Duolingo: The Next Chapter in Human Computation by Luis von Ahn (Full Transcript)

Here is the full transcript of computer scientist Luis von Ahn’s TEDx Talk titled “Duolingo: The Next Chapter in Human Computation” at TEDxCMU 2011 event.

Full speaker bio: Luis von Ahn


MP3 Audio:


Right click to download the MP3 audio:
Download Audio

YouTube Video:



Luis von Ahn – Computer scientist

OK, so I want to start by asking you guys a question: How many of you have had to fill out some sort of web form or even has to read a distorted sequence of characters like this? How many of you found it really, really annoying? OK, I understand. I invented that.

Or, I was one of the people who did it. That thing is called a captcha. And the reason it’s there is to make sure that you or the entity filling out the form, are actually a human, and not some sort of a computer program that was written to submit the form millions and millions of times. The reason it works is because humans, at least, non-visually-impaired humans, have no trouble reading these distorted characters, whereas computer programs simply can’t do it as well yet. For example, in the case of Ticket Master the reason you have to type these distorted characters is to prevent scalpers from writing a program that can buy millions of ticket at a time.

Now captchas are used all over the Internet and since they are used so often a lot of times the precise sequence of random characters that are shown to the user is not so fortunate. So this is an example from the Yahoo registration page. Random characters that happen to be shown to the user were W, A, I, T, which of course spell a word. But the best part is the message that the Yahoo Help got about 20 minutes later. [“Help! I’ve been waiting for 20 minutes, and nothing happens!”] The person thought — this of course is not as bad as this poor person who… [R E S T A R T].

OK, now, this captcha project is something that we did here at Carnegie Mellon about ten years ago and it’s been used everywhere. Let me now tell you about a project that we did a few years later, which is sort of the next evolution of captchas. This is the project that we called Recaptcha, which is something that we started here at Carnegie Melon, then we turned it into a startup company, and then about a year and a half ago Google actually acquired this company. So, let me tell you what this project started.

So this project started from the following realization: it turns out that approximately 200 million captchas are typed every day by people around the world. When I first heard this I was quite proud of myself I thought, “Look at the impact that my research has had.” But then I started feeling bad, so here is the thing: each time you type a captcha, essentially, you waste ten seconds of your time. Because it takes ten seconds to type a captcha — and if you multiply that by 200 million you get that humanity as a whole is wasting about 500 thousand hours every day typing these annoying captchas.

ALSO READ:   Transcript: John Green on Paper Towns at TEDxIndianapolis

So then I started feeling bad, and then I started thinking, well, of course we can’t just get rid of captchas, because the security of the Web sort of depends on them. But then I started thinking, “Is there any way we can use this effort for something that is good for humanity?” so here is the thing, while you’re typing a captcha, during those ten seconds, your brain is doing something amazing. Your brain is doing something that computers cannot yet do. So, can we get you to do useful work for those ten seconds?

Another way of putting it is: Is there some humongous problem that we cannot get yet computers to solve, that somehow we can split into tiny ten second chunks such that each time somebody solves a captcha they solve a little bit of this problem? And the answer to that is yes, and this is what we are doing now. So what you may not know is that nowadays, while you’re typing a captcha not only are you authenticating yourself as a human but in addition you are actually helping us to digitize books. Let me explain how it works.

There is a lot of projects out there trying to digitize books. Google has one, the Internet Archive has one, Amazon, with the Kindle, is trying to digitize books. Basically the way this works is, you start with an old book, like a physical thing, you’ve seen those things right? Like a… book.

So, you start with a book, and then you scan it. Now scanning a book is like taking a digital photograph of every page of the book. It gives you an image for every page of the book. This is an image with text for every page of the book. The next step in the process is that the computer needs to be able to decipher all of the words in this image. That is done using a technology called OCR, Optical Character Recognition, which takes a picture of text and tries to figure out what text is in there.

ALSO READ:   Courtney Griffins: Epigenetics and The Influence of Our Genes at TEDxOU (Transcript)

Now, the problem is that OCR is not perfect, especially for older books, where the ink has faded, and the pages have turned yellow, OCR cannot recognize a lot of the words. For example, the things that were written more than 50 years ago, the computer cannot recognize about 30% of the words. So what we are doing now is we are taking all of the words that the computer cannot recognize and we are getting people to read them for us, while they are typing a captcha on the Internet. So next time you type a captcha, these words that you’re typing are actually words that are coming from books that are being digitized that the computer could not recognize.

Now the reason we have two words nowadays instead of one, is because, you see, one of the words is a word that the system just got out of a book, it didn’t know what it was and it’s going to present it to you, but since it doesn’t know the answer for it, it cannot grade it for you. So what we do is we give you another word, one for which the system does know the answer, we don’t tell you which one is which, and we say, please type both. And if you type the correct word for the one which the system already knows the answer, it assumes you are a human, and it also gets some confidence that you typed the other word correctly. And if we repeat this process to like 10 different people, and all of them agree on what the new word is, then we get one more word digitized accurately. So this is how the system works.

And basically since we released it about three or four years ago, a lot of websites started switching from the old captcha, where people wasted their time, to the new captcha, where people are helping to digitize books. So, for example, Ticket Master, so every time you buy tickets on Ticket Master, you help to digitize a book. Facebook, every time you add a friend, or poke somebody, you help digitize a book. Twitter, and about 350,000 other sites are all using recaptcha. And in fact, the number of sites that are using recaptcha is so high that the number of words that we’re digitizing per day is really, really large. It’s about 100 million a day which is the equivalent of about 2.5 million books a year. And this is all being done one word at a time by just people typing captchas on the Internet.