Table of Contents:
- a. Emergence
- b. The Mature Ant Colony
- a. Growth
- b. Breakpoint
- c. Equilibrium
- a. How the Human Brain Works
- a. Growth
- b. Breakpoint
i. In the Life Cycle
ii. In the Evolution of the Human Species
- c. Equilibrium
- a. The Beginnings of the Internet: The ARPAnet
- b. The Internet Moves to the National Science Foundation
- c. The Internet Goes Global (and Adopts the World Wide Web)
- a. Yahoo!
- b. The First Search Engines
- c. The Rise of Google
- a. The Breakpoint of the Web
- b. How the Web Can Be Improved
This is not a book about the end of the internet, as the controversial title may seem to suggest. Rather, it’s a book about networks (meaning a group of interconnected people or things) and how networks evolve; and its main focus is on internet-related networks and the internet itself (which is one enormous network). The author, Jeff Stibel, argues that there are certain natural laws that govern the unfolding of networks, and that understanding these laws can help us understand how the internet (and other internet-related networks) are likely to evolve over time, and also how we should approach these networks in order to get the most out of them (including make money off of them).
When it comes to the evolution of a network, Stibel argues that there are three main stages here: 1) Growth; 2) Breakpoint; and 3) Equilibrium. In the growth phase, the network grows in size, usually at a very quick (often exponential) pace. This is a precarious time for networks, for if they do not grow fast enough and large enough they will simply wither away and die (the vast majority of networks do in fact die at this stage).
Though a network must grow very quickly in the growth phase just to survive, this initial rate of growth is not something that can be sustained indefinitely. For all networks have a natural carrying capacity that limits how large they can be. This carrying capacity is defined by two factors: energy and organizational complexity. When it comes to energy, a network needs physical energy in order to sustain itself, and thus it is limited by how much energy is available in the environment and that it is able to access (and physical energy is never infinite, so all networks must ultimately have a physical limit).
When it comes to organizational complexity, as a network grows in size it also increases in complexity, and it eventually reaches a point where it becomes so complex that it becomes unwieldy, and begins to lose its utility. Thus a network has an optimal level of organizational complexity, and this optimal level of complexity defines its carrying capacity. (Whether a network hits its carrying capacity due to energy limits or complexity limits depends on the network itself—but whichever limit is met first defines the carrying capacity of that network).
Now, while each network has a natural carrying capacity, a healthy, successful network will almost always grow beyond its carrying capacity during its growth phase. This is because a network never actually knows what its carrying capacity is beforehand, and can only discover this by feeling the effects of having gone beyond it. Once a network exceeds its carrying capacity it begins to perform in a suboptimal way, until eventually, if it keeps on growing, it collapses. The point at which a network collapses is the breakpoint (the second stage in the evolution of a network).
Now, if a network has grown too far beyond its carrying capacity (often due to human interference) it may collapse entirely. However, if the network is allowed to reach its breakpoint naturally, it will usually just collapse in a way that leads it to shrink back in size and complexity to its natural carrying capacity. If the former happens the network dies, if the latter happens the network reaches the third and final stage: equilibrium. In the equilibrium stage the network may lose some of its size, but it is at this stage that it begins to improve in quality and stability.
Take an ant colony, for example. A successful ant colony grows in size until it reaches its breakpoint (sometimes due to an energy limit, but most often due to a complexity limit), at which point it begins shedding off ants to form new colonies. This downsizing process continues until the colony shrinks back to its natural carrying capacity–at which point it enters its equilibrium phase. It is only when it reaches equilibrium that the ant colony becomes as efficient and stable as it can be, and hitting this stage most often allows the colony to persist well into the future.
Or take the human brain. The brain generates new neurons and connections at an incredibly quick pace in the beginning. Eventually, though, it hits a breakpoint, at which time it begins culling back neurons and connections until it reaches equilibrium. It is at this stage that the brain begins developing real intelligence and even true wisdom.
When it comes to the internet—the network that is the focus of the book—we learn that this network is still in its growth phase, and thus it still has much evolving to do before it reaches maturity. Specifically, the internet must still grow beyond its carrying capacity, reach its breakpoint, and collapse back to equilibrium. What this means is that the internet stands to go through some very significant changes in the coming years.
Drawing on evidence from other networks, Stibel seeks to chart out what is likely to happen to the internet (and other internet-related networks) as it passes through its various phases on its way to equilibrium. Stibel predicts that the journey will feature some real growing pains, but that ultimately the internet will emerge better and smarter than ever (and may even develop consciousness).
What follows is a full executive summary of Breakpoint: Why the Web Will Implode, Search Will Be Obsolete, and Everything Else You Need to Know About Technology Is in Your Brain by Jeff Stibel
PART I: NATURAL NETWORKS: THE ANT COLONY AND THE HUMAN BRAIN
The various networks we see around us differ in many ways, but for Stibel, there are some deep similarities between them that we must appreciate if we are to understand them properly.
Now, many of the networks that are most familiar to us (including the internet, and the World Wide Web) were created by us, through conscious intention. But networks do in fact sprout up in nature without conscious intention, and it is instructive to take a look at these networks first, for they can teach us much about the ones that we do create consciously (loc. 145).
