Brain Trust (17 page)

Paul Ekman has written books, including
Telling Lies
, is a frequent police trainer, and is scientific advisor to the show
Lie to Me
. His current research hopes to predict violent assaults ten to twenty seconds before they occur. He thinks he’s about two-thirds of the way to an answer. “It’ll at least allow you to duck,” he says.

You’ve seen the sign: BEWARE OF DOG! Yeah, that’s badass and all. But imagine a yard full of giant humanivorous plants. That’d be totally boss!

And if homicidal plants are your game, then the person to talk to is Louie Yang, ecologist at the University of California–Davis. “There’s a specific recipe for carnivorous plants,” Yang says. “You need ample sunlight, ample water, but a lack of nutrients.” This happens in rain forests, where the massive plant biomass sucks every last speck of nitrogen from the soil. And it happens in the high fens of the Sierra Mountains, where the boggy, sunbaked soil is nearly sterile.

In these nutrient-starved places, plants turn to the flesh of the living for food. Take, for example, the
Nepenthes rajah
, a pitcher plant common to the Borneo highlands. The
N. rajah
has sun
and water aplenty, but its growth is limited by the nutrient-poor soil, and so it’s evolved two foot-long traps with up to a gallon of digestive fluid, capable of trapping and eating creatures as large as mice.

A plant that eats small mammals rocks. But why stop there? Check this out:

When a pitcher plant catches a fly, it enlarges its fly-catching machinery. That makes evolutionary sense: Focus on what works. But when a plant starts focusing its resources on the creation of grabbing tools, its overall growth stalls—meaning it’ll never get big enough to consume, say, your prying next-door neighbor. Or even her cat.

So, once you’ve got a budding Audrey II, resist your urge to keep feeding her flies. Instead, now’s the time to start fertilizing her roots.

Yang caught wind of this trick when he noticed that the largest in a population of carnivorous plants was the one growing next to a pile of deer poop. Again, plants focus on what works: Nutrients entering through the roots signal the usefulness of a more extensive root system. More roots support a bigger plant. As long as the poop holds out the sucker will grow wide, strong, and large.

And this is cool: As a carnivorous plant starts to run out of nutrients, it’ll shift resources back to fly catching.

So once you’ve fertilized your floral army to appropriately monstrous size, starve it to reprioritize growth of its prey-grabbing mechanisms. A hungry plant is a dangerous plant.

When I visited Louie Yang’s lab at UC-Davis
, he was contemplating a refrigerator that held ten thousand cigar-shaped insect traps and wondering how he might most efficiently go about slitting them open and examining the contents under a microscope to see what egg or larval goodies they held. I asked if maybe there were grad students or other proverbial “people for that”-leaving Yang and his oversized brain free to more efficiently design and manage investigations. But Yang echoed many scientists I talked with, saying that having his fingers in the grunt work of data collection is the way he gets ideas-he needs to slit insect traps to generate questions.

“Look at cell phone cameras,” says Brian Sauser, complex systems expert at Stevens Institute of Technology. “Originally they were designed to take pictures of your family. Now everyone’s a reporter.” From a somewhat mundane design purpose came a use that’s fundamentally changed culture and society.

This is emergence: a behavior that arises spontaneously from a system. But just because any specific emergent behavior can only be reverse engineered and not forward engineered (you can tell how it came about, but couldn’t have predicted it), systems designers remain able to put in place elements that maximize the likelihood of emergence.

In fact, according to Sauser, this idea of emergent purpose has become one of the central forces in twenty-first-century systems
design. “It’s been about control,” he says, “but now we have to learn to build something and take our hands off the control.” Look at the evolving use of micromessaging sites like Twitter. Or at the system of fiber-optic lines that carries the data of the Internet itself. From a flexible infrastructure come crowdsourced uses a designer may never imagine. Build it, open it up, and functionality will come—and in this brave new world, emergent functionality may far outstrip the usefulness of a designer’s limited vision.

So how do you design a system with emergence in mind, be it a multicomponent technological marvel or simply a group of people working together on a project? How can you go about intentionally creating a system whose product exceeds your intention?

Sauser thinks of system design from the bottom up—as a combination of the basic building blocks of autonomy, belonging, connectivity, diversity, “and the interaction of the first four gives you emergence.”

Unfortunately, there’s frequently a trade-off, says Sauser. For example, systems of people tend to trade diversity for belonging (think of Salt Lake City). A similar trade-off can be true of connectivity and autonomy—once you streamline communication (connectivity) the temptation exists to use it for micromanagement, thus dooming autonomy.

