Platformer

In order to propose relevant actions, and indeed in order to identify the most potent coalitions, it is necessary to understand the political, economic and human power associated with each individual. A fatal weakness of traditional political organizing is that the need to collect and centralize this information for analysis poses an intolerable risk to privacy and personal security. Not only are there severe moral hazards in attempting to build comprehensive profiles of individuals for a political database, but in many jurisdictions this is expressly forbidden by law. Laws rightly protect individuals from being profiled by political organizations seeking to recruit them, or by corporations seeking to market goods to them.

With Platformer, however, our model has a different center of gravity. Instead of locating the power to identify, categorize, and organize in an entity like a political party, we center everything on the individual. In the same way, so-called “personal data” must remain the inviolable property of the individual. Yet, we want the individual to be able to allow the system to locate him or her within constituencies using this data—without revealing the data or the user’s identity to other users.

The precise means of accomplishing this are one of the areas of research, but an outline of the technical concepts already exists and builds on proven approaches to security and privacy. The key with Platformer is that the system provides verifiable guarantees of the safety of data, and allows an individual to safely build up a very deep profile (what would amount to a corporate marketer’s dream) containing a comprehensive set of information about an individual encompassing everything from income to reading habits to type of abode to usual diet and so on. In today’s world, the prospect of aggregating so much data may seem frightening, but Platformer will provide such a guarantee of security, and will allow individuals to put this data to such spectacular uses, that concerns will be allayed.

So to extend our fictional example above, let us say that the system has identified a significant number of people concerned with the Oregon bird situation who also buy gas regularly from Lukoil, a Russian oil company. Similarly, a large number of the individuals focused on the Russian police issue have indicated that they have office jobs involving appreciable quantities of paper usage. So the system proposes to the first group to pledge a month-long boycott of Lukoil stations unless that company lobbies the Russian government for reform of the police system, and to the second group it proposes a pledge to push their employers to boycott the paper company that is threatening the endangered bird unless the paper company stops obstructing legislation to protect the bird.

While this example may seem strained, hopefully the concept is clear. In fact, the very difficulty that any of us may have in constructing an example such as this is, paradoxically, an illustration of the true power of this approach. Platformer is designed to discover correspondences such as these that could never be reasoned out by mere speculation. Building on decades of research in areas like collaborative filtering and data mining, Platformer is able to leap ahead and produce truly stunning results because of the power of deep profiles.