Adonis Diaries

Archive for April 8th, 2017

Online collaboration: How is it when getting massive?

CAPTCHA, reCAPTCHA, CAPTCHAart, Duolingo, optical character recognition

How can we get 100 million people translating the Web into every major language for free?

How many of you had to fill out some sort of web form where you’ve been asked to read a distorted sequence of characters like this?

How many of you found it really, really annoying? Okay, outstanding. So I invented that. (Laughter) Or I was one of the people who did it.

0:24 That thing is called a CAPTCHA. And the reason is to make sure you, the entity filling out the form, are actually a human and not some sort of 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 squiggly characters, whereas computer programs simply can’t do it as well yet.

So for example, in the case of Ticketmaster, the reason you have to type these distorted characters is to prevent scalpers from writing a program that can buy millions of tickets, two at a time.

CAPTCHAs are used all over the Internet. And since they’re used so often, a lot of times the precise sequence of random characters that is shown to the user is not so fortunate.

So this is an example from the Yahoo registration page. The random characters that happened 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 desk got about 20 minutes later. Text: “Help! I’ve been waiting for over 20 minutes, and nothing happens.” (Laughter) This person thought they needed to wait. This of course, is not as bad as this poor person.

CAPTCHA Project is something that we did here at Carnegie Melllon over 10 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 CAPTCHA.

This is a project that we call reCAPTCHA, which is something that we started here at Carnegie Mellon, then we turned it into a startup company. And then about a year and a half ago, Google actually acquired this company.

 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 everyday 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. See here’s the thing, each time you type a CAPTCHA, essentially you waste 10 seconds of your time. And if you multiply that by 200 million, you get that humanity as a whole is wasting about 500,000 hours every day typing these annoying CAPTCHAs. 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?

While you’re typing a CAPTCHA, during those 10 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 10 seconds?

Another way of putting it: is there some humongous problem that we cannot yet get computers to solve, yet we can split into tiny 10-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’re doing now.

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’re actually helping us to digitize books.

 there’s a lot of projects out there trying to digitize books. Google has one. The Internet Archive has one. Amazon, now with the Kindle, is trying to digitize books. Basically the way this works is you start with an old book. You’ve seen those things, right? Like a book? (Laughter) So you start with a book, and then you scan it.

 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’s using a technology called OCR, for optical character recognition, which takes a picture of text and tries to figure out what text is in there. 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, for things that were written more than 50 years ago, the computer cannot recognize about 30 percent of the words. So what we’re doing now is we’re taking all of the words that the computer cannot recognize and we’re getting people to read them for us while they’re typing a CAPTCHA on the Internet.

the 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. And 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’s which, and we say, please type both. And if you type the correct word for the one for which the system already knows the answer, it assumes you are 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.

this is how the system works. And basically, since we released it about three or four years ago, a lot of websites have 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, Ticketmaster.  Everytime you buy tickets on Ticketmaster, you help to digitize a book. Facebook: Every time you add a friend or poke somebody, you help to 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 large. It’s about 100 million a day, which is the equivalent of about two and a half million books a year. And this is all being done one word at a time by just people typing CAPTCHAs on the Internet.

since we’re doing so many words per day, funny things can happen. And this is especially true because now we’re giving people two randomly chosen English words next to each other. So funny things can happen.

For example, we presented this word. It’s the word “Christians”; there’s nothing wrong with it. But if you present it along with another randomly chosen word, bad things can happen. So we get this. (Text: bad christians) But it’s even worse, because the particular website where we showed this actually happened to be called The Embassy of the Kingdom of God. (Laughter) Oops. (Laughter) Here’s another really bad one. (Text: Damn liberal) (Laughter) So we keep on insulting people left and right everyday.

 we’re not just insulting people. See here’s the thing, since we’re presenting two randomly chosen words, interesting things can happen. So this actually has given rise to a really big Internet meme that tens of thousands of people have participated in, which is called CAPTCHA art.

