Catching Up: Ambient AI, Alpha School, and The Educator of the Future

In this episode of Catching Up, Nate McClennen and Mason Pashia dive into the latest innovations shaping the future of learning. From Alpha School’s groundbreaking two-hour AI-driven learning model to the rise of ambient AI that integrates seamlessly into our everyday lives, this conversation explores the intersection of technology, education, and human connection. They also reflect on the importance of relational intelligence in schools, the role of real-world learning during the remaining six hours of a student’s day, and the growing significance of personalized and competency-based education. Tune in for thought-provoking insights and actionable ideas to reimagine education for a future-ready world.

Introduction and Episode Overview

Nate McClennen: All right, everybody. Welcome to Catching Up. We’re excited for this episode. We have been on hiatus for a little bit longer than two weeks, but we promise this is a good one. It’s a long one, and I think you’re gonna love it, especially the music at the end. So I’m gonna riff a little bit on connection—that seems to be a theme of our work. And then we’re gonna share a little bit about some partner work in Michigan and Virginia that we’re doing, which we’re really excited about. It’s been a busy fall. And then we’re gonna go deep on ambient AI—what happens when AI is all around you and what happens to your learning?

So, Mason, what are you gonna talk about?

Mason Pashia: Yeah, we talk a lot about AI in this episode. So, sorry to our listeners that are tired of that.

Nate McClennen: We always talk about AI.

Mason Pashia: Our click rate and listen rates prove that you are all still interested. So hang with us. I share a story of some good news about an entrepreneurship program called Uncharted Learning. We also take a look at Alpha School—the two-hour AI school day that is sweeping the media nation. And we talk a little bit about a recent blog post called A Day in the Life of an Educator in 2040 and some corresponding work we’ve been doing on that subject. So stick around. It’s gonna be a good one.

Nate McClennen: And hey, we end with, like I said, great music and a story about french fries. So listen to the whole thing.

Mason Pashia: Hey, Nate.

Nate McClennen: Hey, Mason.

Mason Pashia: It is great to see you. I have some very good news for you today.

Nate McClennen: What’s the good news? I always like good news.

Mason Pashia: I think the good news is, I think today we have our best song yet.

Nate McClennen: No kidding.

Mason Pashia: It is really good, and I’m a little bit worried about getting sued for it, but I think Suno would be on the hook, not me. So, it’s very good. I’m excited.

Have you ever played Hurdle? It’s the New York Times game—it’s like Wordle-inspired, but it’s by Spotify.

Nate McClennen: No, I haven’t, but I am looking for more games because I just started the mini crossword puzzle, and I’m very bad at it.

Mason Pashia: Hurdle is really hard. It plays you one second of a song, and you have to guess the song. And then if you can’t do that, you get three seconds of the song, and then you get five seconds of the song. So I think we need the Hurdle technologists to design our…

Nate McClennen: Oh, that’s really good. I could probably, after maybe five seconds, keep the tune going. But I’m not sure I could ever guess the name of the artist. That would be my problem.

Mason Pashia: I think that means you’re as good as Suno. I think that’s what Suno does. I don’t think they could tell you what the song was either, but they could keep it going for you.

Nate McClennen: So, Nate is at least equivalent to Suno at that level? Well, no, we gotta test it.

Mason Pashia: So, I’ve got a little good news story for us today. I think we’re gonna try to incorporate more of these into the…

Nate McClennen: We need more good news, Mason.

Discussion on AI Companionship and Connection

Mason Pashia: Yeah. We both love good news, and we think that’s kind of core to what Getting Smart does—we’re sort of sharing good news from around the ecosystem.

So this one comes to us from our friends at Uncharted Learning, who have this really cool Incubate EDU incubator program that is in a bunch of high schools across the country. It empowers young people to do entrepreneurial pursuits—everything from writing a book to creating board games to starting a nonprofit. It’s kind of all over the map. They sent me this press release recently from a group of students in McAllen ISD in Texas. They noticed that all of their peers were drinking energy drinks like crazy, and they were like, “This is so not healthy for anybody, and it’s expensive. It’s just not a great idea.” So they decided to try and copy this popular Mexican candy—a Chilato gummy snack that’s coated in Chamoy. Chamoy is like a pickled fruit flavoring that’s often on mangoes.

Nate McClennen: Wait, let’s stop for a second. Just describe that one more time for our audience.

Mason Pashia: So, picture a gummy bear.

Nate McClennen: Yeah, I got it. Okay.

Mason Pashia: Okay. So you’ve got a gummy bear, and this Chilato is like a type of gummy snack that they’re often eating. And Chamoy is like a pickled fruit flavor. It’s often on the outside of a mango. It’s like a red gel. It’s kind of got a little bit of a tahin-esque chili kind of flavor to it.

So they are making these gummy bears that are mimicking a popular snack, and they’re imbuing it with all this energy stuff that you can find in an energy drink. And so you really only need a couple of what they call Boosty, which are these little gummies that they’re now producing in a factory and selling to all their classmates to try and bypass the energy drink craze.

