I've Got Questions with Sinead Bovell - AI Gave Every Student a Supercomputer — Education Has to Catch Up

Episode Date: February 19, 2026

In this episode, Sinead takes the stage at SXSW EDU 2025 in conversation with moderator and tech entrepreneur Natalie Monbiot for a thought-provoking discussion on AI and the path forward for education. Together, they explore why simply banning AI isn’t a solution and what it really means to design learning for an AI-first world. The conversation examines how education systems must adapt, from rethinking curriculum and grading to creating environments where critical thinking, judgment, and intellectual independence remain central to learning. They unpack both the promise and the limits of AI in the classroom, emphasizing that technology should amplify human potential, not replace it. Finally, the discussion turns to the skills needed to thrive in a future shaped by emerging technologies, and why most of the capabilities that matter most aren’t technical at all Follow my work here: Website: https://www.sineadbovell.com Substack: https://sineadbovell.substack.com/ Instagram: / sineadbovell LinkedIn: / sineadbovell Twitter / X: / sineadbovell YouTube: / sineadbovell TikTok: https://www.tiktok.com/sineadbovell

I think we need to move away from preparing kids for jobs because jobs are going to change. The way students are taught and what they're taught to optimize for is very at odds with where we're at right now with AI. The safest assumption we have to make in this moment is that kids are going to be using artificial intelligence at home. So the classroom really has to be a place where the deep learning is happening

and where we're raising the bar on knowledge. When you outsource your cognitive work to an AI, you actually become cognitively weaker. This is potentially really detrimental to society more broadly that we become so reliant on these technologies. We stop believing in our own ability to make decisions. In the age of advanced technologies, kids need to read more and we'll have to make school harder.

The most important skills for the future have nothing to do with technology. What should kids be studying and learning today for a future that's going to be transformed by artificial intelligence? and how does the institution of education need to evolve to meet the moment? In the spirit of South by Southwest, I'm going to share a talk that I delivered on this topic where I go into detail on some of these ideas, from where we can expect this technology to take us, to the skills kids in school today need to be cultivating, and the system-wide change the institution of education is going to need to undergo

to prepare kids properly for this world. I'm Sinebeauvel, and this is I've Got Questions. I'm super delighted to be moderating this conversation with the fabulous Chenade Beauval on AI and the future of education. She's got a massive fan base. It was hard to get to this stage, actually, with people kind of coming up to her and saying how much they admire her work. Sheenade is a strategic foresight advisor.

She advises C-suite executives and senior leadership across governments and global corporations. And she's an 11-time United Nations speaker, and she has delivered formal addresses to presidents, royal families and Fortune 500 leaders on topics from synthetic biology to artificial intelligence. And today she has advised, very relevant to this conversation, 16,000 educators, government officials and policymakers on redesigning education for the age of AI and emerging technologies. So, Shanade, tell us what it is to be a strategic foresight advisor and your lens on AI and the future of education. Yeah. Education is the bedrock for a healthy democracy and for a functioning society. And it's not just essential for things like economic mobility and economic security, but fairness as well and for well-being.

I believe there's no such thing as a state that over-invest in children's future. An investment in children is an investment in national interest. So you want to foster an informed and adaptive citizenry that cannot just safeguard the future, but thrive in it, especially a future that's going to be as complex as the one children in school today are entering into, which will be shaped by quantum computing, genetic engineering, artificial intelligence, commuting back and forth to space. This is an incredibly complex world they'll be entering into. So the more that they can understand it, the more we can support them in that journey, the better equipped they are. And that's an investment in a country's economic

security, in our collective health and well-being, and our overall security and national security interests. Goodness. So couldn't be a more pressing topic. And before we dive into some of the kind of final points, where would you say, taking a step back, like, where are we at this moment with AI? So if I were to say where we are, I mean, it's very, very early. Maybe it's 1992. The internet has dropped. Companies are experimenting.

We know it's maybe going to be a big deal, but there's still a lot of doubt. Some people are also kind of playing around on it. But we have yet to fully comprehend the way it. is going to fundamentally transform our world. The Googles, the apples, the Amazon's of the future, they have yet to be invented. But they're coming. And artificial intelligence, it's also a general purpose technology,

so similar to something like electricity. Think of how pervasive electricity is. We don't even think about it at all. It's so foundational that it's moved into the background. So we will soon be streaming artificial intelligence the way we stream electricity. That is going to be a fundamentally different society to live in. And these general purpose technologies, they take time to get so entrenched in society.

But you know when it's reached that point, because when people can't access general purpose technologies, whether that's at a country level, certain neighborhoods, we deem that wildly unethical. Who doesn't get fair access to the internet? Who doesn't get access to electricity? That is the path artificial intelligence. intelligence is on. So if artificial intelligence is going to be this general purpose technology and fade into the background, what does AI and education look like now?

