False Walls

With new methods of production and innovative design processes, architecture has been enabled by processes that promise efficiency but that also complicate the agency of designers through the use of contemporary technology. False Walls examines the use of artificial intelligence and machine learning to understand and further agitate this new era of the design process. While iterating between machine learning, digital design, and model making; for example, novel design opportunities arise from misappropriations of various technologies. In machine learning this is called unsupervised learning in which machine learning models articulate patterns in data that humans do not detect, either by virtue of the complexity of this data or its vast quantity. Allowing algorithms to assist, favors new methods of analysis in the design process. Through the introduction of standard construction methods, the machine discovers frictions in framing techniques that yield interesting design opportunities. These mistakes and transgressions of typical wall-framing tectonics reveal the proclivities of the algorithm and generates new design opportunities in doing so. The new design alternatives discovered through this process will be exhibited in a built frame. This full scale model will be on display in the gallery at the School of Architecture and Urban Planning on April 17th with an accompanying lecture on the discovered design opportunities. In a world of growing technology we have entered a time where we have grown past how technology is used to increase the efficiency of making, and is instead a site that can be mined for design potentials