I wrote recently about the interesting new findings, reported in Nature, in which movement patterns of large numbers of urban dwellers were logged using GPS enabled cell phones. These findings, modest in some ways compared to what's coming, represent the thin edge of the wedge as we try to find ways to make use of the masses of location-based data that will soon come online.
Now, a New York based startup named Sense Networks is one of the first to jump into an area that could not only provide useful information for commercial ventures, but, if it was widely adopted, could revolutionize the ways we make decisions about where to go. Sense Networks has just launched a free service called CitySense, designed for Blackberry and iPhone users which can give an online display of where the action is in a city (at the moment, just San Francisco, but soon other major cities in the US). Beyond the undeniable coolness of a multicoloured display showing where everybody is, CitySense can also learn the preferences of the user, so the display will only show hotspots filtered according to the observer's personal definitions of "heat".
I like all kinds of things about this. Perhaps most of all, the fact that this kind of mind candy will help sensitize users to the warp and woof of social space. The red hot areas (and the cold black ones) will be telling us something tangible about what's going on, and they will invite us to think about why. As a researcher, I'm all over the idea of getting access to this kind of information. What I want to do is to understand how to design spaces in accord with individual psychologies and collective consciousness so that they work well. For my purposes, this is the killer app.
I can also see how a tool like this might change the game for those trying to understand and model the decision-making of large collections of beings (in this case, human ones). In the field generally referred to as complex adaptive system research, one of the modal systems is one in which a large collection of actors are trying to decide where to go based on predictions about where everyone else will be. In his nice readable book on the subject, "Two's Company, Three is Compexity" Neil Johnson invites us to imagine that we're trying to decide whether to go to a popular bar on a Friday night. We might or might not be able to get through the door, depending on what everyone else decides. In the classic case, we make predictions based on past experience. But what if we didn't have to guess? The game changes in all kinds of interesting ways.