Category Archives: collaboration

Behind MIT’s DARPA Weather Balloon challenge win

MIT Red Balloon Challenge Team

As many of you know, the MIT Red Balloon Challenge Team (part of the MIT Media Lab) won the race to locate the DARPA Red Weather Balloon Challenge.    Their system was a reverse Ponzi scheme where those finding the balloon got $2000, and those progressively farther back the invite chain in finding those people got progressively lower payouts;  the surplus got donated to charity.  (Because the payoffs were cut in 1/2 with every additional degree of separation from the balloon finder, there is no way that MIT could owe more than $4000 per balloon, even if path links to MIT were very long, and MIT assumed that many of the path lengths would be short.)

MIT team members reported that they sent out 2 million SMS messages as one of their strategies but that was a complete bust as far as finding the balloons.  Twitter and Facebook on the other hand were far more effective.  They are going to be subsequently distilling their findings on effective viral communication and sharing it at an appropriate venue.

Their victory was a victory of human connections (“social capital“) over number crunching.  A Google Team was racing them using number crunching and image recognition techniques (e.g., crawling the web in real time for images of red balloons) and had spotted 9 of the 10 balloons when the MIT Team found 10.  The MIT Team noted that the balloon finders were using Google Map to determine the coordinates of their balloon sighting (to report to the MIT team) and Google could have captured that information and used it for their own proprietary team but didn’t.

See a blog post about the basic architecture of the MIT reward structure.  DARPA’s network challenge obviously has implications for how to effectively and rapidly spread information in the event of an attack, although clearly the task here (spotting a red balloon) is infinitely easier than other possible challenges which are less observable to the the naked eye (infectious diseases or biological attacks) or actions who cause is less clear (a plane crashing for instance).

DARPA noted how the challenge explored “how broad-scope problems can be tackled using social networking tools. The Challenge explores basic research issues such as mobilization, collaboration, and trust in diverse social networking constructs and could serve to fuel innovation across a wide spectrum of applications.”

Read more here.

Malcolm Gladwell’s The Outliers [UPDATED 3/23/13]

Gladwell’s The Outliers (2008) focuses on success and the hard work, social context and cultural background that explains why some people excel and others don’t.  He has a related article in The New Yorker on genius (trivia note: a related post of his on this topic was rejected a long time ago by the New Yorker).  The Outliers seems better at explaining the success of some than in its prescriptions for how to get others to succeed.  [For more on his 2013 book, David and Goliath, click here.]

While The Tipping Point seemed to focus more on individuals and their power to change society, The Outliers focuses more on the social and cultural context of individuals to explain their extraordinary success.  As per vintage Gladwell, it takes a very eclectic path toward its subject, looking at everything from a genius who lives on a horse farm in Northern Missouri, to why Canadians are better hockey players (and which Canadians are the best), to why Korean pilots are more likely to crash planes.

In a nutshell, Gladwell believes The Beatles’ success was due to the fact that in their early years in Hamburg, Germany, they had to play very long sets at clubs, in a wide variety of styles, which both helped them to get in their 10,000 hours (see below on its importance) and forced them to be creative and excel at experimenting.  He notes the eerie correlation between who is a good pilot and what culture they came from.  He explores why a little town in Eastern Pennsylvania has had zero heart attacks.  He divulges that one 9 year stretch has accounted for more Outliers than any other.  He credits the success of Chinese math geniuses to the their harder studies and greater patience in problem-solving, stemming from a cultural legacy of long days of work in rice paddies; Gladwell contrasts the Chinese proverb ‘No one who can rise before dawn 360 days a year fails to make his family rich’ with the American agricultural practice of letting fields lie fallow in winter, which led to a school year with summer vacations — a practice that works for children of the well-educated but fails children of the less-educated who give up many of their school-year academic gains over the summer. He credits Bill Gates’ success to early and sustained access to high-end computers.  As Edward Tenner notes on Slate: “Memo to overscheduling, hovering, upper-middle-class mothers and fathers: Keep up the good work.”

