Current electronic markets use algorithms to predict consumer behavior. The algorithms collect data from various sources from your friends' choices to your previous online activities. After creating digital patterns for "similar" individuals they offer you a new product, service, song, friend, lifestyle... 

While these recommendations are most of the time surprisingly accurate to our choices, they also narrow us down to a particular user groups. Therefore there is not much space to serendipity in today' s algorithmic world. But are they really predicting or manipulating our choices? How can we interact with such systems in a way, where we make conscious choices?

The sensory filters propose a new way of feeding those systems with alternative data based on individual intuitive perception. Through specific sensors you can tag sounds, structures, images, tastes or scents you like, in a physical way. Would this new way of sensory filtering create a more transparent and personal approach to recommender systems? Or would it become a stronger tool for manipulation of consumption habits?
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 together with Isabel Prade, Ula Reutina, Anton Defant
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