Iconoclast: A Neuroscientist Reveals How to Think Differently (20 page)

The amygdala seems to play the gatekeeper role in flagging the emotional response to faces. As we saw earlier, the amygdala solidifies primitive forms of learning like the association between cues and unpleasant events, especially physical ones. The amygdala also plays a critical role in social judgment. In a study of three patients who suffered complete destruction of their amygdalae, the neuropsychologists Ralph Adolphs, Daniel Tranel, and Antonio Damasio reported a dramatic impairment in judging trustworthiness. These patients were shown pictures of strangers and asked to judge their approachability and trustworthiness. All three patients judged these strangers as more trustworthy than normal, healthy control subjects did.
¹⁴
Similarly, when neuroscientists burned out monkeys’ amygdalae almost a century ago, the monkeys exhibited socially bizarre behavior such as using their mouths instead of their eyes to examine objects, and they became hypersexual.
¹⁵

David Amaral, a neuroscientist at the University of California, Davis, has reexamined the role the amygdala plays in social behavior. Through more precise lesion methods in monkeys, he has found that the amygdala’s role in social function hinges on its processing of environmental dangers.
¹⁶
Amaral has suggested that the amygdala acts as a break on social interactions when it perceives a potential adversary. Such a role is consistent with the wealth of data indicating the amygdala’s central function in fear conditioning and the development of specific phobias. It also explains why human patients with damage to their amygdala become impaired in their ability to evaluate trustworthiness and why monkeys with no temporal lobes try to have sex with almost any other monkey or object.

If facial appearance is so important to judging a person’s character, it follows that racial biases may originate in these same face circuits. Potential iconoclasts need to be aware of how this happens so that they
can take measures to calm the amygdalae of audiences. Elizabeth Phelps, a social psychologist at NYU, has been studying the neurobiology of racial prejudice. In one brain imaging experiment, Phelps presented Caucasian participants with photographs of African American and Caucasian male faces. All the men had short haircuts, no facial hair, and no distinctive clothing. Phelps found that the Caucasian participants consistently displayed more amygdala activation to the African American faces than the Caucasian ones. Moreover, the level of amygdala activation correlated with two subconscious measures of racial bias.
¹⁷
In a follow-up experiment, Phelps found the relationship also holds for African Americans viewing pictures of Caucasians, although others have recently found increased amygdala activation in African Americans viewing pictures of African Americans, too.
¹⁸
Regardless of how these racial biases are learned, their manifestation in the amygdala at the subconscious level means that they are effectively hardwired. Because the amygdala signals danger, the iconoclast needs to minimize the chance of triggering its activation in his intended audience. Things and people that look different set the amygdala on edge, while familiarity soothes it.

Arnold Schwarzenegger is a good example of an individual who has banked on his aura of familiarity to effect legislative change in California. A self-described iconoclast, he was born in 1947 in Austria. Schwarzenegger has traced his nonconformist tendencies to his childhood rebellion against a strict Austrian upbringing. “It was all about conforming. I was one who did not conform and whose will could not be broken. Therefore I became a rebel. Every time I got hit, and every time someone said, ‘you can’t do this,’ I said, ‘this is not going to be for much longer, because I’m going to move out of here. I want to be rich. I want to be somebody.’” Schwarzenegger also knows the power of appearance. “The bigger you are and the more impressive you look physically, the more people listen and the better you can sell yourself or anything else.”
¹⁹

On the surface, Schwarzenegger would appear to be an unlikely candidate for governor, especially a Republican one. But his aura of familiarity, coupled with the invincibility of the Terminator, made him an easy winner in California politics. Certainly, his legislative policies have gone far to the left of Republican ideology. From stem cell research to children’s health insurance, Schwarzenegger has taken stances that are nonconformist with party politics but resonate deeply with the masses. Were it not for Article II of the Constitution, which requires the president to be born in the United States, it is almost a sure bet that Schwarzenegger would be president.

Why the Brain Likes Familiarity

In November 2004,
Rolling Stone
magazine published its list of the five hundred greatest songs of all time. Although the editors gave the nod to Bob Dylan’s “Like a Rolling Stone,” it is the second song on their list that contains the most recognizable five notes in all of rock and roll history. For any fan of rock and roll, hearing Keith Richards’s fuzzed-out riff that opens “Satisfaction” can’t help but bring a smile to the face. It really is quite an impressive feat that the human brain can take five notes and instantly identify where they come from. In fact, two suffice for most people. Sure, the song is vastly overplayed, but it continues to show up on every list of top rock and roll songs of the past fifty years. One might debate endlessly the merits of the song and what accounts for its popularity, whether it’s the disaffected lyrics or the catchy riff itself. Regardless, the fact that it has become so familiar guarantees it a permanent place in the pantheon of popular music. The human brain comes to like that with which it is familiar. And it is this sort of familiarity that the successful iconoclast must strive for. Rightly or wrongly, people put their money into things that they are familiar with.

In the 1960s, the University of Michigan psychologist Robert Zajonc further refined our notion of how familiarity defines what we like. Using
pictures instead of music, Zajonc showed pictures of irregularly shaped octagons to his subjects. The pictures, however, were flashed so briefly on the screen that the subjects had insufficient time to process them. Later, Zajonc showed the pictures again and asked the subjects two questions. The first question asked how confident they were that they had seen a particular picture. The second question asked how much they liked it. Zajonc found that people liked pictures that they had seen previously, even though the pictures had been flashed so briefly that they were effectively unaware of having seen them. He termed this phenomenon “the mere exposure effect.”
²⁰

Does familiarity with someone increase the likelihood of doing business with him? A wealth of economic data suggests that the answer is yes. Gur Huberman, a professor of finance at Columbia University, has examined where investors place their money as a result of familiarity. People who own stock in Regional Bell Operating Companies (RBOCs) tend to invest in the companies that provide their service. For example, whether someone invests in BellSouth or NYNEX is determined primarily by whether they live in the South or the Northeast. Huberman found that the fraction of people investing in local RBOCs was 82 percent higher than that of the next RBOC. From an economic point of view, this is irrational. One should not expect a local company to be a superior investment to any of the other national companies that provide essentially the same service. All of the RBOCs are listed on the NYSE, so there is no barrier to investment in any of these companies. Yet the local bias remains.

