Incognito (23 page)
Authors: David Eagleman
I propose that a useful index of consciousness is the capacity to successfully mediate conflicting
zombie systems. The more an animal looks like a jumble of hardwired input–output subroutines, the less it gives evidence of consciousness; the more it can coordinate, delay gratification, and learn new programs, the more conscious it may be. If this view is correct, in the future a battery of tests might be able to yield a rough measure of a species’ degree of consciousness. Think back to the befuddled rat we met near the beginning of the chapter, who, trapped between the drive to go for the food and the impulse to run from the shock, became stuck in between and oscillated back and forth. We all know what it’s like to have moments of indecision, but our human arbitration between the programs allows us to escape these conundrums and make a decision. We quickly find ways of cajoling or castigating ourselves toward one outcome or the other. Our CEO is sophisticated enough to get us out of the simple lockups that can thoroughly hamstring the poor rat. This may be the way in which our conscious minds—which play only a small part in our total neural function—really shine.
Let’s circle back to how this allows us to think about our brains in a new way—that is, how the team-of-rivals framework allows us to address mysteries that would be inexplicable if we took
the point of view of traditional computer programs or artificial intelligence.
Consider the concept of a secret. The main thing known about secrets is that keeping them is unhealthy for the brain.
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Psychologist
James Pennebaker and his colleagues studied what happened when rape and incest victims, acting out of shame or guilt, chose to hold secrets inside. After years of study, Pennebaker concluded that “the act of
not
discussing or confiding the event with another may be more damaging than having experienced the event per se.”
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He and his team discovered that when subjects confessed or wrote about their deeply held secrets, their health improved, their number of doctor visits went down, and there were measurable decreases in their stress hormone levels.
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The results are clear enough, but some years ago I began to ask myself how to understand these findings from the point of view of brain science. And that led to a question that I realized was unaddressed in the scientific literature: what
is
a secret, neurobiologically? Imagine constructing an artificial neural network of millions of interconnected neurons—what would a secret look like here? Could a toaster, with its interconnected parts, harbor a secret? We have useful scientific frameworks for understanding Parkinson’s disease, color perception, and temperature sensation—but none for understanding what it means for the brain to have and to hold a secret.
Within the team-of-rivals framework, a secret is easily understood: it is the result of struggle between competing parties in the brain. One part of the brain wants to reveal something, and another part does not want to. When there are competing votes in the brain—one for telling, and one for withholding—that defines a secret. If no party cares to tell, that’s merely a boring fact; if both parties want to tell, that’s just a good story. Without the framework of rivalry, we would have no way to understand a secret.
***
The reason a secret is experienced consciously is because it results from a rivalry. It is not business as usual, and therefore the CEO is called upon to deal with it.
The main reason not to reveal a secret is aversion to the long-term consequences. A friend might think ill of you, or a lover might be hurt, or a community might ostracize you. This concern about the outcome is evidenced by the fact that people are more likely to tell their secrets to total strangers; with someone you don’t know, the neural conflict can be dissipated with none of the costs. This is why strangers can be so forthcoming on airplanes, telling all the details of their marital troubles, and why confessional booths have remained a staple in one of the world’s largest religions. It may similarly explain the appeal of prayer, especially in those religions that have very personal gods, deities who lend their ears with undivided attention and infinite love.
The newest twist on this ancient need to tell secrets to a stranger can be found in the form of websites like
postsecret.com
, where people go to anonymously disclose their confessions. Here are some examples: “When my only daughter was stillborn, I not only thought about kidnapping a baby, I planned it out in my head. I even found myself watching new mothers with their babies trying to pick the perfect one”; “I am almost certain that your son has autism but I have no idea how to tell you”; “Sometimes I wonder why my dad molested my sister but not me. Was I not good enough?”
As you have doubtless noticed, venting a secret is usually done for its own sake, not as an invitation for advice. If the listener spots an obvious solution to some problem revealed by the secret and makes the mistake of suggesting it, this will frustrate the teller—all she
really
wanted was to tell. The act of telling a secret can itself be the solution. An open question is why the receiver of the secrets has to be human—or human-like, in the case of deities. Telling a wall, a lizard, or a goat your secrets is much less satisfying.
When I was a child, I assumed that we would have robots by now—robots that would bring us food and clean our clothes and converse with us. But something went wrong with the field of
artificial intelligence, and as a result the only robot in my home is a moderately dim-witted self-directing vacuum cleaner.
Why did artificial intelligence become stuck? The answer is clear: intelligence has proven itself a tremendously hard problem. Nature has had an opportunity to try out trillions of experiments over billions of years. Humans have been scratching at the problem only for decades. For most of that time, our approach has been to cook up intelligence from scratch—but just recently the field has taken a turn. To make meaningful progress in building thinking robots, it is now clear that we need to decipher the tricks nature has figured out.
I suggest that the team-of-rivals framework will play an important role in dislodging the jammed field of artificial intelligence. Previous approaches have made the useful step of dividing labor —but the resulting programs are impotent without differing opinions. If we hope to invent robots that think, our challenge is not simply to devise a subagent to cleverly solve each problem but instead to ceaselessly reinvent subagents, each with overlapping solutions, and then to pit them against one another. Overlapping factions offer protection against degradation (think of cognitive reserve) as well as clever problem solving by unexpected approaches.
