--- title: "Class Disrupted Live: Reed Hastings on the AI-Powered Future of Learning" slug: "reed-hastings-anthropic-board-class-disrupted-live-reed-hastings-on-asu-gsv-2026" author: "Reed Hastings, Michael Horn, Diane Tavenner" date: "2026-04-14 12:00:00" category: "Premium" topics: "ASU+GSV 2026, conference transcript, Equality + Access, K-12, Wellness/Mental Health, AI in Education" summary: "Reed Hastings, speaking from the board of Anthropic and 25+ years of education work, delivered a sweeping assessment of what has and hasn't worked in education reform." banner: "" thumbnail: "" --- > **ASU+GSV 2026 Summit** | Tuesday, April 14, 2026, 10:00 am-10:50 am | Sponsored Partner Programming ## Speakers - **Reed Hastings**, Anthropic board, Netflix - **Michael Horn** - **Diane Tavenner** ## Key Takeaways - Reed Hastings, speaking from the board of Anthropic and 25+ years of education work, delivered a sweeping assessment of what has and hasn't worked in education reform. - He outlined three prior chapters (state policy work on California's Board of Education, charter school advocacy through KIPP, and EdTech investment in DreamBox Learning) and concluded each had limited impact. - His fourth chapter is AI-powered individualized learning. - Hastings used the factory electrification analogy: productivity didn't improve when factories replaced steam engines with electric ones; it exploded when each machine got its own motor. - Education's "sage on the stage" is the power distribution system holding back technology. - He announced funding for a year-long experiment giving 50 median students full-time individual human tutors to establish the actual rate of individualized learning (he suspects 2x). ## Notable Quotes > "The sage on the stage is the power distribution system. It's holding back technology from its natural effects and its ability to teach children directly. We have to be brave enough to try to do school without sage on the stage at all." > > — **Reed Hastings** > "The typical 10-year-old on chess.com is scoring way higher than 10-year-olds of 20 years ago. What's happening is the 10-year-olds are getting tutored by AI. That's true for chess today and could be true for biology and history tomorrow." > > — **Reed Hastings** > "If you want to make money, sell to school districts, make teachers' lives easier. If you want to change the world, focus on the homeschoolers." > > — **Reed Hastings** > "When we figure out software-based AI teaching, we can share that with the entire world. A phone in Kibera runs basically the same operating system that we run." > > — **Reed Hastings** > "DreamBox was one of the early adaptive learning systems. But school districts kept telling us to turn that off, because they didn't want kids to get ahead. If the kid gets ahead, they're disruptive and bored in the class." > > — **Reed Hastings** ## Full Transcript Welcome, everyone, to the Class Disrupted podcast. This is our seventh season doing it. Normally, we are disembodied voices on a screen talking with each other and a guest. But tonight, we've got a live audience, and we want to thank the ASU GSV Summit and all of the amazing staff that has put this on. Huge thanks for all of them, please. And you are all here to make a lot of noise and make this fun, right, Diane? Indeed, that's what we want is a spirited conversation. So who do we've got on tap? Well, tonight, Michael, we have an incredible guest, someone we've talked to before, but it is time to do it again. We have Reed Hastings with us. And I think most people know Reed from Netflix. A lot of people know that he's spent time in education. What you might not know is that for the last year, Reed's been on the board of Anthropic. He's done a deep, deep dive in AI, the recent version, and 40 years ago, earned a master's in AI. So, Reed, you've also had a long set of experiences with education over the years. You were Peace Corps member teaching maths 40-some-odd years ago, I think. And 20-some-odd years ago, you were the chair of the California State Board of Education. The testing period, no child left behind. You had this guy named Roy Romer in Los Angeles as the superintendent for some seven years. What did you learn from that period of time working in education? Well, that was a time of great hope. We had no child left behind, reading first, high school exit exam. We had an accountability system. And I was really an administrator of that on the State Board of Education. And we worked hard on all the technical details. And there was some real progress. And as you mentioned, Roy Romer was very successful as superintendent. He made it seven years in LA Unified as superintendent, set a record for that. And put in a lot of great programs that really raised scores and achievement in learning. And the tragic thing was the next five years after that, I watched it all get dismantled. Independent of its results, it sort of, you know, politically wasn't in favor. New administrations elected. They are like, get rid of the old guy stuff and let's put in different stuff. And so that was true at the school district level and that was true at the state level. And it really woke me up to the hero syndrome we have. And whether it's Tom Pezant's great work in Boston now getting dismantled or Houston, Mike Miles is the hero today. And, you know, watch what will happen in five or 10 years from now, because that's where Rod Page was so great 40 years ago. Of course, there was Joel Klein in New York that so many people worked hard on. So we see this cycle of kind of rise and fall. And I have to say, for all the work that I did and all that state board, there's very little to show for it. So in another chapter where we met was in the charter world and you've been on the board of KIPP National for 20 years now. You have supported countless of us who have been in the work throughout that time. You know, the city fund and this is a long term strategy for you. What are you learning from charters? Well, I would say