Class Disrupted Returns with More Questions About AI

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Hey, Diane, it's good to see you.

It's really good to see you. It's been, it's been a summer that it's funny to not spend as much time with you in the summer. So it's fun to be back. And I guess that's one of the bright spots of returning to the fall. In addition to fall, which is, as you know, my favorite fall is its

own match magic right here in New England. This is like our best season, Diane. This is when, you know, apples, peaches, like we're, we're actually enjoying, you know, the, the limited harvest season compared to you people in California.

Yes, we have, I will say we do have quite an abundant market right now, and we've been spending Sundays there. And I made a very delicious fig jam yesterday with the sort of end of the season figs. So it's been a been quick, fun summer and now we're back this fall with a new season. Michael I can't believe it's season seven.

Yeah, that's wild in itself. I guess we crammed a couple seasons in those first year and a half or something like that because it sort of whipped by during the pandemic and no one was counting years. But we are back by popular demand to focus on AI of all things. DIANE and, you know, same thing theme of this podcast, right? We're not just interested in AI and education for its own sake, but really as a mechanism for rethinking what we have always viewed as a system built for its time, did amazing things in its time, but was never built to optimize each student's learning and chances of really owning their future, particularly in this era. There's a lot of change in this era right now in general in the external environment. So I think, you know, people have been saying we want more about this, follow your curiosity, and we have a lot of questions as well, right?

We do. You know, we thought, I don't know what we were thinking in that miniseries, that we would just sort of figure it out and move on last season, but we did not. I think we just opened more and more curiosity. And so here we are again. And, you know, I think that we have a pretty exciting lineup of guests at least. I'm pretty excited to talk with them this year. And I think they're going to shed a lot of light on a bunch of the questions we have. But we also just want to keep having input from our listeners. So what is on your mind? Who do you want to hear from? What do you want us to talk about. Please send those ideas our way. I hope this season, many of you who wrote in last season are going to find that we took some of your questions, suggestions, ideas, and we're going to try to bring those into the dialogue and conversation. And so we're super open to that. And, and we're thinking about this season a little bit. I guess we're going to start more broadly, Michael. So open the aperture a little bit, if you will, a little bit wider. We want to, you know, we always focus on K12 education. Um, I think a couple things about that this year. One, we're gonna be really specific when we're talking about younger people, middle school, high school, because those things seem to be playing out very differently.

Yeah. And I think some pretty profound differences in last year we were pretty focused on that middle high school segment. And yeah, I think that's just it. Right. Like the AI that's in your adaptive module to build addition skills, very different from how you might use it in high school. Right. And so recognizing those differences, but also recognizing that higher ed and workforce have some pretty big implications on the system as well. And so we're not going to leave those out.

No, not at all. And from my perspective, it's because I want to take more and more the position of what is the journey of the young person. And the young person's journey doesn't sort of have these stark lines between K12 and higher ed.

Those are adult systems, those are not kids systems.

Exactly. And so, so we'll be bringing all of those in when they make sense as we think about the journey of young people. And then, so we're going to start that, I think, with I guess, a little bit of a what's the landscape out there of AI? And, you know, I think last season we talked about, we, we specifically sought out kind of cheerleaders and skeptics and we wanted to hear from those various perspectives. I think this year we're going to look, we're going to at least kick off the season looking at just the big picture in the landscape, like talking to some of the people who are working on the frontier models. We're going to actually turn outside of education for an episode to look at healthcare, which is this very interesting sort of parallel universe to education, and see what we can learn from that lens. Um, and, and ask some big questions about, like, what is happening across the board. And we think that as a result, we, you know, a little bit of forewarning here, we might be talking to people who are a Little bit more on the optimistic side as a result. But we will of course keep, you know, a critical eye on the conversations

that we're having a hundred percent and on the note of optimism. So just so folks can start to envision the arc, we're not going to tell you every guest right now up front because, you know, there could be some. But if we're starting broad, we're starting with people who actually work at some of the companies that do the large language models, healthcare, as Diane said, folks that have sort of this 20,000 foot view of where AI is going more broadly. And then we're going to start to hone in on the education use cases and we're going to go to entrepreneurs. So they're going to certainly be optimistic as well. That's in their nature. They see problems, they want to solve them by building something which is great and they will bring their lens. I will say, Diane, when I moved out to Silicon Valley in, What was that, 2008, 9 or something, and it feels a little bit like it did then, right when you were building the new summit model in 2010, I guess it was. And it feels a little bit like that. A lot of excitement, energy around edtech startups, potentially, I would say a little bit more skepticism or caution maybe is the right word from the investor class because they feel like they've been through this a little bit. But we're curious to talk to a bunch of entrepreneurs and find out what are they doing with AI, what are they excited about? Is this tinkering toward utopia, as someone might have said in a book, or is this like really reinventing education in the ways that we've talked about? And so I think that'll be pretty interesting as well. I'm excited to talk to all those entrepreneurs.

