Who own the future by Jaron Lanier
[A radical view on big data and the winner-takes-it-all distribution]
Here is the current example of the challenge we face. At the height of its power, the photography company Kodak employed more than 140,000 people and was worth $28 billion. They even invented the first digital camera. But today Kodak is bankrupt and the new face of digital photography has become instagram. When instagram was sold to Facebook for a billion dollars in 2012, it employed only 13 people. Instagram isn’t worth a billion dollars just because those 13 employees are extraordinary. Instead, its value comes from the millions of users who contribute to the network without being paid for it. Network needs a great number of people to participate in them to generate significant value. But when they have them, only a small number of people get paid. That has the net effect of centralizing wealth and limiting overall economic growth.
Eventually most productivity probably will become software mediated and software could be the final industrial revolution. It might subsume all the revolution to come.
Popular digital designs do not treat people as being ‘special enough’. People are treated as small elements in a bigger information machine, when in fact people are the only sources or destination of information or indeed of any meaning to the machine at all.
There are two familiar ways that people can be organized into spectrums. One if the star system or winner takes it all distribution. There can only be a few movie or sports stars, for example. So a peak comprised of a very small number of top winners just out of a sunken slope or a long tail of a lot of poorer performers. The distribution of outcomes in fashionable, digitally networked, hyper efficient markets tend to be winner-take it all. It is true for tech startups, for instance, only a few succeed, but those that do can amass stupendous fortunes.
The other distribution is the bell curve. That means, there is a bulge of average people and two tails of exceptional people, one high and one low. Bell curves arise from most measurements of people, because that is how statistics works. In an economy with a strong middle class, the distribution economic outcomes for people might approach a bell curve, like distribution of any measured quality like intelligence. Unfortunately the new digital economy, like older feudal or robber baron economies, is thus for generating outcomes that resemble a ‘star system’ more often than a bell curve.
Start systems starve themselves
Bell curve renew themselves
The perfect investment will quickly anneal into an impermeable and unchallengeable position, by nature a monopoly in its domain. For instance, Peter Thiel, founder of PayPal and a foundational investor in Facebook, taught students in his Stanford course on startup to find a way to create ‘monopolies’.
A Siren server can gather information to reduce its exposure to the risks inherent in its operation, which just means radiating those risks out to the general society and that includes you. The usual complaints about Amazon come from its competitors, and its natural to dismiss them. However, if you are a smaller competing seller of books, the situation is quite stark.
A ‘bot’ program in the Amazon cloud monitors the price of books you sell everywhere else in the world; it automatically makes sure Amazon is never undersold. There is no longer a local intelligence advantage for pricing by small local sellers. This leads to bizarre outcomes such as books being priced for free through Amazon simply because they are being given away as part of a promotion elsewhere. Therefore promotions for ordinary small sellers become more expensive or riskier than they otherwise would be. Information supremacy for one company becomes as a matter of course, a form of behavior modification of the rest of the world.
The total amount of risk in the market as a whole stays the same, perhaps, but it is not distributed evenly. Instead the smaller players take on more risks are reduced - it won’t lose a sale to someone else’s pricing strategy - while local sellers face increased risks if they want to undertake their own pricing strategies.
You can’t see as much of the Server as it can see of you.
In the world of business, big data often works, whether it is true or not. People pay for dating services even though on examination the algorithms purporting to pair perfect mates probably don’t work. It does not matter if the science is right so long as customers will pay for it and they do. Why is big business data often flawed? The unreliability of big business data is a collective project we all participate in. If the server is based on reviews, many of them will suddenly smart to be fakes. Once the server starts to get fooled by phony data, the dance begins. The server hires mathematicians and AI experts who try to use pure logic at a distance to filter out the lies. But to lie is not to be dumb. An arms race inevitably ensues, in which the hive mind of fakers attempts to outsmart a few clear programmers and the balance of power shifts day to day.
The most successful Siren servers also benefit from punishing network effects. These are centered on a fear, risk or cost that makes ‘captured’ populations think twice if they want to stop engaging with a Siren server. In Silicon valley-speak, this is also called ‘stickiness’. Players often can’t take on the burden of escaping the thrall of a Siren server once a punishing network effect is in place.
Google sells ad placements based on auctions. Imagine once again that you are an advertiser. In the old days, if you had been paying, for say, a billboard, you might decide to give that billboard up and instead buy more newspaper ads. Neither you nor anyone else would have had any idea who would place a new ad on the billboard you abandoned. The risk you took by giving up the billboard was vague and uncertain. However, if you give uyp a position on Google’s ad placement system, you know for certain that your next-nearest competitor in the auction will inherit your position. This risk and cost of leaving a position is made specially scary and annoying.
You have to lose a part of yourself to leave Facebook Once you become an avid user. If you leave, it will become difficult for some people to contact you at all. Would you ever be willing to take the risk to server a part of your own life’s context in order to disengage from a Siren Server that ogles you?
Here is 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. If you are getting lot of traffic, through someone else’s server, then you are not really playing the game. If you get a lots 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 and Myspace eta. In other cases you might form an offering out of whole cloth at just the right time and place. This is what Twitter did.
Amazon, by using superior computation, might potentially piggyback on Wal-Mart’s legacy of supply chain optimization and essentially aggregate Wal-mart’s efficiencies into its own. It wasn’t Amazon that brought about all the cheaply available goods, but by having the best spy data at a given time,, Amazon might become the concern that benefits the most from them.
Facebook suggests not only a moral imperative to place certain information in its network, but the broad applicability of one template to compare people. In this it is distinct from Google, which encourages semistructured online activity that Google will be best at organizing after the fact.
Twitter suggest that meaning will emerge from fleeting flashes of thought contextualized by who sent the thought rather the content of the thought. In this it is distinct from Wikipedia, which suggests that flashes of thought be inserted meaningfully into a shared semantic structure. Wikipedia proposes that knowledge can be divorced from point of view. In this it is distinct from the Huffington Post, where opinions fluoresce.
[Karl Popper was an Australian philosopher who famously described how science never achieves absolute eternal truth, but instead gets closer and closer to truth by disqualifying false ideas. Mathematics, in the other hand, does include a concept of absolute, eternal truth, because of proofs]
The idea of copyright would no longer be needed in a networked world was almost impossible to convey for many years. It has finally been made familiar in recent years because it is the principle on which most information services that actually charge for information must operate. For instance, Netflix does not allow its customers to download a video file that is identical to the master file on its servers. Instead it provides software that delivers a video experience by accessing that master file in real time over a network, cached data mirrors to backup their data, or to speed up transmittal, that is not the same as creating multiple logical copies - as users on a Bit-Torrent sharing sites do.
Wikipedia has procedures in place to incorporate material from the 1911 edition of the Encyclopedia Britannica, which has fallen into the public domain. When we build on the past in that way, how will we acknowledge it in a monetized information economy?