I think there’s probably some questionable health results in either of them. You’re still making something that is very sweet and gummy, but I think it’s a pretty exciting way to spot the problem and deliver value—all fueled by entrepreneurship education. So, love it.

Nate McClennen: And I think the branding on that is really good.

Mason Pashia: Boost is fantastic.

Nate McClennen: That is very clever, and I love that students are doing it. And I mean, hey, if it has a little bit less sugar in it than the regular drink, which often has tons of sugar and caffeine but still the same effect, there you go. A couple of things that were on my list that I wanted to share. One is this idea—we’ve talked a lot about this—but it just continues to come across my feeds: What does human connection look like? And how are things like AI and social media distracting from connection? Or maybe, some people would argue, enhancing connection.

There’s an article from Brookings in July that gives an overview of this, talking about how more and more young people are creating companionship with some sort of AI tool. And I think it’s going to get better and better. We’ve talked before about things like Replika and these video avatars. So that’s not new. The thesis there—the argument—is that there are a lot of different apps out there, and more and more people, not just young people, are using them for relationships. The data suggests that some people who are lonely at first may be less lonely, but also those who are not lonely at first may become more lonely.

Mason Pashia: Right.

Nate McClennen: So, you may be solving for a part of humanity that feels lonely by giving them an AI bot, but then there’s a vast majority of people who are feeling more lonely. What they’re arguing, though, is this idea that we need to train teachers in relational intelligence so that technology is used to enhance human relationships, not to displace them. It’s a design principle, not a side effect. They talk about this idea of, if school wasn’t just a place for academic readiness—which it should continue to be—but also a place for, I’m going to use the term “relational readiness.” They use the term “relational hub.”

So, do we need effort in training teachers in connection as much as we need them trained in teaching ELA, math, science, or other pedagogy? I was fascinated by that. In some ways, we think about ourselves as teachers and that relationships are important, but I’m wondering how specific and intentional we now need to be with these other things that are distracting. Thoughts?

Updates on Educational Initiatives

Mason Pashia: Yeah, I mean, it definitely sounds like AI is a catalyst for this, and at the same time, this feels like a skill that teachers, at their best, should always have. Right? Like, this does feel similar to what you were just saying—it’s always been a very important part of what it is to be a teacher: to have relationships and to be able to help young people develop them.

Right when AI was burgeoning, we were all like, “How is this going to make us more human in the end?” And I think these kinds of questions start to get at that. It’s like it’s asking us to do an inventory of what matters. It’s redesigning something that has always been set in stone and hard to change. And yeah, I’m super excited that teachers would be getting more relational intelligence. Part of me wonders if relational intelligence feels like an add-on when relationships feel like something that’s already a part of the description. So, I wonder how much of this is trying to come up with a silver bullet for something that, in theory, has always been right in front of us.

Nate McClennen: Right. So maybe it’s a reminder that in this age of digital connection, we need to really hammer down on that relationships piece. I remember Tony Wagner would write about the three Rs: relevance, relationships, and rigor. So, you’re right—great teachers know how to build great relationships. When we’re implementing technology or AI gets implemented in schools, the argument here from Brookings is we actually have to focus on that, but also think about what technology is doing to distract us from that and teach those connection skills.

Mason Pashia: And notice where there might be a deficiency. Maybe what this does is it actually nuances how we define relationships. You have a student come in who maybe has been engaging with a technology tool mostly, and you’re like, “Oh, they seem like they have a surplus of this kind of signifier from a good relationship,” which is maybe like they always have someone to talk to. But they’re really missing in this other department. Maybe they have really low self-esteem or something, and you’re like, “Hmm, some part of this relationship equation isn’t working.” So, it might be learning how to spot that and then deliver in the places where it’s not currently being met.

Nate McClennen: Yeah.

Mason Pashia: Yeah, it could be intelligence.

Nate McClennen: Maybe we’ll come back to that when we talk later on about this idea of ambient AI, because I’m thinking about how you actually discern this in individuals. That was something that came across. A couple of other things that are shorter:

So, NAEP scores came out—National Assessment of Educational Progress. Everybody said that they were not very good. We have a lot of challenges in literacy and mathematics in terms of what’s being measured on this test. Now, as we’ve talked about before, it could be that students aren’t engaged, or they’re not putting their full effort in. There are all sorts of confounding factors, and we talked about those in a previous pod. But one of the articles from The 74 Million that came out was interesting and thought-provoking.

When about two-thirds of students on NAEP are at or below basic in literacy, it means that they can actually read. So, they can read a street sign or basic text. But the challenge is that the higher-level skills of analysis and critical thinking are more difficult. On the NAEP, they ask questions of all different types: Can you read? Can you analyze? Can you critically think? The article was making the argument that it’s not that students can’t read—it’s that they can’t read at a level that helps them discern, unpack, and decipher all these claims in the media world. They were going back to pseudoscience and the world that students are ingesting through TikTok and Instagram. How do you quickly decipher this? You need analytical skills and critical thinking skills. A huge number of young people are not developing those. So, I think it was a little bit of a call to action. It’s not just literacy, like functional literacy—it’s this idea of civic literacy and, I would even add, media literacy. The ability to interpret and analyze the world when you have so much coming at you at one time.

