students can still meaningfully function without it.
Universities should make students demonstrate their human intelligence, or AI independence, before they are allowed to use AI to advance their studies. They can do this by requiring students to complete a “Human Intelligence Certificate” before embarking on any degree program.
When School Work No Longer Proves Learning
For most of history, performance was treated as evidence of competence. A strong essay suggested strong writing skills. A persuasive presentation suggested communication ability. The work itself served as proof.
Artificial intelligence has broken that assumption.
Today, students can produce polished essays, presentations, reports, and summaries without necessarily possessing the underlying skills those assignments were designed to develop. The output may be excellent. The student’s capabilities may be much less certain.
This is not primarily a cheating problem. It is a development problem.
Today, students can produce polished essays, presentations, reports, and summaries without necessarily possessing the underlying skills those assignments were designed to develop. The output may be excellent. The student's capabilities may be much less certain.
The Value Of Cognitive Struggle
Many discussions about AI focus on academic integrity. While important, this emphasis risks overlooking a more fundamental challenge. Even when students use AI entirely within institutional rules, they may still bypass the struggle through which learning often occurs.
A student who uses AI to improve an argument is learning. A student who uses AI because they cannot construct the argument in the first place may not be. A student who uses AI to explain an unfamiliar concept is learning. A student who uses AI to complete an assignment without understanding it is merely submitting it. The distinction matters.
Outside the classroom, few employers care whether AI helped draft an email, summarize a report, or organize information. What matters is whether the individual understands the content, can evaluate it critically, and can function without the tool when necessary. Universities should focus less on detecting AI and more on teaching, developing, and verifying competence.
Even when students use AI entirely within institutional rules, they may still bypass the struggle through which learning often occurs.
Universities Know How To Evaluate Understanding
Universities often speak as though artificial intelligence has created an unprecedented assessment crisis. It has not. The underlying problem is ancient: how do you ensure that the work being evaluated belongs to the person receiving the credit?
Imperial China addressed the problem by locking candidates alone in examination cells and making them produce the work themselves. Modern universities possess countless equivalents: oral defenses, debates, presentations, handwritten examinations, open ended exam questions, case discussions, and live questioning. We already know how to test competence. What we lack is not methodology. We lack the willingness to accept the cost, inconvenience, and complexity that genuine, daily verification requires.
Universities have never been primarily in the business of information. Their enduring value lies in developing judgment, analysis, communication, resilience, and the ability to learn independently.
Beyond Grades: Building Resilience
Most graduates do not remember every lecture, chapter, or examination question. Yet many remember a particular argument, an uncomfortable realization, a moment when a long-held assumption fell apart, or a conversation that changed how they viewed the world. These intellectual turning points rarely arrive fully formed. They emerge through reading, discussion, disagreement, reflection, and struggle.
Universities do not merely reward students with grades. They expose them to deadlines, expectations, criticism, uncertainty, and responsibility within a relatively controlled environment. Students are not only learning accounting, chemistry, history, or law. They are learning how to function under pressure. Resilience is not an accidental by-product of education. It is one of its intended outcomes.
Artificial intelligence risks allowing students to bypass parts of both processes: the struggle through which ideas develop and the friction through which resilience forms. Rather than focusing exclusively on what students produce, institutions may need to pay greater attention to what students can do independently.
Resilience is not an accidental by-product of education. It is one of its intended outcomes.
Before Using AI, Learn Without It
The solution may be a “Human Intelligence Certificate,” completed before the start of every degree program. The certificate would demonstrate AI independence: the ability to perform essential academic and professional tasks without AI assistance.
Students would write under supervised conditions, participate in oral examinations, defend arguments in discussions, conduct independent research, evaluate sources, and solve problems without technological support.
A Human Intelligence Certificate would certify that they can function without AI – just as pilots must demonstrate they can fly an aircraft before relying on autopilot, and take control when it fails.
