Our 'Biases' About AI

At the outset of an AI-themed season, Diane Tavenner and I take stock of our prior assumptions, hopes, and concerns about the technology’s applications in education. We dive into where we see it being used to make adjustments to the current educational model and envision how it could be applied to revolutionize learning.

Diane Tavenner: Hey, Michael.

Michael Horn: Hey, Diane. Good to see you.

Diane Tavenner: You too. I spent the weekend on a tradition I think we have talked about before, which is we hold a holiday party every year for what are now old friends. Because I think this is our 27th annual, if you.

Michael Horn: 27th annual. Wow.

Diane Tavenner: Yeah. And it just, it makes me appreciate longevity and just like I have such gratitude for deep, long relationships that have built over time. And yeah, it’s just really, it’s a good fill-me-up for the moment.

Diane and Michael’s AI Priors

Michael Horn: Yeah. That’s amazing. We’re obviously recording this as we approach the holiday season, if people can’t figure that out from that intro. That’s an amazing place to start. And the gratitude you have around that, Diane. So very, very neat. Let’s lay out what we’re doing for folks today. And as we get into a little series on the topic that we talked about in the first episode back, which is artificial intelligence. You want to lay it out, Diane, what we’re thinking?

Diane Tavenner: Yeah, I think as folks know, like, we are now following our curiosity and we’ve been doing that for a while. And, you know, I don’t think either of us are just like 100% all in on AI, like huge evangelists. And I do think that we’re at a minimum, cautiously optimistic about the possibilities of it. And so we’re just curious about it. And I think we find ourselves kind of talking about it and asking about it. And so we are going to do a little exploration. We’re not exactly sure. We’ve got some ideas of the format and whatnot. We’re not exactly sure how long it will last for, but we thought we’d just kick off today with where we’re starting that exploration. And I think I, personally, I think you’re with me. I hope I end in a different place, quite frankly, I hope I end in a place where I’ve, like, learned some stuff and talked to interesting people and, you know, maybe think a little bit differently. Hopefully smarter than I am now. But today we wanted to just kind of lay a foundation of where we’re coming from based on what we know so far.

Michael Horn: Yeah, love, love that intro. And what I would add is it’s obviously a hot topic in education. Everyone knows that. But I think what’s also interesting to me anyway has been how OpenAI and Google and, you know, Facebook, like, or Meta, I should say, whenever they talk about AI, they seem to show education use cases is like a major part of all their launches. I’m sure that’s not quite right, but it’s more than I can remember on most product launches outside of maybe the iPad over the last 20 years. And so it’s obviously getting a lot… Education and AI together, Diane, are obviously getting a lot of attention and I find myself anyway, and we’ll talk about this in a moment: I start out with a strong prior and then I read a couple things and I completely flip my opinion and then I have that opinion and I talk to someone and then I change again. And so like I find myself pretty malleable still. But like you, it feels like this technology enabler that could be really, really intriguing. And we need to explore more.

Diane Tavenner: I agree with you and I think we’ll do that in a way that we always do. We’re always looking for sort of third-way solutions that are very practical and very pragmatic and very connected to what’s actually happening with young people in schools, with teachers. And so yeah, I think that, you know, people might be like thinking, oh my gosh, more AI. But I hope that we’re going to bring a, a sort of pragmatic approach to it that that is actually useful for people.

The Teacher- v. Student-Centered Approach to AI

Michael Horn: Yeah, no, perfect. And I will tell you, when you visited my class and showed off Futre with the students, they noted that you never mentioned AI in your talk. So we are certainly not leading with AI, but we think it’s intriguing. And so against that let me start out with the opening framing I’d love to propose to you and then you can sort of react to how that framing sits. But it’s one that I’m stealing from a friend of ours in the venture world. And it’s something though that I’m noticing in the field and I don’t know that everyone who sort of is launching AI education products notices it this way. But what I’m seeing is that there’s sort of on the one hand a lot of AI startups and AI approaches that are very teacher centered or teacher facing as their entree, if you will, into the classroom or learning environments. And then on the other hand you have the student centered or student facing applications. This might be like the Khanmigo or, you know, some of those things that we’ve seen out there. And so there seems to me to be a bit of a dichotomy in terms of the startup space, the investors approach, different entrepreneurial approaches, even teacher, frankly and school designer and educator approaches on how they’re thinking about AI. Is it first a teacher tool or is it a student facing tool. What, what’s your take on that framing before we dig into each side of this?

Diane Tavenner: Yeah, so I think that sadly, and I will say sadly for me, I think most people are thinking about it from a teacher-facing approach.