Like how should educators be considering AI in education, given that it will be in the background, but today we're at this very early phase? Yeah. So I think that there are kind of three pillars that are related, but distinct. in terms of how we should be thinking about AI and education. The first pillar is safe adoption for kids and for learners. So this means equipping kids with the tools to navigate artificial intelligence because they're going to be on these tools at home regardless.

They have supercomputers in their pockets, supercomputers on their iPads. So giving kids the skills to utilize these tools safely. So that's conversations like AI isn't your friend. Right? Your chatbot isn't something that you tell secrets to. This is what we do or don't share with artificial intelligence. And this is also how you ask it good questions and validate its answers. So that's pillar one. Pillar two is how do we more urgently adjust what we are teaching in school or just the formula for what happens in the classroom versus what happens at home, knowing that kids are going to be lenient to these technologies at home to do homework and to complete assignments. The third pillar, and this is where I think we are rushing into, but this is actually the long-term game, is how do we fundamentally redesign the entire system of education for the age of artificial intelligence?

But what seems to be happening in this moment is we are kind of merging all of those pillars in a sense of urgency. And this leads us to deploy AI in schools for the sake of feeling like we need to meet the moment by bringing AI into the classroom. And there are a lot of technologies that aren't ready. So I think we focus on pillar one, giving kids the tools to use these tools safely

if they're going to be using them on their phones. We slightly adjust what we're teaching to account for cheating and homework. But it's much more at the departments of education, the ministries of education level, to take this longer-term lens and fundamentally redesign AI, school for the age of artificial intelligence.

So I think we've heard this week a number of different ways that educators are experimenting with AI, different pilots, different ways of going about it. Like, is now the time to be, sounds like we should be teaching it and educating about it, is now the time to be experimenting with it in deeper ways? Yeah, yeah. So, you know, teaching it's more so AI is a hard skill. So that should be happening. experimenting with it, yes, we need to be running these pilots, we need to be gathering the data as to what's working and what's not, but it has to be in very, very intentional ways and not just assuming that we can just throw in an AI tutor somewhere arbitrarily, and that's going to be sufficient.

And making sure that we're not running social experiments that jeopardize learning outcomes for the sake of just feeling like we need to quickly meet the moment. So yes, I think that these experiments are vital. they should be happening, but they need to be very, very intentional and very, very controlled. I know that you're working with Fortune 50 companies in this space and advising them on how to navigate AI and education. What is some of the data points and the advice that you've been giving them? Yeah, so it's been really, really interesting to look at some of the data that's coming through. And of course, we're still very, very early in the age of using artificial intelligence in education. But there's one clear trend that stands out. So I'm going to walk us through a study

that I find particularly helpful. And this was done by the University of Wharton, the University of I believe Pennsylvania, and Budapest British International School. And it implemented artificial intelligence in math classes. So there were a few math classes in the high school, and they broke the class up into three groups. The control group, which is just your traditional doing homework problems with your textbook, the GPT base group, and this is the students that got uninhibited access to artificial intelligence, and then the GPT tutor group. So these are students that got access to an AI that has been designed to just guide them through problems, give them hints, but not the answers. All students got the base lesson for math together, and then they broke out

into their respective groups and the respective tiers of AI access or not. So the study showed that when it came to the practice problems, the children that got uninhibited access to AI did 48% better on the practice problems than the control group. The students that got access to the GPT tutor did 127% better than the control group. But when it came back time to actually test students without access to AI and do the final post-unit test,

the kids that got the uninhibited access performed 17% worse, so AI harmed the learning outcome. And the children that got access to the AI tutor performed at the same level as the children that didn't get access to any artificial intelligence. And so the conclusion of the study was that generative AI harms learning outcomes. But then there was a second study that happened at Harvard. And of course we have to control for the fact that self-directed learning is a little bit different at a university level. And clearly if you're getting into Harvard, there's also some kind of higher order thinking that you're able to. do. But that aside, it was a physics class, and they broke the physics class into two groups,

the control group, which is the students that went to the traditional lecture with the, with the professor, then they broke out into peer groups and worked with one another and their peers and had instructor-led guidance on solving problems. The second group had no in-class lessons at all. The entire process was done with AI, but they specifically designed the AI to be self-paced, going with the student's needs to provide immediate feedback, whether the student was on the right direction or off the right direction while they're doing the problems to provide motivation and to really take all learning best practices and implement it into that system. And continue to adapt how it tested the child based on how they were evolving and doing the

problems. When they did the general test after those two experiments, the kids that went the pathway of artificial intelligence performed twice. as well as the peers that didn't get access to AI, and they were more motivated and more engaged. And so what we can learn from just those two kind of isolated studies is that you have to adapt the entire ecosystem, right? It's akin to inventing electricity, but only swapping out where the steam engine was and putting light switch there, or light switch there, not building out the entire assembly line and rethinking about how we design the system. That's step one.

