Alexis C. Madrigal

Turns out Twitter is a website after all.

Since shortly after its launch, Twitter had seemed more like a web service. Many users, though certainly not all of them, rarely or never went to Twitter.com, using the service through third-party applications like Tweetdeck and Thwirl on their phones and computers.

But over the last year, the company has been trying to stuff the cats (i.e. users) back into its bag. First, they launched new retweet functionality that worked best on the website. Now, they've revamped Twitter.com in the largest update to the user-facing side of the site in years. In general, the changes help improve the experience, but as Peter Kafka (and others) immediately realized, the revision is likely to change Twitter's business as much as its usage.

Twitter wants to keep you on Twitter.com and the redesign seems shaped around that goal.

For you, the big change is that you can view video and pictures right on the site now. Click on the arrow to the right of a Tweet and the photo or video shows up. The same arrow allows you to find out more about the Tweeter, other people mentioned, and hashtags used. It's an elegant solution to the problem of keeping the site's feel familiar while providing new functionality.

But perhaps the most noticeable thing about the new redesign -- as pointed out by the Times' Jenna Wortham -- is all the blank space in the right toolbar. That looks to me like a great spot for some ads.

How to Think About... is a video series that provides you with quick frames for thinking about the world's blizzard of technologies and services. The idea is simple: imagine we're having a beer and you ask me, "What do you think about X?"

I switch on the camera and respond. These videos are informal, extemporaneous affairs and we hope they feel like the start of a talk. We'd love to hear how you think about these things, too.

It's not easy to map the shape of the changes that technology brings to our minds in real-time. We often start from our own experience of using something -- a car, a phone, a computer -- and spiral outward talking to friends, looking for evidence. Nicholas Carr took exactly this path in charting how he thought the Internet was changing the way we read.

"Over the past few years I've had an uncomfortable sense that someone, or something, has been tinkering with my brain, remapping the neural circuitry, reprogramming the memory. My mind isn't going--so far as I can tell--but it's changing," Carr wrote. "I'm not thinking the way I used to think. I can feel it most strongly when I'm reading. Immersing myself in a book or a lengthy article used to be easy. My mind would get caught up in the narrative or the turns of the argument, and I'd spend hours strolling through long stretches of prose. That's rarely the case anymore."

Noticing his own inability to dig deeply in long articles, he began to wonder what was happening. The article that resulted still receives something like 1,000 visitors a day. Carr's argument style, branching out from anecdote to evidence, has bothered some, but clearly his experience mirrored that of many readers over the last decade.

Carr has drawn some prominent critiques from the likes of Stephen Pinker, who argues that we "shouldn't bemoan technology but... develop strategies of self-control, as we do with every other temptation in life."

You can draw your own conclusions about the importance of the hyperlinked text for your brain, but it's worth checking out some new apps that help you control your reading habits online over on The Toolkit. (Tech taketh away and tech giveth.) 

First though, check out this excerpt of Carr's wonderfully crafted story:

Thanks to the ubiquity of text on the Internet, not to mention the popularity of text-messaging on cell phones, we may well be reading more today than we did in the 1970s or 1980s, when television was our medium of choice. But it's a different kind of reading, and behind it lies a different kind of thinking--perhaps even a new sense of the self. "We are not only what we read," says Maryanne Wolf, a developmental psychologist at Tufts University and the author of Proust and the Squid: The Story and Science of the Reading Brain. "We are how we read." Wolf worries that the style of reading promoted by the Net, a style that puts "efficiency" and "immediacy" above all else, may be weakening our capacity for the kind of deep reading that emerged when an earlier technology, the printing press, made long and complex works of prose commonplace. When we read online, she says, we tend to become "mere decoders of information." Our ability to interpret text, to make the rich mental connections that form when we read deeply and without distraction, remains largely disengaged.

Reading, explains Wolf, is not an instinctive skill for human beings. It's not etched into our genes the way speech is. We have to teach our minds how to translate the symbolic characters we see into the language we understand. And the media or other technologies we use in learning and practicing the craft of reading play an important part in shaping the neural circuits inside our brains. Experiments demonstrate that readers of ideograms, such as the Chinese, develop a mental circuitry for reading that is very different from the circuitry found in those of us whose written language employs an alphabet. The variations extend across many regions of the brain, including those that govern such essential cognitive functions as memory and the interpretation of visual and auditory stimuli. We can expect as well that the circuits woven by our use of the Net will be different from those woven by our reading of books and other printed works.