Mason Pashia: Yeah, super important. Good flag.

Nate McClennen: And then the last one, just to give a little shout-out, is that we are doing—it’s been a busy, busy fall for us here at Getting Smart. We’re doing these two big launches. Our continued work in Michigan with the Future Learning Council, a really great partner that has done so much work in Michigan to amplify the future of learning. They’re really focused on personalized, competency-based learning and helping districts. They have about 60 districts, plus 20 or so ISDs, that are all working together in partnership to try to move a model forward that better engages students to get better outcomes using increasing relevance, competency-based approaches, etc.

And in Virginia, there’s a group called VALEN—same kind of thing. It’s a high school redesign group, and there are about 20 divisions involved, with a bit more than 29 high schools participating. All those schools are thinking about high school redesign. How do we rethink high schools? I’ve been thinking a lot about the coalition of the willing lately and this idea that both these groups are optional groups. No one is forcing them to do it. I’m thinking a lot about this ground-up work—how do we get the coalition of the willing to lead the way in U.S. education to really transform learning? So, we’re excited to work with both those partners—VALEN in Virginia and the Future Learning Council in Michigan—and we’re super appreciative of all the hard work they’ve done to set some great foundations for good learning experiences.

Mason Pashia: That’s great. Yeah, appreciate the shout-out. I’m sure our listeners can tell that we’ve had a busy fall because we’ve had very few Catching Up episodes. So, apologies to our listeners for the delayed release between them.

Nate McClennen: Yes, we’ll get better. I think things are now settling down. I hope so. We’ll get back on our two-week schedule.

Mason Pashia: I hope so too. Yeah. Cool. Those are great shares. Thank you, Nate.

Nate McClennen: Let’s start with a deep dive. Why don’t you take us into the work on Alpha?

Shorts Content

Alpha School and the Two-Hour Learning Day

Mason Pashia: I’m sure that all of our listeners have now heard of Alpha School. I feel like…

Nate McClennen: They do really good publication and promotion, that’s for sure.

Mason Pashia: They definitely are sinking resources into promotion. Yeah, they’re everywhere. I wanted to talk about it a little bit because I think there was this really big article published in Colossus a few weeks ago with…

Nate McClennen: Ah, yeah.

Mason Pashia: …the brain behind Alpha and the technology. It gave me kind of a peek behind the curtain to some stuff I wasn’t really aware of beforehand. I had known about the two-hour AI school day and the ways in which they were thinking about it augmenting learning, not replacing learning and instruction. But I got a couple of things I just want to share about this, and then I have a few questions for you to see what you think.

First and foremost, Alpha School, on paper, is working. Alpha School has been tested in a couple of schools in Texas. If you take all the K-8 scores from the students in Alpha School, they’re ranking in the top 1% nationally, with growth rates in the 90th percentile. The SAT scores were super high—1535 out of 1600. So, on paper, it’s working in the ways we’ve measured success in the past.

Nate McClennen: And just as a quick reminder to everyone listening: Yes, it’s working on paper for the cohort of students that are there. We have to remember that this is a selective private school. So, this is not a sampling of all students. It’s a very specific cohort of students that are typically in the gifted and talented range.

Mason Pashia: Correct. That’s super important. To Alpha’s future credit, they are rolling out a public model to continue testing this iteration. So, they have some visibility into that, but correct—that is the data as it stands.

This article showed me a couple of things, though. So, one, there’s this tool called TimeBack, which is really like the secret sauce of the Alpha School two-hour day. What this does is it tries to adjust for students’ anti-patterns. These are habits that make learning much less effective—whether it’s something as mundane as spinning in your chair or checking Instagram, to something that apparently is a little bit more of a problem in edtech spaces, which is topic shopping. I think I’m very guilty of this in my browser sometimes, where if I have three things that require too much energy, I just sort of click between them for about three minutes until I realize I’m doing that, and then I’m like, “Oh, it’s time to actually commit to one of these.”

So, it’s monitoring this kind of engagement from students, and it’s actually doing it in a kind of dystopian way. It’s got this vision model that’s actually watching the user, and the whole time it’s funneling all this information into what they call a waste meter. It shows students at the end how much potential free time they’re losing if they don’t complete their lessons within the two hours. It’s this really hyper-efficient, hyper-optimized system that, over time, will just continue to get better and better. The founder spoke a lot about video games and the influence of TikTok on some of the ways they’re designing these tools. The goal is really to track what is working in engagement in the broadest sense—using all the tools at our disposal—and to funnel it into this thing that almost tricks people into learning in this two-hour time period. Not to use the word “tricks” negatively, but just like you’re not necessarily supposed to be aware that you’re learning during some of this time.