Step two, immediate feedback is absolutely vital in AI learning outcomes. Gone are the days if we're going to incorporate artificial intelligence where we wait for the unit test or midterms or the end of year exam to see where students are. Artificial intelligence needs to be able to extract the data in real time, this is how somebody is adapting or this is how they're falling behind. And AI needs to provide that feedback or else we learn visibility. We lose visibility into how well things are happening. Self-paced learning is also vital. So if you go back to the high school, everybody had an hour and a half to learn the math problem. So whether you were working with your textbook or working with AI that hurt people that were doing the AI method and it helped people

doing the traditional method. So kids need to learn at their own pace. And the system needs to be able to adapt in real time. So those are just a few of the key takeaways when we think about AI and education. But that's why this is a longer term redesign, and that redesign should not fall on teachers. And that's one thing that I think we need to really make clear, and that this moment shouldn't fall on teachers. They already have way too much on their plate. This is something for government departments heads and those designing curricula more broadly. And I think we're getting that wrong. Right. Yes. I had the opportunity to sit on on a few panels yesterday, and there was definitely a very understandably irate educators. It was like we had COVID. We're in an

underprivileged area. We've got so many pressures. And now we have AI to learn. And we have to do this two-day course. And then the pilot ends. And then we've got to go and do another two-day course. And AI is the last thing that we need. So it sounds like there is a right way to do it. And there are definitely ways that can be harmful. And some of those right ways involve a lot of structural redesign of how students actually engage with AI. Yeah, this is like the institution of education. We need to approach differently. It's akin to asking the accountant to redesign the concrete and the bricks.

That's not what we should be doing. And I know that you, there was a, we had talked about a school, that you had been tracking. So I think it could be helpful to share some of the insights there. Yeah, absolutely. People familiar with Alpha school in the room, a few people. What it is, it's a two-hour learning process where like all the hard skills, all the knowledge that you need to learn at school happens in a two-hour period with an AI tutor. And the experience is entirely personalized and adapted to where that student is at. So if you walk around the classroom, you'll see different students working on completely different math problems, let's say.

And as it's understood what that student is interested in, the math problems become kind of contextualized within topics that they love. And so critically, and again, sort of going back to one of the best practices or, you know, mandatories in AI being successful in schools, there's real-time feedback and performance on performance of that child. They can see their own performance and actually start to own that journey for themselves. And they get everyone into the 99th percentile no matter where they've started in their journey. So I think that's a fascinating way to look at it.

And I think that besides those two hours are the point of getting all of that work done in those two hours. and some people are able to, some students are able to accomplish more, double in those two hours and some on the higher performing end five times more. But the critical part is freeing those students to focus on life skills, on EQ skills, on kind of developing their own human ingenuity. And so I feel like that is, you know, from all the research that you've discussed, just an amazing example of what's happening today. Yeah, totally.

And that's kind of the moment we're in, right? We're in pilots in experimentation and innovation, really a redesigned zoom out wide lens. In some ways, taking risks, but it should never hurt the learning outcome. And it should never be a burden to teachers. And both of those things need to be true. Absolutely. So I did want to kind of like dig in a little bit more into some of the current challenges with AI that, you know, educators, students, parents are experiencing today, which is around AI and cheating and using, you know,

chat GPT to get to the answer right away and what impact that might be having on the learner experience and kind of the point of being at school. Yes. Oh, absolutely. And I think that we're in a bit of a crisis in this moment when it comes to artificial intelligence and cheating. And we can talk about what happens when you kind of short-circuit that thinking. But I think that the safest assumption we have to make in this moment is that kids are going to be using artificial intelligence at home. So whatever happens past 3 p.m., expect that to be powered by a supercomputer in some way. So we have to start there. That means we have to change what we are doing in the classroom. And so in some instances, that means maybe we flip what happens at home, happens in the classroom.

But in other ways, maybe, for example, you teach history. You give children the research portion and they can go home and do all the research with Chatsubit that they want. But the higher order, critical thinking, deep learning and discussion, all of that happens in the classroom. So the classroom really has to be a place where the deep learning is happening, where the testing is happening, and where we're raising the bar on knowledge. But we do have to assume everything passed for is likely going to be. to be done, co-created by, or outsourced to an AI system. And then again, the broader goal and the longer-term goal is that we've entirely redesigned the curriculum to account for the fact that kids can lean into supercomputers. Because that is the actual goal in the end. Kids in school

today are going to step out into a world with advanced robots, with supercomputers that are polymaths. We want them to know how to engage with these tools and these systems, how to utilize them, how to invent with them. And we'll have to redesign education to account for that. And we'll have to make school harder because you do get access to these supercomputers. And so in a kind of superficial way, maybe that means people are learning about quantum computing at seven years old because that learning is facilitated by a teacher and by a supercomputer. But that part is going to take time. So the more urgent kind of redesign is flipping what happens in school versus what happens.