charters haven't failed, but they haven't succeeded at driving up NAEP scores in the high charter states, say like Arizona, Texas, Florida. And of course, unions have fought us to a draw in deep blue states and then in red states were able to grow and we're investing. In again, Florida, Texas, Arizona, Georgia, so lots of states. But even after 20 years, we have good success at the city level. So at the city level, it's actually the only thing that's driven citywide improvement for all kids is high charter share. So if you look, PPI did the graph, the scatterplot showing that cities with low charter share, Portland, Seattle, have had no improvement in closing the gap of achievement between poor kids and all kids over the last 25 years. And then you start walking up the cities that have 10 percent charter share, more improvement, 20, 30, 40, 50, like Newark, Camden. And then you get to New Orleans, which has the highest gap closure in the nation over the last 25 years. And of course, that's 100 percent charter. So charter still promising, but like grindingly hard and slow. Think trench warfare. But it hasn't been reversed. OK, so a lot of positivity. And I continue to be a huge donor in that space and continue to believe in it on maybe a half dozen boards of charter networks. So the third chapter that you then went in on an education is when I met you, 2010, the very first ASU GSV summit, you were there and you were getting involved in education, technology, EdTech and DreamBox learning, of course. And there's been a whole wave of sort of cresting, if you will, with EdTech. What's your take on that chapter? Yeah, well, Rocket Chip was using DreamBox learning and I knew it through there. And I thought, OK, here's a great opportunity to take this amazing software and obviously computers transform everything. And so if we could just get some investment in DreamBox and get it bigger, it would surely transform both district schools and charters. And again, grindingly slow. It turns out that selling to school districts is really hard. The only thing harder is selling to charters because they're small. So the money's on the district side. But grindingly so. And then, you know, DreamBox was one of the early adaptive learning, you know, let kids go at their own pace systems. But school districts kept telling us to turn that off, please, because they wanted to catch kids up to grade level. But they definitely didn't want to get kids ahead because if the kid gets ahead, then they're disruptive and bored in the class. So catching kids up to make the machine work better, very much valued. Letting kids get ahead, which sort of threw sand in the machine, not valued. And so it was an early lesson in sort of the depth and strength of the grammar of schooling that we have. So if I sum up these three chapters, state policy, district work, pop of success gets wiped away. Charters making progress haven't failed. Grindingly slow. EdTech, no real discernible change yet. I know you're not trying to depress us. I know you're trying to help us know that you're learning and still in the game, which we know you are. So let's get back to AI. When's it going to cure cancer? You know, when is it going to figure out fusion so energy is free? When is it going to autonomously drive us all over the place so we don't have to deal with parking lots anymore? Like, when is it going to make our lives better? By the end of the summer. Predicting AI is tricky because it's growing so fast in quality. You know, it was three years ago when Chet GPT came out and it could barely do third grade math. And now all of the major AI systems are very impressive. And they'll continue to improve. And what's happening is we're on one of these curves where it's, let's call it doubling every year in quality. So it will be twice as good as it is today a year from now and then twice as good and then twice as good and then twice as good. So whatever challenge you think AI is not up to, just wait a year. OK. And so that's the amazing thing. And there's no guarantee that the exponential will continue forever. But it has been the last several years. And, you know, it's getting very, very impressive at many scenarios like the ones you talked about and many others. So the amount of change that we're going to see in our society, mostly positive, but there'll be some negative. From AI getting better and better is hard to grasp because of this doubling, doubling, doubling. You know, just when you think we've got it like situated, like how's it going to work with society? Then it gets even better again. And so we're in for the ride of our lives, both on the positive side. So during cancer, energy, you know, abundance, these kinds of things. And on the stress side of everything is different than it was when we grew up. Well, that's the question I want to ask you, because not only is there this anxiety and stress, as you know, people are also worried, will people get hurt as it gets better? And, you know, you can imagine a myriad ways that could play out. What's your take on how do we prevent people from getting hurt? Yeah, I mean, again, that's happened with some tragic cases of, you know, teens and suicide already. And look, at the societal level, we make certain choices, sometimes explicitly, sometimes implicitly. And we tend to accept the choices that are already made for us and be scared about new ones. But, for example, you know, we lose 40,000 people a year to car accidents in the U.S. and about half a million globally. And if we just ban cars, you know, we wouldn't have those deaths, okay? But we're not willing to pay the price. So implicitly, we're making a tradeoff of 40,000 U.S. deaths a year. So I look at it and say, you know, is it as powerful as a car? And if it is, then I'm like, I know where society is in making those tradeoffs. So I don't want to pay that price. I don't want to see 400,000 or 40,000 a year deaths. I think when we get all excited about four deaths, we're sort of losing perspective