by Jeff Stibel
I
Of course, you should already know all about networks because you have a pretty sophisticated one right inside your head. Our brains are perhaps the most complex networks but, like ant colonies, they too have humble parts.
Until recently, the brain was truly a mystery. It is only in the last 50 years—with the emergence of new brain-imaging technology—that we have been able to peer into our minds. Before that point, we considered the brain a peculiarity, something unknowable, beyond science, even mystical. Many people still hold this belief today. It’s easy for us to compare the human heart to a pump, the eye to a camera lens, and a bone joint to a hinge. What analogy could there possibly be to the brain—a three-pound sticky lump of wrinkled matter lying silently in the skull?
Ants.
Turns out, the brain is nothing more than an ordinary organ doing extraordinary mechanics. Like a colony of ants, the brain is basically a huge network, albeit composed of neurons instead of ants. There are around a hundred billion neurons in the human brain, each less than a millimeter in size. Individual neurons are pretty dumb—each neuron does only one thing: it turns on and off. Collectively, however, neurons are capable of doing robust calculations, making decisions, communicating, and storing information. Individual neurons communicate through chemicals (like the ants) but also through electrical currents. These tightly packed neurons work together, forming patterns that allow us to think, move, and communicate. “It’s like they are sending each other little Twitter messages that have no content; they just use the rate at which they receive them to decide what to do next. It’s a system of communication where the interaction itself is the whole message.” Dr. Gordon said this of her ants, but it could just as easily have been said of the neurons in her brain.
Like an ant colony, the human brain grows rapidly early on. The growth of our early years helps create network connections. We’re talking about one hundred billion neurons connected to each other a hundred trillion times. Those connections are nothing more than a way of passing along little bits of on/off information. This is the language of the mind. Combine enough simple messages and pretty soon they become complex: 300,021 firing neurons (neurons that are turned “on”) combined with 22,011 suppressed (“off”) neurons in one brain region can yield a pretty sophisticated message—“Don’t forget to turn off the stove.”
But don’t think that neurons are what make us smart any more than an ant makes a colony smart. Both ants and neurons are inept without the networks to which they belong. Left to their own devices, for example, certain ants outside of their colony will move in circles until they die from exhaustion. In humans, most of our neurons are formed by birth, yet we remain feeble infants. The network connections also don’t make us smart. We actually lose most of our connections as we grow older. The brain prunes its weakest links regularly and removes faulty neurons in a natural process called “cellular suicide.” It replaces sheer quantity with quality, making us smarter without the need for additional volume. When the brain stops growing and reaches a point of equilibrium in terms of quantity, it starts to grow in terms of quality. We gain intelligence and become wise.
That is an important biological point and is worth repeating: as the brain shrinks, it grows wiser. Dr. Gordon’s harvester ant colonies do the exact same thing. They hit equilibrium during the fifth year and shed off all but about 10,000 ants. Remember, when the colony stops growing, it begins to reproduce—the fertile females and the male ants get sent off to mate and create new colonies. That prevents the original colony from growing too large. At this point, things change for the colony. Much like the neural network of the human brain, the ant colony grows smaller and paradoxically gets wiser. Their reactions to various incidents become quicker, more precise, and more consistent.
Dr. Gordon knows this because she goes out and harasses the ants—messing up their nests, spreading toothpicks everywhere and the like. She has learned that when she does these experiments with colonies that are five years or older (that is, the ones that have reached equilibrium), they are consistent in their reactions from one time to the next. They’re “much more homeostatic. The worse things get, the more I hassle them, the more they act like undisturbed colonies, whereas the young, small colonies are much more variable.”
After completing its explosive growth phase, the colony seems to change its focus from quantity to quality. The colony itself becomes an intelligent network, just like the human brain. And when you look to nature more broadly, it quickly becomes clear that this pattern is true across all biological networks.
II
In the history of technology, we have often looked toward nature as a guide for our newest innovations. We trained our sights on birds to build the first airplane, on the heart to create pumps, on the eye to create a lens. So it should come as no surprise that the greatest technology of our lifetime also has its roots in nature.
The internet was created in the 1960s but didn’t gain widespread adoption until the onset of the World Wide Web in 1993. It is hard to believe how young the internet is from an evolutionary point of view. Most people can’t imagine living without it: a recent survey found that the average person is more willing to forgo coffee, sleep, TV, even sex, than to give up online access. Tufts University philosopher Dan Dennett likened it to an alien invasion in which we were taken hostage and voluntarily gave up our most primal needs and desires. Some psychologists claim that we created a technology that is now rewiring our brains. Despite its impact on our lives and our businesses (for better or worse), very few people understand what the internet actually is or how it is evolving.