But now imagine New York City. “At one level, it’s extremely diverse,” says Sauser. “You have Chinatown, Little Italy, etc.” But on another level it’s inclusive: “People came because by being different, they were normal.” Sauser points to New York City as a rare example of a system with both high belonging and high diversity. Despite the individualistic spirit commonly held as essential to the New York mentality, “people walking down the street don’t believe they’re isolated,” says Sauser. Instead, “People believe they’re part of something bigger.” Likewise, New Yorkers’ high connectivity detracts little from their autonomy.

Certainly people in New York City could be more diverse, autonomous, connected, or belonging, but somehow this system has managed to push all four factors fairly high simultaneously. And this is why, according to Sauser, so much culture, innovation, and vision emerge from the city—outcomes for which you could never specifically design.

The same combination characterizes the best teams. To maximize the chance for emergence from a hypothetical group of people, “Think about the first four characteristics as win/win or win/lose,” says Sauser. Try to increase each of these four factors without your group composition and protocols creating decreases elsewhere. For example, if you’ve brought diverse people together, you may need to train belonging. Or in a group with high autonomy, you may need to work to increase connectivity. Or in a team with massive belonging, you might need to ensure that team members remain able to work autonomously. You get the point.

You won’t ever reach 100 percent in any factor, but by edging each higher without ceding the others, you can maximize the chance that the system you design will create emergent products that neither you nor any individual member could imagine.

Does diversity have inherent value?
This may be the twenty-first century’s most important question. Think ecosystems, think countries and immigration policies, think financial markets. Scott Page, professor of complex systems and political science at the University of Michigan–Ann Arbor and author of the book
Diversity and Complexity
, explored the question in the realm of problem solving. First, he and collaborator Lu Hong gathered a group of college students and tested them on a range of puzzles. Then they wondered: How would a team randomly chosen from this pool perform against a team of the top problem solvers? What they found is surprising—diverse teams outperformed homogenous teams of all-stars—but only if three conditions existed: (1) a baseline level of competence in all puzzlers (no total duds); (2) a wide enough range of puzzle types to nix the power of specialization (a complex system); and (3) a wide enough puzzler pool to ensure diversity is present.

Imagine a basketball team. “One power forward is great and two power forwards is good, but three is ridiculous,” says Page. At a certain density of power forwards, you’ll get every rebound but your homogeneity makes you susceptible to counter by one specific strategy: the full-court press. A team of power forwards would never get the ball up the floor.

In complex systems like basketball teams, “the hope is you create this interesting, innovative, pulsing, growing system,” says Page. If your team does something noncomplex, like picking apples, you’d want a team of strong apple pickers. If your team’s going to compete with Apple, Page shows that diversity for diversity’s sake, as long as everyone reaches baseline competence, has value.

Do you concentrate best under pressure?
Do you contemplate best when melancholic? Are you most analytic when angry? A pair of studies shows it’s best when mood matches the problem. Specifically, researchers at Northwestern University found that when they showed subjects a short comedy routine, amused subjects were then better at solving word puzzles with sudden insight. On the flip side, Dutch researchers showed that teams better solved analytic tasks when a certain degree of animosity existed in the room.

If you’re a laid-off bum looking for work while living in a van down by the river, wouldn’t it be great to know which field is poised for the kind of leap your skills could help create—aka, who’ll hand over the $$ for work you’re naturally inclined to do?

You’ve heard about evolution in industry—how today’s techniques are built on yesterday’s innovations—and it turns out there’s a common progression of this evolution that allows you to predict, surf, and potentially profit from what’s next in any field. “From semiconductor manufacturing to agriculture to aeronautics to firearms to professional services like architecture, all industries seem to fit a developmental model of six stages,” says Roger Bohn, director of the Global Information Industry Center at the University of California–San Diego.

An industry starts as a craft, which you learn through experience or apprenticeship. “It’s the ‘lone gunman’ or ‘intrepid flier’ stage,” says Bohn. Picture a gent in a leather helmet and goggles
peering over a precipice with a stick-and-skin glider strapped to his back.

Some of these people survive, and enter what Bohn calls “the rules-and-instruments stage.” The effort becomes collaborative as the (lucky) intrepid flier adopts and installs others’ innovations that allow him to fly in a more structured way. The Wright brothers took to the sky in 1903, but it was Paul Kollsman who added the accurate altimeter in 1928 and Jimmy Doolittle who showed pilots how to use the artificial horizon in 1932. As you’ll note, both when you’re going to hit the ground and at what angle you’re likely to hit it are good things to know. “Before the artificial horizon, if you flew into a cloud, you were probably gonna die,” says Bohn. This applied even to expert pilots—we use our inner ear to tell us which way is up, and in an airplane it doesn’t work right.