Gladwell gave a related talk at the New Yorker’s conference last year called “Genius: 2012”. In the talk Gladwell explains how success in the 21st century is less about sheer intelligence and more about collaboration and hard work to get to the level of mastery in a topic (which he says typically takes 10,000 hours).  Outliers describes how Bill Gates was able to get to 10,000 hours while still in middle and high school in Seattle due to 9 incredibly fortunate concurrences: among them, that his private school could fund a sophisticated computer in their computer club, and fact that he lived close to the U. of Washington, where he could use an even more sophisticated computer. Gladwell concedes that Gates is obviously brilliant, but still notes that many other brilliant youth never had the chance to become computer stars of Gates’ magnitude because they didn’t have access to these sophisticated computers.

In the New Yorker conference, Gladwell uses the contrast of Michael Ventris (who cracked the undecipherable code called Linear B of Minoans from Knossos on Crete) – and Andrew Wiles (a Mathematics Professor who solved what some thought might never be solved: Fermat’s Last Theorem).

Michael Ventris was the pre-modern genius: working mainly alone, in his free time, utterly brilliant and solving in a flash of insight after 1.5 years of free time during nights and weekends spent on the problem. Andrew Wiles, on the other hand, took about ten years to solve the theorem (close to those same 10,000 hours), and built on scholarly work over decades by a dozen other mathematicians. Gladwell notes that Wiles was less a pure genius and more a master at diligently working away at this problem, and building on the shoulders of other math giants. He also points to the important of hard work by showing that what separates better oncologists from worse oncologists was not intelligence or training, but how long they spent trying to find cancers from the colonoscopy results (*the mismatch problem*). [The mismatch was that oncologists often chosen for their brilliance and how fast they could examine the colonoscopies.] Gladwell notes that he thinks we need to think more about how to get a dozen Andrew Wiles than one Michael Ventris and thus we need to focus on *capitalization* (how some groups, like Chinese-Americans, are better able to translate given levels of IQ into managerial experience at 33% higher rates than White Americans.)

Speaking at a recent PopTech conference in Camden Maine in 2008, after explaining America’s abysmal capitalization rate, Gladwell’s gloom and doom gave way to optimism. “We have a scarcity of achievement in this country, not because we have a scarcity of talent. We have a scarcity of achievement because we’re squandering that talent. And that’s not bad news, that’s good news, because it says this scarcity is not something we have to live with. It’s something we can do something about.”

Gladwell: “Our romantic notion of the genius must be wrong. A scientific genius is not a person who does what no one else can do; he or she is someone who does what it takes many others to do. The genius is not a unique source of insight; he is merely an efficient source of insight.”

As advocates of the importance of social capital, it is obviously self-validating that Gladwell shows how social networks (beyond mere brilliance) is one of the factors Gladwell tags as a key to success. Scholars like Ronald Burt and others have clearly showed that lifetime earnings is more clearly a function of social interconnections than of levels of education.

There is interesting parallel work to Gladwell’s which shows up in work by an economist named David Galenson in an intriguing book called Old Masters and Young Geniuses.

Galenson believes that artists fall into two categories:

1) conceptual innovators who peak creatively early in life. They know what they want to accomplish and then set out with certainty to accomplish this. (Examples include Pablo Picasso, T.S. Eliot, F. Scott Fitzgerald, and Orson Wells).

2) experimental innovators who peak creatively later. They dabble, try new things (some of which succeed and some fail), learn from their mistakes, and make incremental improvements to their art until they’re capable of real masterpiece. Examples include Paul Cezanne, Frank Lloyd Wright, Mark Twain, and Jackson Pollock).

Galenson’s work parallels Gladwell’s in his belief that many “geniuses” are not born great but have the capacity to learn from others and learn from failures along the way.  See interesting talk by Gladwell discussing Galenson in “Age Before Beauty.”

Previewing  The Outliers in New York magazine, he talks about the case of Canadian hockey players:

Gladwell explains why the relative-age effect (a compounding of some initial advantage over time), explains why a disproportionate number of elite Canadian hockey players were born in the first half of the year (popularizing  the research of a Canadian psychologist). Because Canada’s eligibility cutoff for junior hockey is January 1, Gladwell writes, “a boy who turns 10 on January 2, then, could be playing alongside someone who doesn’t turn 10 until the end of the year.” Since the differences in physical maturity are so great at that age, this initial advantage in when one starts playing competitive hockey helps explain which kid will make the league all-star team. And similarly, by making the all-star team earlier, the January 2 kid gets another leg up in more practice, better coaching, tougher competition, that compound that difference. Gladwell says it explains why by age 14, the January 2 birthday kid  becomes so much better at hockey than the January 1 birthday kid. Gladwell says the solution is doubling the number of junior hockey leagues—some for kids born in the first half of the year, others for kids born in the second half. Or, as it applies to elementary schools, Gladwell believes that elementary and middle schools should put group students in three classes (January-April birthdays, May-August birthdays, and September-December birthdays) to “level the playing field.”

