AI Literacy in the Digital Age: A Conversation with Dr Stella Lee
As part of the run up to the Young People’s Summit, last week I spent 90 minutes talking about AI literacy with Dr Stella Lee. Stella is an AI literacy architect who works with educators and organisations worldwide, trying to understand the techno-social changes being brought about by the mass adoption of AI. She’s developed her own framework for AI literacy through her consulting work, and she comes at this from a practical, boots-on-the-ground perspective – including helping educators in real classrooms make real decisions about AI tools.
I came to the conversation with the eight-part framework I developed for my Beyond Digital Natives primer, which focuses on how citizens can maintain agency and well-being in an algorithm-dominated world. I’m using the framework for a new course I’m teaching at the University of Malta, on critical digital and information literacies. Different starting points, but as we discovered, we’re basically climbing the same mountain from different sides.
Here’s a summary of what we talked about – and why it matters to young people.
1. The Truth Crisis (Or: Why “Just Google It” Doesn’t Work Anymore)
We started with the elephant in the room: how do you know what’s real when AI can generate such convincing content at scale?
Stella dropped this observation that stuck with me: for GenZ, the default position is mistrust. They assume things are fake until proven otherwise. That’s a profound shift from how older generations approached information.
We agreed that traditional “check your sources” advice isn’t enough anymore. When LLMs hallucinate with complete confidence, and deepfakes are indistinguishable from reality, you need something deeper.
What actually helps: Domain expertise. That gut feeling when something is “fishy” or “not quite right.” You develop that by actually knowing stuff deeply, not just skimming surfaces.
And yes, prompt engineering matters. Not because it’s a hot skill for your resume, but because it keeps you in the driver’s seat. When you know how to interrogate AI tools effectively, you’re not just passively accepting whatever they spit out: you’re maintaining intellectual control.
2. The Invisible Infrastructure (Or: Why “I Have Nothing to Hide” Is Tripe)
Our second chunk of conversation went deep on ethics, data, and all the invisible systems that make AI work.
We kept circling back to: AI is only as good as the data it learns from. And that data is messy, biased, and collected in ways that should probably make you uncomfortable.
Stella emphasised something crucial: data fluency isn’t about becoming a data scientist or being good at math. It’s about understanding how data shapes the AI models you use, and more importantly, knowing what questions to ask.
What questions to ask vendors when they want your data. What questions to ask platforms about how they’re using your information. What questions to ask institutions that want to implement AI systems.
This is where the “I have nothing to hide” mentality falls apart. It’s not about having secrets. It’s about maintaining your digital rights and understanding your data footprint. We need to move beyond resignation and start pushing back.
3. The Education Crisis (Or: Why Your University Is Freaking Out)
This is where we got blunt. Stella described the university approach to AI as “very pessimistic, very reactive”: institutions banning tools, treating assessment as a “pain,” and basically having a collective panic attack. I observed that in a remarkable break from tradition, the University of Malta is actually encouraging students to use AI mindfully, and made an enterprise version of NotebookLM available to those who wish to use it.
Yet most academic institutions continue to flounder, also missing the wood from the trees. Assessment models haven’t really worked well for centuries anyway. AI is forcing the question: what are we actually evaluating? We’re not sure that the sudden turn to oral examinations or pen and pencil exams will be sustainable ‘solutions’ without the academy doing a deep dive to understand its very reason for being – besides the power of the academic credential, and the social and economic capital attached to that. The academy was shocked into the digital domain when the Covid pandemic started to lockdown lecture halls. Since then, many in the academy treated the sudden turn to digital as a momentary lapse of reason. The AI crisis is unlikely to disappear in the matter of three years.
Stella championed an idea I like: “process as product.” Instead of just submitting a final essay, you document the steps you took, the prompts you used, the iterations you went through. You make your thinking visible.
This isn’t about catching cheaters: it’s about building genuine transparency into how we work with AI. It’s about establishing protocols for Human-AI collaboration that enhance your research capacity while keeping you in control.
Here’s what this means practically: when you use AI in your work (and you are), be explicit about it. Show your process. Demonstrate that you’re using AI as a tool for augmentation, not replacement.
4. The Bigger Picture (Or: Why This Is About More Than Just You)
Our final segment zoomed way out to look at the psychological and structural impacts of AI.
Stella raised something that’s probably resonating with many young people: the deep anxiety young people feel about an uncertain, rapidly changing world. The AI generation is dealing with existential uncertainty that previous generations didn’t face in quite the same way.
This is where our frameworks really aligned. Digital challenges need systemic solutions, not just individual behavior change. You can’t mindfulness-app your way out of structural problems.
We both called for radical reform. I argued that the current academic model – designed to protect tenure and profit – should “almost be blown up” to create alternatives better suited to technological change. Stella’s work with educators shows that people on the ground are hungry for better frameworks, but institutions are moving too slowly.
We need to keep advocating for platform accountability. Push for regulatory reform. Don’t accept “this is just how things are” as an answer. The Young People and Information – A Manifesto we published last year remains as timely and relevant as ever.
The One Skill That Matters Most
We ended our conversation by trying to define what distinguishes a critically engaged citizen from someone who just happens to have grown up with technology.
The answer we landed on: continuous vigilance.
Not paranoia. Not cynicism. But the ability to constantly question assumptions, to not take things for granted, to keep asking better questions.
Sometimes that means antagonising AI models to test their limits. Sometimes it means making educators and institutions uncomfortable by pointing out contradictions. Always it means rigorous, informed engagement.
What This Means for You
Whether you frame it as making informed decisions (Stella’s angle) or maintaining agency (my angle), the goal is the same: empowering you to harness technology’s benefits while actively resisting its potential harms.
You’re not just users. You’re not just consumers. You’re citizens who need to inhabit digital futures “with intention, wisdom, and care.”
That’s a hell of a responsibility. You can start by questioning everything. Including (and especially) what I just wrote.
Check out my Beyond Digital Literacies primer. Stella Lee’s consulting firm is Paradox Learning. The Young People’s Summit is on November 7-8, in Valletta, Malta.