The internet is, as the name implies, fundamentally a network. Just replace Deborah Gordon’s ants and pheromones with computers and broadband lines. As revolutionary as it is, the irony is that there is nothing terribly sophisticated about the internet. The internet is a combination of two core technologies: the computer and the telephone. Telephones are tools for communication. Computers, for their part, compute and store. Put them together and you have yourself an internet.
Unlike ants, the internet has scaled to epic proportions. There are 2.4 billion people online, surfing over 600 million websites. One site alone, YouTube, did more traffic last year than the entire internet did in 2000. Netflix, our online local video shop, drives even more traffic than YouTube. Facebook now has more users than the entire internet had in 2004. Mobile internet traffic independently grew 70 percent in 2012 and is now twelve times the size of the entire global internet in 2000.
The internet handles this growth with a little-known but fundamentally important technology called Transmission Control Protocol (TCP). TCP is a simple and elegant network technique that allows efficient transmission of information. It works by monitoring the speed of information retrieval and sending additional information only at that same speed. If information flow is fast—because relatively few people are on the internet at that time—information return will be fast; otherwise, TCP will slow down the internet. With this, it creates a state of equilibrium, thereby avoiding a risk that the internet will become congested and stop altogether. TCP is the reason the internet was able to scale from a few computers to the billions that exist today. The alternative to TCP would be constant bottlenecks, like a crowded highway system without stoplight on-ramps.
TCP was invented by a couple of internet pioneers in 1974, but the technology was discovered through evolution millions of years prior. In 2012, none other than Deborah Gordon and one of her colleagues realized that ants use TCP to forage for food. Ants are sent out of the colony in clusters to determine food availability. When food is plentiful, more ants are sent to forage; when food is scarce, TCP restricts the flow of ants. Gordon and her colleague predictably dubbed their findings “the anternet.”
But TCP is not uniquely an anternet peculiarity. The brain, too, regulates the flow of information. In fact, the brain has built-in TCP filters
that limit the rate of information flow. The brain regulates that information transmission based on neuronal feedback. In other words, each neuron independently regulates the flow of information depending on the capacity of the network and the task at hand.
In effect, the internet is a brain. This analogy works on many levels, certainly with regard to TCP. But you can push further and compare computers on the internet to neurons in the brain. Neurons are connected to each other with axons and dendrites, just as computers have broadband connections. Our memory system, with its distributed links from one memory to another, is similar to websites and their respective links. And the best memories, the most popular and relevant ones, have the most links. The founders of Google used this trick when creating Google’s search algorithms: they reasoned that they could look at website links and determine relevance depending on how many links a website had.
The internet is simply a network that enables storage, computing, and communication. If you own a smartphone or a laptop today, you are as much a part of the internet as is the mainframe at MIT. Here’s the kicker: that’s all the brain is as well. When you break it down to its fundamental building blocks, the brain is just like the internet: a computing, storage, and communication device. And so is an ant colony. The internet is an ant colony is a brain.
III
There is a curve that has followed me throughout my career. It is not a normal distribution curve; in fact, it doesn’t look anything like a bell. It is abnormal, yet I saw it regularly in science—first as a doctoral student, then throughout my research, and later beyond my primary field. As I began my business career, it appeared everywhere, but I couldn’t make sense of it. It is rarely spoken about in technology circles, yet it is persistent there as well. The curve appears in brains, ants, the internet, and virtually all other networks. It is a curve of success and looks like this:
Image 2.1: The Network Curve
Biological networks all follow similar paths and obey simple laws of nature. It should come as no surprise that technology’s greatest networks do so as well. What is surprising, however, is how predictable these networks are and how little of that predictability we actually use to advance technology. The biological basis of TCP is millions of years old, and we have understood it in terms of the brain for at least 100 years. Yet when it came time to “invent” TCP for the internet, we did it from scratch, the hard way. We don’t need to wonder whether the internet, or any other network, would have developed quicker “had we known” because we do actually know.
And it is not just the internet or even just technology that can benefit from an understanding of how networks function. All businesses, all consumers, all individuals can stay ahead of the turbulence and create an environment of success by understanding what lies ahead. Networks are pretty enigmatic, but they are also predictable.
Network laws are easily understood and have profound implications that enable us to predict where a network is headed. Want to know whether your friends will be on Facebook? How about whether you will be using Google in five years? Is Apple going to remain the golden stock? What’s the next big thing? All of these questions have answers, and they come in the form of what happens to biological networks.
Image 2.2: Three Phases of Networks
There are three phases to any successful network: first, the network grows and grows and grows exponentially; second, the network hits a breakpoint, where it overshoots itself and overgrows to a point where it must decline, either slightly or substantially; finally, the network hits equilibrium and grows only in the cerebral sense, in quality rather than in quantity.
Phase 1: Growth
Internets, ant colonies, and brains all start small, grow steadily, and then explode into hypergrowth. In nature, all species multiply as much as resources allow. This expansion may start linearly, but it quickly becomes exponential. Populations of plants, animals, yeast, and brain cells grow unencumbered until they reach the maximum quantity that the environment can sustain, the carrying capacity of an ecosystem.
