Reflections from a conversation with Stewart Brown of Code4Kids
Last week, I had the opportunity to sit down with Stewart Brown, Director of Partnerships at Code4Kids, for a rich and wide-ranging conversation that ultimately zeroed in on something I’ve been turning over in my mind for months: AI literacy, and why it’s not just a new subject, but a foundational shift in how we prepare students for the world they’re inheriting.
And here’s the truth that settled in for me during that discussion: AI literacy is not about teaching kids to use tools, it’s about preparing them to shape the world with those tools.
“Code as Language, AI as Literacy”
Stewart said something that stuck:
“We don’t teach math so every child becomes a mathematician. We teach it because it teaches reasoning. The same is true for code, and now for AI.”
This hit me. The comparison reframes AI not as a technical elective but as a fundamental layer of 21st-century fluency. Just as reading and writing allow us to interpret and influence our world, AI literacy offers students the lens to understand how their world is being shaped, and gives them the tools to participate in that shaping.
It moved me from thinking about AI as a skill to master toward a deeper truth: AI literacy is cultural literacy.
Moving Beyond “How It Works” to “What It Means”
Too often, conversations around AI in education are narrowly focused on how we can use tools like ChatGPT in classrooms: for lesson planning, for automation, for convenience.
But the real question is:
How do we teach young people to think critically about how AI impacts their choices, their identities, and their futures?
From our conversation, a key takeaway was that understanding bias, data, agency, and ethics in AI isn’t optional, it’s essential. We’re raising a generation that will make decisions not just with information, but alongside algorithms. The stakes are far higher than we often acknowledge.
What the Future Learner Profile Must Include
Through Thinkering Collective, we’re always evolving the idea of what today’s and tomorrow’s learners need. This conversation pushed me to update that vision.
Here’s how I now define the Future Learner Profile:
AI-Fluent — Not just using AI but understanding how it’s built, why it behaves the way it does, and what to do when it doesn’t serve all users equally.
Ethically Grounded — Able to question who benefits and who is left out in automated systems.
Builder-Minded — Equipped to not just consume tech, but create with it, from storytelling prompts to real-world problem-solving.
Critically Curious — Willing to ask hard questions about power, privacy, and possibility.
These are the “new literacies” our learners need, and AI isn’t a standalone subject, it’s threaded through every domain of learning and life.
From Tool → Mindset → Movement
What Stewart and I returned to again and again was this: AI literacy isn’t just a curriculum decision. It’s a mindset shift. And if we do this right, it becomes a movement, a generational redefinition of what it means to be “educated.”
It’s not enough to prepare learners to adapt to a world shaped by AI.
We need to prepare them to critique it, redesign it, and lead within it.
What’s Next
This conversation has reshaped how I approach not just curriculum design, but mentorship, community building, and the design of learning experiences within Thinkering Collective. We are committed to embedding AI literacy into the soul of what we do, not just as content, but as context.
Let this be an invitation:
To educators: How are you reframing AI as part of your learner outcomes?
To students: What questions are you asking of the tech you use every day?
To all of us: What does it look like to be AI-literate together?
Because this isn’t just about understanding machines,
It’s about understanding ourselves in a rapidly shifting world.
Stay curious, stay courageous.
— Garrett