Sometime in 1882, Friedrich Nietzsche bought a typewriter--a Malling-Hansen Writing Ball, to be precise. His vision was failing, and keeping his eyes focused on a page had become exhausting and painful, often bringing on crushing headaches. He had been forced to curtail his writing, and he feared that he would soon have to give it up. The typewriter rescued him, at least for a time. Once he had mastered touch-typing, he was able to write with his eyes closed, using only the tips of his fingers. Words could once again flow from his mind to the page.

But the machine had a subtler effect on his work. One of Nietzsche's friends, a composer, noticed a change in the style of his writing. His already terse prose had become even tighter, more telegraphic. "Perhaps you will through this instrument even take to a new idiom," the friend wrote in a letter, noting that, in his own work, his "'thoughts' in music and language often depend on the quality of pen and paper."

Read the rest of Carr's "Is Google Making Us Stupid?"

Revisit more pieces from The Atlantic's archives with the Technology Channel.

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The practice of recording the ambient sound of cities has exploded over the last few years. Every one with a smartphone is carrying around a fairly high-quality audio recorder that can upload instantly to the internet. Combined with mapping tools, people have built unprecedented archives of how our cities sound.

Seoul, Barcelona, New York, Madrid, Vancouver, Toronto, Berlin, New Orleans. All these places have active soundscape mapping projects. All over the world, people are walking outside and recording whatever is happening. Then, a different set of people is putting on their headphones and plunging into the aural world of a jamon shop in Spain, glasses clinking all around.

Tools like Audioboo, a simple service that lets you geolocate and upload recordings from a smartphone, are enabling whole nations to be enlisted as distributed recorders. Earlier this year, Scion partnered with The Smalls to launch a US soundmapping initiative called Street Sounds. The British Library teamed with Audioboo to create a nationwide sound archive of the United Kingdom this year, too.When people look back at 2010, they will have a pretty good idea about the noises dense agglomerations of people make in our time.

Touring the sound of these cities across the globe, I began to wonder if I could do the same thing in time. Could I go back a hundred years and listen to New York or Paris?

When it comes to film, you can see all kinds of old places. Sometimes even in high resolution, thanks to the work of archivists like Rick and Megan Prelinger. These films are incredibly important records for historians and citizens alike. They give us eyes in the past.

There's an amazing film sequence of San Francisco in 1905. A camera was placed on a streetcar and driven down Market Street, the diagonal that cuts through the city's core. Pedestrians, cars, carts, horses, the whole dizzying array of urban life before electricity and the automobile turned our cities inside-out. We recognize our buildings, but not our city. Similar recordings exist of most major cities.

I figured that there had to be similar documentation of the metropolitan soundscape, or any soundscape really.

But there isn't.

 

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You could easily be fooled into thinking that a very early recording of a city exists. At the University of California Santa Barbara, the Cylinder Preservation and Digitization Project holds a brown wax recording labeled, "Urban scene- newsboys yelling "Extra, extra"; car horns; and other sounds of the city, sometimes in non-English language." It was made between 1890 and 1902.

Listen to it.

It's scratchy and difficult to discern independent sounds, but maybe we hear a bell ringing, some horns and some vrooms, the clop-clop of horse hooves, a couple of people singing. When Suzanne Fischer, an archivist at the Henry Ford Museum in Detroit sent me this link, I thought I had found my city soundscape! And it was just like I thought it would be. Horse hooves and horns, people singin' in the streets.

But this earliest recording of a city is actually fake. Or perhaps that's too harsh a term. What we hear is a performance of an urban soundscape. A banal radio play.

Actually recording the sturm-und-drang of a city would have been next to impossible impossible. "It would have been very difficult to do an on-the-spot actuality recording," explained Matt Barton, the curator of recorded sound at the Library of Congress. "It was very difficult to do the kind of documentary recording that would be analogous to filming."

We have to go back to the actual physical recording technologies used to understand why we couldn't record cities.

 

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Sound was evanescent until 1877 when Thomas Edison brought out the phonograph. People went nuts for it. Phonograph parlors began to dot large cities. You'd go in, record your voice, and then get to hear it played back. There was something almost mystical about the experience.

