Chapter Three, Part III

Herders may think they want to be right, and perhaps they do. But for the most part, they’re following the herd because that’s where it’s safest. They’re assuming that John Maynard Keynes was right when he wrote, in The General Theory of Employment, Interest and Money, “Worldly wisdom teaches that it is better for reputation to fail conventionally than to succeed unconventionally.” And yet there is the fact that the crowd is right much of the time, which means that paying attention to what others do should make you smarter, not dumber. Information isn’t in the hands of one person. It’s dispersed across many people. So relying on only your private information to make a decision guarantees that it will be less informed than it could be. Can you safely rely on the information of others? Does learning make for better decisions?

The answer is that it depends on how we learn. Consider the story of plank-road fever, which the economist Daniel B. Klein and the historian John Majewski uncovered a decade ago. In the first half of the nineteenth century, Americans were obsessed with what were then known as “internal improvements”—canals, railroads, and highways. The country was growing fast and commerce was booming, and Americans wanted to make sure that transportation—or rather the lack of it—didn’t get in the way. In 1825, the Erie Canal was completed, linking New York City to Lake Erie via a 363-mile-long channel that cut travel time from the East Coast to the western interior in half and cut shipping costs by 90 percent. Within a few years, the first local rail lines were being laid, even as private companies were busy building private turnpikes all over the eastern part of the country.

There was a problem, though, that all this feverish building did not solve. Although the canals and railroads would do an excellent job of connecting major towns and cities (and of turning small villages into thriving commercial hubs merely by virtue of going through them), they made it no easicr for people who lived outside of those towns—which is to say, most Americans—to get their goods to market, or for that matter to get from one small town to the next. There were local public roads, different stretches of which were maintained by individual villages (much as in a city people take care, at least in theory, of the patch of sidewalk in front of their apartment), but these roads were usually in pretty bad shape. “They had shallow foundations, if any, and were poorly drained,” write Klein and Majewski. “Their surfaces were muddy ruts in wet weather, dusty ruts in dry; travel was slow and extremely wearing on vehicles and on the animals that drew them.”

An engineer named George Geddes, though, believed he had uncovered a solution to this problem: the plank road. The plank road—which, as its name suggests, consisted of wooden planks laid over two lines of timber—had been introduced in Canada in the early 1840s, and after seeing evidence of its success there, Geddes was convinced it would work in the United States as well. There was no question that a plank road was superior to a rutted, muddy pth. What wasn’t clear was whether a plank road—which would, in most cases, be privately owned and supported by toils—would last long enough to be cost-effective, Geddes believed that a typical road would last eight years, more than long enough to provide a reasonable return on investment, and so, in 1846, he convinced some of his fellow townsmen in Sauna, New York, to charter a company to build the state’s first plank road.

The road was a roaring success, and soon plank-road fever swept through first New York, then through the mid-Atlantic states and the Midwest. Geddes became a kind of spokesman for the industry, even as other promoters played a similar role in states across the country. Within a decade, there were 352 plank-road companies in New York, and more than a thousand in the United States as a whole.

Unfortunately, the whole business was built on an illusion. Plank roads did not last the eight years Geddes had promised (let alone the twelve years that other enthusiasts had suggested). As Klein and Majewski show, the roads’ actual life span was closer to four years, which made them too expensive for companies to maintain. By the late 1850s, it was clear that the plank road was not a transportation panacea. And though a few roads—including a thirteen-mile stretch along what is now Route 27A in Jamaica, Queens—remained in operation until the l880s, by the end of the Civil War almost all of them had been abandoned.

PLANK-ROAD FEVER WAS a vivid example of a phenomenon that economists call an “information cascade.” The first Salina road was a success, as.were those which were built in the years immediately following. People who were looking around for a solution to the problem of local roads had one ready-made at hand. As more people built plank roads, their legitimacy became more entrenched, and the desire to consider other solutions shrank. It was years before the fundamental weakness of the roads—they didn’t last long enough—became obvious, and by that time plank roads were being built all over the country

Why did this happen? The economists Sushil Bikhchandani, David Hirshleifei and Ivo Welch, who offered the first real model of an information cascade, suggest that-it works like this. Assume you have a large group of people, all of whom have the choice of going to either a new Indian restaurant or a new Thai place. The Indian restaurant is better (in an objective sense) than the Thai place. And each person in the group is going to receive, at some point, a piece of information about which restaurant is better. But the information is imperfect. Sometimes it will be wrong—that is, it will say the Thai place is better when it’s not—and will guide a person in the wrong direction. So to supplement their own information, people will look at what others’are doing. (The economists assume that everyone knows that everyone else has a piece of good information, too.)

The problem starts when people’s decisions are not made all at once but rather in sequence, so that some people go to one of the two restaurants first and then everyone else follows in order. Remember, the information people have is imperfect. So if the first couple of people happen to get bad information, leading them to believe that the Thai restaurant is great, that’s where they’ll go. At that point, in the cascade model, everyone who follows assumes— even if they’re getting information telling them to go to the Indian restaurant—that there’s a good chance, simply because the Thai place is crowded, that it’s better. So everyone ends up making the wrong decision, simply because the initial diners, by chance, got the wrong information.

In this case, a cascade is not the result of mindless trendfollowing, or conformity or peer pressure. (“Everyone likes that new Britney Spears song, so I will, too!”) People fall in line because they believe they’re learning something important from the exam- pie of others. In the case of the plank roads, for instance, it wasn’t simply that George Geddes was a smooth talker, or that townspeople across the country said, “We just have to have a new plank road because the town across the river has one.” Plank-road fever spread because plank roads really seemed to be a better solution. They cut travel time between towns in half. You could ride on them in any kind of weather.-And they allowed small farmers to expand the markets for their goods far beyond what had previously been possible. These were genuine improvements, and as more and more plank roads were built, the fact that those improvements were real and long lasting seemed increasingly plausible. Each new road that was built was in a sense telling people that plank roads worked. And each new road that was built made coming up with an alternative seem increasingly improbable.