at home. What happens if we don't do that, and I think it's quite obvious, right, we, we end up just short-circuiting the thinking. So there shouldn't be anything to cheat on, because what happens at home isn't what we are evaluating. And that is, I think, the kind of the baseline that we need to move towards. And that's, I think, what we should be doing more urgently. So many places to go from everything that you just said there. But I'd say, you know, So maybe a positive example of how outside of hard learning and maybe an AI tutor helping you learn the things that you need to learn at your own pace in the most individualized and sort of data-rich manner, well, how can you use AI outside of that core learning

in a way that helps children become more human, right? So like what does human flourishing kind of look like? And does AI have a role in that? I think we need to learn how they work. and learn how to use them. But also, what should we as humans be focused on? Because we want to collaborate with AI. So what are the sorts of subjects and skills that are deeply human that we can focus on?

And something I've been thinking about quite a bit recently is like different types of knowing. There's a cognitive scientist called John Viveki. And he plots out different types of knowing and kind of the most sort of like academic or kind of research based and fact and knowledge based learning is procedural knowing. And that's the kind of knowing that AI is really good at and is getting increasingly good at. But what AI doesn't have is lived experience and deep insights that change you as you experience them in the world, change your perception of the world and then change how you connect with others. And so I've been really interested to hear some of the talks this week about experiential learning environments. I learned about thinkery, which is here

in Austin, and it's kind of this interactive learning museum environment. And it's just really interesting to think about what are those deeply human skills that we can be focused on teaching students while they're learning what AI is and the best ways to collaborate with AI? Yeah, I think that that's vital. And I just wanted to quickly. go back to the cheating, another thing we'll probably need to do in the short term is introduce more pop quizzes and surprise tests and they don't need to count towards grades, but to see where students are as we are in this kind of new territory. So a lot of times we don't know how much they're using AI, how much they're cheating with it to insert more chances for assessment and be

tracking that data because that's another thing. We don't have a lot of visibility into how this experiment is going. In terms of what AI can do and what AI can't do, and therefore what should we be teaching kids in particular and what skills should be fostering. My philosophy is we should never assume AI will never be able to do something. And the reality is we cannot predict the future, what jobs will be there, how advanced AI is going to get, and how quickly. That means we have to prepare kids for absolutely anything, whichever way the future evolves, however quickly we get to the moon, start genetic engineering, kids can pivot, adapt, and think critically about the world around them. And most of those skills don't actually have anything to do with technology.

They require deeper thinking. Critical thinking is absolutely vital. In the age of advanced technologies, kids need to read more, read for the sake of reading, and read in a way that they can come back to school or with their parents and discuss the ideas and have those ideas challenge. kids need to play more in the age of advanced technologies. The future Steve Jobs of the world, they're not going to come from a corporate cubicle. They're going to come from people that have imagination that can play, freely, experiment, work collaboratively, long-term thinking.

So getting kids to think beyond the immediate horizon and beyond just this unit test in chemistry or in math, but how could this impact things in five, ten years to come? and even cross-disciplinary thinking. Kids in school today are likely to hold 17 jobs across five different industries. They won't be doing just one thing. So we have to get them to think, how does math connect to what I just learned in history, which may connect to what I do in philosophy or in English.

So all of these new, and they're not even new skills, but it's just about centering these types of skills. Most of the important, the most important skills for the future are ones we can foster for free. And that's what I think we can sometimes miss in these moments where tech, we feel like we have to lean into technology for the sake of it. But it's actually the other skills that we need to make sure we are doubling down on in the age of advanced technologies. And one kind of lived example that I do with my nieces and nephews constantly since the age of about six or seven, I theoretically introduced. them to technology, and this is what can happen in the classroom as well, I explain concepts in age-appropriate ways like genetic engineering, and I ask them to interpret what that would

mean for their world and their sense of ethics. So if we could theoretically make sure nobody gets sick in the world with these technologies, should we do that? But what if, to my nephew, it meant all that basketball practice you do, somebody didn't have to do, because that same technology allows them to suddenly be really good at basketball. How should we think about that? They engage in the higher order thinking. They're exposed to the longer term concepts of technology without actually having to play around passively on an iPad. So these are the types of deep conversations and higher order thinking that can happen into the classroom that teachers are uniquely positioned to deliver and to facilitate. I mean, when you think about a teacher and they don't

get enough credit for all of the things that they do. I mean, the curriculum is one small part of it. They are social workers. They are therapists. They know their children inside and out. So being able to go deep into these types of conversations, that's what we also need to be focusing on. And I know it sometimes feels counterintuitive because I'm a futurist and I spend most of my days in patents and technologies talking about robots, uploading brain interfaces. Yet the most important skills for the future have nothing to do with technology. Great. And I want to go back to something that you said. So technology for the sake of technology is absolutely not the right way to go about things. But learning for the sake of learning is. And some really interesting insights this week about how schools and test-based learning does not set students up to enjoy or take pride in just the sort of active learning. and, you know, sort of encouraged and optimized to find the answer, get the answer right.