I am too. And so what we wanted to do today, before we hop into those conversations in these next episodes, is just sort of, sort of laid down our baseline foundation of where we are right now. You and I are always on a learning journey and so we always like to reflect back of like, where did we start these conversations? Where did we end? What's changed? What's different? And so we sort of asked ourselves these questions leading into this episode of, you know, based, based on where we left off three months ago, which is sort of a long time and sort of not a long time at all. Um, you know, what's kind of stayed the same? What do we, what do we feel like? Oh, we thought that three months ago and we kind of still think that, you know today what's changed in our thinking, if anything, and what's blowing our minds. Hopefully, you know, maybe something, given what you just said about the moment in time we're in. So we thought we'd just ask each other those questions, get a. A level set baseline of where we're starting the season, and then. And then we'll get into it.

That sounds good. Let's. Let's dive in that first category. I want to hear from you. We're coming back three months later. We put a lot of our priors on before. We also talked about our own evolution in the end of the last two episodes of last season. If people want to go back and see how we have remained true to our roots of trying to be malleable and keep learning, I'm curious what stayed the same in your mind that has not changed from where we left off?

Yeah, it's funny because we decided on these questions, and then as I started thinking about them, I was like, oh, maybe I want to shift them to what is still.

All right, go where you want to go.

Still disappointing me a little bit, but it's stayed the same. So that's where the disappointment comes from. I think that I. I feel like I spend a lot of time really, like, digging and poking to understand what's underneath all the. In some cases, hyperbole around AI and, like, what's actually happening and what's really going on in there. And sue, despite all sort of the energy and the talk and the, you know, everything that's happening, I find when I'm digging that mostly AI still in education, not still, it is currently being used kind of at the individual level, if you will, whether it be the individual teacher or maybe sort of a little bit of an interface with the students. And I would contrast that to it being used, you know, more broadly around the system or how we actually do schools. And I think a lot of that usage is still in the efficiency category. So how can we gain more efficiency in things we're doing? And there still seems to be a very significant focus on chatbots. Um, and I have been a skeptic of. Of the ultimate utility of chatbots since the very beginning. As you know, I don't. I don't think that they're the manifestation of AI that I'm excited about and hopeful for and whatnot. And so I guess that's a little bit of my. That's definitely stayed the same. I haven't changed. My opinion hasn't changed.

And just to make sure people understand what you're saying when you say at the level of the individual, you mean interactions within the existing models to make them a little bit more efficient, but not actually fundamentally change what those interactions or assumptions or baseline processes are in the system? Is that what you're saying?

Yeah, it's kind of like we're using AI to maybe do things we've always done, maybe just a little bit faster, a little bit easier, a little bit better, you know, with fewer humans potentially. And so, I mean, I look at and we'll get in and we'll talk with folks from these places, but I think about, you know, the big announcements over the summer from, you know, Gemini and OpenAI about study mode and, and the variety of products from, from Google, DeepMind, Gemini, and they still feel to me like, yeah, that's kind of the way we've always done it in school. It's just like, are we making it a little bit fancier, personalized, easier, better?

Yeah, I think I'm in the same place, Diane. Actually, we, and just the audience knows we didn't talk about our answers in advance because we were trying to surprise each other, but we may have failed on the first one anyway, so I wrote a piece over the summer saying, Like AI EdTech, it's going to continue to disappoint as long as we're layering it over existing models as opposed to reinventing the model itself. It's frankly the central premise of disrupting class that I think, frankly, the majority of ed tech entrepreneurs got wrong in the 2000 and tens. I think because I was in it a little bit, I was trying to learn and be curious at that time. I kind of feel like I'm just going to be a little bit more blunt this time and say if you think you're like serving the existing system and the existing classrooms in the existing schools, you're not going to reinvent and you're not going to get us to where we need to go. Full stop. Full stop. And so I think the new models, you in your. Yeah, I know I'm a little bit more annoyed at this point. Right. But like the, the new models, I think in the entrepreneurial energy from outside of the system, truly, I think is even more important than it's, than it's been. So I think I've stayed the same on that and maybe even gotten a little bit more passionate about it. But let's shift to where our minds have changed next. What, what, what, what is different in your mind?