I’m sure some of you have heard about it. Here’s how it works. Imagine you’re using the Internet and you see a CAPTCHA that you think is somewhat peculiar, like this CAPTCHA. (Text: invisible toaster) Then what you’re supposed to do is you take a screen shot of it. Then of course, you fill out the CAPTCHA because you help us digitize a book. But then, first you take a screen shot, and then you draw something that is related to it. (Laughter)

That’s how it works. There are tens of thousands of these. Some of them are very cute. (Text: clenched it) (Laughter) Some of them are funnier. (Text: stoned founders) (Laughter) And some of them, like paleontological shvisle, they contain Snoop Dogg.

 so this is my favorite number of reCAPTCHA. 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% 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, 100,000.

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?

 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. Okay, that’s Severin Hacker.

So I posed the question to my graduate student. 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?

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. So that’s what I would like to do.

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.

let me show you an example of something that was translated with a machine. Actually it was a forum post. It was somebody who was trying to ask a question about JavaScript. It was translated from Japanese into English. So I’ll just let you read.

This person starts apologizing for the fact that it’s translated with a computer. So the next sentence is going to be the preamble to the question. So he’s just explaining something. Remember, it’s a question about JavaScript. (Text: At often, the goat-time install a error is vomit.) (Laughter) Then comes the first part of the question. (Text: How many times like the wind, a pole, and the dragon?) (Laughter)

Then comes my favorite part of the question. (Text: This insult to father’s stones?) (Laughter) And then comes the ending, which is my favorite part of the whole thing. (Text: Please apologize for your stupidity. There are a many thank you.) (Laughter) Okay, so computer translation, not yet good enough. So back to the question.

10:53 So we need people to translate the whole Web.  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.

 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.

12:25 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 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. And so basically they’re learning by doing.

the way this works is whenever you’re a just a beginner, we give you 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.

13:17 Now the crazy thing about this method is that it actually really works.

First of all, people are 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.

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.

So let me show you one example. This is a sentence that was translated from German into English. The top is the German. The middle is an English translation that was done by somebody who was a professional English translator who we paid 20 cents a word for this translation. And the bottom is a translation by users of Duolingo, none of whom knew any German before they started using the site.

You can see, it’s pretty much perfect. Now of course, we play a trick here 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.

 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 dollars-worth 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.

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. 

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.

15:57  So here’s the site. 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. We haven’t yet launched this Duolingo.

16:18 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. So thank you.

“If we can put a man on the Moon with 100,000 people, what can we do with 100 million?” – Luis von Ahn
This question motivated Luis von Ahn and his team to come up with a lot of mega-collaborative projects for greater good, like CAPTCHA/reCAPTCHA and duolingo…
The last ‪#‎TEDTalk‬ screened at last week’s ‪#‎TEDxSKE‬ salon.
‪#‎TED‬ ‪#‎TEDTalks‬ ‪#‎TEDx‬ ‪#‎Salon‬ ‪#‎Collaboration‬ ‪#‎CAPTCHA‬ ‪#‎ReCAPTCHA‬

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After re-purposing CAPTCHA so each human-typed response helps digitize books, Luis von Ahn wondered how else to use small contributions by many on the Internet for greater good. In this talk, he shares how his ambitious new project, Duolingo,…|By Luis von Ahn

Soon, your Privacy is Privatized: To be purchased

In the 1960s, mainframe computers posed a significant technological challenge to common notions of privacy. That’s when the federal government started putting tax returns into those giant machines, and consumer credit bureaus began building databases containing the personal financial information of millions of Americans.

Many people feared that the new computerized databanks would be put in the service of an intrusive corporate or government Big Brother.

 published in NYT this March 23, 2013 under “Big Data Is Opening Doors, but Maybe Too Many”

“It really freaked people out,” says Daniel J. Weitzner, a former senior Internet policy official in the Obama administration. “The people who cared about privacy were every bit as worried as we are now.”

Along with fueling privacy concerns, the mainframes helped prompt the growth and innovation that we have come to associate with the computer age.

Today, many experts predict that the next wave will be driven by technologies that fly under the banner of Big Data — data including Web pages, browsing habits, sensor signals, smartphone location trails and genomic information, combined with clever software to make sense of it all.

Proponents of this new technology say it is allowing us to see and measure things as never before — much as the microscope allowed scientists to examine the mysteries of life at the cellular level.

Big Data, they say, will open the door to making smarter decisions in every field from business and biology to public health and energy conservation.