His invention was followed quickly by two others, the graphophone and the gramophone. While each differed in its details -- the gramophone's ability to record to discs instead of cylinders would prove decisive -- they required the same recording setup.

To make the fake city recording, the unnamed creators would have had to gather these sound effect actors around a giant horn. To "mix" the sound, people would have actually been distributed and moved through the room.

As they made noise, the acoustic horn would funnel the vibrations down to a diaphragm, which would move a stylus up and down, creating grooves of different depths. The sound was being physically etched into the wax -- carved like letters into a tree -- for later playback.

And that's the problem: the range of sound that could be picked up by the acoustic horn and then etched was narrow. The devices were also finicky and heavy and awkward.

Even recording musicians, who were trained to direct their noises into an acoustic horn, was incredibly difficult. Here's Mark Katz describing the recording booth in his 2004 book Capturing Sound: how technology has changed music:

"The room was usually small, windowless, overheated, and empty, save for a large megaphone-shaped horn and a small red light or perhaps a buzzer attached to one wall. During the performance, musicians had to be careful not to make extraneous, recordable noises, not to gesture unduly (lest they knock the equipment over), and not to sing or play too loudly or softly."

Only certain types of musical instruments recorded well. Horns were great; violins not so much. Certain singers recorded well; the best learned to move their heads and bodies around the horn to create the right kinds of effects. Women's voices, particularly on the higher end, were hard to pick up, too, as pointed out by historian Lisa Gitelman, into the late 1890s.

"The Boswell Company of Chicago offered its 'high grade original' records in 1898 with the assurance that 'At last we have succeeded in making a true Record of a Lady's voice. No squeak, no blast; but natural, clear, and human,'" she wrote. "The Bettini Phonograph Laboratory in New York similarly claimed "The only diaphragms that successfully record and reproduce female voices."

Obviously, these recording setups were not made for fieldwork. You couldn't just take them outside and flip a switch. It wasn't until the 1920s, Barton said, that microphones were developed. They could electronically amplify sounds and enabled the recording of soundscapes. From the very first, film could be used as a documentary device, easily recording ambient scenes. Sound recording, on the other hand, required performance for its first 50 years.

This timeline, when you match it up with other technological changes, has some very important consequences.

There will always be a large gap between our visual and audio historical records. Decades when we can see our places, but not hear them. We will never know what New York, Los Angeles, or any other city sounded like before the automobile hit the streets and electricity was commonplace.

Some things, like what it sounded like for a million Americans to live together without internal combustion engines on wheels, can be lost forever.

Images: 1. MadridSoundscapes.org 2. Library of Congress. 3. New York Public Library.

MIT innovation expert Eric Von Hippel is putting economic rigor behind the intuition of a generation of technologists that the Internet and computing more generally were leveling the playing field between large producers and other types of innovators.

In a talk on Tuesday at the Berkman Center for Internet and Society at Harvard University, Von Hippel will lay out his idea that individual users of products and open source collaborations are becoming more competitive with the traditional manufacturing engines of the economy.

Economists have long looked at big producers with many users -- say, a car company -- and said that the reason they built individual innovators is that they can spread their costs over a large number of users. "A manufacturer can spread his costs over all his users and that means that the manufacturer should be able to innovate more by spending more money than users," Von Hippel told The Atlantic.

But the two major components of innovation -- designing something and telling people about it -- are both dropping.

"I can design with tools as good as those that the car companies use, that Intel uses. It's just cheap software that lets me design, simulate and test," he said. "Communication costs are also dropping because of the Internet. That lets users actually undertake bigger problems because each one does a chunk of the work. I can do part of Linux. You can do another part of Linux."

The net effect is that you need less money to accomplish the same amount of innovation -- and producers are no longer the only route towards accomplishing some product goals. New areas are opening up where individuals and groups of people can compete head-to-head with large companies in the pursuit of making new things.

The shift is already underway, Von Hippel thinks, and that's a good thing. Now the government needs to play policy catch-up to support small and open innovators, particularly around intellectual property laws.

"What's happening is that the whole IP system is placing a tax on open people," he argued. "People who want to be open have to prove that somebody else doesn't own the damn thing. So, yes, there are in-built biases in the system. The system was designed for big-company, industrial kind of things and policy is not properly designed for this new era."

