Autonomous Artificial Artists (ITPG-GT 2497)

Autonomous Artificial Artists (AAA) is a class to explore ways of making artworks “autonomous.” In this context, “autonomy” brings together three independent but related criteria: 1) artificial intelligence being a primary determinant in an artwork’s aesthetics 2) autonomous software principles culled from peer-to-peer network design, blockchain and decentralization technology, serverless and federated machine learning, cryptoeconomics, and agent-based multiplayer simulation. 3) crowd-sourced art where mass, unbounded cooperation of many participants creates novel artworks which represent the “hive mind” or collective input. The goal of this class is to learn a little bit about each of these seemingly disparate fields, and see how they may interact in interesting new ways. The idea of autonomous artworks is very new, and is being actively discussed by a small group of interdisciplinary researchers and artists since 2016/2017. Although the topic is highly experimental, it is nevertheless based on concrete technologies, making simultaneous use of several techniques which are under active development and have potentially far-reaching ramifications well outside the domain of art. The time is ripe for people within more design-oriented fields to begin thinking about how they might be used in a broader context. The class has both a theoretical component (learning about each of the individual technologies and their interplay) as well as a practical component: training and deploying generative models on computational environments that are as close to decentralized or autonomous as possible. In addition, we will explore prior notions of crowd-sourced or mass-collaborative art, touching on older principles and strategies such as Oulipo, exquisite corpse, and crowd-sourced computational artworks like Electric Sheep, Exhausting a Crowd, and others.

Interactive Telecommunications (Graduate)
2 credits – 5 Weeks

Sections (Spring 2020)


ITPG-GT 2497-000 (22882)
04/06/2020 – 05/11/2020 Mon
3:00 PM – 6:00 PM (Late afternoon)
at Brooklyn Campus
Instructed by Kogan, Gennady