about the size of the prize and the other tradeoffs that we have and continue to make in society. So, you know, AI, I think, will reduce deaths, and in particular with self-driving cars that should be able to eliminate 90% of those 40,000 U.S. deaths through self-driving if we can get that adopted, okay? But then you see the story of the one Tesla death that happens, and again, that death's tragic. I'm not trying to take away from it, of course. But in comparison to all the lives that self-driving is already saving, it's quite small. So let's take that into education now, because one of the things that I love about you is that you keep learning and you stay in the work when a lot of people leave. And I know that there is a fourth chapter that is going to be written in your work, and it's going to involve AI. And so what does education look like in the age of AI? What does school look like in the age of AI? What does learning look like in the age of AI? Yeah, well, in my first 25 years, I've spent the time trying to do the better classroom, whether that's from the state board level and testing and assessment, how do we make schools and classrooms better, whether that's using ed tech like DreamBox Learning to make the classroom better, charter schools, which has had some progress in making the classroom better. But it reminds me of the story about steam-powered factories in the 1800s. So in the 1800s, all of our factories that had a big steam plant that burned coal and rotated an engine, and then throughout the factory, we had a rotating rod, which carried power through the plant, and then we had belts and pulleys and wheels that then spun the individual looms or other machines. And these were highly developed, mechanized, and lots of belts and pulleys throughout the factory. You know, a lot of productivity. Then electricity comes, and we replace the big steam engine with a big electric engine, and that saves some money. But real productivity of the factories didn't change, and this puzzled economists for a long time. And then people started saying, hey, the power distribution system, all those pulleys and rods spinning, that's the problem. And if we get rid of that and then go to individualized electric motors, so each loom has its own motor, then it can be designed sideways because the power is not all in one direction. Then it's variable speed. You can turn off some motors and turn on other ones. And all of these subtle effects, then we had a huge increase in factory productivity from basically using electricity the way it should be used in lots of small, relevant motors rather than replace the one big motor. And I remember hearing that story and thinking, oh, my gosh, that's what's happening in education. We're putting tech into the classroom, and the classroom, the sage on a stage, is the power distribution system. The sage on a stage is holding back technology from its natural effects and its ability to teach children directly. And we have to be brave enough to try to do school without sage on a stage at all, OK, to have all of school be learning individually, your daily lesson plan from the system, executing. We want to maintain the social development. So the person in the classroom really becomes a social worker. They're specializing in learning and emotional maturity and doing valor type circles and these kinds of things. But the, quote, education learning stuff all becomes individualized where it's mastery-based learning. And the question is, how much more would kids learn? So one experimental way to get at this is to think about Bloom 40 years ago. And Bloom said two sigma improvement from individual tutoring. But it hasn't been revalidated in a large-scale way in a while. And so one of the projects we're doing is funding that and take 50 random kids, median kids in a median school, and give them a full year of the whole school day individual tutoring and try to figure out, OK, how much more do they learn? And so Ben Rosen, who's here at the conference and runs RecessGG, he's running this project and recruiting tutors. And so let's see for second graders in the ideal condition, how much can they learn? What is the rate of learning of typical human seven-year-olds? And I think we're going to see it's a whole lot faster than one grade level in one year when, again, completely individualized tutor. They can do everything moral and legal they want to help the kid learn more in that year, all kinds of motivational things, all kinds of different teaching techniques. But again, it's one-on-one, dedicated. And you might say, well, look, that's so expensive, $100,000 per kid per year. It's ridiculous. And I would say that's what it is now. But with AI, it gives all the AI developers a target of what they're trying to do and how much more learning. And what we want the world to understand is, no, there really is twice as much learning that could be happening per day, per hour than today, because I suspect that we'll find that it is twice as much, which roughly means by the time you get to eighth grade, you know as much as a typical high schooler today. Or by the time you get to 11th grade, you know as much as a typical college student today, because of the time compression and the learning and the stimulation. And that would lead to not just lifting the bottom, which, of course, it does, but just a tremendous revolution in the possibilities of the human brain. And there's a positive example of this. So about 25 years ago, Deep Blue beat Gary Kasparov in chess. And from then on, AI chess has been better than human chess. And so you might think, well, everyone stopped playing chess, and it's kind of gotten irrelevant. But in fact, chess has grown. And now the typical 10-year-old on chess.com is scoring way higher than the 10-year-olds of 20 years ago on a stable, vertically scored system. And what's happening is the 10-year-olds are getting tutored by AI and the 12-year-olds and 14-year-olds. And so we're seeing this rise in chess