Human programmers approach a problem by assuming there’s a
best
way to solve it, or that there’s a way it
should
be solved by the robot. But the main lesson we can extract from biology is that it’s better to cultivate a team of populations that attack the problem in different, overlapping manners. The team-of-rivals framework suggests that the best approach is to abandon the question “What’s the most clever way to solve that problem?” in favor of “Are there multiple, overlapping ways to solve that problem?”
Probably the best way to cultivate a team is with an evolutionary
approach, randomly generating little programs and allowing them to reproduce with small mutations. This strategy allows us to continuously discover solutions rather than trying to think up a single perfect solution from scratch. As the biologist
Leslie Orgel’s second law states: “Evolution is smarter than you are.” If I had a law of biology, it would be: “Evolve solutions; when you find a good one,
don’t stop
.”
Technology has so far not taken advantage of the idea of a democratic architecture—that is, the team-of-rivals framework. Although your computer is built of thousands of specialized parts, they never collaborate or argue. I suggest that conflict-based, democratic organization—summarized as the team-of-rivals architecture—will usher in a fruitful new age of biologically inspired machinery.
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The main lesson of this chapter is that you are made up of an entire parliament of pieces and parts and subsystems. Beyond a collection of local expert systems, we are collections of overlapping, ceaselessly reinvented mechanisms, a group of competing factions. The conscious mind fabricates stories to explain the sometimes inexplicable dynamics of the subsystems inside the brain. It can be disquieting to consider the extent to which all of our actions are driven by hardwired systems, doing what they do best, while we overlay stories about our choices.
Note that the population of the mental society does not always vote exactly the same way each time. This recognition is often missing from discussions of consciousness, which typically assume that what it is like to be you is the same from day to day, moment to moment. Sometimes you’re able to read well; other times you drift. Sometimes you can find all the right words; other times your tongue is tangled. Some days you’re a stick in the mud; other days you throw caution to the wind. So who’s the real you? As
the French essayist
Michel de Montaigne put it, “There is as much difference between us and ourselves as there is between us and others.”
A nation is at any moment most readily defined by its political parties in power. But it is also defined by the political opinions it harbors in its streets and living rooms. A comprehensive understanding of a nation must include those parties that are not in power but that could rise in the right circumstances. In this same way, you are composed of your multitudes, even though at any given time your conscious headline may involve only a subset of all the political parties.
Returning to
Mel Gibson and his drunken tirade, we can ask whether there is such a thing as “true” colors. We have seen that behavior is the outcome of the battle among internal systems. To be clear, I’m not defending Gibson’s despicable behavior, but I am saying that a team-of-rivals brain can naturally harbor both racist and nonracist feelings.
Alcohol is not a
truth serum. Instead, it tends to tip the battle toward the short-term, unreflective faction—which has no more or less claim than any other faction to be the “true” one. Now, we may
care
about the unreflective faction in someone, because it defines the degree to which they’re
capable
of antisocial or dangerous behavior. It is certainly rational to worry about this aspect of a person, and it makes sense to say, “Gibson is capable of
anti-Semitism.” In the end, we can reasonably speak of someone’s “most dangerous” colors, but “true” colors may be a subtly dangerous misnomer.
With this in mind, we can now return to an accidental oversight in Gibson’s apology: “There is no excuse, nor should there be any tolerance, for anyone who thinks or expresses any kind of anti-Semitic remark.” Do you see the error here? Anyone who
thinks
it? I would love it if no one ever thought an anti-Semitic remark, but for better or worse we have little hope of controlling the pathologies of xenophobia that sometimes infect the alien systems. Most of what we call thinking happens well under the surface of cognitive control. This analysis is not meant to exculpate Mel
Gibson for his rotten behavior, but it
is
meant to spotlight a question raised by everything we’ve learned so far: if the conscious you has less control over the mental machinery than we previously intuited, what does all this mean for responsibility? It is to this question that we turn now.
*
Although this system works, it strikes me that there is a way to better match this business model to the neurobiology. The problem is that weight loss demands a sustained effort, while the approaching deadline for the loss of money is always distantly in the future until the day of reckoning is suddenly upon you. In a neurally optimized model, you would lose a little money each day until you have shed the ten pounds. Each day, the amount you’d lose would increase by fifteen percent. So every day brings the immediate emotional sting of monetary loss, and the sting constantly grows worse. When you’ve lost the ten pounds, then you stop losing money. This encourages a sustained diet ethic over the entire time window.
**
There may be other advantages to having a large collection of alien systems with flexible allocation. For example, it may reduce our predictability to predators. If you had only one subroutine and ran it every time, a predator would know exactly how to pick you off (think of the crocodiles grazing on the wildebeest that swim across African rivers the same way, at the same time, every year). More complex collections of alien systems enjoy not only flexibility but a better shot at unpredictability.
***
Some people are constitutionally incapable of keeping a secret, and this balance may tell us something about the battles going on inside them and which way they tip. Good spies and secret agents are those people whose battle always tips toward long-term decision making rather than the thrill of telling.
Blameworthiness Is the Wrong Question
On the steamy first day of August 1966,
Charles Whitman took an elevator to the top floor of the University of Texas Tower in Austin.
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The twenty-five-year-old climbed three flights of stairs to the observation deck, lugging with him a trunk full of guns and ammunition. At the top he killed a receptionist with the butt of his rifle. He then shot at two families of tourists coming up the stairwell before beginning to fire indiscriminately from the deck at people below. The first woman he shot was pregnant. As others ran to help her, he shot them as well. He shot pedestrians in the street and the ambulance drivers that came to rescue them.
