As AI becomes part of students’ daily lives, one advocate argues schools should focus less on the tools—and more on understanding the systems behind them.
INTERVIEW | by Victor Rivero
Artificial intelligence is quietly becoming part of students’ everyday lives.
It shows up in the search results they see, the videos recommended to them, the apps they use—and increasingly, in tools that can write, solve, and create on demand. For many students, AI isn’t a future technology; it’s already woven into the digital world around them.
But Stewart Brown believes schools may be missing a crucial question.
If students are growing up surrounded by AI systems, do they actually understand how those systems work—or how they shape the information students see and the choices they make?
Through his work with districts across the United States at Code4Kids, Brown focuses on strengthening computer science learning in the elementary and middle school years—an area he believes has been largely overlooked as many schools still treat computer science as a high school elective rather than a foundational literacy.
His premise is simple: meaningful AI literacy begins with understanding the systems behind the tools. Students need more than access to powerful technologies—they need to understand the data, logic, and algorithms shaping them if they are going to question, interpret, and use AI responsibly.
Originally from South Africa and now based in the United States, Brown previously founded and led international education programs serving college students across multiple countries, experience that helped shape his systems-level perspective on education and long-term student outcomes. Today he works with school systems to move computer science beyond enrichment and into sustainable classroom practice beginning in the early grades. As the father of two young children, he also thinks about these questions not only as an educator, but as a parent.
We spoke with Brown about the origins of Code4Kids, the evolving role of computer science education, and why the conversation about AI in schools may need to start much earlier than many realize.
What originally inspired the creation of Code4Kids, and what problem in K-12 computer science education were you determined to solve?
The problem we set out to solve is that computer science is still treated in many schools as a high school specialization when it ought to be considered a foundational literacy in the age of AI.
‘…computer science is still treated in many schools as a high school specialization when it ought to be considered a foundational literacy in the age of AI.’
Our founder often tells the story of how he discovered coding himself. Like many people in tech, it wasn’t something he learned in school. He stumbled across programming while studying engineering in college and taught himself how to code.
That one skill completely changed the direction of his career.
He wondered what might happen if kids were exposed to those ideas much earlier. So he spent some spare time teaching his eight-year-old niece how to code — about 30 minutes here and there each week.
Over the course of two years, by the time she was ten, she could pass an entrance exam for a software engineering job that required a college degree.
He couldn’t believe what was possible at such a young age, especially since he wasn’t a teacher and his niece wasn’t a top-of-the-class student. They had simply spent a little time learning together.
That experience made one thing very clear: kids are capable of learning far more about technology than we often assume. The bigger issue was that schools simply weren’t teaching these ideas.
When his niece’s school heard about it, they asked him to come teach a few lessons to her class. Other schools began asking the same thing. Eventually it became clear this needed to grow beyond a few classrooms and that’s what led to the creation of Code4Kids.
With AI tools now able to generate code instantly, some people question whether students still need to learn programming. How do you see the role of computer science education evolving in the age of AI?
The question of whether students still need to learn coding often misunderstands what computer science education is actually about.
Learning computer science was never about producing professional programmers. Its real value lies in helping students understand how digital systems work.
It teaches ways of thinking that apply far beyond technology careers. Students learn how to break complex problems into smaller steps, design logical processes, test ideas, and fix things when they don’t work the first time.
‘Students learn how to break large problems into smaller pieces and design solutions step by step. They also develop creativity as they build games, simulations, and digital projects connected to their own interests.’
Those habits are also the foundation of meaningful AI literacy.
Students who understand the basic ideas behind software and algorithms are far better positioned to question AI outputs, recognize when something might be wrong, and use these tools thoughtfully rather than simply accepting what they produce.
In that sense, AI doesn’t make computer science less important. If anything, it makes understanding the systems behind technology even more important.
Beyond technical skills, what kinds of thinking should computer science education develop to prepare students for a world shaped by AI?
One of the biggest misconceptions about computer science education is that it’s mainly about technical skills.
In reality, it develops ways of thinking that extend far beyond programming.
Students learn how to break large problems into smaller pieces and design solutions step by step. They also develop creativity as they build games, simulations, and digital projects connected to their own interests.
Just as importantly, students start asking bigger questions and learn to think critically about technology – how algorithms influence the information we see, how bias can show up in digital systems, and how technology shapes decisions in society.
Perhaps the most important outcome is that students develop a sense of agency.
Technology stops feeling like something mysterious and instead becomes something they can understand, question, and shape. That mindset becomes increasingly important as AI systems become part of everyday life.
Teachers often feel intimidated by both coding and now AI. How can platforms like Code4Kids help educators build confidence while keeping up with rapidly changing technologies?
One of the biggest challenges schools face is simply the shortage of computer science teachers.
Most schools don’t have dedicated CS specialists, and most classroom teachers were never trained in programming themselves.
That’s why computer science needs to be designed in a way that regular classroom teachers can facilitate, even without prior experience.
Teachers don’t need to be the experts in the room. In many classrooms, teachers learn alongside their students – guiding exploration, asking questions, and supporting problem solving.
Another reality schools face is limited instructional time. Literacy and math demands are high, and educators are under pressure to improve outcomes in those areas.
So computer science can’t compete with core instruction for time. It has to connect with it.
That’s why our lessons are designed to integrate across subjects and reinforce the core curriculum rather than sitting outside it.
Looking ahead five to ten years, how do you see AI transforming both how students learn to code and how schools approach technology education more broadly?
AI will undoubtedly change how students learn.
Tools that help students test ideas, debug programs, and explore concepts quickly will become powerful learning partners when used thoughtfully.
But their presence also makes something increasingly clear: if technology can generate answers instantly, the real educational challenge becomes helping students understand the systems behind those answers.
‘…if technology can generate answers instantly, the real educational challenge becomes helping students understand the systems behind those answers.’
That’s where foundational computer science education becomes critical.
Over time, I believe computer science — and the problem-solving skills that come with it — will increasingly sit alongside reading, writing, and mathematics as part of the core literacy students need to navigate the modern world.
In many ways, computer science is becoming the foundation for AI literacy.
The goal isn’t to turn every student into a programmer. It’s to ensure students grow up understanding the technologies shaping their lives, and feeling capable of shaping them in return.
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Victor Rivero is Executive Producer of Future Focus Forums (F3) and Editor-in-Chief of EdTech Digest. Write to: victor@edtechdigest.com
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