31 – #SHOW

Mobile service in India costs quite a bit less than in the developed world. In 2009, during a price war, most of the nation’s carriers cut voice call rates to half a paisa a second – with 100 paisa in a rupee, that’s roughly one-hundredth of a US cent per second, roughly one-fiftieth the price a caller might pay in Australia or Europe for the same service. And although the average Indian mobile user spends only US $3 a month on their mobile subscription, for a huge number of India’s most poor, that’s too much.

As is customary for mobile carriers globally, Indian customers pay nothing if their calls can not be completed, but the recipient of the call knows who had called – their mobile records the caller’s number. It didn’t take long for someone to figure out that this ‘missed calling’ could be used as kind of signalling.

Many years ago, when interstate calling was still very expensive in the United States, I remember visiting aunts and uncles making missed calls to our home phone, informing us they’d arrived home safely. A single ring (on the single household phone), then silence. It saved them a few dollars, and saved us all some worry. For as long as direct dialing has been available, people have been missing calls intentionally, signalling one another. One ring: safe. Two rings: call me. Three rings: emergency.

India went from very little wired infrastructure – one phone per hundred people – straight into hyperconnectivity. At least half of all Indians now own a mobile. But without a wired history, how did the practice of missed-call signalling develop? Someone might have invented it on their own, but more likely it came via a visitor from a country where missed-call signalling was already commonplace. As soon as missed call signalling is practiced in front of someone else, it is understood, and begins to replicate. When a behavior is practiced on the network, it replicates quickly and broadly, soon becoming pervasive.

Human beings are excellent imitators. From our birth we imitate everyone around us, beginning with learning how to talk – an inconceivable feat of intellectual accomplishment, listening to and imitating our parents and older siblings. We learn so fast because we imitate one another so well. Wired for mimesis – imitation – we embody ‘monkey see, monkey do’.

If imitation has any boundaries, we haven’t found them. Harvard researcher Dr. Nicholas Christakis has spent the last decade studying how behaviors spread through our relationships. First, Christakis learned that tobacco smoking (and the decision to quit smoking) follows from our social connections. The more smokers we are in relation with, the more likely we are to smoke ourselves. The more of our friends decide to quit, the more likely it is that we, too, will stop.

More than just like finding like, Christakis showed that these behaviors actively spread through our connections. One person deciding to smoke makes it more likely their connections will smoke. One person deciding to quit makes it more likely others will follow. Christakis then found that this also characterized obesity: you are more likely to be obese if your connections are with the obese, and more likely to go on a diet if those around you have made that decision.

Our capacity to imitate one another so well makes us peculiarly susceptible to the actions of others. Everyone has heard a lecture on good behavior from their mothers that culminates with, “If everyone else jumped off a cliff, would you?” The answer, as it turns out, is probably yes. Our innate desire to imitate one another will even wrestle against the drive for self-preservation: we know that smoking and obesity are bad for us, but, under the influence of our connections – peer pressure – we surrender.

It goes deeper. Studies have also revealed that divorce spreads through our connections. If a couple you’re connected to breaks up, your marriage is in greater peril. Why is this? Does a close-to-home divorce get couples thinking about the dissatisfactions of marriage? Or is it simply a desire to imitate one’s friends, in sickness and in health?

Seen in this light, our connections have an almost epidemiological quality, acting as carriers for diseases of the body (obesity) and heart (divorce) which can infect us and leave us changed. Parents and mentors warned us to ‘be careful who you hang out with’; it’s common knowledge that maintaining connections with ‘the wrong crowd’ can be ruinous. Now we understand why. We are in each other’s heads, the best and worst parts of us always leaking out, or leaking in.

As we research how behaviors spread through the human network, we may attempt to medicalize our connections, creating a cordon sanitaire for ourselves and our children, places beyond the reach of these socially-transmitted diseases. This reaction – typified in the growing number of gated communities – only moves the threat, but never removes it. When you pick your friends, your colleagues, and your neighbors, you adopt their minds.

Humans have always been a colony organism, moving in sync together. The closer our connections, the closer our minds. Half a billion seconds ago, those connections, limited by speed and proximity, gave infections-of-the-mind a natural range. They could not spread quickly, nor very widely. Hyperconnected and disseminated at lightspeed, behaviors now go from unknown to ubiquitous in a few days. Half a billion seconds from now, it will all happen in a matter of seconds: hypermimesis.

Some behaviors – such as missed-call signalling – become immediately pervasive because they offer an improvement in connectivity, spreading through hypermimesis. Demonstration of a behavior over the network allows billions to observe and imitate that behavior. Every improvement in our connectivity (text messaging and missed-call signalling are but two among many) also improves our ability to imitate one another, via the network. Showing is doing, and doing, showing.

