Politics as applied math
The puzzle starts to come together: every single piece of information is gathered and processed ;afterwards, it is linked to a profile; a model or pattern is then generated; finally, cluster classification or homogenous grouping is performed. Unique kinds of information are extracted to contribute to a new knowledge. Unavailable to the public, this dark data is hidden from the user-voter, who unwillingly supplies it following a ‘rational’ economic agreement: free access to information on the Web is given in exchange of personal data. Dark data can then be sold to generic advertising companies - as in the notable case of Google; alternatively, they can be distributed to governmental and non-governmental control offices for alleged security reasons. Otherwise - as in our example - these data form the basis of the rank and file of any political movement based on network cultures. Data is data and the better are the data, the better are the analyses, the results; and, as in the case of Google, the better is the capacity and overall performance of search algorithms’ the more rewarded are its users. Why does a user-voter choose a certain party? Why does she/he feel more empathetic to certain topics rather than others? What are the user-voter’s personal inclinations? How much and how finely can a user’s profile be tailored? (...)
Painting: Stelios Faitakis
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