Well, it's interesting. I think I'm going to build on where you're going. Because the thing that was coming to me was how I'm feeling is shifting. And you know, I. I live in Silicon Valley, so, you know, I'm very sort of shape. It, it is, it is the dominant conversation here. It's everywhere you go. It's what everyone's thinking about. It's just in the culture and the water. And I. If feels like over the summer it's shifting from sort of this amazement and awe and wonder and curiosity of like this new incredible thing to a little bit of like a gold rush. Like people have realized, not that they didn't before, but really realize there's so much money to be made in AI. The. If you're tracking at all the valuations of companies and the funding, you know, the venture funding going to startups and things like that, not necessarily in education, but in other sectors, there's so much money and that just sort of adds an. An element that is far less about curiosity, wonder, awe, possibility and much more about. I just feel like the sharp elbows start to come out and there's a level of aggressiveness. There's people who hop into it who I don't think or care very much about transforming systems for the better, but it's really about who's going to dominate, who's going to be in power, who's going to make money, who's going to, you know, and there's just the. It just feels a little. It's inevitable and it just doesn't feel as kind of, I don't know, noble. Yeah.

Is that what you have?

No, I think that. That's right. Fascinating.

Maybe the caveat I could say is like, there's nothing wrong with people making money off of it. We just, I think we both believe that the bigger opportunities for good are not where the money is at the moment, at least in education. Right. Like the dominant spend is still in the existing system, which is why. I get it, it's why people sell into the existing system. I just think we just really shortchange the longer transformation opportunities as a. I

think that's exactly right. It feels like there's two totally different dialogues going on and, you know, neither is aware of each other a little bit. And so, yeah, it's just, it's interesting. It's an interesting cultural time. There's a big, you know, sort of gathering next week of the, you know, AI enterprise stack gathering. And so we're just going to start to see a whole bunch of, um. Yeah, that kind of focus, I think yeah, that's interesting.

I will say the sums of money and I'm not talking about education at the moment, I'm talking more generally that these startups are raising. It feels very.com era. Right. Um, it's been staggering from my perspective to, to watch it and I'm, I'm very removed from the Silicon Valley. You know, I'm, I'm a decade or whatever out from having been in those waters. But it feels a lot like those times. It always reminds me, Clay always said, you know, like when you're truly disrupting, you're going after non consumption. And by the def. By definition that means there's no market at the beginning. So it's really hard to chase nothing and pick that. So I, I think some of that is also going on. I'll say for me, I don't know if it's letdown is the right word because I'll contradict myself, like, I think in our next question, but like, I, I've become less impressed with the power of these models professionally. And yeah, I, and I don't know. And I think a large part of it is like they are prediction machines at the end of the day. Like they are not logic. Right. Like at the end of the day, they're not people. They're, they are absorbing a fraction of the senses we use to think about the, and perceive the world. Right. Largely language and, you know, some image. Right. But it's basically eyesight and prediction machines. Yes. Like, you know, some of the thinking that you can do by having it recurse on itself, it's pretty cool. And I just, it feels like for an, like when you're an expert in a field, the things that it does for you just feel sort of generic to me, Diane. And maybe it's how I'm using it, but I've, I, because of that lack of logic, I've, I've become a little bit more, or tempered. I think maybe that's the right word about some of these models. So it could be me.

But no, let me double click on that because I feel like I might be having a similar experience. So tell me if this rings true for you. I find myself, I think I've gotten a lot better at prompts, prompting, and to get what I want pretty darn quickly. And so I actually really use it as an assistant kind of all day, every day, you know, quite efficiently, much more efficiently than in the beginning, and I think in a much more kind of fluid way. And to your point, it feels very much like, like an Assistant. You know, again, like not a lot of like this is kind of magical anymore. Is that what you're talking about or.

I think that is exactly what it is. Right. And sometimes I conclude just like I would with a assistant. Oh man, the. The amount of times we're gonna have to go back and forth on this, it's not worth it. I'm just gonna do it myself. And so I'm. I find myself making that calculation much more. Maybe this will go to the blowing your mind, which is I will say, like per. In my personal life, I actually find it the utility to have gone up tremendously because I'm not an expert in a lot of those questions that I bring to bear. And it allows me to ask the naive question that I'm not always great at finding the person I should ask to. And the chat mode with GPT5 like and, and. And showing a video and, and like having conversations about stuff. I, I find it incredible for personal learning and just sort of general questions there. I find it incredibly valuable at bringing up like a couple hunches or, or disproving things that I might be thinking and so forth. And just like, okay, I'm coming in with a much higher baseline now than I was before that I found really, really compelling on the personal side. The professional side may be a little bit less so. What about you?

