Why AI literacy must include supporting student – and faculty – well-being

We did not set out to become advocates for digital well-being. Our work in this area began, as so much does, with a simple request. A colleague at Virginia Tech invited us to speak about artificial intelligence. We were already exploring its role in teaching and learning, but the invitation reframed the conversation. It wasn’t just about what AI could do. It was about what it was doing to our students – and, increasingly, to us.

Across universities, responsibility for this issue remains unclear. Is digital well-being a student affairs issue? A teaching and learning issue? A policy issue? The result of this uncertainty is a murky landscape, where expectations are rising faster than guidance, and faculty are left to navigate its consequences in real time.

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Meanwhile, AI is rapidly being embedded into curricula. We, for example, are both involved with the AI undergraduate curriculum development initiative, a university-wide programme for faculty to layer AI into current and new courses. As this work has evolved, one thing has become clear: teaching AI cannot be separated from teaching about well-being.

Beyond detection and discipline

Conversations around AI in higher education once centred on academic integrity – that is, are students cheating? Now the discussion is more complex, and more human. Students are not only using AI to summarise readings or draft essays. They are using it to manage stress, to seek reassurance, to avoid struggle, and sometimes to replace interaction with others.

We’d like to acknowledge that faculty may feel this, too. Many of us are experimenting ourselves – using AI, questioning it. We are also carrying the emotional weight of deciding when to intervene in student use, how to respond to it and what it means for our relationships with learners. That uncertainty creates its own cognitive and emotional load that we may also struggle with.

Six questions we now teach

Because we cannot monitor every student-AI interaction, we focus instead on helping students develop habits of self-monitoring and self-regulation. We have created a simple approach or tool. The six questions that students – and faculty – can ask themselves when engaging with AI cover purpose, reliability, boundaries, distance, privacy and human connection.

1. Purpose: Why am I using this? Without intention, AI use drifts. What begins as a study aid can quickly become a substitute for thinking. Naming the role – tool, tutor, creator – helps students to act deliberately rather than reflexively.
2. Reliability: Can I trust this? AI is fluent, persuasive – and often wrong. Students must go beyond surface-level checks to question sources, biases and assumptions. This is not just information literacy; it is about developing a healthy relationship with knowledge itself.
3. Boundaries: How much is too much? AI is always available, always responsive. But learning depends on friction. If students outsource difficulty entirely, they risk losing the very processes that build confidence and competence, cheating themselves out of real skills.
4. Distance: Am I treating AI like a tool or a person? For example, when a student describes AI as “someone who listens”, we may need to remind them that AI is not a “someone”. Maintaining that distinction matters, especially when students turn to it for advice or support.
5. Privacy: What am I sharing – and where does it go? AI interactions feel private, but they are not necessarily so. Data can be stored, analysed and exposed. Your information may seem safe – until the next data breach inevitably occurs. A simple rule applies: if you wouldn’t post it publicly, don’t prompt it.
6. Human connection: Am I prioritising people? AI can assist, but it cannot replace the relational core of learning. If its use begins to displace interaction with peers, mentors or teachers, something essential is lost.

Knowing when AI helps – and when it harms

A question we are often asked is: how will you know when AI use becomes a problem? When is AI standing in the way of student learning or student well-being? The answer is that it depends on the student, on the situation, on the moment. The same tool can reduce anxiety in one moment and deepen dependency in another. It can support learning – or quietly erode it. It can offer clarity – or encourage avoidance. The difference lies less in the technology itself than in how, why and how often it is used.

That is why self-awareness matters. If students can recognise when AI is replacing effort, distorting trust or displacing connection, they are better positioned to use it well.

A shared responsibility

If there is one message we would offer colleagues globally, it is this: digital well-being cannot remain peripheral to AI integration. As institutions, we are moving quickly to embed AI into curricula. But if we do so without attention to how it shapes students’ thinking, relationships and sense of self, we risk solving one problem while creating another.

This does not necessarily require a stand-alone course – although it may justify one. It requires something both simpler and more demanding: that we embed questions of well-being into everyday teaching. That we create space for reflection, conversation and uncertainty. And that we acknowledge our own need, as faculty, for support in navigating this terrain.

Amy Allen is assistant professor of social studies in the elementary education programme, and David Hicks is professor of history and social science education, both at Virginia Tech. Their latest open access book is Teaching History with Chatty Geeps: A Technocurious Approach to Generative AI in the Classroom (VT Press, 2026).

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