Architecture and Technology in Contested Terrain: An Application of Machine Learning in Interactive Spaces

Abstract: This thesis investigates the potential application of Machine Learning in architecture to help mitigate contested terrain. The process is defined by research and insights retrieved from it. The initial analysis includes a historic overview of Mostar, as well as a status analysis of the current socio-political climate in the town, after which a brief introduction of Machine Learning lays the groundwork for the potential application in architecture, in order to achieve the objective of mitigating contested terrain. The final result is a design project in the shape of a Center for Contemporary Art that hosts an exhibition space that, with the help of Machine Learning, aims to take people out of their filter bubbles by exposing them to art/messages that they would not have been inclined to take part of on their own.