Even if you've heard similar arguments before, what's important about Von Hippel's work is that he's translated technologist jargon into economist jargon. He's formalized what small and open innovators do and why they're important.

If you'd like to hear more about Von Hippel's ideas, check out the livestream on Berkman's website tomorrow at 12:30 p.m. EST. You can also check out Von Hippel's most recent paper, Modeling a Paradigm Shift: From Producer Innovation to User and Open Collaborative Innobation.

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"The process works this way. When I sit down to write a letter or start the first draft of an article, I simply type on the keyboard and the words appear on the screen."

With these words, Atlantic readers entered the personal computer era through James Fallows' landmark July 1982 feature, "Living With a Computer." The piece is a finely observed quest through the wild technological moment in which new machines became accessible to individuals. Looking back, we almost can't believe how much has changed.

Nearly all of the systems that allowed people to get work done without computers have withered away. "What was so exciting? Merely the elimination of all drudgery, excerpt for the fundamental drudgery of figuring out what to say," he wrote. People used to type and retype and retype. This hasn't been a part of our lives for 25 years. It's also amazing to read Fallows describe wanting to electronically send his work to The Atlantic instead of "fighting the crowds at the Express Mail window." Crowds at the Express Mail window?!

Nearly all the companies building system components that Fallows mentioned are gone or bit players now: Optek, Ball Corporation (of canning jar fame), Lanier, Wang, Digital Research, Heath-Zenith, Victor. As Fallows noted, it was like the automobile industry of 1910, "a thousand little hustlers trying to claim a piece of the action." Neither Apple nor Microsoft made it onto his radar.

But where Fallows' article is most fascinating is his intuition that the computer, more than any other technological artifact, was changing his relationship with his family. He had become "hopelessly addicted" to it, staying up into the wee hours of the morning for months learning BASIC, a programming language, and nearly destroying his health in the process.

The shape computers rounded into back in the mid-1980s is the shape they still have today. But the iPad and other high-powered, mobile devices are challenging the idea that a computer's primary purpose is the processing of words as mediated by a keyboard.

All of which makes it a perfect time to revisit this perfectly observed portrait of one individual's world Before and After the Computer.

I'D SELL MY COMPUTER before I'd sell my children. But the kids better watch their step. When have the children helped me meet a deadline? When has the computer dragged in a dead cat it found in the back yard?

The Processor Technology SOL-20 came into my life when Darlene went out. It was a bleak, frigid day in January of 1979, and I was finishing a long article for this magazine. The final draft ran for 100 pages, double-spaced. Interminable as it may have seemed to those who read it, it seemed far longer to me, for through the various stages of composition I had typed the whole thing nine or ten times. My system of writing was to type my way through successive drafts until their ungainliness quotient declined. This consumed much paper and time. In the case of that article, it consumed so much time that, as the deadline day drew near, I knew I had no chance of retyping a legible copy to send to the home office.

I turned hopefully to the services sector of our economy. I picked a temporary-secretary agency out of the phone book and was greeted the next morning by a gum-chewing young woman named Darlene. I escorted her to my basement office and explained the challenge. The manuscript had to leave my house by 6:30 the following evening. No sweat, I thought, now that a professional is on hand.

But five hours after Darlene's arrival, I glanced at the product of her efforts. Stacked in a neat pile next to the typewriter were eight completed pages. This worked out to a typing rate of about six and a half words per minute. In fairness to Darlene, she had come to a near-total halt on first encountering the word "Brzezinski" and never fully regained her stride. Still, at this pace Darlene and I would both be dead--first I'd kill her, then I'd kill myself--before she came close to finishing the piece. Hustling her out the door at the end of the day, with $49 in wages in her pocket and eleven pages of finished manuscript left behind, I trudged downstairs to face the typewriter myself. Twenty-four hours later, I handed the bulky parcel to the Federal Express man and said, "Never again."

Read the rest of Fallows' "Living With a Computer."

Revisit more pieces from The Atlantic's archives with the Technology Channel.

How to Think About... is a video series that provides you with quick frames for thinking about world's blizzard of technologies and services. The idea is simple: imagine we're having a beer and you ask me, "What do you think about Facebook and Twitter?" I switch on the camera and respond. These videos are informal, extemporaneous affairs and we hope they feel like the start of a talk. We'd love to hear how you think about these things, too.

Welcome to The Atlantic's new Technology Channel.

