In the last twelve months we have seen a tremendous spike in the interest of “AI art,” ushered in by Christie’s and Sotheby’s both offering works at auction developed with machine learning. Capturing the imaginations of collectors and the general public alike, the new work has some conservative members of the art world scratching their heads and suggesting this will merely be another passing fad. What they are missing is that this rich genre, more broadly referred to as “generative art,” has a history as long and fascinating as computing itself.
A history that has largely been overlooked in the recent mania for “AI art” and one that co-curators Georg Bak and Jason Bailey hope to shine a bright light on in their upcoming show Automat und Mensch (or Machine and Man) at Kate Vass Galerie in Zurich, Switzerland.
Generative art, once perceived as the domain of a small number of “computer nerds,” is now the artform best poised to capture what sets our generation apart from those that came before us - ubiquitous computing. As children of the digital revolution, computing has become our greatest shared experience. Like it or not, we are all now computer nerds, inseparable from the many devices through which we mediate our worlds.
Though slow to gain traction in the traditional art world, generative art produces elegant and compelling works that extend the very same principles and goals that analog artists have pursued from the inception of modern art. Geometry, abstraction, and chance are important themes not just for generative art, but for much of the important art of the 20th century.
Every generation claims art is dead, asking, “Where are our Michelangelos? Where are our Picassos?” only to have their grandchildren point out generations later that the geniuses were among us the whole time. With generative art we have the unique opportunity to celebrate the early masters while they are still here to experience it.
The Automat und Mensch exhibition is, above all, an opportunity to put important work by generative artists spanning the last 70 years into context by showing it in a single location. By juxtaposing important works like the 1956/’57 oscillograms by Herbert W. Franke (age 91) with the 2018 AI Generated Nude Portrait #1 by contemporary artist Robbie Barrat (age 19), we can see the full history and spectrum of generative art as has never been shown before.
Emphasizing the deep historical roots of AI and generative art, the show takes its title from the 1961 book of the same name by German computer scientist and media theorist Karl Steinbuch. The book contains important early writings on machine learning and was inspirational for early generative artists like Gottfried Jäger.
We will be including in the exhibition a set of 10 pinhole structures created by Jäger with a self-made pinhole camera obscura. Jäger, generally considered the father and founder of “generative photography,” was also the first to use the term “generative aesthetics” within the context of art history.
We will also be presenting some early machine-made drawings by the British artist Desmond Paul Henry, considered to be the first artist to have an exhibition of computer generated art.
In 1961 Henry won first place in a contest sponsored in part by well-known British artist L.S. Lowery. The prize was a one-man show at The Reid Gallery in August, 1962, which Henry titled Ideographs. In the show, Henry included drawings produced by his first drawing machine from 1961 adapted from a wartime bombsight computer.
The show features other important works from the 1960s through the 1980s by pioneering artists like Vera Molnar, Nicolas Schoeffer, Frieder Nake, and Manfred Mohr.
We have several generative works from the early 1990s by John Maeda, former president of the prestigious Rhode Island School of Design (2008-2014) and associate director of research at MIT Media Lab. Though Maeda is an accomplished generative artist with works in major museums, his greatest contribution to generative art was his invention of a platform for artists and designers to explore programing called "Design By Numbers."
Casey Reas, one of Maeda’s star pupils at the MIT Media Lab, will share several generative sketches dating back to the early days of Processing. Reas is the co-creator of the Processing programing language (inspired by Maeda’s “Design By Numbers”) which has done more to increase the awareness and proliferation of generative art than any other singular contribution. Processing made generative art accessible to anyone in the world with a computer. You no longer needed expensive hardware, and more importantly, you did not need to be a computer scientist to program sketches and create art.
Among the most accomplished artists to ever use Processing are Jared Tarbell and Manolo Gamboa Naon, who will both be represented in the exhibition. Tarbell mastered the earliest releases of Processing, producing works of unprecedented beauty. Tarbell’s work appears to have grown from the soil rather than from a computer and looks as fresh and cutting edge today as it did in 2003.
Argentinian artist Manolo Gamboa Naon - better known as “Manolo” - is a master of color, composition, and complexity. Highly prolific and exploratory, Manolo creates work that takes visual cues from a dizzying array of aesthetic material from 20th century art to modern-day pop culture. Though varied, his work is distinct and immediately recognizable as consistently breaking the limits of what is possible in Processing.
With the invention of new machine learning tools like DeepDream and GANs (generative adversarial networks), “AI art,” as it is commonly referred to, has become particularly popular in the last five years. One artist, Harold Cohen, explored AI and art for nearly 50 years before we saw the rising popularity of these new machine learning tools. In those five decades, Cohen worked on a single program called Aaron that involved teaching a robot to create drawings. Aaron’s education took a similar path to that of humans, evolving from simple pictographic shapes and symbols to more figurative imagery, and finally into full-color images. We will be including important drawings by Cohen and Aaron in the exhibition.
AI and machine learning have also added complexity to copyright, and in many ways, the laws are still catching up. We saw this when Christie’s sold an AI work in 2018 by the French collective Obvious for $432k that was based heavily on work by artist Robbie Barrat.
Pioneering cyberfeminist Cornelia Sollfrank explored issues around generative art and copyright back in 2004 when a gallery refused to show her Warhol Flowers. The flowers were created using Sollfrank’s “Net Art Generator,” but the gallery claimed the images were too close to Warhol’s “original” works to show. Sollfrank who believes “a smart artist makes the machine do the work” believed she had a case that the images created by her program were sufficiently differentiated. Sollfrank responded to the gallery by recording conversations with four separate copyright attorneys and playing the videos simultaneously. In this act, Sollfrank raised legal and moral issues regarding the implications of machine authorship and copyright that we are still exploring today. We are excited to be including several of Sollfrank’s Warhol Flowers in the show.
While we have gone to great lengths to focus on historical works, one of the show’s greatest strengths is the range of important works by contemporary AI artists. We start with one of the very first works by Google DeepDream inventor Alexander Mordvintsev. Produced in May of 2015, DeepDream took the world by storm with surreal acid-trip-like imagery of cats and dogs growing out of people’s heads and bodies.
Virtually all contemporary AI artists credit Mordvintsev’s DeepDream as a primary source of inspiration for their interest in machine learning and art. We are thrilled to be including one of the very first images produced by DeepDream in the exhibition.
The show also includes work by Tom White, Helena Sarin, David Young, Sofia Crespo, Memo Akten, Anna Ridler, Robbie Barrat, and Mario Klingemann.
Klingemann will show his 2018 Lumin Prize-winning work The Butcher’s Son. The artwork is an arresting image that was created by training a chain of GANs to evolve a stick figure (provided as initial input) into a detailed and textured output. We are also excited to be showing Klingemann’s work 79543 selfportraits, which explores a feedback loop of chained GANs and is reminiscent of his Memories of Passersby which recently sold at Sotheby’s.
Automat und Mensch takes place at the Kate Vass Galerie in Zürich Switzerland and will be accompanied by an educational program including lectures and panels from participating artists and thought leaders on AI art and generative art history.