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(Laughter) That’s how it works. There are tens of thousands of these. 7:11 8:14 9:05 8:94 9:37 10:19 So this is the favorite thing that I like about this whole project. This is the number of distinct people that have helped us digitize at least one word out of a book through reCAPTCHA: 750 million, which is a little over 10 percent of the world’s population, has helped us digitize human knowledge. And it is numbers like these that motivate my research agenda. So the question that motivates my research is the following: If you look at humanity’s large-scale achievements, these really big things that humanity has gotten together and done historically—like for example, building the pyramids of Egypt or the Panama Canal or putting a man on the Moon—there is a curious fact about them, and it is that they were all done with about the same number off people. It’s weird; they were all done with about 100,000 people. And the reason for that is because, before the Internet, coordinating more than 100,000 people, let alone paying them, was essentially impossible. But now with the Internet, I’ve just shown you a project where we’ve gotten 750 million people to help us digitize human knowledge. So the question that motivates my research is, if we can put a man on the Moon with 100,000, what can we do with 100 million? So based on this question, we’ve had a lot of different projects that we’ve been working on. Let me tell you about one that I’m most excited about. This is something that we’ve been semi-quietly working on for the last year and a half or so. It hasn’t yet been launched. It’s called Duolingo. Since it hasn’t been launched, shhhhh! (Laughter) Yeah, I can trust you’ll do that. So this is the project. Here’s how it started. It started with me posing a question to my graduate student, Severin Hacker. By the way, you did hear me correctly; his last name is Hacker. So I posed this question to him: How can we get 100 million people translating the Web into every major language for free? Okay, so there’s a lot of things to say about this question. First of all, translating the Web. So right now the Web is partitioned into multiple languages. A large fraction of it is in English. If you don’t know any English, you can’t access it. But there’s large fractions in other different languages, and if you don’t know those languages, you can’t access it. So I would like to translate all of the Web, or at least most of the Web, into every major language. Now some of you may say, why can’t we use computers to translate? Why can’t we use machine translation? Machine translation nowadays is starting to translate some sentences here and there. Why can’t we use it to translate the whole Web? Well the problem with that is that it’s not yet good enough and it probably won’t be for the next 15 to 20 years. It makes a lot of mistakes. Even when it doesn’t make a mistake, since it makes so many mistakes, you don’t know whether to trust it or not. So we need people to translate the whole Web. So now the next question you may have is, well why can’t we just pay people to do this? We could pay professional language translators to translate the whole Web. We could do that. Unfortunately, it would be extremely expensive. For example, translating a tiny, tiny fraction of the whole Web, Wikipedia, into one other language, Spanish. Wikipedia exists in Spanish, but it’s very small compared to the size of English. It’s about 20 percent of the size of English. If we wanted to translate the other 80 percent into Spanish, it would cost at least 50 million dollars—and this is at even the most exploited, outsourcing country out there. So it would be very expensive. So what we want to do is we want to get 100 million people translating the Web into every major language for free. Now if this is what you want to do, you pretty quickly realize you’re going to run into two pretty big hurdles, two big obstacles. The first one is a lack of bilinguals. So I don’t even know if there exists 100 million people out there using the Web who are bilingual enough to help us translate. That’s a big problem. The other problem you’re going to run into is a lack of motivation. How are we going to motivate people to actually translate the Web for free? Normally, you have to pay people to do this. So how are we going to motivate them to do it for free? Now when we were starting to think about this, we were blocked by these two things. But then we realized, there’s actually a way to solve both these problems with the same solution. There’s a way to kill two birds with one stone. And that is to transform language translation into something that millions of people want to do, and that also helps with the problem of lack of bilinguals, and that is language education.
11:09 12:01 12:30 13:13 13:84 14:41 15:09 So it turns out that today, there are over 1.2 billion people learning a foreign language. People really, really want to learn a foreign language. And it’s not just because they’re being forced to do so in school. For example, in the United States alone, there are over five million people who have paid over $500 for software to learn a new language. So people really, really want to learn a new language. So what we’ve been working on for the last year and a half is a new website—it’s called Duolingo—where the basic idea is people learn a new language for free while simultaneously translating the Web. So basically they’re learning by doing. The way this works is whenever you’re a just a beginner, we give you very, very simple sentences. There’s, of course, a lot of very simple sentences on the Web. We give you very, very simple sentences along with what each word means. And as you translate them, and as you see how other people translate them, you start learning the language. And as you get more and more advanced, we give you more and more complex sentences to translate. But at all times, you’re learning by doing. Now the crazy thing about this method is that it actually really works. First of all, people are really, really learning a language. We’re mostly done building it, and now we’re testing it. People really can learn a language with it. And they learn it about as well as the leading language learning software. So people really do learn a language. And not only do they learn it as well, but actually it’s way more interesting. Because you see with Duolingo, people are actually learning with real content. As opposed to learning with made-up sentences, people are learning with real content, which is inherently interesting. So people really do learn a language. But perhaps more surprisingly, the translations that we get from people using the site, even though they’re just beginners, the translations that we get are as accurate as those of professional language translators, which is very surprising. Now of course, we play a trick to make the translations as good as professional language translators. We combine the translations of multiple beginners to get the quality of a single professional translator. Now even though we’re combining the translations, the site actually can translate pretty fast. So let me show you, this is our estimates of how fast we could translate Wikipedia from English into Spanish. Remember, this is 50 million dollarsworth of value. So if we wanted to translate Wikipedia into Spanish, we could do it in five weeks with 100,000 active users. And we could do it in about 80 hours with a million active users. Since all the projects that my group has worked on so far have gotten millions of users, we’re hopeful that we’ll be able to translate extremely fast with this project. Now the thing that I’m most excited about with Duolingo is I think this provides a fair business model for language education. So here’s the thing: The current business model for language education is the student pays, and in particular, the student pays Rosetta Stone 500 dollars. (Laughter) That’s the current business model. The problem with this business model is that 95 percent of the world’s population doesn’t have 500 dollars. So it’s extremely unfair towards the poor. This is totally biased towards the rich. Now see, in Duolingo, because while you learn you’re actually creating value, you’re translating stuff—which for example, we could charge somebody for translations. So this is how we could monetize this. Since people are creating value while they’re learning, they don’t have to pay their money, they pay with their time. But the magical thing here is that they’re paying with their time, but that is time that would have had to have been spent anyways learning the language. So the nice thing about Duolingo is I think it provides a fair business model—one that doesn’t discriminate against poor people. So here’s the site. Thank you. (Applause) We haven’t yet launched, but if you go there, you can sign up to be part of our private beta, which is probably going to start in about three or four weeks. By the way, I’m the one talking here, but actually Duolingo is the work of a really awesome team, some of whom are here. ” Thank you. (Applause) MASSIVE-SCALE ONLINE COLLABORATION 7
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