Free Everything Is Obvious by Duncan J. Watts Page A

best songs could fail to win sometimes, while the worst songs could do pretty well. And for everything in the middle—the majority of songs that were neither the best nor the worst—virtually any outcome was possible. The song “Lockdown” by 52 Metro, for example, ranked twenty-sixth out of forty-eight in quality; yet it was the no. 1 song in one social-influence world, and fortieth in another. The “average” performance of a particular song, in other words, is only meaningful if thevariability that it exhibits from world to world is small. But it was precisely this random variability that turned out to be large. For example, by changing the format of the website from a randomly arranged grid of songs to a ranked list we found we could increase the effective strength of the social signal, thereby increasing both the inequality and unpredictability. In this “strong influence” experiment, the random fluctuations played a bigger role in determining a song’s ranking than even the largest differences in quality. Overall, a song in the Top 5 in terms of quality had only a 50 percent chance of finishing in the Top 5 of success.
    Many observers interpreted our findings as a commentary on the arbitrariness of teenage music tastes or the vacuousness of contemporary pop music. But in principle the experiment could have been about any choice that people make in a social setting: whom we vote for, what we think about gay marriage, which phone we buy or social networking service we join, what clothes we wear to work, or how we deal with our credit card debt. In many cases designing these experiments is easier said than done, and that’s why we chose to study music. People like to listen to music and they’re used to downloading it from the Web, so by setting up what looked like a site for music downloads we could conduct an experiment that was not only cheap to run (we didn’t have to pay our subjects) but was also reasonably close to a “natural” environment. But in the end all that really mattered was that our subjects were making choices among competing options, and that their choices were being influenced by what they thought other people had chosen. Teenagers also were an expedient choice, because that’s mostly who was hanging around on social networking sites in 2004. But once again, there was nothing special about teenagers—as we showedin a subsequent version of the experiment for which we recruited mostly adult professionals. As you might expect, this population had different preferences than the teenagers, and so the average performance of the songs changed slightly. Nevertheless, they were just as influenced by one another’s behavior as the teenagers were, and so generated the same kind of inequality and unpredictability. 17
    What the Music Lab experiment really showed, therefore, was remarkably similar to the basic insight from Granovetter’s riot model—that when individuals are influenced by what other people are doing, similar groups of people can end up behaving in very different ways. This may not sound like a big deal, but it fundamentally undermines the kind of commonsense explanations that we offer for why some things succeed and others fail, why social norms dictate that we do some things and not others, or even why we believe what we believe. Commonsense explanations sidestep the whole problem of how individual choices aggregate to collective behavior simply by replacing the collective with a representative individual. And because we think we know why individual people do what they do, as soon as we know what happened, we can always claim that it was what this fictitious individual—“the people,” “the market,” whatever—wanted.
    By pulling apart the micro-macro problem, experiments like Music Lab expose the fallacy that arises from this form of circular reasoning. Just as you can know everything about the behavior of individual neurons and still be mystified by the emergence of