That’s really interesting. It happens in two hours, and then they say there’s another six hours of the day to get your childhood back—to go do things that are more real-world and immersive. I have two core questions for you. One, what do we do with these other six hours? If you’ve got these two hours in the morning for all these core classes and basic literacies, what are you doing with the other six? And, tell me if I’m just being a little bit like the boy who cried wolf on this, but can you make learning too addictive? I know people who don’t exercise unless they have the watch on to track the exercise because, then, it doesn’t count. So, there’s a concern for me that if you’re not actually within this optimized environment, you’ve become used to the kind of incentives and rewards that actually defeat the purpose over time, and you only want to learn in that kind of environment. Feel free to start with whichever one, but those are my two big questions after this story.

Nate McClennen: Okay. I have a lot of questions. I’m going to push back. I’m going to comment on these, but I want to push back first. Would you put a TimeBack video on your computer to help you do better every day? Especially if it was just for you—meaning Getting Smart wouldn’t see it, it was just for you. Would you do it or not do it?

Mason Pashia: I don’t think I’d do it.

Nate McClennen: Okay.

Mason Pashia: Yeah, I don’t think that I learn well under those conditions, and I’m not sure it would tell me something about myself that I don’t already know.

Nate McClennen: Right. Yeah. I’m not sure either. I think it feels very surveillance-like. It could be interesting, but like you said, I’m already pretty self-aware of when I’m flipping back and forth between three decisions and just have to move forward. That was my question.

The other six hours—so, I’ll tackle that question first. I do think that, especially in the younger grades, play is important, and probably some sort of version of play in the older grades. We’ve lost that a little bit. I do think that passion projects or student-directed learning with appropriate structure—by appropriate structure, I mean if you’re in the public sector, you’ve got to meet science outcomes, social studies outcomes, and all these things that are not ELA and math-related. Maybe you are creating—or AI is helping you create—learning experiences that you’re interested in co-designing, and then connecting them to these other various outcomes that you need to meet. So, sort of passion project, self-directed learning type work. Some play, passion projects, and self-directed learning.

Then, I think that connects with real-world learning, but some sort of contribution-type piece. You and I have talked a lot about contribution, and it could be work-based learning where you’re going into a workplace at all the grades and learning what that’s like. That’s less contribution, so I might say experiencing the world as an adult—just to test out some things. But also, there’s a part of it that’s about contribution. I think that needs to fill up the day as well. I think there needs to be a lot of time spent working in teams, learning how to connect, like we talked about before, and practicing that connection. I’d like to see times where there’s no technology involved so students can continue to think about that.

Those are the things that I would fill up. Honestly, the other piece—and this is dependent on family and work situations—but if you can in any way buy back family time, if the family is a good place for you and there’s time, that’s a powerful thing as well. Often, everyone’s working, and there’s no time. Kids come home from school, they have to do homework, and there’s just no time to connect or sit down as a family and eat a meal together. I recognize that can’t happen with every family with different jobs and things like that. That’s how I would use that six hours.

That’s the incentive to put a TimeBack machine on my device—because I’m going to get all my work done in two hours. Now, that’s actually a great add-on. We should figure out how to make that happen because it feels like it’s an infinite list at work, to be honest.

Mason Pashia: Yeah, for sure. That is the one to solve.

Nate McClennen: Yeah. So, that’s my first one. And then, can learning become too addictive? I mean, probably, because let’s think about gaming, right? Gaming is learning. You’re learning how to master a particular set of challenges. And I’m not a gamer, but those are learning experiences. You’re training your brain to do something, and they certainly are addictive because of the leveling up and the gamification. So, can it become too addictive? If it helps you become a better person and it helps you make the world a better place, I don’t actually care if people are addicted to that. That’s my personal piece. What do you think?

Mason Pashia: There are so many… I was really hung up on the fact that it’s being modeled after things like TikTok, which I feel like right now we don’t have the best interpretation of what social media has done to our brains—whether that be attention spans or bridging differences. So, using that technology as an example of what you’re trying to build freaks me out a little bit, to be totally honest. It does feel a little bit like the endlessness of the feed and also sort of the illusion of learning. The number of people I know who spend a lot of time on social media and always have things to share, but they feel kind of out of context—it’s kind of more like a pull quote. It’s sort of like… I think that Alpha School, because it’s personalized and modular, and of course, that’ll be a little different, will probably be nested within context. But I do think that without application, learning can become too addictive. I think learning can actually be a paralyzing force rather than an enabling one if you’re not scaffolding it correctly with opportunities to actually do something with it.

So, that’s my hope for the six hours in the day—that that’s what that’s for. And I’m not actually that… I think that the two hours of this kind of focused learning and then six hours of experiential and relational learning is actually a pretty beautiful portrait of what school could be in the future. I think that breakdown makes sense to how my brain interprets what were the most impactful parts of school. And yet, I just… anything that claims to be a silver bullet, I just get a little bit wary of.

Nate McClennen: As you should.

Mason Pashia: Yeah, and I’m super interested to see what comes out of these two hours, though, because they’re going to have a lot of data.

Nate McClennen: Yeah. I suspect—I mean, I think I read the same article, and this is a billion-dollar investment with a couple hundred employees working on this. This is a backend startup that no one talks about that’s really thinking about the operating system for education and what it looks like. One other thought I was thinking about is, I am not convinced that the two hours have to be in a single block. I’m sure they are convinced of that because that’s the way the structure is, but really the power is you can satisfy your ability to learn math and your ability to read and write in a two-hour time period.