talent because they're individually tutored by AI. And so that's true for chess today and could be true for biology and history tomorrow. I know Michael has a lot of questions, but before we just move, hold, hold. Because I don't want this to get lost, and I think people often get confused when we talk about the power of individual tutoring, and they think kids are going to be learning by themselves. And that is not what you're saying here. I know that's not what you're saying. A dark room, nothing there, locked in. We can reuse containers. No. You want all the social development that we have today. So it's really... Because those chess kids are playing chess with other kids, right? That's right. And if you just take the school day and say the time that's direct instruction, stage on the stage now becomes individualized tutoring. And all the play time and all the time that's do a project together stays as that. And in fact, you can be... The teachers can then focus on that aspect of the day. And again, social-emotional learning we all know is important, but imagine if the teacher is an expert in it and focuses on that because understanding and doing well and the stuff that's tested is done by the software. And by the way, stage on the stage is a very lonely experience anyway. So let's not pretend. Biggie from experience. Well, I was going to say, you're going to finally disrupt class, which I'm thrilled by. Yes. But I'm curious because I talked to a lot of EdTech entrepreneurs at this conference and elsewhere. What's your advice to them? Because they do a lot of times what DreamBox did, right? Which is sell to the existing system, the districts, the schools, the stage on the stage. What's your advice to them? Yeah, that's a great point. The short term is if you want to make money... tell in a school district, makes teachers' lives easier. Don't worry about learning too much. But if you make teachers' lives easier, you'll sell well. If you want to change the world, focus on the homeschoolers. Focus on people who are able to go at their own pace and build systems that are individualized. And as the benefits of that are more and more clear, not meaning 5%, but meaning twice as much learning, school districts will move towards that. And so if you build that now, you're skating to where the puck is going, which is this individualized education. And so think of it as trying to do the pure play where you don't need a teacher. It is the self-driving car, where most of the market is like the map in the car to help the human. That's where most of our ed tech is. And instead, we need to build the self-driving car in terms of education, which is the self-learning, self-teaching. And again, the AI is getting better and better at the emotional motivation. So the vast majority of people seeking therapy today are getting therapy from chat, not from waiting a week and going and seeing someone at $80 an hour. It's vastly expanded the market. And you can say, well, it's uncertified, and that's all true, but it is satisfying to people. And it's not perfect in any way. It is getting better and better rapidly, back to that doubling. And so the understanding the emotional nuance of humans is something that actually the software is quite good at and getting better. And we could talk for days and days about how this leads to agency, and self-direction, and entrepreneurial spirit, and when they're getting what they need. Yeah, once you can learn how to learn from software and from the interaction, the world's your oyster, because then you go off and you want to do physics or you want to do history. Again, a lot of it is there. So before, yeah, let's take it to the world. So what does this mean to the world? You are working globally. CJ is here in the audience with us. Tell us about your work in Africa. Yeah, it's one of the most exciting secondary effects of this AI revolution is it's very shareable. When we figure out good teaching practices, like Success Academy or KIPP, it's very hard to export that to a Brazilian or African context. But when you figure out tech, it's very easy to share. So if you think of Kibera outside Nairobi, people live in $100 or $1,000 homes, a piece of corrugated tin, compared to our half-million, million-dollar homes. So it's wildly different. But if you think of their phones, it runs basically the same operating system that we run as the same apps. It's barely any different. And so if we can figure out software-based AI teaching that really does all the work, we can share that with the entire world. And so the project that CJ is leading is trying to figure out one tablet per child in Rwanda, which is a great test lab. And if that works, as we hope, we'll do the hardware and operating system level. Various application developers in the US will do amazing work there. We'll put those together, and we'll see Rwanda rise to be the most successful education state, first in Africa, maybe in the world. And that will then prove at that point, which the formula is really one tablet per child around the world. No pressure, CJ. No pressure. Number one in the world. CJ, stand up, everyone. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. We're going to get all these people you're working with lots of attention out of this, and so that we can multiply these efforts. Live from the ASU GSV Summit, thank you, Reed, for joining us on Class Disrupted. Yeah. Awesome. Yeah. Mm-hm. Mm-hm. And it's Ben Summers, not Ben Rosen, who's running the project. I don't think Ben's here, but who does Recess GG. Awesome. Get it right. Guys, thank you so much for being here and for making this work on the impromptu. Great. Thank you, guys. --- *This transcript was put together by our friend [Philippos Savvides](https://scaleu.org) from Arizona State University. The original transcript and additional summit resources are available on [GitHub](https://github.com/savvides/asu-gsv-2026-summit-intelligence). Licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).*