We can’t ignore the fact that this exhibition was initially six months earlier. The reasons are still pressing and urgent, and our world has changed significantly since then. Not only did we gain a novel genotype virus, but also our socio political world has reorganised under what proceeds as the New Normal. The latter is the unfolding paradigm under which technological surveillance, socio-geometric constraints of human interaction, biopolitical signifiers, border control and national lockdown rhythms have become prerequisites to mitigate the consequences and calamities of the pandemic. However, the existential questions that do emerge from the pandemic, are not answered by the disappearance of its consequences: if the present heralds a glimpse of what the New Normal will bring, is it the future we want? In response to the emergencies of the New Normal, this exhibition went through an update. The visitor finds itself present as subject and observer of a simulated surveillance state. In the exhibition facial recognition algorithms extract and compute emotional profiles of the visitors which are then processed into characters (BB_Worker) of a 3-channel gaming engine. An AI surveillance system displays, detects, calculates, and predicts the collective- and individual interactions of the BB_Workers. The gaming engine is an adjusted version of Joshua Epstein’s computational model of Civil Violence (2002).

Keywords:
Artificial Intelligence, Unreal Engine, Surveillance Capitalism, Computational Social Science, GAN

Keywords:
Evolutionary Algorithm, Unreal Engine, Agents, Blobs

All images below are screenshots of the simulation. The variety of BB_Workers are created with an evolutionary algorithm in Blender.

The gaming engine is populated with virtual surveillance cameras that are channeled through a 'deepstream' system that observes the collective behaviour of the BB_Workers. The Darknet AI framework is used and the YOLOV4 model is trained on a synthetic dataset.