And then even in a critical thinking class that cognitive scientist Christine Legare talked about yesterday, even in that class where there is no right answer, what the students wanted is they wanted the rubric to get there. And what she said to them is like, well, you know, do you think you're going to, when you have a job in the real world, do you think that there is a way? Like, you know, you're not going to be asked to, you know, discover the answer or where we should go or the right path, I should say, by being given the rubric. So it sort of seemed very, we're at this kind of acute moment

where the way students are taught and what they're taught to optimize for is very at odds with where we're at right now with AI. and the fact that it is designed to give you the answer. And I actually talked to a teacher who said teaching 16 to 18 year olds. And she was like, okay, so what I do to try and kind of circumvent the use of AI and writing is I have my students write in class. And, you know, I do give them a bit of a rubric. Like this is, you know, a good structure for an essay. And then when it comes time to actually submit the essay, they go home and type it up.

In some cases, more than in a few cases, that student had kind of ripped up their essay and basically just completely generated a new one in chat GPT. And what that said to me was, I mean, there was no like time saved or cognitive load saved in doing that. What that says to me is that there's like a, we're in a confidence crisis. Yeah. And this is this is potentially really detrimental to society more broadly, not just kids, but. all of us, that we become so reliant on these technologies, we stop believing in our own ability to make decisions. And no matter how good technology gets at something, there will be times when we have to deviate from the technology's advice. And we have to make sure we are ready for

all of those moments. And you might even hear people talk about optimizing every aspect of your life with artificial intelligence. And I somewhat take issue with that. Because if writing that email, is the one time in the day where you think deeply, you move through your ideas, you have to structure what you want to say, and you pass that to an AI, unless you were replacing that time and that thinking of something else, that's a dicey bridge to be walking down. And there was a recent study,

I believe it was Microsoft and Carnegie that joined forces for this study, and it did show that over-reliance on artificial intelligence can reduce our ability to think, critically. So we need to make sure we are strengthening these skills as we start to move and work alongside artificial intelligence. And there was another study that was really helpful that showed this in real life in the workforce where entrepreneurs were given access to AI systems to help with their small businesses. The high-performing entrepreneurs that had deep critical thinking skills, AI supercharged their performance because they knew the right questions to ask of the AI

and they knew how to apply the AI's answer to their business. When the lower-performing entrepreneurs asked AI questions, they ended up doing worse and it hurt the company because they asked the wrong questions, they just gave up and asked the hard questions, and they didn't know how to apply the material to their actual startup. So we don't want to build societies

where we are 100% reliant on these systems. And that's something that we have to really think carefully about from at an adult age and at a child age. And I think we're already seeing it in terms of our attention spans, spelling. I'm sure there's a lot of people in this room, myself included, who feel like I spelled that word last week and now I have no idea how to spell it this week. We want to make sure we're not short-circuiting the thinking in this age. So again, really centering, deep problem-solving, critical thinking, and deep learning. Yeah, there's been a number of studies like the Carnegie Mellon, Microsoft one, that shows when you outsource your cognitive work to an AI.

you actually become cognitively weaker. And that seems like extremely critical at an age, you know, in a period in time where, you know, students are supposed to be honing their cognitive abilities. But then it's like, well, how do, you know, how can you engage with that AI, you know, in a way to actually benefit from it? And knowing that you, if you outsource the cognitive load

and you're not doing the cognitive work yourself, not only are you missing that moment, but you're missing that the insights kind of living within you and kind of settling within you and kind of becoming who you are and increasing your body of knowledge and your resilience and your strength and your expertise. And it seems like in this day and age,

where it's so uncertain what jobs will look like, what the future will look like, kind of radical self-dependence is something that we should, be teaching and it would be great to kind of hear a little bit about where we think that kind of responsibility lies in that respect. Yeah. And I always hesitate to, when I think about responsibility, to bring in parents because everybody is coming from a different place and we can't really control what happens in the home. That's an entire other week of South by, making sure that all homes are equal and have access to the same things.