Whether or not that has to be blocked, I don’t know. Some students might be better working for 15 minutes and then going to run around for 45 minutes and then repeating that for the rest of the day. So, I think there are some variations on this, but I do think we’re going to see more and more, especially around core skill acquisition—the stuff that’s usually tested on standardized tests, which may or may not stay the same. That will become more and more AI and personalized. I’m continuing to think that’s important.

It goes back to our prior conversation about how we help educators adjust to really work on that six-hour other part of the day. I think that’s really important.

Mason Pashia: Me too. And I think my closing thought on this is just to kind of continue to weave conversations we’ve been having on these and off of these. If there’s this moment where a student is learning for two hours and it is very data-rich and evidence-full, I think that actually makes it more important than ever to find ways to capture and credential the rest of that learning day, or else it loses value and validity. That has the chance to actually augment the gap we already see between real-world learning and normal learning, where real-world learning is so hard to prove, explain, or articulate because it’s outside of the bounds of what we’ve always known to be learning in some ways—or “always known” in quotes, like defined as learning. So, I just think that this is a big occasion to continue to invest in those technologies and figure out how the heck we’re going to tell the story of an internship in a world of surveillance for two hours a day.

Nate McClennen: Yeah, right. You could see a place where you have a thousand times more data in your ELA and math…

Mason Pashia: Right, exactly.

Nate McClennen: …than your six hours the rest of the day. Well, I think that’s interesting, and I think it’s a good segue into my next piece, which is a nice natural transition here.

Ambient AI and Learning Assessment

Nate McClennen: Well, I think that’s interesting, and I think it’s a good segue into my next piece, which is a nice natural transition here. So, GSV Ventures, which is part of ASU+GSV—the big conference that happens every spring—they’re a venture firm that focuses on education and do a lot of edtech work. I shared with the rest of Getting Smart, and I think we all saw it, their forecast for learning and earning in 2025-2026. We’ll put it in the show notes. It’s really, really good and a great thought-provoking document for any school leadership team or a group of innovative teachers to jump into and talk about. There’s a lot of thought-provoking stuff here.

This is about 2025-2026, so it’s a one-year prediction. The one that I thought was most interesting was this: the chapter titled AI is Air: Ambient AI in Every Breath, Step, and Swipe. I’m going to actually read a few sentences because it’s really articulate. It says:

“With ambient AI, assessment becomes continuous. A classroom debate, a customer service call, or a lab presentation can all feed into dynamic profiles of skills and growth. Done right, the shift could measure real learning and impactful feedback. Done wrong, it risks turning schools and workplaces into surveillance states. The long-term outcome: skills become the substrate. Competency graphs will travel with learners from K-12 into careers, more predictive than a GPA or even a degree. Everyday artifacts of work become evidence of mastery.”

So, this is what you and I have been talking about, right? This idea of, in our framework, what we call the learning ecosystem—everything around possibilities. That’s the “where” part of our framework. And then the “for whom” is all about the signaling and credentialing. It’s combining the “for whom” and the “where” elements of our framework. But I hadn’t heard this term “ambient AI” before.

The two bullet points that were important were this idea of us building shadow profiles. When we collect data about our learning, we’re suddenly building a shadow profile. This is no different than our advertising media profile that we all have. We all have a stunt double out there—that’s everything we browse, everything we buy—that’s built up. I have this vision of these zeros and ones that look like me, stacked all together, and it’s for sale on the market, and I have no control over it. So, this idea of a shadow profile of learning is real, and it’s already happening. If you’re on Khan Academy, you’re storing data there.

Then, that jumps into this idea of a learning operating system, which is integrating everything into a single profile. My question is, how do we deal with this in the six-hour day? What does this look like in the six-hour day? Can you imagine someone out playing with a bunch of buddies on the field—they’re playing Frisbee—but they’re learning something along the way? Do you want ambient AI, this learning operating system, to be tracking that and saying, “Hey, Mason, you just actually solved the challenge between two of your friends who were about to fight over a Frisbee. Ding, ding, ding.” And there’s a little alarm that goes off somewhere, and you get some points. How far do we want to take this, Mason?

Mason Pashia: Whew. That is a big question. In my past life in marketing, I got really close to those shadow profiles. So, that’s not quite a zero-one example of Nate, but I could probably tell you more about you than you gave me based on a shadow profile. I’m really torn. I think there are two versions of this: one that actually fits more into what we’ve historically described as assessment as a way of seeing the shadow, and one that leans more into the surveillance version.

The first one—I’m really bullish that I think a lot of the first touches going forward with admissions, employment, etc., is actually going to be a simulation rather than a person. You’re going to say, “I want this job,” apply, and that’s going to prompt a simulation-type experience where you have to demonstrate capability in a scenario. I think people designing those simulations will be able to do that in a way that captures a pretty well-rounded view of some of your durable skills and abilities. Through that, it might scaffold some evidence onto your readout at the end. Maybe it says something like, “You were really good under pressure in that. Tell me about something that made you feel like you’re good under pressure.” I think we’re going to come up with new ways to do collaborative storytelling with some of these AI tools that actually make it easier to tell your story, rather than harder.

