Who Owns the Future? (26 page)

Yet another interesting example is Craigslist. This is a fascinating, idealistic Siren Server that is mildly for-profit. It only charges for certain types of ads, such as from prospective employers, while offering most services for free. Craig Newmark could probably have built his business into a giant along the lines of eBay or Amazon. Instead, he created a service that has greatly increased convenience for ordinary people, while causing a crisis in local journalism that once relied on paid classified ads. To me, Craigslist has a tragic quality, since it is as modest and ethical as it can be, eschewing available spying opportunities, and yet it still functions as a Siren Server despite that.

In some cases, ordinary people are persuaded to put extraordinary work into correcting and sorting the data in an Siren Server, at their own risk and expense. A fine and maddening example is credit rating agencies, which provide a labor-intensive path for people to correct mistakes in their own data.

The Human Shell Game

Computation done within a Siren Server occasionally still requires some human involvement from insiders to the scheme.
*
Today, for instance, Amazon has skilled, real people answer the phone to provide customer service.

*
There’s usually a ritual in place to make sure everything possible is done to avoid actual human involvement for as long as possible, even if it is inevitable. The cliché we’ve all lived through is that you call about, say, a problem in how an insurance or credit rating Siren Server has screwed up a key decision about your life. Perhaps you were denied coverage for needed medical treatment. After an hours-long battle with the maze of a robo call center, you finally talk to a real person, probably in India or the Philippines. This might be the first time real human eyes associated with the Siren Server have perceived your data.

However Amazon is also exploring how to get non-elite service jobs out of the way of the Siren Servers of the future. The company offers a Web-based tool called Mechanical Turk. The name is a reference to a deceptive 18th century automaton that seemed to be a robotic Turk that could play chess, while in fact a real person was hidden inside.

The Amazon version is a way to easily outsource—to real humans—those cloud-based tasks that algorithms still can’t do, but in a framework that allows you to think of the people as software
components. The interface doesn’t hide the existence of the people, but it still does try to create a sense of magic, as if you can just pluck results out of the cloud at an incredibly low cost.

The service is much loved and celebrated, and competes with other similar constructions. My techie friends sometimes suggest to me in all seriousness that writing books is hard work and I should turn to the Mechanical Turk to lower my workload. Somewhere out there must await literate souls willing to ghostwrite for pennies an hour.

The Mechanical Turk is not really that different from other Siren Servers, but it is so up front about its nature that it stands out. Those who take assignments through it often seem to even enjoy the fun of emulating an intelligent machine for someone else’s profit.
¹

The charade has a triply dismal quality.

Of course there is the “race to the bottom” process that lowers wages absolutely as much as possible,
²
making temp jobs in the fast-food industry seem like social climbing on-ramps in comparison. Yet there are people ready to step up and take such roles. More than a few recruits appear to be the live-at-home kids of middle-class Americans, whiling away their time.
³

Whenever there is a networked race to the bottom, there is a Siren Server that connects people and owns the master database about who they are. If they knew each other, comprehensively, they might organize a union or some other form of levee.

The second dismal quality is that artificial-intelligence algorithms are getting better, so gradually it will become more possible to not even acknowledge the contributions of real people to the degree done now.

Finally, the Mechanical Turk is often applied to the more pathetic tasks associated with Siren Server contests. One journalist found that 40 percent of the tasks on offer are to create spam.
⁴

CHAPTER 15

Story Found

The First Act Is Autocatalytic

A newly launched Siren Server is like a tiny baby creature in a hostile ecosystem that must grow fast enough to survive in a world of predators. The most common means to survival is to route enough data fast enough so that by the time predators notice you at all, they won’t find it worthwhile to go after your niche.

There are a variety of Siren Servers, ranging from consumer-facing Silicon Valley startups tempting people with “free” bait, to financial servers that skim the cream off the economy in relative obscurity, to providers of infrastructure who realize that they can also play the big data game, to governments and other entities yet to be discussed.

In all cases, there has to be some way for a particular Siren Server to gain enough initial momentum to become the beneficiary of network effects. Therefore, the primary enemy of a fresh server is not competing wannabe servers, but rather “friction.”

Friction is what it feels like to be on the bad side of a network effect. Even the slightest expense or risk might slow the initial growth spurt, so every possible effort is made to pretend there are no costs, risks, or even delayed gratifications. This can never really be true. Yet it feels true as you sign up for a social network or an app store for the first time.

Since You Asked

Here’s typical advice I’d give to someone who wants to try the Silicon Valley startup game: Obviously you have to get someone else to do something on your server. This can start out as a petty activity. eBay started out as a trading site for people who collected Pez candy dispensers. The key is that it’s your server. If you’re getting a lot of traffic through someone else’s server, then you’re not really playing the game. If you get a lot of hits on a Facebook page, or for your pieces on the
Huffington Post,
then you are playing a little game, not the big game.

In some cases you can be the predator. You might start by noticing some other pretender to a throne that isn’t growing as fast as it could and overtaking it once it has identified a viable Siren Server niche to be won. This is what Facebook did to Friendster, Myspace, et al.

In other cases you might form an offering out of whole cloth at just the right time and place. This is what Twitter did.

Some part of me still wishes that serious technical innovation were more essential to hatching Siren Servers. Google was initially based on genuine algorithmic innovation. Facebook certainly has had its engineering challenges, mostly related to getting big fast without a reliability crisis, but it’s hard to see much computer science innovation in it, at least in its foundation.

