A recent op-ed piece in the NYT by Jason Lanier discussed how to fix the digital economy (see: Fixing the Digital Economy). I have been blogging for more than seven years and access to this blog, as is usually the case, is free. I have always believed that this is a good idea but now I am not so sure. Below is an excerpt from his article:
Two big trends in the world appear to contradict each other. On the one hand, computer networks are said to be disrupting centralized power of all kinds and giving it to the individual....But then there’s the other trend. Inequality is soaring in rich countries around the world, not just the United States...The job market in America has been hollowed out; unpaid internships are common and “entry-level” jobs seem to last a lifetime, while technical and management posts become ever more lucrative....Technological change might sometimes seem to be an automatic threat to the middle class.... In this century, however, we have forgotten that wisdom and decided that when it comes to digital networks, more and more people will not be paid for what they do even though what they’re doing is needed. Jobs involving communication and expression ...are suddenly much harder to come by, because information is now held to be free....
As this century unfolds, technology will continue to evolve....There is no magical “artificial intelligence.” When a big, remote computer translates a document from English to Spanish, for instance, it doesn’t understand what it is doing. It is only mashing up earlier translations created by real people, who have been forgotten because of the theater of the Internet. There are always real people behind the curtain. The rise of inequality isn’t because of people not being needed...it’s because of an illusion that they aren’t even there. Dissect almost any ascendant center of power, and you’ll find a giant computer at the core.....Now to be powerful can mean having the most effective computer on a network. In most cases, this means the biggest and most connected computer, though very occasionally a well-operated small computer can play the game, as is the case with WikiLeaks....
The new class of ultra-influential computers come in many guises....Siren Servers can function profitably only if people aren’t paid for the data that is used to calculate their statistical schemes. Siren Servers drive apart our identities as consumers and workers. In some cases, causality is apparent: free music downloads are great but throw musicians out of work. Free college courses are all the fad, but tenured professorships are disappearing. Free news proliferates, but money for investigative and foreign reporting is drying up....Keep track of where information came from. Pay people when information that exists because they exist turns out to be valuable, no matter what kind of information is involved or whether a person intended to provide it or not. Let the price be determined by markets.
The gist of what Lanier is saying is that we need to begin to begin to pay people for generating information or adding value to existing information. Here's a link to an article that provides additional analysis about Lanier's ideas (see: GoogleMart). Here's the key quote from it:
Lanier's suggestion is everyone gets paid, via micro-payments, linked back to the value they helped create. These payments continue so long as people are using their stuff, be it a line of code, a photograph, a piece of music, or an article.
This kind of tracking that is required for micropayments to all of the people who generate information on the web is complex but certainly within the realm of possibility. Unless we take some rapid corrective action, other knowledge industries may suffer in the same way as the newspaper and music industries and, soon, higher education. To put this bluntly, giant computers (i.e., siren servers) are contributing to the hollowing-out of the middle class, particularly in the the information-based industries. In order to correct this imbalance, we need to compensate the people who generate the information that is the basis for the earnings of companies like Google.