The surveillance version—I keep thinking of the early Google Glass days. I can imagine there being a combination that’s less like a satellite watching you from above and more like a biometric wearable that’s doing low-frame-rate capturing of your life and monitoring biometric data at the same time. It might say, “Oh, that was an exciting moment you just had. Reflect on it.” So, I think there will be a way to embed data capture in life that’s non-obstructive and doesn’t ruin the moment you’re having. But I think a lot of people are going to opt out of that system, and I’m worried about who that harms in the long term. We have a lot of these issues already. Not to make it overtly political, but there are conversations about surveillance for safety. Communities that don’t want surveillance are often the most historically excluded communities. If the way these tools roll out feels more like surveillance, I think a lot of them are going to opt out, and that will harm them in any chances of economic mobility or communicating what they can and can’t do. The challenge gets additionally sticky beyond what’s possible into how we make it accessible and something that everybody benefits from.

Nate McClennen: I think it’s really interesting, and I think we just need to pay attention to it. The idea of ambient AI is going to become more and more prevalent—not just in learning, but across the world we live in. The fact that it showed up in this forecast and came up in our earlier conversation about the six-hour day and what happens during the rest of the day is important. It’s come up over and over—how do we capture this learning ecosystem? You and I have this vision of expanding the learning ecosystem—learning happens everywhere, and that’s really laudable and important. But how do we do this in a way that maintains sovereignty of the data and self-sovereignty for the learner themselves, so they gain the advantages but don’t have the drawbacks of being surveilled all the time?

Mason Pashia: Totally. I think there’s a lot of potential here, but it’s going to require a lot of intentionality. I think the idea of self-sovereignty is key. There has to be user control—certainly user opt-out. Not everybody has to have it. That may be problematic if the entire employability ecosystem works to say, “Hey, you need to do your submission via some learning profile.” But maybe there’s a way to give users control. I’m imagining an on-off switch, right? There’s something like, “Hey, I’m doing this thing right now that might be really important for me to capture this skill. I’m going to go do a job interview quickly, and I’m going to actually record it.” But I control it. Maybe it’s an app on the phone. In the surveillance world, it would be, “I’m turning on surveillance, and I’m turning off surveillance,” but it’s on my device. I’m trying to think of how you get users to control it and still give advantages to those who might really benefit from something like this.

Nate McClennen: Yeah, that’s really interesting. I think there’s something about probably self-sovereignty and user control that’s going to be critical. Certainly, there needs to be an opt-out option, but I also think there’s a way to make it more user-driven. Maybe it’s something like, “I’m going to turn this on because I want to capture this moment or this learning experience.” It could be something as simple as an app or a wearable device that allows you to control when and how data is captured. That way, it’s not something that’s always on or feels intrusive.

Mason Pashia: Yeah, I think there are some early examples of this kind of thing. For instance, back when Facebook was more widely used, people would check in at locations to remind themselves where they’d been. That was a voluntary way of mapping your experiences. Similarly, we already create a paper trail with things like ticketed events or flights. If you have your Apple Wallet, you’ve got a record of flights, ticket stubs, and other experiences. Maybe there’s a way to interface with those kinds of systems to create a learning profile that’s more voluntary and user-driven. It could be something like, “Tell me about this experience. Who were you with? What did you learn?” Over time, those could stack into something meaningful without feeling like constant surveillance.

Nate McClennen: Yeah, I think that’s a great point. It’s about finding a balance between capturing meaningful data and respecting individual privacy. I think we just need to keep paying attention to this space and see how it evolves. The idea of ambient AI is definitely going to be a big part of the conversation moving forward—not just in education, but in many other areas as well.

Day in the Life of an Educator in 2040

Mason Pashia: Let’s shift gears a bit. We’ve been writing this series about imagining different stakeholders of learning in the year 2040. We’ve done a few perspectives from learners, and we’ve got a couple more in the queue from a bunch of different perspectives. But we recently published one on A Day in the Life of an Educator in 2040. This was kind of a culminating resource after our recent work with Ed3 DAO, a great organization we’ve been working with on a project called Portrait of a Teacher in the Age of AI. It’s been a really fun project. It’s let us get under the hood of what the teacher competencies of today are, who’s defining them, and what the teacher competencies of tomorrow might look like. We’ve also explored what AI is doing in between. Then, we put it all together and tried to make an assessment about what the actual role of a teacher will be going forward.

We’ve had a lot of fun with this. Check out the article if you want a first-person account from 2040. We did not travel to 2040—just a full disclaimer! But we looked at a couple of different things. We looked at competencies and skills that were represented in these frameworks. We looked at roles and responsibilities that tended to be captured within the job description of modern-day educators. It was a really compelling look at which of these things are going to hold constant, which of them are going to get less important as AI enters the picture, and which of them are going to become doubly important for humans to spend time on and get really skilled in. Honestly, it’s similar to what you were talking about earlier with relational intelligence—that would be an interesting example to throw into the pot for what people need to be good at.