If you put one bacterium in a Petri dish with some nutrients, the bacteria population will literally double every minute until the dish is completely full and can’t grow anymore, which only takes about an hour. In the human brain, we see a rapid expansion of neurons (called neurogenesis) in utero, where our brain size peaks at around 100 billion neurons. A fetus can generate an astronomical 250,000 neurons per minute.
There is a good evolutionary reason for this, and survival often depends on it. The world is a competitive place, and the best way to stomp out potential rivals is to consume all the available resources necessary for survival. Otherwise, the risk is that someone else will come along and use those resources to grow and eventually encroach on the ones you need to survive. The same is true of technology and business: if you don’t dominate a market, you will give potential upstarts an opportunity to grow and eventually compete with you. Monopolies prevent competition, which is as good in business as it is in nature—if, that is, you are the monopoly.
Remember the early days of the internet? It started as a network of only a few connected computers, growing slowly in the early days but expanding rapidly thereafter. Around the year 2000, the number of devices connected to the internet exploded, growing to five billion within eight years. There are now more devices connected to the internet than there are people on earth.
It is in this exponential growth phase that most networks die. In biology, species are weeded out here through natural selection. Very few organisms have the fitness to ultimately hit the growth curve that ensures sustainability. In technology, 95 percent of all innovations don’t make it through this critical phase. We can look back and clearly see the tremendous growth in the early days of Google, Facebook, Twitter, and Instagram. But for each of these successful companies, there were myriad others that flamed out before getting anywhere close to their carrying capacity (remember Eons.com, eToys, or AltaVista?). When an environment has excess carrying capacity, competitors will inevitably rise up and seize the opportunity to steal it. Just as it does in nature, Darwinian selection somehow selects out unfit technology as well.
Phase 2: Breakpoint
Networks rarely approach their limits in a measured, orderly fashion. There are two reasons for this. First, exponential growth is hard to control, even for Mother Nature. Second, networks often don’t know the carrying capacity of their environments until they’ve exceeded it. This is a characteristic of limits in general: the only way to recognize a limit is to exceed it. It is for this reason that the breakpoint of a network—the time at which it exceeds the carrying capacity of its environment—is so critical.
Think about it: the only way to know that you should really only have two drinks at the company holiday party is because last year you had four. The only way for the city to determine an appropriate speed limit is to determine the unsafe speed and then subtract a few miles per hour. How are weight limits determined on elevators? How do we know the maximum oven temperature for a pizza? Because someone has exceeded the limit at least once.
Biological networks almost always exceed their limits by growing too large for the carrying capacity of their environments. In ecology this is called “overshoot,” and it’s true in technology as well as nature. How do ants know they’ve reached their maximum suitable colony size? The colony gets a little oversized, which results in too much congestion, noise, and confusion. This is how the ants know it’s time to start sending fertile ants out of the colony to reproduce elsewhere.
The brain does a similar culling, by shedding neurons and neural connections. By the time a child is five years old, there are nearly 1,000 trillion neural connections. Through a process of selective pruning, the 1,000 trillion connections shrink to roughly 100 trillion by adulthood.
So in ants and brains, Phase 2 is best described as an “overshoot and pruning” or an “overshoot and collapse.” So
why is the breakpoint so important? Because once you overshoot the carrying capacity, everything changes. The most important thing is to determine where the breakpoint actually resides and act accordingly. The goal is to identify the breakpoint and reduce the friction that the overshoot causes.
Carrying capacity is elastic: if you overshoot too far beyond the breakpoint, your capacity will drop proportionally in the opposite direction. In those cases, the reduction is truly a catastrophic collapse. But if you identify the breakpoint and limit the growth beyond it, the network will merely shrink back to a respectable level. While exciting to investigate, no one wants to be part of a catastrophic collapse, which often ends up being fatal for both biological and technological networks.
Consider what happened to MySpace. It grew out of control, growing from zero to 100 million accounts in three years. The average user went from a handful of friends to 200 friends, acquaintances, and complete strangers in the same time period. The navigation frames grew from just a few links to 15 in the main bar and 28 more in the services box. MySpace pages became cluttered with automatically playing songs, videos, glitzy wallpaper, and other widgets. Basically, it got congested, noisy, and too confusing to navigate—MySpace grew too far beyond its breakpoint. The graph of MySpace’s collapse looks very similar to that of the St. Matthew Island reindeer.
Image 2.3: When Networks Collapse: MySpace and St. Matthew
Island Reindeer
Phase 3: Equilibrium
Unless there is a natural disaster, biological networks generally don’t fail in such a dramatic fashion. For that, it takes some human interference. Remember, the reindeer were brought to St. Matthew Island by people; Mother Nature never put reindeer there. And MySpace was certainly a human invention.