But in school, I think we really need to think about building confidence as a skill for kids. So they can continue to trust the questions that they're asking and their own ability to generate answers. And again, it doesn't mean, of course, in a world where AI is a master of quantum computing, we want kids to be able to ask questions, but we help them think more deeply about the questions that they're answering. And they have a broad understanding of the questions that they're asking, they have a broad understanding of the answers that AI can give them. And again, that is a fundamentally different

society, right, where we go from what is the answer to what is the question. And that's why that is part of that bigger system-wide redesign. But I think centering confidence, encouraging kids to speak in front of class, classmates, engage in conversation because that is also the interface of the future. It's conversing with these AI systems is absolutely critical. And then in terms of you ask, what are the jobs of the future? Nobody can really predict. them. We can predict the jobs that are going to be automated. That's much easier to see. But the same way nobody 20 years ago could have predicted a social media manager was going to be vital to a company's existence, most of the jobs we can't really see. We know that there's going to

be some convergence of synthetic biology and artificial intelligence and space. But again, it's about preparing kids for anything, not just trying to, I think we need to move away from preparing kids for jobs because jobs are going to change. And that much, we can guarantee. And that also means moving away from coupling identity to jobs. We have to move away from that entire philosophy, right? That idea that we learn, we work, we retire. That's all changing. So instead, we encourage kids to lean into the problems that they want to solve, the skills that they want to adopt, and the amazing ways that they want to change the world. I mean, tell kids about the robots and the AI systems that they'll be living.

with and ask them what they want to do with it versus coupling identity to jobs because that is just going to end up in a crisis and we're moving away into an entirely different type of world. And so some of the skills that we can teach children to kind of prepare for this new future, people sort of use the term like metacognition, right? So how to think. And it was interesting in a talk yesterday. So, you know, one educator was saying, you know, well, you can't.

necessarily stop people from you stop students from using chat GPT but something that he does is like okay you used it show me your prompts show me the questions that you asked it like show me how you pushed chat GPT because if you can ask good questions and if you can become a good communicator and you don't necessarily and you kind of know where you want the answer to go and you can prompt in that direction then then that's that's a skill that's a skill for today and for the future. Another skill that sort of came up as kind of an experimental sort of skill, the New York Times recently covered a story about using this term like a vibe engineer,

which is this idea that kind of almost anyone with the will and the passion to do it, and that's something that I think, you know, we need to double down on encouraging in every individual. But anybody with the will and the desire to create an app can basically do that. now. And it's this thing called like vibe engineering. So a lot of people kind of creating apps for themselves or apps for just a few people. And so one of the kind of emerging skills that was discussed, I was like around human-centered design. So if anybody can design products for others, like how do we get into, you know, well, what would be good for others?

And so that felt like another territory that felt rich. Yeah. Yeah. I think centering the human experience in an age of advanced technologies is an investment that we should definitely be doubling down on. And yeah, and again, that does mean introducing kids to these ideas, to these technologies, but then bringing it back to the human to just kind of the core fundamentals. I mean, I think history, ethics, philosophy, these are subjects that become more important,

the more advanced and technical our societies get. And like you mentioned earlier, you know, the computer scientists learning today are going to be the future tech tycoons of tomorrow. And so what can we be teaching them to create more ethical AI and, you know, exponential technologies that are good for people that are designed in a way that is good for society? And so I think that's a really hopeful message that we are in that moment now where that next generation of builders are kind of, we have that opportunity to kind of coach them and help them ask the right questions and design for the good of society.

Yeah, I don't think I could have sort of better myself. Yeah. So actually a bit of a segue into the question of just ethics in this space more broadly. and actually maybe before we kind of like dive into some of those areas, what do we think of kind of the role of the educator in all of this? And how does that shift? So let's say in a great situation where you've got AI tutor, that is the entire reimagined approach that you mentioned

where you have an AI tutor that's giving you adaptive, learning, personalized and all of that. What is the role of the educator and all of that? I think that that's going to evolve, the more these pilots and the more the studies come through, the different positioning that the educator takes. So whether that's deep expertise in some areas, which will be vital,

whether that's facilitating the right questions to ask, the right way to think about material, and the right way to think about learning. I think the role of the educator stays deeply coupled with kids understanding and knowing how to learn. And that is what education was supposed to be for, learning. And so I think it goes back to that. We've become, we've redesigned education to prepare people for work.

And I think we need to move towards preparing people for life. But the educator still stays central to that process. I mean, I don't think many people would want to send their kids to a school with 95 robots and no people. I don't think that's the future that we're all aiming for. Right. So I guess in some of these kind of very innovative models like Alpha School where it's two hours of intensive, personalized learning with an AI tutor, the rest of the day is all about human connection with teachers and instructors and guides that help kind of uncover the passion of that student. and help to nurture it and help them to have the confidence to kind of deliver on that. But with that, wanted to touch on, you know, the ethics of this space a bit more.

