The New Addiction? What AI Can Learn from Social Media’s Mistakes
Updated: Aug 31
The scroll that never ends.
It is past midnight. A university student lies in bed, phone glowing in the dark. The thumb flicks upward again: TikTok, Instagram, Snapchat, YouTube. One clip, one post, one algorithmically selected distraction after another. Hours disappear. We all know this story now.
Social media gave us extraordinary opportunities for communication, creativity and connection. But many platforms also became extraordinarily good at capturing and holding human attention. And importantly, there is already a great deal of AI involved in this environment. AI helps determine what appears in our feeds, what is recommended next, which content is likely to keep us engaged, which advertisements we see and which patterns of behaviour platforms learn from us.
So perhaps the arrival of generative AI is not the beginning of the relationship between artificial intelligence and human attention. It is the next chapter. And higher education should pay very close attention to what we have already learned.
From capturing attention to capturing thought
Social media largely competed for our attention and generative AI enters a much more intimate territory. It can participate in our thinking.
A student can ask a question and receive an answer immediately. They can ask for reassurance, explanations, ideas, feedback, summaries, arguments, interpretations and suggestions.
The interaction is conversational. Responsive. Patient. And increasingly, it can feel remarkably human.
That is precisely why I think we need to approach AI in education with both curiosity and responsibility. The problem is not simply whether students use AI. The more important questions are:
What happens to the learner when AI becomes part of the learning process?
What happens to curiosity?
What happens to persistence?
What happens to judgement?
What happens to the uncomfortable but necessary experience of not knowing?
And what happens to human relationships when a machine is always available to explain, reassure, suggest and respond?
Social media should have taught us something
One of the mistakes we made with social media was treating technology as though it were simply a neutral tool that people would learn to use responsibly. However, we must not forget that technologies also create environments. They shape behaviour through their design, incentives and affordances. Infinite scroll encourages continued consumption. Notifications interrupt attention. Recommendation systems reduce the effort required to decide what to look at next.
None of this means that social media is inherently bad. It means that the conditions surrounding technology matter. This is particularly important in education because learning is not simply the acquisition of information. Learning requires attention, effort, uncertainty, repetition, dialogue, reflection and sometimes frustration.
The difficult parts are not necessarily failures in the learning experience. Sometimes the difficult part is the learning experience. If AI removes every moment of uncertainty, immediately resolves every problem and produces every first draft, we may make education more efficient while accidentally removing some of the experiences through which human capability develops.
That is the challenge of responsible AI.
Responsible AI is not only about using AI correctly
Much of the conversation about responsible AI understandably focuses on important questions such as privacy, bias, transparency, academic integrity and misinformation. Again, I see another question belongs alongside them:
What human capabilities are we trying to protect and develop?
A responsible approach to AI in education cannot only ask whether the technology works. We also need to ask what happens when humans work with it. Does AI extend a student's thinking — or replace it? Does it stimulate curiosity — or satisfy it too quickly? Does it help students question information — or encourage them to accept plausible answers? Does it support reflection — or perform the reflection for them? Does it strengthen agency — or quietly encourage dependence? These are pedagogical questions as much as technological ones. And they are why educators become more important in the age of AI, not less.
Enter the Knowledge Mentor
When information becomes abundant, the educator's role changes. The lecturer is no longer valuable simply because they possess information that students cannot access elsewhere. Information is everywhere. AI can explain concepts, summarise readings, generate examples and answer questions within seconds.
Access to knowledge is not the same as knowing what to do with it. Students still need to learn:
What can I trust?
What is missing?
Whose perspective is represented?
What assumptions sit underneath this answer?
How does this connect to what I already know?
When should I challenge it?
What should I investigate next?
And ultimately:
What will I do with what I know?
This is what I call the Knowledge Mentor.
The Knowledge Mentor does not compete with AI to provide information faster. They help learners navigate knowledge. They create the conditions in which students learn to question it, connect it, test it, contextualise it and eventually develop the judgement to stand on their own. That role becomes essential when AI can produce convincing answers almost instantly.
The danger is not AI. It is cognitive outsourcing without awareness.
AI can be an extraordinary intellectual partner. It can help students explore unfamiliar ideas, compare perspectives, practise arguments, overcome language barriers, generate questions and receive feedback. We just need to keep in mind, that support and substitution are not the same thing.
There is a difference between using AI to extend human capability and using AI to avoid developing that capability in the first place. Imagine a student struggling to formulate an argument. AI could write the argument. Or AI could ask:
What do you think the strongest evidence is?
What assumption are you making here?
What would someone who disagrees with you say?
What evidence might change your mind?
The technology is the same. The learning experience is completely different. One removes cognitive effort. The other can create productive cognitive effort. Responsible AI therefore requires more than teaching students how to write prompts. We need to teach them when to use AI, why they are using it, what they are delegating to it and what they need to continue doing themselves. That is AI literacy. However, I would argue it is also something larger. It is education for human agency.
We need digital resilience, not digital avoidance
The answer is not to remove AI from education. Nor do I think educators should romanticise a pre-digital classroom.
AI is becoming part of the environment in which our students will learn, work and make decisions. Our responsibility is therefore to help them develop the capacity to live intelligently within that environment. That means creating learning environments that deliberately strengthen:
sustained attention rather than constant stimulation;
curiosity rather than immediate resolution;
critical judgement rather than automatic acceptance;
dialogue rather than isolated consumption;
productive struggle rather than effortless completion;
reflection rather than endless generation;
human relationships alongside technological assistance;
and agency rather than dependence.
This is what responsible AI should ultimately be about. Not protecting humans from technology.
Developing humans who can make educated choices within technological environments.
AI can learn from social media's mistakes (if we do learn)
Social media showed us what can happen when technological capability develops faster than our understanding of its human consequences. We should not repeat that mistake.
The lesson is not that technology is dangerous. The lesson is that conditions matter. What we reward matters. What we automate matters. What we make frictionless matters. And what we deliberately choose not to automate matters too.
Learning does not thrive because everything becomes easy. Human capability develops through the interaction between knowledge, experience, relationships, challenge and reflection.
AI can participate in that environment, but it should not become the environment.
From the ancient port to the AI classroom
In my earlier blog about the ancient ports of the Mediterranean, I explored empathy as something that enabled people to navigate difference, uncertainty and unfamiliar worlds.
The modern classroom faces a different landscape, but perhaps a related challenge. We are again learning how to navigate unfamiliar territory. This time the new participant is artificial intelligence. The question is not simply whether AI belongs in our classrooms. It already does.
The question is what kind of classroom we create around it. Will we optimise primarily for speed, efficiency and output? Or will we also protect curiosity, sustained effort, judgement, presence and authentic human connection? This is where the Knowledge Mentor matters.
Educators do not need to become walking databases competing with machines that can retrieve and generate information faster than any human ever could. Their value lies somewhere much more important.
They create the conditions in which another human being develops.
They notice.
They challenge.
They ask the question the student has not yet thought to ask.
They introduce uncertainty when an answer seems too easy.
They connect knowledge with context, experience and consequence.
And gradually, they help learners develop the judgement and agency to navigate knowledge for themselves. That is not a diminished role for the educator. It may be one of the most important roles educators have ever had.
The question is no longer whether AI will shape education. It will. The question is whether we will allow it to shape learners accidentally, or whether educators, institutions and students will consciously decide what should remain profoundly human.
Responsible AI begins right there.
I would love to hear your reflections on this topic.
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