Most tech coverage on the Web is predictable: Google vs. Microsoft; the next gadget from Apple; what ever happened to my jetpack? We aim to take a broader view of technology. We're going to write about the financial algorithms that rule our markets, the tradeoffs of our energy system, how a fork is designed, and, yes, an iPad app that is just plain cool. We see technology not just as hardware and software but as a frame through which to view the great stories of our time.

First, I should introduce myself. I'm Alexis Madrigal and I'll be your lead writer and host. I came to The Atlantic from Wired.com and fresh off finishing a book about the history of green technology. Through both pursuits, I came to think about tech in ways that I think are missing from most of what you see in the big newspapers, tech blogs, and glossy magazines. Technology coverage can't just be about gadgets and gizmos: it's the story of humans reshaping and re-engineering the world they confront.

We hope to do four things on this site. First, we want to deliver reported features on emerging technological trends. Second, we want to bring you short, smart takes on the big news of the day. Third, we want to highlight the deep and important original reportage from around the Internet. Fourth, we want to build a community of people here on the channel who care less about the Kindle's pricing strategy and more about how literacy is changing. We're excited about a kind of journalism that is equally committed to fact-finding, making sense of a confusing world, and hosting a conversation for a smart and curious set of readers. Most of all, we aim to deliver the same depth and sophistication we try to apply to politics, business, and culture.

With today's launch, we're introducing some new features.

• Toolkit is a way of cutting through the gadget clutter. You probably don't care about the endless procession of new objects and services. What matters is how you can use those things to improve your life. Each day we'll be answering your tech questions (and some of our own) from how to share files between computers to whether or not you should buy the new iPhone. (You can submit your questions to amadrigal@theatlantic.com).
• The Tech Canon is a list of the most important works about technology. Some of the items are movies and magazine articles. Most are books. They cover a broad range of technologies, writing styles, and eras. Think of them as the classics you need to know.
• Our video series, How to Think About... gives you quick frames for how to think about the blizzard of technologies and services out there. From Twitter's impact to Google and privacy the to the differences between Silicon Valley and Silicon Alley, How to Think About is a quick way to get familiar with how we're thinking about the big tech issues of our time.
• And we'll plunge deep In the Archives to show how The Atlantic has explored the entanglement of the American idea and American technology for the past 153 years. You'll see that this magazine has published some of the most prescient and important thinking on this subject ever written.

So, bookmark us, put us in your RSS reader, follow us on Twitter, or just keep coming back. And along the way, let us know what you think -- by commenting on stories, sending me an email at amadrigal@theatlantic.com, or talking to us on Facebook and Twitter. We'd like to provide the smartest tech coverage out there, but we'll need your help.

When The New Yorker profiles someone, you expect to really get something from it. Take the piece on energy innovator Saul Griffith's from earlier this year. Brilliant work on a fascinating character. Griffith's thinking and personality lead you to new understanding about technology and energy.

But that's not the case with this week's Mark Zuckerberg profile. It's 6,000 words of stuff that's not surprising, barely interesting, and leave us knowing little more about Facebook or Zuckerberg than we did before.

If this is what passes for the interesting bits ("Zuckerberg lists 'Ender's Game' as one of his favorite books") in a deep profile of someone, you know there's not much there. But I'm not sure that's Jose Antonio Vargas' fault.

Zuckerberg is a boring guy who seems to suck the life out of any writing about him. Whatever percentage of evil he has brewing inside has long been channeled away from his persona. No one gets anything to stick to him. At best we find he's something of an insolent teenager. We assume he's bent on dominating the Internet, and no profile has ever found otherwise.

The most damaging snippets -- the 19-year old Zuckerberg's IMs -- were revealed long ago by Silicon Alley Insider. We learn little about Facebook as a company or Zuck's leadership within it beyond that he's kind of a tough guy to work with.

The two most interesting tidbits -- one personal, one professional -- are left hanging. The personal one comes when he arrived at his house with the New Yorker writer and his girlfriend is there studying. "Surprised, Zuckerberg approached her and rubbed her right shoulder. "I didn't know you were going to be here," he said. She touched his right hand and smiled," Jose Antonio Vargas wrote. It's a nice moment -- tender verging on maudlin -- but then it's over. We hear a little more about the two of them, but that's nearly it.

Google's search engine is getting a major makeover today. Mountain View's finest debuted Google Instant today, which returns results for you as you type.

