Food for Algorithms
when we think of big data, we think of algorithms so powerful and enduring that they can reveal patterns, insights, and truth in data sets too huge to be processed by humans and more importantly too huge to be influenced by individuals. big data is the death the individual from an informational perspective. this projects aims to create counter algorithms ( created by individuals ) that are capable of creating huge amounts of plausible data sets that are likewise produced by algorithms.
these data sets are:
- technologically plausible settings
- on the border of credibility
- completly fake!
- presented in a serious manner
implementations of this idea might be:
- GPS data from chicken farms ( laying batteries )
- (simulations of population sub-sets)
- (modulated social network data sets)
- accelerometer data from abuse human bodies
- accelerometer data of mobile phone users
there is no such thing as raw data, hence every data set has an agenda. in this case the twist ( i.e the fake ) applied to each subset aims to override the inital agenda to introduce a new one. thus discussing a topic not by relying on the vermeintliche truth of a dataset, but by its fabrication.
the algorithms creating these data sets might be:
- virtual physics simulation ( GPS and accelerometer data )
- mesh ups of exhisting data sets ()