19 – #LOOP

Charles pulls up to the curb in a brand-new Lincoln Towncar, black and sleek, radiating wealth and privilege, and stops before me. His car is mine, and Charles is my driver — temporarily. I have magicked him up from my mobile, firing off a text message with my address to a service called Uber. I receive confirmation of receipt of my request, then, just a few seconds later, confirmation that Charles would be with me in three minutes.

If I had been using a smartphone, the process would have been slicker and more visual. I would have launched an app that would locate me – using GPS – then place me on a map, showing all of the nearby available limousines. After I my pickup request had been received and accepted, all of those limousines would disappear from the map, except the one coming to fulfil my request. As the car drew closer to me, I’d see it approach, allowing me to meet it precisely as it arrived. Seamless coordination, courtesy of the mobile.

Even though it costs a fair bit more than a taxi, with this kind of convenience Uber has been blessed with raging success. People like the feeling of control – real or perceived – that comes from watching their driver approach. While they stare down into the screen, Uber gives its users a sense of ominpresence. They know, if not everything, much more than ever before. That knowledge allows them to do more, giving them a small taste of the freedoms enjoyed by the very wealthiest.

Limousine drivers like Charles love Uber, too. Before the service launched, those drivers would spend half their time doing nothing, idling their hours while waiting for the next pickup call to come in. Drivers now add Uber jobs to their regularly scheduled pickups, nearly doubling their earning power within the same eight-hour shift. Mobiles have given limousine drivers the same economic acceleration that mobiles gave the fishermen of Kerala fifteen years ago – creating a highly efficient market which satisfies an increased demand, dramatically improving the earning potential of everyone connected.

Economists recognize that when a sudden change in market dynamics produces a burst of new wealth it encourages people to enter the marketplace. A ‘gold rush’ begins, as everyone looks for a way to vacuum up some of the new-found fortune. Most markets have ‘barriers to entry’ – to be a fisherman, you need a boat and rigging and nets and a crew; to be a driver you need a rather pricey limousine. These barriers make it difficult for the market to become immediately overcrowded, but the lack of competition increases the incentive for everyone already participating in the market to maximize their productive behavior. The more productive you can be within a closed but growing market, the more you will earn.

For Uber drivers, this means putting their limousines where they’re most needed. But they’re not alone in this, so the busiest parts of the city are also those with the greatest supply of drivers, which means drivers still have to wait for jobs. Even closed markets can be locally oversupplied – particularly where participants within a market can smell all the money to be made.

Uber drivers run a companion version of the smartphone app that Uber customers use. This app allows them to bid on pickups, but does not reveal the location of any of the limousines around them, competing for the same business. Uber’s drivers have less information than Uber’s customers. As a consequence, limousines tend to cluster, because drivers don’t know that they’re all converging on the same small – and presumably lucrative – area.

My driver Charles has a solution for this dilemma: he owns two mobiles, and runs both Uber apps. The driver app delivers pickup requests, while the customer app reveals the locations of any limousines nearby. “One evening I came into the city,” Charles reports, “and there were four limousines within a block.” Knowing this, Charles moved on, finding another, under-served area of the city, and got plenty of work.

Uber may not want its drivers to know about the location of other drivers, but it wants to reveal that information to its customers, so drivers simply poke holes in the wall that separate the two sides, peering through, and learning where to position themselves for greatest profit. The drivers use all information on offer – from every source – to give themselves the greatest advantage.

Charles says he’s one of the few Uber drivers using his smartphone to give him the inside track with a degree of omnipresence. It’s a technique new to him, and he doesn’t say whether he thought it up himself, or if he copied it from another driver. Either way, as Charles’ success becomes more visible, his peers, watching what he does, will copy his keys to success. What he knows will be replicated throughout the fleet of drivers until this exceptional behavior becomes pervasive and normal.

Soon, Uber will either need to provide drivers with all of the information drivers provide to Uber, or every Uber driver will use two mobiles, one for orders, and another for omnipresence. As drivers learn more about one another, they learn how to avoid economically damaging behaviors, such as clusters. The drivers self-organize, spacing themselves throughout an area in a way which generates the greatest economic advantage for each individual. They will act as a unit – as if they all answered to a common mind – although they have no central command, accept no controlling influence, and simply work to maximize their own financial interests. This emergent behavior – seen first along the Kerala coast – is the inevitable consequence of connectivity.

The information flows of connectivity move back and forth, never just in one direction, looping through us, out into the world, and back again. At every step, this information, transformed by the individuals it passes through, also transforms those individuals. “All knowing is doing, and all doing, knowing.” To connect is to know, to know is to do, and doing carries with it the opportunity to connect.

This never stops, nor ever slows.