“This data is a new asset,” says Alex Pentland, a computational social scientist and director of the Human Dynamics Lab at the M.I.T. “You want it to be liquid and to be used.”

But the latest leaps in data collection are raising new concern about infringements on privacy — an issue so crucial that it could trump all others and upset the Big Data bandwagon.

Dr. Pentland is a champion of the Big Data vision and believes the future will be a data-driven society. Yet the surveillance possibilities of the technology, he acknowledges, could leave George Orwell in the dust.

The World Economic Forum published a report late last month that offered one path — one that leans heavily on technology to protect privacy.

The report grew out of a series of workshops on privacy held over the last year, sponsored by the forum and attended by government officials and privacy advocates, as well as business executives.

The corporate members, more than others, shaped the final document.

The report, “Unlocking the Value of Personal Data: From Collection to Usage,” recommends a major shift in the focus of regulation toward restricting the use of data.

Curbs on the use of personal data, combined with new technological options, can give individuals control of their own information, according to the report, while permitting important data assets to flow relatively freely.

“There’s no bad data, only bad uses of data,” (even if false and erroneous?) says Craig Mundie, a senior adviser at Microsoft, who worked on the position paper.

The report contains echoes of earlier times. The Fair Credit Reporting Act, passed in 1970, was the main response to the mainframe privacy challenge. The law permitted the collection of personal financial information by the credit bureaus, but restricted its use mainly to three areas: credit, insurance and employment.

The forum report suggests a future in which all collected data would be tagged with software code that included an individual’s preferences for how his or her data is used.

All uses of data would have to be registered, and there would be penalties for violators.

For example, one violation might be a smartphone application that stored more data than is necessary for a registered service like a smartphone game or a restaurant finder.

The corporate members of the forum say they recognize the need to address privacy concerns if useful data is going to keep flowing.

George C. Halvorson, chief executive of Kaiser Permanente, the large health care provider, extols the benefits of its growing database on 9 million patients, tracking treatments and outcomes to improve care, especially in managing costly chronic and debilitating conditions like heart disease, diabetes and depression.

New smartphone applications, he says, promise further gains — for example, a person with a history of depression whose movement patterns slowed sharply would get a check-in call.

“We’re on the cusp of a golden age of medical science and care delivery,” Mr. Halvorson says. “But a privacy backlash could cripple progress.”

Corporate executives and privacy experts agree that the best way forward combines new rules and technology tools. But some privacy professionals say the approach in the recent forum report puts way too much faith in the tools and too little emphasis on strong rules, particularly in moving away from curbs on data collection.

“We do need use restrictions, but there is a real problem with getting rid of data collection restrictions,” says David C. Vladeck, a professor of law at Georgetown University. “And that’s where they are headed.”

“I don’t buy the argument that all data is innocuous until it’s used improperly,” adds Mr. Vladeck, former director of the Bureau of Consumer Protection at the Federal Trade Commission.

Vladeck offers this example: Imagine spending a few hours looking online for information on deep fat fryers. You could be looking for a gift for a friend or researching a report for cooking school. But to a data miner, tracking your click stream, this hunt could be read as a telltale signal of an unhealthy habit — a data-based prediction that could make its way to a health insurer or potential employer.

Dr. Pentland, an academic adviser to the World Economic Forum’s initiatives on Big Data and personal data, agrees that limitations on data collection still make sense, as long as they are flexible and not a “sledgehammer that risks damaging the public good.”

He is leading a group at the M.I.T. Media Lab that is at the forefront of a number of personal data and privacy programs and real-world experiments. He espouses what he calls “a new deal on data” with three basic tenets: you have the right to possess your data, to control how it is used, and to destroy or distribute it as you see fit.

Personal data, Dr. Pentland says, is like modern money — digital packets that move around the planet, traveling rapidly but needing to be controlled. “You give it to a bank, but there’s only so many things the bank can do with it,” he says.

His M.I.T. group is developing tools for controlling, storing and auditing flows of personal data. Its data store is an open-source version, called openPDS.

In theory, this kind of technology would undermine the role of data brokers and, perhaps, mitigate privacy risks. In the search for a deep fat fryer, for example, an audit trail should detect unauthorized use.

