VOTING BOOTH is the top-of-the-line product of the fictitious Govtech Startup smile to vote.
By means of AI-based facial scanning, the Smile to Vote e-voting booth gages the political conviction of any given person and emulates the process of digitally casting a vote at the 2019 European Parliament elections by simply looking into a camera. (Versions for German Federal Elections and Bavarian State Elections are also available upon request).
Building on the basis of Wang and Kosinski [Wang, Kosinski, 2017, Deep Neural Networks Are More Accurate Than Humans at Detecting Sexual Orientation From Facial Images], the Smile to Vote – software employs AI-based computer vision analysis to gage the facial characteristics of a person and compare them to photo datasets, which have been classified by political conviction.
By using a neural network, that has been trained on photos of people who’s party membership and political affiliation are unequivocal, it becomes potentially possible to deduce, in real time, the political conviction from the face of any given person, that is captured by the camera [Peterhaensel, 2018, Smile to Vote: Towards Political Physiognomy Analytics – Predicting Electoral Behavior from Live Video].
Interaction with the Smile to Vote – voting booth translates the complex ramifications of delegating decision making to IT systems into an aesthetic experience, and therefore makes these ramifications immediately perceptible and intuitively comprehensible for the recipient. The work confronts us with the implications for political processes as well as for our understanding of self-determination and freedom of will, once privacy is phased out for good and predictability of our very behavior through IT systems becomes ubiquitous.
VOTING BOOTH is an artefact of the artistic research project Smile to Vote – Political Physiognomy Analytics.