Beyond the Algorithm: How Do We Bring Higher Education Back to the Learning?
For me, it feels as though AI has become the focal point in higher education. Every conference, workshop, and committee meeting now appears to revolve around the same question: What does/will AI mean for…? Then fill in the blank with anything from teaching, assessment, academic integrity, or any other education theme.
These conversations are important, urgent, even. But somewhere along the way, our collective gaze has narrowed. Have we started to mistake the discussion about AI for the broader, deeper conversation about learning itself?
The AI Overload
AI has quickly become shorthand for innovation. Universities are writing policies, redesigning assessments, and establishing task forces. The pace of AI discussions and debates feels relentless, and for good reason. Tools like ChatGPT, Claude, and NotebookLM are reshaping how information is accessed, processed, and produced.
Yet the widespread discussion of AI has created a strange paradox: the more we talk about it, the less room there seems to be for conversations that matter just as much in higher education, like motivation, belonging, curiosity, creativity and learning.
In many ways, AI has become the mirror through which higher education reflects on itself. However, mirrors only show what we decide to look at. The danger is that our focus on AI might cause us to overlook the truly human elements of learning.
When Tools Eclipse Purpose
Educational history is filled with instances where advances in technology sparked both excitement and apprehension among educators. The advent of the World Wide Web was heralded as the moment we would gain instant access to all the information we could ever need. MOOCs were to be a step toward democratising education, while Learning Management Systems aimed to transform student engagement. I was in high school when digital photography and video were introduced as the replacement for film and videotape formats. I still shoot film photography alongside digital, but that’s a topic for another time.
These are only a few examples of technologies meant to replace earlier forms. Although each introduced “innovation” and new opportunities, they eventually found their natural roles. They proved useful, but none were truly transformative by themselves.
As with previous technological innovations, AI will likely follow a similar path. The true change won’t come from the algorithms but from how we teach students to think, question, and find meaning in an AI-enabled world. That’s a pedagogical challenge, not a technological one, nor a matter of cheating or integrity.
Despite this, much of the current discussion and debate is focused and centralised on: “How do we stop students from using AI to cheat?”, “What can we hide in the assessment information to catch them out?”, rather than “What kind of learning makes cheating irrelevant?”
Have we lost our way? It appears we’ve shifted from emphasising curiosity to support learning, to designing learning experiences and assessments that are controlled and that have educators consistently questioning the integrity and intentions of the student.
The Narrow Lens
Maybe the core issue isn’t AI itself, but what it has revealed about higher education’s responses. Institutions are heavily focused on compliance, ethics, and detection. Meanwhile, discussions about how students genuinely learn, through reflection, feedback, collaboration, and taking risks, have been sidelined.
As discussions increasingly centre on AI, learning becomes mere background noise. The irony is that AI, when used thoughtfully, can actually help us reconnect with the essence of learning. It can support reflection, foster creativity, and deeper engagement. But only if we view its use as a tool in education, rather than the protagonist.
Recentring the Learning
So how do we get the discussion back to learning?
It starts with different questions, not centralised around control, but rather around curiosity. Instead of “How do we regulate it?”, we could ask, “What do we want our students to learn precisely because AI exists?”
This reframing shifts the conversation from fear to purpose. It reminds us that our responsibility isn’t just to manage the risks of new technologies, but to cultivate the dispositions that make learning meaningful, curiosity, criticality, creativity, and care.
At its core, teaching has always been about connection: between student and teacher, theory and practice, knowledge and identity. If our conversations about AI don’t strengthen those connections, then they are distractions, however well-intentioned.
The Broader Conversation
Perhaps what higher education needs now is not more AI debate, but broader debate. AI should sit alongside, not above, the conversations about curriculum design, wellbeing, assessment reform, and educational equity.
We need to bring AI into the whole learning ecosystem, not treat it as the ecosystem itself. Otherwise, it risks becoming the new tick-box, signalling progress while distracting us from purpose.
The deeper work of teaching, nurturing curiosity, building confidence, and fostering dialogue cannot be automated or outsourced. These are human acts. And they remain at the core of what makes education transformative.
Back to the Heart
AI is a powerful catalyst. It’s forcing us to confront important questions about authorship, originality, and the nature of knowledge. But its true value lies not in what it does, but in what it asks of us. For this, the answer may begin where it always has, in the messy, relational, human act of learning itself.
Reflections
When was the last time a discussion about AI at your institution led directly to a discussion about learning?
How might you reframe your next AI conversation to focus on pedagogy rather than policy?
What essential human capacities must education still nurture? Regardless of technological change.
How can your institution ensure AI becomes part of a broader conversation about teaching quality and student experience?
If we paused the AI debate for a moment, what conversations about learning have we been neglecting, and how might we bring them back?