Yeah. And this is something we have to really think carefully about artificial intelligence, data and children. That's already a deeply questionable intersection. And ethics appears in a few ways. So the first is what data are these AI systems going to be collected? when it comes to children. Are parents aware, and did they give consent, or are we just kind of rushing AI tools into class, and what can be interpreted from the data that gets collected on children? So we want to know where their stamina is on math.

We don't want to interpret other emotional cues unless we have figured out how to do that safely with parent consent. So that's one area that I think we need to really understand. The second is the strange way, shows up in AI systems. We often think about facial recognition and the cases where we know it more intimately. But there are unique ways that AI can make predictions about you when you interact with it and then change the level of advice that it gives you or how well it performs for you based on what it knows about you. So there is a study done using most of the most famous AI systems.

And it shows that when you ask the AI systems about African Americans, it gave all great reviews. When you gave the AI system an example of text that had more traditional African-American English in it and asked the AI system's questions about that user, the AI system would say, oh, this person's never going to go anywhere. I can't even imagine a job for them. They'll be in low-wage jobs. Picture this in education. The AI system detects somebody has this kind of ethnic background or is this gender and then gives the teacher worse feedback on that student in terms of assessments or gives the student worse advice in problem solving because it has already made a prediction that student is not going to go anywhere in life. So these are the more subtle ways we have

to apply foresight to ethics, or ethics and foresight in academia. And I'd say the final thing that we're going to have to watch out for. And we saw this with social media after the fact is the relationships kids are going to build with these systems. We are now giving kids access to an infinite never-ending opportunity to engage with an imaginary friend, something that is always on, can answer all of their questions. That is a recipe for a new type of addiction. And we have to really be looking out for this.

We kind of miss the boat on smartphones and now we're all trying to get them back out of the classrooms. We can see this line of sight directly with AI systems and chatbots. And this isn't, of course, all on educators. This has to come to, you know, tech companies, how we design these systems, age-gating them, but something to look out for is this kind of new addiction that might form

between kids and chatbots, and that is not going to end up well. And do our best to bring parents on board with that. So even if that's at parent-teacher interviews, just casually saying, look out for the amount of time your kids spends chatting with a chatbot. I noticed they were a little bit more disengaged in class. That could be where. So this is another area that we have to apply foresight to, but we can see that line of site happening quite clearly if we don't intervene.

Yeah, in a similar way that we've been talking about, you know, parents and learners having that visibility into their own data and kind of their performance and how engaged they are with their work. Should there be a case where everybody has that visibility into the relationships with these chatbots? Where do you think that line can be drawn? But I feel like if there is that visibility, then people can be a little bit more relaxed, but then is that?

Yeah, I would say that question needs to be answered by a psychiatrist and a psychologist. That is why these are multidisciplinary conversations. We need to bring everybody to the board. An addiction or a relationship with a chat bot shouldn't be something that kids download in the app store. So psychologists, psychiatrists, doctors, I welcome you to this conversation because we need your voice in it. It can't just be happy out of Silicon Valley. It can't just be left to parents to deal with on their own. Everybody needs to come to the table.

we saw what happened with social media, we don't have to do that social experiment again. So well said. Okay, we're going to take some questions here. This one's from Rob. How do you see AI increasing the digital divide, especially in underserved communities in developing nations? And how do we as leaders stop this cycle? And we can see that general purpose technologies build on each other, right? So the communities that didn't get equal access to electricity, they're the communities that don't get, that are struggling with the digital

divide and then there'll be an AI divide. That is why that first pillar that I discussed, AI as a hard skill, teaching kids how to use artificial intelligence, how to prompt it, how to use it safely is vital because that may be the only opportunity kids get access to these AI systems. So that's why it's not pushing AI out of schools. It's being very careful about adjusting how kids learn with AI. But making sure we build AI as a hard skill is absolutely vital in schools and in education. When it comes to the broader world, this is a question that nation states are facing urgently, making sure there are things like sovereign AI that every country gets access to computing power, the opportunity to build the STEM skills within their population,

to adopt these technologies. That is a global conversation that's also happening against a very geopolitically uncertain time. But it's a really important question. And unfortunately, I wouldn't be able to answer it in 30 seconds. Yeah. And I don't know, just to add something just small to that, in a way, could AI introduced to everyone because everyone's got a smartphone, regardless of the socioeconomic situation, if students aren't taught how to use it and just over-rely on it, and, you know, that could be some at a disadvantage. Let's take another question.

We're aware that AI cannot replace in-person instructors, but will it and should it replace the online asynchronous instructors in higher ed? I'm not exactly sure what is meant by this question. Yeah, I guess how I interpret this question is, so we know the value of in-person instruction and the need for that human connection. there are other modalities of learning, some is kind of like on-demand learning, and then you've got some which is like live, synchronous, sort of synchronous, but digital.