One place where networks do sprout up in nature is in communities of social species (of which we are one). Indeed, the communities of social species are nothing but complex networks—and some of the most complex networks around—and thus this is a very appropriate place to begin.
Now, the most complex communities of social species belong to a particular class of these species—known as the eusocial species—and of these there are but a handful. They include only bees, wasps, termites, ants and we humans (loc. 1326). And of these, the ant stands out as the one species whose communities are closest to our own—for the simple reason that their communities come closest to matching the sophistication and complexity of ours (loc. 2369).
Communities of ants are so much like ours, in fact, that it has been suggested that though chimpanzees are closest to us in evolutionary terms, that ants are in fact the species that are most similar to us in functional terms (loc. 2369). As researcher Mark Moffet puts it, “no chimpanzee group has to deal with issues of public health, infrastructure, distribution of goods and services, market economies, mass transit problems, assembly lines and complex teamwork, agriculture and animal domestication, warfare and slavery” (loc. 2369). And ants not only deal with all of these issues, but they handle them in a way that approximates the sophistication that we display.
Given, then, that ant colony networks are some of the most complex and sophisticated in nature, it is appropriate that we begin with them.
Section A: Ants
1. Natural Networks Exhibit A: The Ant Colony
A mature ant colony is a truly remarkable thing. Take the leaf-cutter ant, for instance. Leaf-cutter ants derive their name from the fact that they cut and collect leaves to bring back to their nest (they can often be seen lugging leaves several times their own size [loc. 2312]). Interestingly, leaf-cutter ants don’t actually eat these leaves (loc. 2312). Rather, they use them as mulch, which they feed to a fungus that they cultivate in their nests, and the fungus is what they live on (loc. 2312). As Stibel explains “leaf-cutter ants eat fungus that they nurture, fertilize, and harvest themselves. The fungus thrives on leaves, hence all the leaf cutting and transporting” (loc. 2312).
Here is an excellent clip on the incredible leaf-cutter ant:
This whole process requires a very elaborate set-up in the nest (to say the least). Here is Stibel describing the nest of a community of leaf-cutter ants that was excavated back in 1994, in Botucatu, Brazil: “a marvel of modern engineering, one mound covered an above-ground surface area of nearly 725 square feet. The largest nest had tunnels extending 229 feet below the earth, making the entire structure as large as a skyscraper and as wide as a city block. Its construction required the ants to move untold tons of soil. The extensive labyrinths of the largest nest contained 7,863 chambers reaching as far down as 23 feet, each with a specific purpose: there were garden compartments, nurseries, even trash heaps. The tunnel system connecting the chambers looked like a superhighway system, complete with on-ramps, off-ramps, and local access roads. The structure itself looked as if it had been designed by an architect” (loc. 2307).
Here is a nice clip that features the excavation of a leaf-cutter ant colony:
And that’s not all. In addition to constructing garden chambers for the express purpose of cultivating their fungi, the ants also organize their nests in such a way that optimizes the growing conditions therein. For example, their nests feature an elaborate air-recycling system that keeps fresh air flowing in and stale air flowing out (loc. 634, 2309). What’s more, they actively open and close air ducts that regulate the temperature and humidity in their growing chambers to make them just right for the needs of their precious fungi (loc. 2315).
Other varieties of ants live very differently from the leaf-cutters, but often no less impressively. Take the slave-making ants, for instance. The slave-making ants make a living pretty much as their name suggests. Here’s Stibel to explain: “slave-making ants don’t clean house, cook food, or take care of their babies. They actually don’t even know how to do any of those things. They’re pretty much good at only one thing: finding others to do their work. Slave-makers raid the nests of other ant colonies and steal all their eggs. Those ants grow up as slaves, and they do pretty much everything for their masters: groom them, feed them, defend them from bigger insects, you name it. If the colony moves to a new nest, the slaves will even carry their masters to their new abode… In order to steal the eggs of another colony, the slave-makers must first go to war—these prodigious ants ruthlessly kill any ant that gets in the way. Opportunistic slave-maker queens follow these raiders into a colony and take advantage of the chaos created by the raid. The young aspiring queen slips into the nest, finds the queen ant, and literally chokes her to death. Then she eats the old queen so that she smells like the queen’s pheromones. The rest of the ants never know the difference, giving the young slave-maker queen an instant colony of her own” (loc. 644).
The following is a very good (albeit melodramatic) segment on one variety of slave-making ant (the part about the ants begins in earnest at the 50 second mark):
Now, from a moral point of view we may well admire the leaf-cutter ant much more so than the slave-maker. But from a strictly organizational point of view, we must grant that both varieties of ant are incredibly sophisticated in how they make a living.
2. How Ant Colonies Work
The sophistication of ants is all the more impressive when we consider just how limited their brains are. As Stibel explains, “their brains have something on the order of 250,000 cells (compared to the 16 million brain cells of the average frog)” (loc. 167). And if you take an ant out of its colony, the behavior that it exhibits reflects just about what you might expect from something with 250,000 brain cells. For example, as the author explains, “certain ants outside of their colony will move in circles until they die from exhaustion” (loc. 202).
*For prospective buyers: To get a good indication of how this (and other) articles look before purchasing, I’ve made several of my past articles available for free. Each of my articles follows the same form and is similar in length (15-20 pages). The free articles are available here: Free Articles