That's interesting. Well, that feels very, very true to me. I mean, I'm using it for everything from like how to care for my plants to how to make. Curate a playlist for our family dinner nights in the summer and you know, talk to my kids and they'll tell you how much of a fail or success that was. But you know, it is, it is like I don't feel ashamed to ask it dumb questions. And I. Every time we watch a movie, I'm like, I feel like I'm having an, you know, an analysis with it afterward. I, I chalk that all up too. It is significantly better than search, I think. Like it's this big leap forward better than search. Let's see. For me, I'm super interested in and curious about these what feel like. I'm sure they're not, but feel like sort of overnight upending of practices in other sectors and fields that I'm aware of. And it does feel like there's some structural change happening in other fields, which is. Makes me a little bit envious. I'm wanting that in education. And I'll just give you a couple of examples. Like one just as simple as like online retail I mean, so many people I know in this space, you know, it, it is fundamentally changing the space because you don't need to have. This sounds silly but like you don't need to have models trying on clothes or modeling your, you know, your wares that you're selling because literally you can just do that using AI so you take pictures and like consumers can do that now literally I can go try things on my stuff self online, you know, and see what it will look like on me now. Again, that sounds trite, but it does feel like it's going to revolutionize this kind of industry in many, many ways and then kind of on the more serious end. And this is why I'm excited to have a healthcare conversation. There's just such phenomenal opportunities that I see happening in healthcare that, that are really profound and I think are going to fundamentally change the system. I'm, I feel like it's.

Well, it's going to be the same analogy I think though, in education, right, Because I see a ton of AI that is improving the exist, sustaining the existing system and making it better, more efficacious, efficient. And then I see some AI outside the system, right, like more direct to patient, very different value network and that, that, that stuff depending on, you know, if we let it, it's very interesting.

So, so I think those are the places where I feel like myself saying wow. Like wow. And a little bit of mind blowing.

Well, I, I'm excited to learn a lot more in the season. As we said, it's going to be a really interesting group of guests. We're, and like you said at the beginning, you know, last time we purposely had optimists and pessimists up there. So we could really put the different arguments against each other and think about this. We'll take a very different line of inquiry, it's safe to say with each guest we have based on how they're coming in and what we're hoping to learn from them. I cannot wait. But before we close out this welcome back primer, if you will, of an episode, let's go to our, our segment that some people keep track of, which is the what are you reading, watching, listening, etc. Outside of work stuff, ideally, although sometimes we fail and slip into work. But what, what, what, what is what is on yours?

I might be sort of failing right out of the gate, but. So I read this book recently. I think it's been around for a bit, so it might not be new for a bunch of people. It's called How Big Things get done and taglines very long, surprising factors that determine the fate of every project, from home renovations to space exploration and everything in between. That's by Bent Florg and Dan Gardner. And first of all, I will be honest, it stressed me out to read this book because like every ex, it feels like every big project is fraught and there's so many potential. The likelihood you're going to be successful is really slim. So it did give me a little bit of stress, especially as I thought about projects that I'm currently working on and was evaluating through their framework. But one of the things I loved about it was how data driven it is. And it really looks at these big data sets to take a critical lens at how we do projects and how we could do them better. And I think this might be a theme that comes up a lot this season is the power and importance of data. I think that that doesn't get talked about nearly enough and really might be the most important thing that we're grappling with here. So if you do any sort of

projects, I should read this. You're telling me. All right, all right, now you're scaring me. But I'll, I'll. I remember when the book came out. I have not read.

Yeah, they'll look back on your home renovation and be like, I was about

to say, is this gonna make me, like, feel really dumb on a bunch of things we do? Okay, yes. The answer is yes. So, yeah, so. But I'll learn. All right, well, mine is gonna be work based as well, by the way. It's interesting. Like, we haven't seen each other in three months, so we've watched and read a lot of things. So we're sort of picking. Right. I was, I had all these TV series that I actually watched. I was gonna be like, hey, look what I did, Diane. But, but I think I should give a shout out to my other co host of the podcast. Jeff Salingo's new book, Dream School. Finding the College that's Right for you came out September 9th. So the day before we're recording this, but it'll be a few weeks out by the time this comes out. And it's a fun book that tries to get people away from thinking that you just have to go to the selectives, the, and, and, and take a wider aperture and give you some criteria to do so as you go through that journey. So we'll see. We'll, we'll, we'll, we'll see. But enjoyed reading it. And I'll put that on my list.

Awesome. Well, I'm excited for that one. I think you know with my new project Future we are attempting to do that as well. And when we.

Yeah, I saw that in the, in, in the feature set you have the, you have that little part part where like it depending on your pathway. Once you pick if you go in the four year college pathway it starts to suggest some schools that might be better fits based on both outcomes if I understood it. But also based on the things that you seem to be gravitating towards.

Yeah. And not the usual suspect schools but schools that based on data are performing are, are better access and better outcomes for young people. So I look forward to check out

the, check out the appendix. He built a cool little, I think he put in the appendix because he didn't want another list out there. But there's a list. But it's. What's more interesting is the criteria that he chose to come up with schools that you might want to look at. So it's interesting. That's the plug. But we're excited to dive into this season. I think we're going to learn a lot. Can't wait to be on the journey with you. And as Diane said up front, tell us what you want to hear. Tell us what you want to ask people. We will try to start teasing some guests ahead of time perhaps so you can be ready to ask us or tell us what you want us to ask. And we can't wait to get into it with you all on season seven of class disrupted. We'll see you next time. It.