It’s interesting, as New York magazine points out, that at some level The Tipping Point was all about how one individual, taking advantage of connectors and influencers and the structure of social networks can move the world.  The Outliers starts at the other pole and argues that people’s opportunity to move the world and excel, while partly driven by talent, is largely structured by opportunities provided externally.  The Outliers is an invitation for governmental-policy to ensure that those who are talented can achieve, rather than be left to chance of who happens to be given the opportunities.  While Gladwell is quick to seize upon the accumulated advantages of those who succeed, he overlooks the role of persistance and motivation (which someones arises out of adversity).  Slate has a brief historical discussion of figures like Oppenheimer who overcame their disadvantages and quotes Sarkozy who said: “What made me who I am now is the sum of all the humiliations suffered during childhood.”

N.B.: Interestingly, Gladwell, who is a rare breed of journalist-celebrity, such that Fast Company once called him “a rock star, a spiritual leader, a stud”, insists that he is not an Outlier; he says “I’m just a journalist.”  He does explain that he put in his own 10,000 hours at the Washington Post from 1987-1997, and it was only because of that investment in the craft of journalism that he could succeed when he moved to the New Yorker in 1997.

Read excerpts of Outliers here.

Related article “Genius: The Modern View” by David Brooks (NYT Op-Ed, 5/1/09).

The book, BTW, is panned by Michiko Kakutani of the NYT in “It’s True: Success Succeeds and Advantages Can Help” (11/17/08).

Interesting video of Gladwell presenting at AIGA’s Gain conference here; he discusses success via detailed story of Fleetwood Mac and shorter discussion of the Beatles. (PSFK)

Games with a purpose: a spoonful of sugar…

GWAP (Games with a Purpose) hopes to save the world (or at least make it easier to find out information about saving the world) through people playing games for free.

gwaplogo

GWAP pairs individuals in games against each other to improve search algorithms. For example, in Tag a Tune, you try to figure out if you and an opponent are listening to the same song by trying to describe it (and in the process help search methods for MP3 files). Or the ESP Game shows you and a partner (in different locations) the same image and you try to guess what words your partner is using to describe this image.

Now, if only they can find a way to use game playing to increase social trust and collaboration outside of games…

We reported on other efforts to use the public to do tasks of public good (like Mechanical Turk to map the surface of Mars in this blog post) or here or here.

E-searching together: the hunt for Steve Fossett

Technology is enabling complete strangers to cooperate for social good: in this case, the hunt for adventurer Steve Fossett, whose plane disappeared recently in the U.S. southwest.  (I’ve written about other attempts to use techology for such social goals here and here.)

Google’s Amazon Mechanical Turk has farmed out pieces of the southwestern landscape to up to 20,000 strangers who are searching the landscape from their computers (thanks to Google Earth).  If 10 individuals find nothing in their *sector*, the patch of ground is ignored.  If one or more of the 10 see something, it is passed off to humans to actually scan the terrain on the ground.

What is the impact of such collaboration, above and beyond their potential important benefit in locating stranded victims like Steve Fossett?  Such efforts obviously show cooperation and are pro-social.  But they don’t build any social capital (in other words, Jane who is searching this piece of land and Charles who is searching that piece of land don’t build up any social interconnections).  What’s less clear is whether such actions have any bearing on social trust:  does my participation in this act of altrusim together with some 20,000 others change my conception about whether strangers can be trusted?  At a logical level, probably not (20,000 individuals are a very small percentage of the world’s population), but behavioral economists are increasingly demonstrating that we often do not behave in the logical fashion that classical economists expected.

For a story on this, see: Searching by Land, Sea and the Web (NYT Week in Review, 9/16/07)