Networks are copying machines.  There is no magic to them, beyond this: data presented at any point on the network can be copied to every other point within the network, nearly instantaneously.   A text message can be reproduced across six billion mobiles within a few seconds.  A single email, copied and multiplied, could reach every one of the greater than two billion of us with Internet access.  Neither of these extraordinary events require anything beyond the networks already in place.  The network can copy all of us in on the same memo.

Networks have no other point: they copy and copy and copy.  They can’t do anything else.  Every other quality we ascribe to a network (and this book describes a multitude of them) is a product of our own interactions across the network, not of the network itself.

Short of unplugging it, there is no way to stop a network from copying.  The network doesn’t perform copying as one of its features: to network is to copy.  Networks allow the replication of information at speeds nearing that of light, so every point of connection, however far-flung, acts upon the same data.

The Internet, born to service a resilient command-and-control system, designed to withstand the Mutually Assured Destruction of thermonuclear war, replicated the tactical information within each of the US Defense Department’s strategic installations, so that each base had a complete, real-time overview of the battlefield.  Should part of the network vanish – vaporized – the remaining portions of the network could pool their tactical observations to maintain situational awareness.  To disrupt the tactical capability provided by the network, it must completely destroyed, because for as long as any part of the network exists, it will continue to replicate information.

In the years between the genesis of the Internet and hyperconnected present, we have created networks for militaries, governments, businesses, institutions of all kinds, and, finally, individuals.  The network is nearly coextensive with the species, with nearly eighty-five percent of humanity continuously connected to it.

These networks, like all networks that have ever existed, replicate information, but now do so ubiquitously.  Reports of an earthquake travel faster than the earthquake itself.   Copied from those who have the information to those who need to have it, the more important something is, the faster it replicates across the network. Because it copies, network is an information amplifier, making anything whispered almost infinitely loud.

We feed the network with things we find important, and if others share our enthusiasm, those things will be copied across the network.  At one extreme, it could be news of a massive temblor; at the other, it could be a melodramatic pop song that struck just the right emotional chord.  The network does not care what it copies, has no awareness of ‘media’, only information.  A tune or an image or a cry for help: although each will be replicated faithfully, they mean nothing to the network.  The network does not know; it only knows to copy.

When information is replicated across the network, the recipients of that information respond to it.  “All doing is knowing, and all knowing is doing.”  The cry for help will be answered, the image viewed, the tune heard.  Within us, the response to information is nearly as automatic a function as the replicating function of the network.  We respond to everything we are exposed to, even if only in a change of thought or mood.

Some responses are stronger than others.  Some responses are so strong that they provoke attacks on the network itself.  Confusing the strength of the provocation with the capability of the network, and ascribing to the network an agency which it can not possess, attempts are made to shoot the messenger.   But the network can not provoke, it can only copy.

When the network is attacked, news of that attack is copied across the network.  Whether that attack comes from a hydrogen bomb or a lawsuit is of no particular consequence.  The existence of the attack is enough.  Networks copy the state of each of their endpoints: if any endpoint comes under threat, all other endpoints know of it.  In short order, the attack provokes a response.  The network, sensitized to the existence of a threat, answers across its entirety.

That brings us to the present moment, to a network responding to a perceived attack.  The legislative cudgel of SOPA/PIPA, with its implicit threat of censorship (censorship is any process which prevents the network from faithfully replicating information) has become common knowledge, propagated by the network it seeks to control.  The responses, at first marginal, then measured, have recently cascaded into a non-linear zone of amplification, as the network demonstrates to itself what it means to tamper with its essence as a replicating machine.

Wikipedia is a near-perfect instance of a product of a network replicator.  Facts presented at any point in the network become instantly available – for consumption, review, editing or discussion – across the entire network.  In less than a decade Wikipedia went from wishful thinking to indispensable resource, serving as a factual foundation for our intellectual efforts.

It isn’t until that foundation disappears that we recognize our dependency upon it: fish are unaware of water.  We are immersed in a sea of factual information orders of magnitude greater than any generation before us, knowledge instantly and ubiquitously accessible, via the network.  We use that information to broaden our knowledge, and with that knowledge, make better, more-informed decisions.  “All doing is knowing, and all knowing is doing.”

Any interruption in knowing must inevitably weaken our ability to do, narrowing the scope of our capabilities.  That is the price of censorship in any form – political, cultural, or economic.  In a wholly networked world that price becomes immediately visible.   “Mene, mene, tekel, upharsim.”   People will not suffer the destruction of their capabilities, not when they can use the network to defend those capabilities.

Now that the knowledge that the network can be used to defend itself has replicated throughout the network, the network has become exponentially more resilient and resistant to any attempts to alter its fundamental replicating function.  Trying to kill the network has only made it stronger.