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Exploration versus Exploitation in Google's Think Quarterly

In Google's first issue of "Think Quarterly," it's new business to business publication, Susan Wojcicki, Google's employee number 16, sums up the classic exploration versus exploitation tradeoff writing, "We face the classic innovator’s dilemma: should we invest in brand new products, or should we improve existing ones?"

James March laid out this ubiquitous dilemma, which every organization faces in one form or another, in his now classic paper, "Exploration and Exploitation in Organizational Learning."  Each summer at the University of Michigan's ICPSR Summer Program on Quantitative Methods I co-teach a course on complex systems models in the social sciences in which I often discuss March's famous paper (in fact, we just discussed the paper today).  In going over the paper this summer I was struck again by the continuing relevance of his insights.

The quote that grabbed me today was, "... adaptive processes characteristically improve exploitation more rapidly than exploration ... these tendencies to o increase exploitation and reduce exploration make adaptive processes potentially self-destructive."  Here, March says we have to constantly be on guard to preserve exploration in our organizations.  Our natural tendency, just by doing what's best for us in the short run, is to gradually scale back exploration in favor exploitation, until all we do is exploit.  But, in doing so, we ultimately doom our organization to failure because we're no longer able to adapt to changing environment, or we lock into a sub optimal solution and eventually our competitors surpass us (see the earlier post on Borders).  March issued this warning to all organizations long before Clayton Christensen's Innovator's Dilemma.  The process of adaptation that makes us good at what we do now will destroy us down the road if we don't actively work to preserve exploration in our organization.  Which brings us back to Google.  Google is famous for so-called "20 percent time" in which engineers are asked to dedicate a full day a week to things "not necessarily in their job description."  This is Google's way of actively maintaining exploration in their organization.  So far, it seems to be working for them.

in Innovation / Research  by pj 0 comments

Another Social Media Disaster: The Milk "Everything I Do is Wrong" campaign

The New York Times chronicles another example of an online ad campaign gone bad.  This time the California Milk Processor Board ran a campaign at everythingidoiswrong.org (since replaced with gotdiscussion.org) touting the abilities of milk to help reduce PMS symptoms that clearly made light of women from a stereotyped males perspective.  As we well know by now, in the age of social media, a misstep like this can quickly turn into a disaster.

in Contagion / Networks / Social Media  by pj 0 comments

The Internet didn't kill Borders, Borders killed Borders

There is a nice article on Slate today about the demise of the bookseller Borders.  The overall point is that, while the rise of Internet retailing created challenging circumstances for bricks and mortar bookstores, the real cause of Border's demise was its own poor strategy.  The article echoes one of the themes of the System Dynamics class that I taught at Sloan the past few years: there's no such thing as side effects, there's just effects.  What we mean by this is that when a company (or a person, or any orgaization) takes an action, and something unintended or unforeseen happens, we tend to call these outcomes "side effects" as though we were somehow not responsible for them.  But in the end, these so called side effects are still the consequences of our own actions.  The only thing that distinguishes them is that we didn't plan for them to happen.  Recognizing and taking responsibility for these effects is a first step towards anticipating and preventing them.

in Prediction  by pj 3 comments

The Christakis and Fowler Social Networks Influence Brouhaha

Recently there has been a spirited conversation kicked off by the publication of an article, "The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis," by Russell Lyons regarding the well-publicized work of Nicholas Christakis and James Fowler on social contagion of obesity, smoking, happiness, and divorce.  The discussion has been primarily confined to the specialized circle of social network scholars, but now that conversation has spilled out into the public arena in the form of an article by Dave Johns in Slate (Dave Johns has written about the Christakis-Fowler work in Slate before).  Christakis and Fowler's work has received a huge amount of attention, appearing on the cover of the New York Times magazine, on the Colbert Report TV program, and a ton of other places (see James's website for more links).  Many others have made detailed comments on Lyon's article and on the original Christakis-Fowler papers.  I wish to address some of the related issues raised in Slate about scientists in the media

The article seems to criticize Christakis and Fowler for their media appearances, as though this publicity is inappropriate for scientists who should be diligently but silently working in the background, leaving it up to policy makers and the media to make public commentary and recommendations.  I think this criticism is not only wrong, but dangerous.  Many if not most researchers do work silently in the background, shunning the spotlight and scrutiny of the media, not out of shyness or fear of embarrassment, but because of a pervasive misunderstanding of scientific uncertainty.  Hard science is simply much softer than many people realize.