Now, let's be clear: the search engine itself didn't change much today. Pages will be ranked exactly where they were before. But the user experience just changed considerably, as Google executives and engineers emphasized in a San Francisco press conference.

Predictably, they trumpeted the benefits of the service. With Google Instant, they say users save an average of two to five seconds per search. Multiplied by the billions of searches that Google users execute each day, the societal time savings add up.

I also love one feature. As you're searching, Google is auto-completing other searches for you. Hit your down arrow and you see those results. So, let's see you start off searching for "The End of Men," but you realize you'd rather search for "The End of World," when Google shows it to you. This happens:

In a keynote talk at a German electronics conference, Google's Eric Schmidt delivered his vision for the future of search.

"The next step of search is doing this automatically. When I walk down the street, I want my smartphone to be doing searches constantly - 'did you know?', 'did you know?', 'did you know?', 'did you know?'" Schmidt said. "This notion of autonomous search - to tell me things I didn't know but am probably interested in, is the next great stage - in my view - of search."

What's fascinating about this is that it's basically the opposite of search now. Search is about finding what you want, not about finding what you are statistically likely to want. I think there is a key difference between those two things.

This is what Google thinks I am statistically likely to search when I type in "religion is":



What we're thinking about is only hazily connected to any of the things that Google can know about me. If I'm sitting in an office in San Francisco around lunchtime, Google may think, "Yes, he probably wants lunchtime recommendations." Or if I type in "religion is," Google's algorithms may be able to make certain suggestions, but our thoughts are not that accessible to the web's spiders.

How could they possibly know when I'm thinking about Manfred Clynes and cyborgs? Or Russia's Kola borehole? Or the mythical luz bone in Hebrew scripture?

That's one reason search is so great: I get to "pull" whatever I want out of the Internet, no matter how old I am or where my house is or what I bought last on Amazon or what anyone else has searched for.

What Schmidt is describing is push-push-push. It sounds like narrowcasting, that awkward phrase for broadcasting in an era without mass audiences. Might that be useful? Absolutely. But I don't think it will ever replace or even be seen as similar to search. Except, that is, for how Google will sell it to advertisers.

I've had Gmail Priority Inbox for about six hours and I am already in love with it.

If you haven't heard, Priority Inbox is a new tool from Google that algorithmically (i.e. automatically based on a few factors) separates your incoming email into two categories: Important and Everything Else.

For me, the emails marked Important actually reflect my own evaluation of them. So far, out of the hundred or so emails I've gotten, only one has been mislabeled.

I'm sure there is some magic in the machine somewhere, but really, just floating all the emails that are specifically addressed to me (as opposed to a listserve or where I'm CC'd) does wonders.

Over the six years I've had Gmail, I've signed up for a number of things that are no longer essential, but not so bothersome that I don't want to receive them. All my Google alerts for "history + solar," NASA press releases, or emails from my athletic club all fall into that category. Having a place to store them without cluttering up my main inbox is brilliant.

Could I have accomplished much the same thing by setting up a bunch of filters? Sure. But the extra work required always seemed to outweigh the minor hassle of not reading or deleting a bunch of semi-precious emails. Now, Google's done all the work for me in one simple stroke.

I did make one important tweak to the default Priority Inbox settings. The default setting is that your priority inbox only shows things that are Important and Unread. That made me feel uncomfortable. I like seeing the important things even after I've read them.

Priority Inbox might not be for everyone. If you're tidier about how you run your email already, maybe you don't need it. If you don't manage a huge volume of email, again maybe you don't need it. But if your email inflow is variegated and heavy, it will be a useful tool for you.

[Oh, one last note: Google rolls out new features progressively, so you may not have access to this functionality yet. If you don't, just sit tight. You'll have it soon!]

Stanford's Clifford Nass has devoted his career to understanding how people interact with computers. In hundreds of papers, one key lesson emerged: we treat computers like people, even though they clearly are not. He used that insight to improve design interfaces, making them friendlier and more helpful.

In a new book, he's inverted that work. Now, he's asking what we can learn from computers about how to be better people. The Man Who Lied to His Laptop comes out today from Current Books.

From a research perspective, using computers instead of people to study human interactions reduces the amount of noise that gets produced when people talk to people. Humans are just too specific to yield generally useful data about how to behave. We all know that the strategies that work for charming, good-looking people won't necessarily work for everyone.

