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If this episode makes you think, please let us know in the comments and support us by subscribing and leaving a review. Thank you. Today we are exploring a really insightful piece from Forbes, written by John Coetzee, a senior contributor there. The article is titled, and I think this really nails it, the real AI education problem isn't cheating, it's Passivity It's a conversation with Navan Gurney, who is the CEO of Code Ninjas, which is the world's largest kids coding franchise. Now, when ChatGPT first exploded onto the scene, the big panic, the big conversation in education, was all about cheating, wasn't it? We saw surveys like one from Study.com, which the article mentions, suggesting that nearly 90% of college students had used AI for homework, nearly half for an at home test and and over half to write an essay. And I don't think any of us would expect those numbers to have dropped in the three years since. But what Gurney argues and what Coetzee explores is that while those numbers certainly raised eyebrows, they might not be the scariest numbers we should be looking at. The real concern. The real AI in education problem, according to Guernany, is the percentage of kids who now just automatically reach for an AI chatbot before they even try to solve a problem on their own. And honestly, when I read that, it really resonated with me because it hits on one of my core philosophies. We should always aim to outsource our doing, not our thinking. If students are skipping the thinking part entirely, they're not just using a tool, they're short circuiting a fundamental part of the learning process. Gurnani puts it very clearly in the Tech first podcast interview that Kitzia references, saying that if kids are being taught or being steered in the direction of hits, this is a cool tool you can just use and you'll get the answers. And that's what you see most kids doing. Then they learn nothing. And that's the heart of it, isn't it? The real value in learning isn't just in the answer, it's in the process, the productive struggle, the wrestling with a problem that ultimately builds understanding and resilience. If a student bypasses that struggle, they're not just missing out on a few marks, they're missing out on the learning itself. So what's the solution to this passivity? Gurney suggests we get kids building with AI? It's about understanding the underlying mechanics, not just passively consuming the outputs. He talks about asking questions like what is an LLM? How does it work. How do you create an image in AI? What is a sensor? How do you visualize this data? Because through these activities, as he says, they learn the fundamental principles. This really got me thinking about AI literacy and what we mean by that in schools. It's not about becoming a coder, necessarily, but it is about understanding how these systems operate, their limitations and their failure modes. It's about developing that reflective awareness, that theory of mind about what the AI knows or doesn't know. Think about it. We wouldn't just give a student a calculator and say, here's your answer for the maths problem. We teach them how to use it, when to use it, and why. The answer makes sense. We expect them to understand the mathematical principles behind the calculation. It's the same with AI. We need to move beyond just using AI as an answer engine and empower students to truly understand, interact with, and even create with it. The piece makes the case that the divide in education isn't really between kids who use AI and kids who don't. It's between kids who consume AI and kids who build with it. One group, as the article puts it, is outsourcing their learning. The other is turbocharging their own education. And that's the core difference between enhancement and replacement, isn't it? Are we using AI to augment our capacity for thinking and creativity, or are we letting it replace our capacity for productive struggle and judgment? We want our students to be teaching students not to outsmart machines, but to outthink them. Now, this isn't just about academic integrity in schools either. The article broadens the lens, pointing to the rapid drumbeat of AI attributed job cuts in companies like Oracle, Snap and Cisco. The message gone and has for parents and students is stark. If you're just following AI and just using it and being a passive consumer, then you certainly place yourself at a great disadvantage. He continues, that's the fear that people should have that I could be completely marginalized. Whereas if you know how to create with it, now you're leading, now you're telling AI setting the stage. That job will never go away. So what does a future ready kid look like in the age of AI, then? Gurnani's answer really surprised me because it wasn't about prompt engineering or the latest tech skill. It was about something much more foundational, a character trait that we valued for generations. Grit. He highlights grit as one of the top skills that differentiates those who succeed from those who don't. And sitting on top of that base, he lists critical think and logic, problem solving, communication, adaptability and the ability to fail at something and keep going. That's a beautiful list, isn't it? It connects so directly to what I cannot do. Machines can compute, but they cannot wonder. They cannot care. They cannot exercise judgment or imagination or wisdom. Grit is the ultimate human characteristic in the face of challenge. This emphasis on grit and these deeper human skills makes me think about how we design learning and assessment. If we want to cultivate grit and productive struggle, we need to design learning that cannot be faked because it demands depth, care and imagination. It's about cognitive stretch. We have to ask ourselves, can AI complete this without the students unique context, perspective or judgment? If the answer is yes, then perhaps we need to rethink the task. Maybe we need to shift our assessment approach to the three P's looking at the product, yes, but also the process. How did they get there? Including their AI interaction logs and their performance in a live demonstration of understanding. Gurnani's final piece of advice for parents is to start early. He urges them not to be intimidated by AI or keep their kids away from it, thinking it's evil or dangerous. Instead, get close to it and understand it. And I think that's excellent advice for educators too. We can't avoid AI, so we need to embrace its potential to deepen learning. The article shares a wonderful anecdote about a 9 year old boy named Adam at a Code Ninjas center. He walked out with his arms up shouting I am sensei today. Because he'd earned the right to start teaching six year olds. His mother, watching, had tears in her eyes seeing her child feel like Superman. That's the kind of agency and confidence we want to foster in all our students. That's what happens when they move from being passive consumers to active builders and thinkers. AI is helping us hold the complexity so we have capacity for creativity and for these deeply human moments of wonder and mastery. The real value is not in what the machine produces, but in how the student responds and how we empower them to take ownership of their own learning journey. It's an evolution, not a revolution, but it requires a conscious shift in mindset for all of us. That's all for today. Thanks for listening.