My thought on that is I think when content is pre-recorded, maybe that's not the best use of a teacher's time to have sat in front of a camera and kind of read through all of that content themselves. Maybe that is a scenario where you can outsource that to. an avatar or an AI in a different format that is proven to be more personalized and adaptive. And I would imagine that any human to human interaction that's focused on human connection is good, whether that's in person or has to be online. And I think that there's also something interesting here.

And we actually don't know that the answer to this question. But if you're taking, say, a physics class online, what now happens when the physics teacher is also now powered by these supercomputers and how their perspective on physics changes and how they see the world and then getting access to that person in addition to the AI. So the answer, I think the jury is still out on how that would unfold specifically as it relates to online learning. Yeah, absolutely. And, no, there are, you know, I work with a company that creates AI twins for experts. And what's going to happen next is that experts, expertise that they trade on, they own their expertise. but they're going to be able to enrich that expertise with real-time data that they choose to bring in.

And so, you know, would you speak to that real expert or would you speak to that expert's AI twin? Well, in some cases, it might be advantageous to speak to the AI twin. Even though the expert, you know, the real in-person experience, you can have, you know, much more creative conversations, there might be scenarios where the AI twin is actually more valuable in that for certain contexts. I think tackling the last one is interesting. What are the pros and cons of developing skills for prompts when using AI? It is becoming critical for a career. How will it impact social skills? So the pros are, the more you understand how to direct an artificial intelligence system, the better response and access to how the AI kind of processes that data you'll get. So that I think is very helpful. Another pro, is teaching people how to process what is in their mind and formulate that into a question that can lead to some response. The con I see is that we end up refining all of our ideas and knowledge

and optimizing it for algorithms. So how algorithms, we will become optimization engines for algorithms. And I don't think that's the world that we want to get into. I think there are unique advantages. that artificial intelligence provides and how it interprets data. And there are unique advantages to how humans approach data. And we don't want to make our approach to thinking optimized for artificial intelligence. We want AI to be optimized for us.

And so I think that that would be the con. I think that this is going to be only a temporary challenge. As we're seeing, the kind of nature and the science of prompting is continuously evolving. And eventually it will turn to be much more conversational. So the way you talk to your colleague or you talk to your teacher or your friend, you'll be able to engage with AI in that way. But that still means communication is absolutely vital, understanding how to share your ideas. And that isn't something that we always center in education, but being able to vocalize your ideas, refine the knowledge that you have in a way that's easy to understand and to interpret for the general public and not just for AI, but will be vital in the future. Yeah, and I think as AIs become better at prompting themselves and all of that, you know, well, where does the human go? The human needs to go deeper. They need to get more creative. Like, what are these prompts even about? What is it that I'm trying to achieve? What could I achieve? And so I think that trajectory is a positive one for humans. Like, how do you dig a deeper into your human ingenuity? Because all of these things can be handled for you. And so I think that's a net positive for, you know, you know, you know, you know,

using AI kind of in the right way. I know that there's a question that's received the most likes, and I wonder why. What occurs when the U.S. Department of Education is demolished? And how do we move forward to make sure all states receive equal AI education? And I think this goes back to the first question. Investing in children's future is an investment in national interest. They are fundamentally coupled.

So if you want to talk economic strength, economic security, and national security, you are inherently talking about the success of the next generation. So I am not involved in how this is being dismantled, but I really hope we are prioritizing and centering children and their ability to self-actualize and reach the maximum capabilities that they can in the decisions that are made because that is going to be deeply coupled with the longevity

and state continuity. So they can't be decoupled. And that's why I say education is a national security issue. They need to be in the same room. So these are fantastic questions. I did want to leave just a couple of minutes for Chenade to share just some final rounding thoughts on this last day

of South by Southwest EDU on AI and the future of education. Well, first of all, just a major shout out to teachers, because this is an incredibly complex time, and they are dealing with the most prized asset on the planet, which is children. So this is, I mean, I think that they don't get enough credit for the moment that they're navigating. And I think something to remember, we're going to continue to hear about advanced artificial intelligence systems, quantum computing, space, all of these deeply technical advancements, but some of the most important skills have nothing to do with the technology. And even for parents, it's not being able to navigate an iPad passively at 5 that will dictate

whether your child will do well in the future. If you said, you know, my child doesn't really like working on the iPad, but she's reading four books a day. She loves her sports teams. She wants to spend too much time at the park. I would say that child is going to thrive. in the future. So even though there's a lot of pressure to adapt to this moment, remember, it is the non-technical skills that we need to be centering because we are preparing kids for a future we cannot see, which means we have to prepare them for anything, regardless of the way technology evolves. And on that note, I think we will close. Thank you for being an absolutely fantastic audience.