Nate McClennen: Yeah, I mean, I think the idea that we settled on—this idea of machine emphasis versus human emphasis—was really interesting. As we started thinking about what the future of education looks like, we were modeling it off Horizon 3 or a transformational model. We asked, “Where would machines play a bigger role?” In this case, AI is the machine we were thinking about. And, “Where would humans play an important role?” Some of the stuff was as we predicted—things like lesson planning, learning experience design, and assessment are all going to become more and more machine-driven. Then, things that involve relationships will become more and more human-driven, especially things that are real-world experiences—going back to the six hours of the rest of the day kind of thing.

It was fun to break it down in relation to the existing competencies and skills that describe teachers in various frameworks from around the world, as well as the roles and responsibilities we pulled out from job descriptions. I think the end result, over the course of the next six months, will be producing something that’s a useful tool for anybody who’s thinking about what skills a teacher should know in the present and moving forward over the next five to 10 years as AI becomes more and more ubiquitous.

The other thing it made me think about—and I need someone to push back on me for this, so if there’s a listener out there who thinks I’m totally off base, let me know—is that I still think we have a sparse landscape in education schools. These are the undergraduate programs for those who want to become teachers. How are those programs adapting to an age of AI that’s emerging? Not only an age of AI, but an age of AI and a transformational model. Let’s say both of those things hold true—some of this learner studio work that’s been talking about what a transformational model in the age of AI looks like. I think because universities work really, really slowly to change coursework—they’re not super nimble places—the programs of study are actually preparing young people for an expiring vision of what education could be. It doesn’t mean it’s going to go away. Things like classroom management, teaching literacy, and teaching math are still going to be important skills and basic pedagogy of a classroom. But I think we need a big redesign.

We’re seeing a little bit of this in graduate schools. High Tech High’s graduate school is doing some work on AI for tomorrow’s teachers. Two Revolutions has a graduate program now in competency-based education. USC Rossier has a master’s in AI and learning design. So, there are some things out there, but they’re typically at the master’s level. What I’m really interested in is, who is going to be the first undergraduate education program—beyond the relays, High Tech Highs, ASUs, and ISTEs—that will fundamentally redesign? Just like we’re redesigning K-12, who’s going to do that in education schools at one of these big universities that serves tons and tons of teachers every year? Because right now, I think we may be doing a disservice.

Mason Pashia: Totally agree.

Nate McClennen: That’s my takeaway from this. I hope schools of education are looking at this resource once it’s built and doing some mirror-looking, saying, “We need to do some redesign.”

Mason Pashia: Yeah, that makes a lot of sense. I think the other takeaway—because it never hurts to say it—is that after doing this, it reaffirmed our assumptions that teachers do a lot. They’re asked to do a lot of different things, and I think that’s, in some ways, proof that it will not be—not that people are trying to replace teachers—but it would not even be easy to replace teachers. So many of their roles and responsibilities are multifaceted, varied, incredibly human, and incredibly technical. They’re all over the map, and they usually ask for a lot of them at the same time. This work really illustrated that we ask a lot of our educators. So, for all of our educators listening, thank you very much.

Nate McClennen: Yeah, exactly. It is a lot to help a human being grow and develop. I agree with you completely. That was a ton of stuff here. I’d love to start doing some school shout-outs. We often do examples of schools, but I want to add a section on just specific schools. For those listeners out there, if you have something worth highlighting and we haven’t done it yet on Getting Smart, or you want a shout-out on the show, please let us know. We’re really thinking about schools that are pushing new learning models with really good results and thinking deeply about human learning and what it looks like.

School Shout-Out: University Charter School

Nate McClennen: The one I want to talk about today really quickly is down in Livingston, Alabama—University Charter School. I’ve been involved with them since they started. They’ve been around for five, six, seven years now. I was involved with them before they even started. They’re a combination of really strong academics—because it’s an area where Alabama has a challenge with literacy and math scores—and they really defeated that challenge and said, “We’re going to actually change the paradigm here.” So, they’ve done that. They’re a school that focuses on connecting learners to local places. They’re a place-based school, which is how I got connected with them.

They’ve been doing this internally, and they’ve started, over the last two years, something called the UPrep program. Now, they’re trying to impact the schools that are surrounding them and broader in Alabama. I really applaud this idea of scaling. Once you have a model that works, you can impact more than just your own students. It’s hard work, and that’s why we put it in our framework—there’s a scaling section in our framework—because we think that when you have something that works, it should be scaled and more people should look at it. In fact, the schools they worked with—the vast majority of schools that did this two-year cycle—their outcomes improved as well, which is really interesting to see in this preliminary data.

So, kudos to schools out there who have not only focused inward and done great work to create transformational experiences but also focused outward to share with others who are also in need to increase access to great models. University Charter School, Livingston, Alabama.

Mason Pashia: That’s amazing. Great shout-out.

Uniquely Human Experiences and Closing

Nate McClennen: All right, let’s close with some humanness. Mason, what’s been uniquely human for you lately?

