Higher Education Leaders Need to Ask Hard Questions About AI
College presidents and academic leaders face a choice: treat AI as a tool that supplements learning or as a replacement for the work that builds critical thinking. The decision matters more than the technology itself.
That's the core argument from one college president who examined how his institution should respond to AI adoption. Rather than offering prescriptions, he posed a framework of questions that leaders should work through with their communities.
What is the actual purpose of higher education?
Start with fundamentals. Does your institution exist to build skills? Transfer knowledge? Form character? Most likely, it's all three - but the balance matters when deciding how to deploy AI.
Consider what students actually need. They require specific skills tied to their field: an accountant needs to know accounting principles, not just how to look them up. They need general skills like critical thinking and teamwork. And they need formation - the development of whole persons with integrity, work ethic, and respect for truth.
AI can assist with some of these outcomes. It cannot shortcut others. A student who uses AI to generate an essay hasn't developed the thinking skills that writing demands. A graduate who relies on AI to perform calculations hasn't internalized the principles that make those calculations meaningful.
The question isn't whether to use AI. It's whether your use of AI advances or undermines what your institution claims to do.
Who gets a voice in this decision?
Most institutions have obvious stakeholders: faculty, students, staff, employers, accreditors. But AI raises questions that go beyond traditional education policy.
Philosophers, ethicists, and faith leaders belong in these conversations. So do people who understand privacy implications, military applications, and workforce disruption. Higher education is uniquely positioned to bring these perspectives together - arguably the only institution designed to do so.
Without this broader input, institutions risk adopting AI without understanding its moral and ethical implications. A college that integrates AI into every course without asking what that means for student privacy or autonomy has made a decision by default, not by design.
How do students actually learn?
The research on learning hasn't changed. Students master skills through reading, thinking, practicing, and making mistakes. They don't learn by having information downloaded into their brains - that only works in movies.
This creates a practical problem. Students naturally take the easiest path available. If AI can generate an answer, many will use it to avoid the harder work of thinking. Institutions need systems that ensure students are learning, not just submitting AI-generated output.
That doesn't mean banning AI. It means being deliberate about when and how students use it. An economics student might use AI to check their work on a problem set. The same student shouldn't use AI to avoid working through the problem in the first place.
What does responsible AI use look like in practice?
Individual leaders should model the behavior they expect. One college president said he's deliberate about setting his phone down during conversations and avoiding AI when listening or engaging in dialogue. Thinking and creating remain fundamentally his work.
At the same time, he uses AI for specific tasks: finding research, answering factual questions, analyzing reports. He's used it to assess how he spends his time against his strategic plan. In each case, he had a clear learning objective and always checked the AI's work.
The pattern is consistent: AI as a tool for specific, bounded tasks, not as a replacement for judgment or critical work.
The compass without a map problem
Many institutions say they want to produce "AI-literate graduates" or integrate AI into student learning. Those statements describe direction but not destination. They're a compass without a map.
Leaders need to understand where their institution currently stands on AI and where it wants to be. That requires honest conversation about values, purpose, and what the institution owes its students and society. Only then can AI adoption serve institutional goals rather than drive them.
The questions don't have universal answers. But institutions that ask them - and involve their full community in answering them - will make better decisions about AI than those that don't.
For educators navigating these decisions, resources on AI for Education and learning paths for teachers can help build the knowledge needed for these conversations.
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