ALL scientific conclusions — from physics to sociology come with uncertainty (this does not apply to mathematics, which is actually not a science).  A "scientific truth" is actually something that we're only pretty sure is true.  But we'll never be definitely 100% sure, that's just how science works.  When one scientist says to another, we have observed that X causes Y, it is understood that what is meant is, the probability that the observed relationship between X and Y is due to chance is very small.  But, statements like that don't make for good news stories.  Not only are they uninteresting, but for most people they're unintelligible (which is not to say that the public is stupid — the concepts of uncertainty and statistical significance are extremely subtle and often misunderstood even by well-trained scientists).  So, many scientists avoid the media because we're asked to make definitive statements where no definitive statements are possible, or we make statements that include uncertainty that are ignored or misunderstood.

But we need scientists in the media.  Only a fraction of Americans believe the planet is warming and 40% of Americans believe in creationism.  Scientists in the media can help correct these misperceptions and guide public policy.  And, maybe even more importantly, scientists in the media can make science sexy.  We already live in a world where science and politics are often at odds, and in which scientists that avoid the media are often overruled by politicians that seek it out.  Scientists are already wary of making public statements that implicitly contain uncertainty for fear of them being interpreted as definitive. Christakis and Fowler have done us a great service by taking the risk of making statements and recommendations in the public arena based on the best of their knowledge, by raising public awareness of the science of networks, and by making science fun, interesting, and relevant.

in Contagion / Networks / Research  by pj 2 comments

Social Networks in the Classroom

Today's New York Times has an article on an educational software start-up that "has a social-networking twist."  The company, Piazza, provides a course page where students can ask and answer questions with moderation from the instructor.  I'm not sure what the "social networking" component of this site is.  From the Times article, it sounds simply like a message board with a few bells and whistles.  A quick search for the company's website left me empty handed, so we can only speculate that there is actually something more here.

In passing, the article raised another interesting point though: "As in the case of Facebook, the wildly popular social network that sprang from a Harvard dorm room, the close-knit nature of college campuses has helped accelerate the adoption of Piazza."  The idea that close-knit communities lead to increased technology adoption is something that I prove in my recent paper, "Friendship-based Games."  The idea of closely knit communities is captured by the clustering coefficient of a network.  This metric measures the probability that two individuals that share a mutual friend are friends with one another.  In the paper, I show using a game theoretic model that new (beneficial) technologies have an easier time breaking into a market in networks with high clustering.  The basic idea is that small communities of users can adopt the new technology and interact mainly with one another, protecting themselves from the incumbent.  This may be one of the reason that college campuses, which probably exhibit higher clustering than many other social networks, prove to be such fertile ground for the adoption of new innovations.

in Contagion / Networks / Research / Social Media  by pj 0 comments

"Social Media in Tornado Alley"

A recent New York Times newsletter contained an article, "Social Media in Tornado Alley," in which they describe how resident posted YouTube videos and reporter Twitter feeds contributed to their coverage of the tornado devastation in Joplin, Missouri.  They created a video by piecing together YouTube clips and their reporter Brian Stelter, "immediately began filing a stream of Twitter updates that provide a unique and up to the second account of what he was seeing on the ground there."

It's interesting to see how the Times and other "traditional" news organizations are folding social media into their portfolio.  On the one hand, social media is seen as a challenge to traditional news sources, since so much information is available via the Web. But, I think we're seeing how organizations like the Times can serve as curators of this information by collecting the most interesting/important/reliable pieces and adding expert commentary and analysis.

in Crowdsourcing / Social Media  by pj 0 comments

Crowdsourcing the Palin Email Release

Slate reports that several major news outlets, including the Washington Post and the New York Times, are planning to use crowdsourcing to scour thousands of pages of emails from her time as Governor of Alaska that will be released on Friday.

In many ways this is a perfect crowdsourcing task.  It would be hugely time consuming for news reporters to sift through the more than 24,000 pages of email themselves.  And automating this process would be next to impossible because what counts as "interesting" is very difficult to program into a natural language processor. On the other hand, it is relatively easy for for humans to pick out.  The task comes with built in motivation: first, people are personally interested in reading Palin's emails; second, Palin's detractors are motivated to try and dig up embarrassing information and supporters will be motivated to respond; and third, finding something interesting comes with the promise of acknowledgement in the pages of a major news outlet.  All this adds up to the fact that you don't need to pay anyone to do this and do it well.  The biggest potential pitfall is that crowdsourcing relies fundamentally on local information.  Each individual looks through a handful of emails, which is good for finding particular juicy quotes, but not so good for identifying larger patterns.  To combat this, the news outlets could rely on wiki-like interfaces where the crowdsourcers could post "leads" that other individuals could add to in order to piece together larger narratives.

in Crowdsourcing / Politics  by pj 0 comments

One person, one vote?