Mason Pashia: Well, I’ve been kind of vaguely house hunting lately, so I’ve been going to a lot of open houses and touring houses. It’s a really interesting reminder of just the footprints of humans—the marks we leave along the way. You go into a house, and in the basement, in this weird corner, there’s the classic height marking of the family that lived there before you. Or, in Seattle, where property is quite expensive, the plots are often smaller, and that makes people get really creative with how they do their yards. There will be these super weird parts of a yard that you can tell someone made just so they could bring a chair out and sit there. It’s really lovely to see the oddities and intricacies of being human through the lens of a house—not necessarily through encountering the people themselves.

Nate McClennen: Yeah, like the shadows of the past in some ways that are still there. When we moved, we took the sideboard that had all the height markings on it so we could bring it to our new house. In the house I grew up in, which was an old New England farmhouse in Massachusetts, there was an old well in the corner of the kitchen. I didn’t even know it existed when I was growing up because my dad had built cabinets around it. But when my parents sold the house, the new owners thought it was really interesting. They put a plexiglass covering over it as part of their counter, added a light at the bottom of the well, and you could turn on a little switch to look all the way down this old stone well. It was super clever and interesting. When I went back to visit the house, I was like, “What’s this?” My dad said, “Yeah, that’s been there the whole time. I just covered it up with cabinets.” It’s amazing to see those kinds of footprints.

Mason Pashia: Wow, that’s such a cool story. It’s like a hidden piece of history brought back to life.

Nate McClennen: Yeah, it made me think about how we leave these marks—these footprints—that aren’t necessarily physical footprints but are still meaningful. My last one, just to finish this off before we get to the music, is a story from when I was traveling a couple of weeks ago. I was helping someone whose shoulders weren’t working right. After I got off the plane, I went to sit down at one of those tables, and an elderly woman came over and sat down with a big plate of fries and a hamburger. I was just working on my computer, and she looks up and says, “Hey, do you want some of my french fries? I just had way too many.” It was just this idea of sharing with a stranger—this random act of kindness. It made me smile and think, “If everybody did these little random acts of kindness, the world would slowly and steadily become better.”

Mason Pashia: Totally. I’m looking forward to the next wearable technology that makes those kinds of interactions easier rather than harder. I feel like if I have headphones in at the airport, I miss 20% of the opportunities to help people or connect with them. I’m looking forward to some sort of transparency that lets me be more a part of the world rather than apart from it.

Nate McClennen: Yeah, and then you can click on your ambient AI device and say, “Oh look, I offered french fries to someone,” and your compassion index goes up. Then you get points, and those points go into your digital wallet, and then you can…

Mason Pashia: And then everyone’s way nicer because they know they get points for it. Peloton for kindness?

Nate McClennen: Peloton for kindness—exactly. All right, maybe not in our lifetime. Let’s finish with some music. Mason, what do you have for me?

What’s That Song?

Mason Pashia: I’ve got a song for you. Get ready. Here we go.

Another day, another lesson,
The teacher drones on, a fight digression,
Keys apart, dream all day,
Dreams all clean, I gotta focus to stay.

Catching up, catching up is all I ever do,
Catching up, catching up to something shiny.

Books stacked high, reaching the sky,
Each page a challenge, I can’t deny,
Equations dancing in a dizzy haze,
Lost in the modern learning maze.

Catching up, catching up is all I ever do,
Catching up, catching up to something shiny.

Nate McClennen: Oh my gosh, that’s a really good one.

Mason Pashia: It’s pretty great. That chorus has been stuck in my head for days.

Nate McClennen: Catching up. Oh man, that is outstanding. The influence of that one—I could imagine a smoky bar with someone singing at the front of the room. Like a 1920s jazz club vibe.

Mason Pashia: Yeah, but it’s got a pop part to it too. I used lo-fi groove and specified the lead instrument as harpsichord. That jangly sound is kind of hip. Anybody else who wants to use harpsichord as a lead instrument—do it. But that transition into the chorus is so Billie Eilish, and all of the phrasing is very Ariana Grande. It’s like…

Nate McClennen: It’s pulling from what’s popular out there and aggregating it into what you think is a novel creation, but it’s really an aggregation of the most famous elements.

Mason Pashia: Exactly. And then they’re like, “But we didn’t actually train on any real artists, so…”

Nate McClennen: Right, right. It’s wild. Anyway, great episode today, Mason. Always good to catch up and great to see you.

Mason Pashia: Great to see you too, Nate. Until next time.

Nate McClennen: Until next time.

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Links

• Watch the full video here
• What happens when AI chatbots replace real human connection?
• American Friendship Project
• Boosties
• Tylenol, Autism and the Perils of Basic-Level Literacy
• 7 insights about Chronic Absenteeism
• Transcend: The Relationship Between Student Experiences and Outcomes
• COVID Worsened Long Decline in 12th-Graders’ Reading, Math Skills
• A Day in the Life of an Educator 2040
• USC Rossier Master of Education
• Ambient AI GSV Publication
• Boosties Press Release