Gaming as the Future of Education with Duolingo CEO Luis von Ahn

**Sarah** (0:05)
Hi, listeners, and welcome back to No Priors. Today, we're joined by Luis von Ahn. Luis earned his PhD in Computer Science from Carnegie Mellon, and went on to found ReCAPTCHA, which was acquired by Google in 2009 He's now the co-founder and CEO of Duolingo, the world's most popular education app, with over 116 million monthly users, a market cap of 17 billion, and an owl mascot that faked its own death. We're going to talk about AI for Education, why motivation is the hardest problem in learning, taking risks with your company brand, why vibe cartooning is important, and the 16,000 A-B tests that got us here. Luis, thank you so much for doing this.

**Luis von Ahn** (0:41)
Thank you for having me.

**Sarah** (0:42)
Lots of people know what Duolingo is, but I would love to hear you describe it, and in terms of, you know, beyond the language learning app it is today, what you want it to become.

**Luis von Ahn** (0:52)
Well, it's a language learning app. It's the most popular way to learn languages in the world. As of the last couple of years, we also teach math and music, and as of very soon, we will also teach chess. The idea is, you know, we're trying to be an app where you can go there and learn the things that a lot of people want to learn, but that also take a long time to learn.

**Sarah** (1:14)
You were a professor when you started Duolingo in 2011 I hope it is not offensive to say that, like, lots of professors start companies, a few of them start, like, gamified consumer companies. How did this happen?

**Luis von Ahn** (1:28)
It's not like I expected to start a gamified company. The way we got started is, I was a professor. I had a PhD student named Severin, who is now the CTO and was a co-founder, but we were looking for a PhD thesis topic for him. And what we agreed on is we were going to work on something related to education, where computers would teach you something. After a while, we agreed that a good topic to teach was languages, in particular because of learning English. In most countries in the world, knowledge of English increases your income potential. And there's like 2 billion people in the world learning English. So we thought, okay, well, let's teach languages, and let's teach them with a computer. And then we started working on it, and we ran into this problem. So I made the first Spanish course because I'm a native Spanish speaker. And Severin is a native German speaker, and he made the first German course. And we agreed that we were going to learn each other's language. The problem that we ran into is that we couldn't get ourselves to do it because it was so boring. I'm like, oh my god, I did not want to learn German. He did not want to learn Spanish. We were very worried because we're like, okay, well, if we ourselves can't get it, you know, we can't get ourselves to do it, then we can't expect anybody else to do it. The solution was to turn it into a game as much as possible. And so by the time we launched, it was pretty fun.
But it's mainly because we were trying to get ourselves to do it. And part of the reason that was the case is neither of us likes learning languages. We actually are not language lovers. We don't like learning languages. And I think because of that, we made a product that works for the average person, as opposed to for people who are obsessed with learning languages.

**Sarah** (3:09)
So much there I would like to unpack, but I want to go back to just initial confusion. What makes this a good PhD topic? What was the computer science problem you were interested in?

**Luis von Ahn** (3:19)
The computer science problem was basically trying to teach things to people.

**Sarah** (3:25)
Is that a computer science problem?

**Luis von Ahn** (3:27)
Well, how to get computers to do it. There's a lot there, how to do adaptive, how to use the data to adapt to the student. There's also motivation problems in human-computer interaction. So there was a lot there that we could have used. And by the way, also, at the time, this was, AI at the time was just starting to get to the point where we could have thought about training models, too. And this is not large language models. This is just training classifiers to kind of teach better or something like that. So there's a lot there that could have been a PhD thesis topic.