Ever since I read Timothy D. Wilson’s magnificent “Strangers to Ourselves“, I have been fascinated with the fact that we often know less about ourselves than our closest friends and family (thanks probably to our many cognitive biases) .
Enter MIT’s Reality Mining Project:
[O]ur ultimate goal is to create a predictive classifier that can learn aspects of a user’s life better than a human observer (including the actual user)…
Kevin Kelly explains:
Can our devices know us better than we know ourselves? It seems obvious that this must be true. Human self knowledge is plagued by all kinds of limits: bias, sampling error, memory failure, and lack of sufficient processing power to recognize complex patterns. Machines do not suffer from the first three of limits, and the last is under steady assault from Moore’s law. But for computers to help us know ourselves better, they need two things: better data, and new analytical tools for transforming this data into predictions. These are problems that the Reality Mining researchers (among others) are trying to tackle.
…Proving that people can be effectively tracked using low-power Bluetooth transmissions has a certain technical interest, but of course the true power of this work lies in beginning to understand what kinds of things can be learned from such tracking. Eagle and his colleagues, for instance, found it easy to predict when two people were likely to encounter each other, as long as the users had fairly regular habits.
…Their claim is that their system can predict social behavior among people who are easily predictable. Such a result might seem the very definition of trivial, but it’s not as pointless as it sounds. Such a result functions as a kind of system tuning, a check on whether the basic parameters of Bluetooth tracking and social predictions are plausible. Once you know that it works on the easy cases, you can start trying to generate the more interesting analytical tools necessary to get more surprising results.
If Sociology in the 21st Century, User Behaviour Modelling , Relationship Inference, Social Serendipity, Organizational Dynamics, Epidemiology, Information
Dissemination and Eigenbehaviors are your thing, then get over there and find out what your overlords have install for you next.