Why the Networked World Seems Chaotic

Lately, the depths of pettiness seem unbounded. Why do so many people use Pinterest?
*
There were many competitors offering similar designs. By now Pinterest enjoys rewarding network effects so there’s no mystery. People now use it because others do. But why
did Pinterest grow enough to win network effect prizes, instead of any of the many other similar infant creatures in the ecosystem?

*
It’s always tricky to write about these things since I must guess what points of reference will survive long enough to mean anything to this book’s readers years hence. Pinterest is a fast rising star among consumer-facing sites. You can copy photos and other data from around the Web onto virtual pin boards and share them.

There’s a well-supported analytic class—statisticians and MBAs employed by venture capitalists, big companies, and private capital firms—that attempts to model the qualities of hopeful startup sites, in order to predict which ones will take off. This is like predicting the weather, a challenging kind of science. Some progress has been made, but there remains an element of chaos and unpredictability. No one can know all the little fluctuations that were in play that gave a site like Pinterest its window of opportunity.

What makes one Siren Server take off while a seemingly identical one flops? This is like asking why some silly Internet memes rise and others fall. There are many factors, mostly uncounted.

It’s entirely imaginable that Pinterest would have flopped if circumstance had been just slightly different. A butterfly might have flapped its wings on the other side of the world, as the saying goes. Of course, the proprietors of a site that takes off are always certain it was because they did exactly the right thing.

When Are Siren Servers Monopolies?

As explained in the sections on network effects, when users put effort, money, or important data into a particular service, like a social network, then network effects tend to create a single Sirenic presence, a monopoly for that particular kind of data or pattern of use.

Many Siren Servers of this kind are subject to something like a Pauli exclusion principle, or if you prefer, they tend to discover and uniquely occupy pseudo-monopolistic roles. There can’t be both a Friendster and a Facebook. One of them must win.

When a Siren Server is more a mediator than an accumulator of primary data sources, then it can have company. There can be multiple travel sites, as explained earlier, because they don’t own the primary reservation-related data that they mediate. There can be multiple Sirenic financial services because none of them own Wall Street.

Similarly, there can be both a Bing and Google, since neither owns
the Web. To be more precise, there can be two search engines,
*
but Google still tends to be monopoly-like in selling advertising based on search, which is a different matter. That is because, as an accumulator of advertiser relationships, Google does enjoy a monopoly-like network effect.

*
This observation only applies to traditional personal computers. On mobile phones, Google generally enjoys a structural advantage because of preferred placement.

Another example is that Amazon and Barnes & Noble can coexist as booksellers, because they don’t own the books, but if they also become major publishers, then one would probably have to kill the other.

Sometimes potential Sirenic monopoly is blocked because of a structural or legal blockade that limits reach. For instance, a language barrier might limit a social network to certain regions of the world, or a mobile carrier might be able to capture users by contract instead of through pure data effects.

Even when there is only one Siren Server to a niche, there can be a lot of niches, however.

Free Rise

What’s the threshold for rewarding network effects to kick in? For consumer-facing sites, it is the point at which enough people are using a site to support each other’s expectations of dynamism. An additional threshold is that a critical number of people have to stick together long enough so that the site becomes a habit for them. Then the dynamism won’t decay.

It’s not as if there is no technical requirement at all for a site to catch a wave and become huge. The site generally has to be at least consistently available, though in its early years Twitter wasn’t.

Once you reach a critical point, you have a population or two locked in. You might very well grow to global proportions and exert influence like a messiah, tweaking the design of human experience at large.

If you’ve made it to the point that growth is accelerating, you’ve entered the honeymoon phase, or free rise (the opposite of free fall). Some entrepreneurs promote like crazy during this phase, while others are just consumed with keeping the thing running. If you want free rise to continue until your Siren Server becomes a monster, you’ll have to attend to a few things . . .

If the first phase goes well, you can experience an amazing lift, as you aggregate connections and data at an intense clip. During this period, all the usual rules of life and commerce are suspended. It’s free rise, and anything can happen.

During free rise, you can see patterns in data no one else can see, as if you were an oracle. You will suddenly know more about some slice of human life than anyone else. Maybe you’ll see something about eating habits, sex, shopping, or driving patterns.

A few of the folks you have aggregated will inevitably get an insane lift from being hitched to you, and they’ll create even more excitement. An early investor in your fund will get superrich superfast, or a user of your free service will earn a windfall from sudden exposure. This will happen to only a tiny token number of people, though. It is really you, the proprietor of the Siren Server, who will benefit above all others.

At first, all you’ll have is rewarding network effect. That means that people will benefit from using your server because other people are using it. A virtuous cycle causes more and more people to use your offering. That’s not enough, however, if you want to build a world-class, persistent Siren Server. In addition, you have to inject some sort of punishing network effect.

Make Others Pay for Entropy

Once both rewarding and punishing network effects are taking hold, another crucial task is to make sure that risk is being radiated out to other people and institutions, and not accruing to your server. Sites like Pinterest invariably demand that users click through an agreement that places all responsibility for copyright violations or anything else squarely on the user.

If people are paying money to use your server, don’t accept any of it directly if you can possibly avoid that. You should be a broker between buyers and sellers to the degree that’s possible. You can then earn commissions, placement fees, visibility fees, or any number of other fees yet to be conceived, but without taking any responsibility for the actual events that took place.