The best use of AI is as a shortcut, but only after the underlying skills already exist. AI can draft emails, identify weaknesses in arguments, summarize texts, organize information, and improve efficiency. In these situations, it accelerates tasks we are already capable of doing ourselves.
The danger arises when the shortcut becomes a substitute for the skill rather than a tool that enhances it. A shortcut is valuable because it shortens a journey we already know how to complete ourselves.
The greatest educational change brought by artificial intelligence may not be that students have answers. It may be that students are no longer forced to sit alone with questions. For most of human history, students wrestled with uncertainty, confusion, and incomplete understanding. Today, an answer is always seconds away. Yet confusion is not necessarily evidence that learning has failed. It is often evidence that learning has begun.
The greatest educational change brought by artificial intelligence may not be that students have answers. It may be that students are no longer forced to sit alone with questions.
Learning To Think Like A Lawyer
The strongest AI users are rarely those who depend on AI. They are those who can challenge it. They can identify errors, verify sources, recognize weak arguments, and detect hallucinations. In other words, they are precisely the people who do not actually need AI in order to function.
Employers have spent decades complaining that graduates possess credentials but lack competencies. Artificial intelligence risks widening that gap. The challenge facing universities is not merely producing impressive work. It is producing capable graduates.
The good news is that universities do not need to invent an entirely new educational model for the proposed Human Intelligence Certificate syllabus. A tried, tested, and remarkably effective one already exists: legal reasoning.
Contrary to popular stereotypes, legal education is not primarily about memorizing rules. It is training in disciplined thinking. Students learn to work from facts to principles, compare situations, distinguish meaningful differences, reconcile competing interpretations, and defend conclusions under scrutiny.
Most professions operate under uncertainty. Lawyers rarely know every fact. Managers rarely possess perfect information. Policymakers rarely understand all consequences. Legal reasoning is valuable because it teaches students how to think when certainty is unavailable.
The Socratic method pushes this process further. Students are required not merely to provide answers but to explain, defend, and refine their reasoning. Weak assumptions are exposed. Contradictions emerge. Certainty becomes more difficult to maintain.
Artificial intelligence is remarkably good at producing answers. The future may belong not to those who can generate information, but to those who can evaluate, challenge, and refine it.
A Month of Law School for Everyone
What is needed is not a course about legal rules. It would be a course about thinking.
College students would read carefully, annotate texts, identify assumptions, distinguish facts from opinions, construct arguments, defend conclusions, challenge unsupported claims, and participate in Socratic discussions where every answer invites another question. They would brief cases, apply legal reasoning frameworks, evaluate competing interpretations, and learn how small factual differences can produce entirely different outcomes.
They would write objective analyses and persuasive arguments, debate controversial issues, argue both sides of the same question, identify logical fallacies, and separate confidence from credibility.
The goal would be to teach them how to think when information is abundant, answers are cheap, and certainty is unavailable.
For a month, students would work largely without screens, AI tools, or digital assistance. They would read, write, discuss, debate, annotate, analyze, and defend ideas in person. Students who successfully demonstrate the required skills would earn the Human Intelligence Certificate and could then be trusted to use artificial intelligence however they see fit. Students who fall short would receive additional training and another opportunity to demonstrate competence.
For a month, students would work largely without screens, AI tools, or digital assistance. They would read, write, discuss, debate, annotate, analyze, and defend ideas in person. Students who successfully demonstrate the required skills would earn the Human Intelligence Certificate and could then be trusted to use artificial intelligence however they see fit.
Preserving Human Intelligence In The Age Of AI
The principle is simple: before college students are permitted to rely on AI, they should first demonstrate that they do not need it.
The irony of the AI era is that the students who benefit most from AI are often those who need it least. They already possess the skills necessary to question, verify, refine, and improve its output. Universities should incorporate that understanding in their curricula and assist every student in gaining this skillset.
The original Turing Test asked whether machines could imitate human intelligence. Universities may increasingly face the reverse challenge: proving that humans still can.
