An experimental research in machine-learning that identifies and analyzes the concept of social normalcy.
Each participant is presented with a video line up of 4 previously recorded participants and is asked to point out the most normal-looking of the 4. The person selected is examined by the machine and is added to its algorithmically constructed image of normalcy. The kind participant’s video is then added as a new entry on the database.
As the database grows the Turing Normalizing Machine develops a more intricate model of normal-appearance, and moves us closer to our research goal: to once-and-for-all decode the mystery of what society deems “normal” and to automate the process for the advancement of science, commerce, security and society at large.
The Turing Normalizing Machine, by Mushon Zer-Aviv
Part of several exhibitions shown in Israel, Athens and Kiev
Software developed using OpenFrameworks in a Hotel in Athens.
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