Dr. Pentland’s group is also collaborating with law experts, like Scott L. David of the University of Washington, to develop innovative contract rules for handling and exchanging data that insures privacy and security and minimizes risk.

The M.I.T. team is also working on living lab projects. One that began recently is in the region around Trento, Italy, in cooperation with Telecom Italia and Telefónica, the Spanish mobile carrier.

About 100 young families with young children are participating. The goal is to study how much and what kind of information they share on smartphones with one another, and with social and medical services — and their privacy concerns.

“Like anything new,” Dr. Pentland says, “people make up just-so stories about Big Data, privacy and data sharing,” often based on their existing beliefs and personal bias. “We’re trying to test and learn,” he says.

A version of this article appeared in print on March 24, 2013, on page BU3 of the New York edition with the headline: Big Data Is Opening Doors, But Maybe Too Many.

Should Joan Baez endorse Bernie Sanders?

Pledged my allegiance not to a flag or a nation state but to humankind

 Joan Baez· April 7, 2016 at 7:12am ·

I’ve had conflicting feelings as to whether or not I should officially endorse Bernie Sanders as the Democratic nominee for President of the United States.

I would be making this decision for only the second time in my life.

The first time was for Barack Obama, the master of the spoken word whose brilliance (and smile) brought people together and ignited our spirits for the first time in decades. Aside from endorsing Barack Obama, I have refused to step into the arena of party politics.

My choice, from an early age, has been to engage in social change from the ground up, using the power of organized nonviolence.

A distrust of the political process was firmly in place by the time I was 15. As a daughter of Quakers I pledged my allegiance not to a flag or a nation state but to humankind, the two often having little to do with each other.

Ideally, both Obama and Sanders could have used their unique gifts to build a grass roots movement, sidestepping the Oval Office and going directly to the streets to organize from the sidewalks, street corners, living rooms and churches.

Gandhi himself refused to be part of the newly formed Independent India government after he led the country to independence, and remained committed to nonviolent opposition.

Can a true political revolution ever start from within the party system?

It does seem like an insurmountable contradiction. And to imagine that more than a fraction of Bernie’s agenda could ever come to fruition is probably setting expectations too high.

Yet Bernie has won my heart.

He supports causes in which I have been personally involved for decadesI take great strength from his firm stance against the death penalty, (amazing!) his belief that Palestinians should have a place at the bargaining table, (unheard of!) his understanding that the prison system must transform its agenda from punishment to rehabilitation,

his desire to treat immigrants as human beings, and of course by his grass roots funding and astonishing refusal to sell himself to the devil on Wall Street, or anywhere else for that matter.

I am profoundly moved by this elder statesman, his compelling honesty, and his ability to engage young people.

Why am I not spending my time trying to woo Bernie into grass roots organizing?

For the moment I’m going with my heart, which I mentioned, he has won. I am not sold on “the system” and never will be. I’m sold on the guy from Brooklyn.

I’ve learned a lot while writing this piece. I know that I am ambivalent about supporting someone who will be thrown to the lions if he wins.

He is a lion in his own right, and I want to see him win. Not just to conquer the growing evil in the other party, but also to see what he can do to bend the system towards a less corrupt and more generous country than we are at present.

I joyfully and wholeheartedly endorse Bernie Sanders to be the nominee for the Democratic Party in the 2016 Presidential Election.

-Joan Baez

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How to refresh the listener’s emotions?

Is ignorance the problem?

It’s nice to think that the reason that people don’t do what you need them to do, or conform to your standards, or make good choices is simply that they don’t know enough.

After all, if that’s the case, all you’ll need to do is inform them, loudly and clearly.

So, that employee who shows up late: just let her know that being late isn’t allowed. Threaten to fire her. That’ll do it.

The thing is, ignorance is rarely the problem. (Are we talking about work environment? Technical matters?)

The challenge is that people don’t always care about what you care about.

And the reason they don’t care isn’t that they don’t know what you know.

The reason is that they don’t believe what you believe.

The challenge, then, isn’t to inform them. It’s to engage and teach and communicate in a way that shares emotion and values and beliefs.




April 2017

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