People root for the home team, and they feel comfortable investing their money in a business that is familiar to them. Familiarity bias is not limited to telephone companies. U.S. equity managers tend to prefer domestic stocks, and their portfolios reflect this bias. This home-country bias extends to other countries as well. German business students, when compared with their American counterparts, view German stocks more favorably than American ones.
²¹

While familiarity increases the chances that people will like something, it also makes them feel comfortable. To bridge the gap between the mere exposure effect and the closing of a business deal, the iconoclast eventually needs to make his audience feel comfortable with his idea. From the perspective of the brain, familiar items are not necessarily more pleasurable or rewarding; it is simply that unfamiliar things tend to be alarming and potentially dangerous.
Familiarity quiets the amygdala
.

The iconoclast has several means at his disposal for increasing the familiarity of his idea with his intended audience. Publicity exposure and liberal use of mass media outlets certainly create an aura of familiarity. Schwarzenegger is proof of the benefits of good PR. Being prolific, like Picasso and Chihuly, also helps create an omnipresence of work and increases the chance that people will run into the iconoclast’s ideas. Exposure creates inroads to tamp down the amygdala, but neuro-economic evidence suggests that something else is required to elicit actual investment decisions. There is the issue of reputation.

Shadow Networks and Why Who Knows Whom Matters

Milgram’s lost-letter technique seems quaint, almost antiquated in today’s world of digital communication. Apart from the occasional holiday card, written mail has ceased to be a useful form of correspondence. And while grammarians and future historians may bemoan the death of letter writing, snail mail has suffered the fate of all technologies—obsolescence. Every technology, even one that has been around for millennia, such as written correspondence, will eventually be replaced by something that is more efficient. So one might wonder in today’s networked world whether people are really just six e-mail hops away from anyone in the digital domain as they are in the physical world.

In 2003, Duncan Watts, a professor at Columbia University who studies social networks, conducted a digital version of the Milgram
experiment.
²²
Watts set up a Web site where people could register to participate. Each of the 98,847 people who registered was randomly assigned to get an e-mail message to one of 18 targets. There was a huge attrition rate. Even though almost 100,000 people registered, data was recorded on 24,163 chains, and of these, only 384 reached their targets, for a 1.6 percent completion rate. Nevertheless, these 384 chains allowed Watts to estimate the average degrees of separation to be 4.05. But this estimate reflected the level of connectedness for successful chains only. Incomplete chains might have failed because some people were more distant and required more steps. Because each step incurred a probability of the person dropping the ball, the incomplete chains provided important data for the true degrees of separation. Taking this into account, Watts found the average degrees of separation to be closer to 7. This was a somewhat larger number than Milgram found, but then again these were international targets. Watts also found no evidence of funneling. He concluded that “social search appears to be largely an egalitarian exercise” and not dependent on a small minority of connectors.

On the surface, this may seem to be good news for iconoclasts. If there are many routes to reach any individual, then it might not really matter which route a person uses. This conclusion, however, ignores the issue of provenance. A message originating from a good friend or trusted business associate carries more weight than one coming from the high school acquaintance to whom you haven’t spoken in twenty years. And a message originating from a stranger carries almost no value at all. Watts’s study also underscored the high attrition rate of digital messages. Even in 2003, before spam really started to choke in-boxes, recipients tended to ignore these e-mail messages and effectively terminated a chain. If we make the rather optimistic assumption that the odds are fifty-fifty that a random recipient will pass along a message, after six steps, only 1.5 percent of the messages will remain—a percentage that is almost identical to the rate Watts found.

Perhaps the world really is bigger than we would like to think. Jon Kleinberg, a computer scientist at Cornell University, proved mathematically that small-world networks don’t arise from random connections.
²³
Messages won’t reach their intended recipient by bouncing randomly between people, in the hopes that someone will serve as a connector to another small world. People in a network need to know something about the other members, such as who they are likely to be connected to. You need a sort of shadow network, what Kleinberg called an
underlying lattice
, that serves as a black book of who knows whom.

Both kinds of networks, whom-you-know and who-knows-whom, played critical roles in the development of Linux, the first computer operating system created using the open-source model of software development. In 1991, Linus Torvalds, a Finnish computer science student, famously posted this query on the USENET list comp.os.minix:

Hello everybody out there using minix -

I’m doing a (free) operating system (just a hobby, won’t be big and professional like gnu) for 386(486) AT clones. This has been brewing since april, and is starting to get ready. I’d like any feedback on things people like/dislike in minix, as my OS resembles it somewhat (same physical layout of the file-system (due to practical reasons) among other things).
²⁴

Minix was a miniature version of the common, and bulky, operating system known as UNIX. It had the advantage of using very little memory, which meant it could fit within the paltry confines an IBM PC, which had less than 1 MB of RAM. Torvalds received a smattering of replies to his open call, but he also knew enough about what others were doing to not reinvent everything from scratch. Here is where Kleinberg’s shadow lattice came in handy. The USENET groups made such a network possible, providing a map of who was doing what and, most importantly, how to find people who could contribute chunks of computer code.