Who is Edmond de Bellamy?

Edmond de Belamy is a 2018 painting created using a type of Artificial Intelligence algorithms called Generative Adversarial Networks.

The work which is part of a series of images titled La Famille de Belamy -made by french collective Obvious– was expected to be sold for $7,000-$10,000 at Christie’s auction house in New York, however the painting was finally purchased for $432,500.

Obvious was founded by 3 young students who are based in Paris: Pierre Fautrel, Hugo Caselles-Dupré and Gauthier Vernier. The main goal of this group of friends, artists, and researchers is to explain and democratize the advances in Artificial Intelligence through art. They started working together in 2017 when they discovered a set of Deep Learning algorithms that generate images called Generative Adversarial Networks (GANs).

Deep Learning is a revolutionary form of Machine Learning made with different layers of Artificial Neural Networks, a set of algorithms modeled loosely after the human brain that are designed to recognize patterns. They interpret sensory data through a kind of machine perception, labeling or clustering raw input. Therefore, Deep Learning is a type of Artificial Intelligence architecture that makes computers learn from experience and understand the world in terms of a hierarchy of concepts by building them out of simpler ones. Since the computer gathers knowledge from the experience of processing different data-sets, there is no need for a human operator to formally specify all of the knowledge needed by the computer.


This historic event -the so-called auction of the “first artwork made by an AI” (of course we are omitting the pioneering job of Harold Cohen’s robot painter AARON, for example)- raises 3 interesting questions about authorship, originality, and the arts as a space for scientific inquiry:

1) Autorship: Frédérique Baumgartner, an art historian at Columbia University, says that the portrait of Edmond de Bellamy has a light semblance with those paintings made by the old master Rembrandt. In the past, artist like Marcel Duchamp also raised questions about intention and authorship when he emphasized that the artist’s idea was the key element in the creation in clear opposition to the classical perspective centered in technique and aesthetics. This new art created by Generative Adversarial Networks radically flips this idea, not just creating a new thought for an object, but creating an artifact (the AI) capable of doing the thinking and creating for us. Computational systems are not human and so we should accept the creativity they exhibit as legitime creativity, but not as we know it since they will never be exactly the same as the one homo sapiens exhibits.

2) Originality: Google AI engineer François Chollet, creator of an open source Neural Network library called Keras, proposed a seductive name for this kind of artworks: GANism. In general, open source refers to any program or cultural artifact whose source code or components are made available for use or modification as users or other developers see fit. When Hugo Caselles-Dupré, the tech lead for Obvious and a machine learning PhD student in Paris, found Robbie Barrat’s open-source algorithms in code sharing website Github he simply used them to generate the Edmond de Belamy portrait. Does this make the artwork less original? From sampling in hip-hop to the influence of african-art in Picasso’s paintings, the creative world is full of examples of artworks made by recombination.

3) The arts as a space for scientific inquiry: Ahmed Elgammal (professor of Computer Science at Rutgers University and director of the Art and Artificial Intelligence Laboratory) thinks that considering the whole process of creating artworks with GANs the outcome is something more like conceptual art than traditional painting. Certainly the question of to what degree algorithms are tools, as opposed to active collaborators, is a very interesting debate in which the artists can contribute interesting reflections. Although, still this machines are not self-directing agents, we must accept this kind of AI more of an ideation partner, rather than simply a tool for making new products.


According to Blaise Agüera y Arcas -founder of the Artists and Machine Intelligence program at Google– the transformation of artistic practice and theory that attended the 19th century photographic revolution is equal to the current revolution in machine intelligence, which promises to democratize the means of reproduction and production. Let’s make the best out of it!

*(Pictures: cnbc.comanalyticsindiamag.com, Tiphaine Rolland & Poladroid).

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