An article in the New York Times describes recent research by economists Brian Knight and Nathan Schiff on the relative impact of votes from different states in the presidential primaries. They estimate that a vote in an Iowa or New Hampshire primary has the impact of five Super Tuesday voters. The focus of the Times article is on the policy implications of this impact inequality. One of the interesting things about this research is how "impact" is measured.  What the article doesn't mention is why there is any impact difference in the first place. After all, mathematically, a vote in Iowa or New Hampshire counts just as much as one in New Jersey or Montana.

The way the Knight and Schiff estimated "impact" was to look at election polls before and after each primary.  They found that the polls shifted the most after early primaries.  Their theory is that voters are uncertain about the quality of different candidates, but learn (or infer) something about that quality by observing others.  This is kind of like noticing that a lot of people drive a certain type of car and then inferring that therefore it must be a pretty good car.  But, we could imagine several other stories.  For example, If voters that prefer candidate A perceive candidate B as a lock-in to win the nomination, then maybe they decide not to vote.  Prospective voters for candidate B on the other hand may continue to vote because they enjoy being on the winning side.  Some undecided voters may shift towards candidate B for the same reason.  A question that has perplexed political scientists and economists for decades is why does anyone vote in the first place.  A more careful look at these results could shed light on that question.

in Politics / Research  by pj 0 comments

Nicholas Christakis at WIDS@LIDS

Today and tomorrow I’m at the Interdisciplinary Workshop on Information and Decision in Social Networks at the MIT Laboratory for Information and Decision Systems (WIDS@LIDS).  Nicholas Christakis gave a thought provoking talk this morning drawing on a lot of material from his book, Connected, written with James Fowler.  One of the first ideas he raised is that humans are unique in having a social pressure on our evolution.  Humans  and other species also face environmental and other species evolutionary pressures.  But, he argued that humans are unique in this social pressure because we live in close proximity and other human groups are one of the biggest threats that  we face.  He went on to say that possibly this unique social pressure is responsible for humans evolving intelligence, because in order to navigate the complexities of social interactions, we need substantial intelligence.  I’m not sure that I buy this argument though.  What about ants, bees, wolf packs, ... ?  All of these species work in groups, cooperate, and face competitive pressure from other groups, but none of them have evolved intelligence on a human scale.

Christakis ended his talk asking about why certain ideas are “sticky.”  I think this is a super interesting and super difficult question.  I’ve been talking with Adam Berinsky in the Political Science Department at MIT about this question in relation to political rumors.  Why does the rumor that Obama was born in another country stick around, but other rumors die out?  Christakis suggested that this might somehow be a tractable question, but I think it is much more subtle.  First of all, there are no natural metrics for judging ideas.  Second of all, we can’t just look at which ideas have actually taken off and which haven’t, because so many other chance factors come into play.  Because of the big positive feedbacks involved in the spread of ideas, this process is highly susceptible to chance tipping (see the work by Salganik, Dodds, and Watts).  It’s very east to fall into the trap that Duncan Watts sums up in the title of his recent book, Everything is Obvious Once You Know the Answer.  Once an idea does “go viral,” like the Birther rumor, it is tempting to make up a narrative that says, well of course that rumor spread because it has attributes x, y, and z.  But, if the rumor had died we could just as easily construct a different narrative explaining its failure.  Paul Lazarsfeld’s paper on The American Soldier gives a fantastic example of how we can trick ourselves into believing this kind of after the fact rationalization.

in Contagion / Networks / Research  by pj 0 comments

"I mourn the loss of thousands of precious lives ... "

There is a great story on the Atlantic’s website about a fake quotation that exploded on Facebook and Twitter after Osama Bin Laden’s death.  The quote, wrongly attributed to Martin Luther King Jr. is:

“I mourn the loss of thousands of precious lives, but I will not rejoice in the death of one, not even an enemy.”

The author of the article, Megan McArdle, traces the origins of the wrongly attributed quote to a facebook post from a 24 year old Penn State graduate student (check out the article for the fascinating story).  This brings up some interesting issues about rumors and social media.  An open question regarding information and the web, is whether technologies like social media and the Internet in general increase or decrease the prevalence of false information.  On the one hand, the “wisdom of the crowd” might be able to pick out the truth from falsehoods.  True statements will be repeated and spread, while false statements will be recognized by a great enough number of people to squelch them.  On the other hand, we know that systems like this with strong positive feedbacks can converge to suboptimal solutions.  If you think of retweeting some piece of information as like casting a vote that it is true, we might expect information cascades of the sort described theoretically by Bikhchandani et al..  In this case, two things seem to have happened.  Initially, there was a sort of information cascade that led to the spread of the quote.  Then it wasn’t the wisdom of the crowds that led to the squelching of the rumor, but the efforts of knowledgable individuals tracing the quotation back to the initial post.  What the Internet provided was a way to uncover the roots of the false information for those willing to take the time to look.

in Contagion / Social Media  by pj 0 comments