"What the computer does is allow us to get at that which is most fundamental, most basic, but also most powerful in the way people interact with each other," Nass told me.

"The quote-unquote deficiencies of the computer enable it to come up with rules that will work for anybody," Nass said.

That is to say, if a computer can consistently elicit a certain emotional response from people, it's safe to assume that people could succeed in similar ways. "If there are social rules that work well for the most pathetically unsocial thing you can conceive of -- the computer -- think how much better it's going to work with real people."

Rule number one? People love to be flattered. Here, we present a case study from the book about the exceptionally high value of telling people how great they are. Speaking of which, have I ever told you how smart and successful The Atlantic's audience is. Best readers in the world!

Is Flattery Useful?

My exploration of flattery, then, became the first study in which I used computers to uncover social rules to guide how both successful people and successful computers should behave. Working with my Ph.D. student B. J. Fogg (now a consulting professor at Stanford), we started by programming a computer to play a version of the game Twenty Questions.

The computer "thinks" of an animal. The participant then has to ask "yes" or "no" questions to narrow down the possibilities. After ten questions, the participant guesses the animal. At that point, rather than telling participants whether they are right or wrong, the computer simply tells the users how effective or ineffective their questions have been. The computer then "thinks" of another animal and the questions and feedback continue. We designed the game this way for a few reasons: the interaction was constrained and focused (avoiding the need for artificial intelligence), the rules were simple and easy to understand, and people typically play games like it with a computer.

Having created the basic scenario, we could now study flattery. When participants showed up at our laboratory, we sat them down in front of a computer and explained how the game worked. We told one group of participants that the feedback they would receive was highly accurate and based on years of research into the science of inquiry. We told a second group of participants that while the system would eventually be used to evaluate their question-asking prowess, the software hadn't been written yet, so they would receive random comments that had nothing to do with the actual questions they asked. The participants in this condition, because we told them that the computer's comments were intrinsically meaningless, would have every reason to simply ignore what the computer said. A third control group did not receive any feedback; they were just asked to move on to the next animal after asking ten questions.

The computer gave both sets of users who received feedback identical, glowing praise throughout the experiment. People's answers were "ingenious," "highly insightful," "clever," and so on; every round generated another positive comment. The sole difference between the two groups was that the first group of participants thought that they were receiving accurate praise, while the second group thought they were receiving flattery, with no connection to their actual performance. After participants went through the experiment, we asked them a number of questions about how much they liked the computer, how they felt about their own performance and the computer's performance, and whether they enjoyed the task.

If flattery was a bad strategy, we would find a strong dislike of the flatterer computer and its performance, and flattery would not affect how well participants thought they had done. But if flattery was effective, flattered participants would think that they had done very well and would have had a great time; they would also think well of the flatterer computer.

Participants reported that they liked the flatterer computer (which gave random and generic feedback) as much as they liked the accurate computer. Why did people like the flatterer even though it was a "brownnoser"?

Because participants happily accepted the flatterer's praise: the questionnaires showed that positive feedback boosted users' perceptions of their own performance regardless of whether the feed¬back was (seemingly) sincere or random. Participants even considered the flatterer computer as smart as the "accurate" computer, even though we told them that the former didn't have any evaluation algorithms at all!

Did the flattered participants simply forget that the feedback was random? When asked whether they paid attention to the comments from the flatterer computer, participants uniformly responded "no." One participant was so dismissive of this idea that in addition to answering "no" to the question, he wrote a note next to it saying, "Only an idiot would be influenced by comments that had nothing to do with their real performance."

Oddly, these influenced "idiots" were graduate students in computer science. Although they consciously knew that the feedback from the flatterer was meaningless, they automatically and unconsciously accepted the praise and admired the flatterer. The results of this study suggest the following social rule: don't hesitate to praise, even if you're not sure the praise is accurate. Receivers of the praise will feel great and you will seem thoughtful and intelligent for noticing their marvelous qualities--whether they exist or not.

Excerpted from THE MAN WHO LIED TO HIS LAPTOP: WHAT MACHINES TEACH US ABOUT HUMAN RELATIONSHIPS by Clifford Nass by arrangement with Current, a member of Penguin Group (USA), Inc., Copyright (c) Clifford Nass, 2010.