The fundamental problem with an information cascade is that after a certain point it becomes rational for people to stop paying attention to their OWfl knowledge—their private information— and to start looking instead at the actions of others and imitate them. (If everyone has the same likelihood of making the right choice, and everyone before you has made the same choice, then you should do what everyone else has done.) But once each individual stops relying on his OWfl knowledge, the cascade stops becoming informative, Everyone thinks that people are making decisions based on what they know, when in fact people are making decisions based on what the.y think the people who came before them knew. Instead of aggregating all the information individuals have, the way a market or a voting system does, the cascade becomes a sequence of uninformed choices, so that collectively the group ends up making a bad decision—spending all that money on plank roads.

That original model is far from the only theory of how cascades work, of course. In The Tipping Point, for instance, Malcolm Gladwell offered a very different account, which emphasized the importance of particular kinds of individuals—what he called mavens, connectors, and salesmen—in spreading new ideas. In Bikhchandani, Hirshleifer, and Welch’s model of cascades, everyone had as much private information as everyone else. The only thing that made the early adopters of a product more influential was the fact that they were early, and so their actions were the ones that everyone who came after them observed. In Gladwell’s world, some people are far more influential than others, and cascades (he writes of them as epidemics) move via social ties, rather than being a simple matter of anonymous strangers observing each other’s behavior. People are still looking for information, but they believe that the ones who have it are the mavens, connectors, and salesmen (each of whom has a different kind of information).

Do cascades exist? Without a doubt. They are less ubiquitous than the restaurant-going model suggests, since, as Yale economist Robert Shiller has suggested, people don’t usually make decisions in sequence. “In most cases,” Shiller writes, “many people inde -pendentl choose their. action based on their own signals, without observing the actions of others.” But there are plenty of occasions when people do closely observe the actions of others before making their own decisions. In those cases, cascades are possible, even likely. That is not always a bad thing. For instance, one of the most important and valuable innovations in American technological history was made possible by the orchestrating of a successful information cascade. The innovation was the humble screw, and in the 1860s a man named William Sellers, who was the most prominent and respected machinist of his era at a time when the machine-tool industry was the rough equivalent of the technology industry in the 1990s, embarked on a campaign to get America to adopt a standardized screw, which happened to be of his own design. When Sellers started his campaign, everyAmerican screw had to be handmade by a machinist, This obviously limited the possibilities for mass production, but it also allowed the machinists to protect their way of life. In economic terms, after all, anything tailor-made has the advantage of locking in customers. If someone bought a lathe from a machinist, that person had to come back to the machinist for screw repairs or replacements. But if screws became interchangeable, customers would need the craftsmen less and would worry about the price more.

Sellers understood the fear. But he also believed that interchangeable parts and mass production were inevitable, and the screw he designed was meant to be easier, cheaper, and faster to produce than any other. His screws fit the new economy, where a premium was placed on speed, volume, and cost. But because of what was at stake, and because the machinist community was so tight-knit, Sellers understood that connections and influence would shape people’s decisions. So over the next five years, he targeted influential users, like the Pennsylvania Railroad and the U.S. Navy, and he successfully created an air of momentum behind the screw. Each new customer made Sellers’s eventual triumph seem more likely, which in turn made his eventual triumph more likely. Within a decade the screw was on its way to becoming a national standard. Without it, assembly-line production would have been difficult at best and impossible at worst. In a sense, Sellers had helped lay the groundwork for modern mass production.

Sellers’s story is of a beneficial cascade. The screw’s design was, by all accounts, superior to its chief competitor, a British screw. And the adoption of a standard screw was a great leap forward for the U.S. economy. But there is an unnerving idea at the heart of Sellers’s story: if his srew was adopted because he used his influence and authority to start a cascade, we were just lucky that Sellers happened to design a good screw. If the machinists were ultimately following Sellers’s lead, rather than acting on their own sense of which screw was better, it was pure chance that they got the answer right.

In other words, if most decisions to adopt new technologies or social norms are driven by cascades, there is no reason to think that the decisions we make are, on average, good ones. Collective decisions are most likely to be good ones when they’re made by people with diverse opinions reaching independent conclusions, relying primarily on their private information. In cascades, none of these things are true. Effectively speaking, a few influential people—either because they happened to go first, or because they have particular skills and fill particular holes in people’s social networks—determine the course of the cascade. In a cascade, people’s decisions are not made independently, but are profoundly influenced—in some cases, even determined—by those around them.

We recently experienced perhaps the most disastrous information cascade in history which was the bubble of the late 1990s in the telecommunications business. In the early days of the Internet, traffic was growing at the rate of 1,000 percent a year. Beginning in 1996 or so, that rate slowed dramatically (as one would expect). But no one noticed. The figure “1,000 percent” had become part of the conventional wisdom, and had inspired telecom companies to start investing tens, and eventually hundreds, of billions of dollars to build the capacity that could handle all that traffic. At the time, not investing seemed tantamount to suicide. Even if you had doubts about whether the traffic would ever materialize, everyone around you was insisting that it would. It wasn’t until after the bubble burst, when most of the telecom companies were either bankrupt or on the verge of going out of business, that the conventional wisdom was seriously questioned and found wanting.


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