Quanta is an experimental animation in which several individuals tell stories of their happiest moments, except their narratives are recomposed through the lens of machine learning. Whereas one might expect machine learning to be used to merge or blend commonalities, this animation looks for similarities and distinctions between storytellers by pealing back and revealing the interconnecting layers of the algorithm.
Artificial Intelligence and Machine Learning (AIML) are rapidly changing nearly every aspect of post-modern life; but, do we really understand it? Quantum Computing will only accelerate the adoption of AIML as the new algorithm(s) for universal computability emerge. Explainable AI (XAI) is a burgeoning field of research with the goal of opening the AIML black box and explaining how it works. From the technical standpoint, this is typically calculating and demonstrating input-to-output connections with the hope of generating more trust in AIML. The intent of this animation is to create and reveal the inner workings of an AIML from a visual arts standpoint – visual arts XAI.
Learn more about the process and technical documentation, visit the GitHub repository: https://github.com/shawnlawson/XAI-Visual-Guts
Created with the generous support of Da Vinci Labs, https://www.davincilabs.eu
Vilolist – Chris Fisher-Lochhead
Electronic Instrument System (EIS) – Michael Century
Audio Engineer – Ross Rice
EIS – Expanded Instrument System, with the Permission of The Pauline Oliveros Trust and The Ministry of Maat. https://www.ministryofmaat.org
Data Set Wrangler – Jeremy Stewart
Storytellers – Haley Day, Mike Esperanza, Olivia Link, Kendall Niblett, and Nia Sadler
Machine Learning Hardware Support – Research Computing, Arizona State University
Sound Recording Facilities – Experimental Media & Performing Arts Center, Rensselaer Polytechnic Institute