The Artist Who Drew With Computers, Before Computers Were a Thing Vera Molnár, a little-known founding mother of computational art and thinking, will feature in MoMA’s new exhibition on art and technology, "Thinking Machines: Art and Design in the Computer Age.” By Min Chen Published November 13, 2017 at surfacemag.com Long before she had access to a computer, Vera Molnár was already thinking like one. To create her geometric images in the 1950s, she invented a systematic procedure: a series of exploratory steps and rules that aped a computer’s inputs and outputs, and dictated the final, hand-drawn form of her work. Dubbed “machine imaginaire,” her process was as much a tool as it was a concept with which to reprogram traditional visual practices. It was a radical adoption of technology—however much imagined—that would blaze a trail for computational art and design in the decades to come. Working at a time before new media was widely embraced, Molnár’s canvases have largely been forgotten—that is, until now. The pioneering contributions from this 90-year-old artist, who is still working today, will be celebrated this November at the Museum of Modern Art’s new exhibition, “Thinking Machines: Art and Design in the Computer Age,” open today. Examining how art and technology interacted between 1959 and 1989, when personal computers were just arriving on the mass market, the exhibition (which will also highlight artists Waldemar Cordeiro, Lee Friedlander, and Alison Knowles) turns the spotlight on Molnár’s inventive use of machines, and her overall impact on the field. “Because of her conceptual approach to computing, Molnár’s work is an important part of this exhibition’s thesis: that the computer and its attendant logic were used by artists and designers even when they weren’t working directly with those tools,” explain the exhibition’s curators, Sean Anderson and Giampaolo Bianconi. “What viewers are seeing is the simultaneity of a rigorous process as well as the work itself. Read as transparencies, the process and conceptual meet.” From 1968, the Hungarian-born Molnár transitioned from thinking like a machine to actually working with them, incorporating a computer and plotter into her process. With these new tools, her images bloomed with complexity. The minimalist logic of her 1957 “Slow Movement” series would evolve into the intricate matrix of “Square Structures” in the ’80s, demonstrating her commitment not just to geometry and sequential thinking, but also to enhancing her practice with technology. Exhibited at MoMA will be two iterations of Molnár’s noted work “A la recherche de Paul Klee”—a digitized reimagining of Klee’s cubist aesthetic, hypnotic in its geometric embroidery—one a plotter drawing from 1970 and the other a felt-tip pen on paper from 1971. However similar on first glance, the computer-aided version bears more detail and nuanced
colors than the hand-drawn version, highlighting how the plotter enabled her to reach beyond the limitations of the felt tip and her manual labor. Whether working with a “machine imaginaire” or a “machine réelle,” Molnár maintained the computer as a formal instrument, constantly probing its purpose and possibilities. She employed a plotter, but never allowed the tech to overwhelm her work—thus preserving in her computer images a vital human aspect. As the distance between machines and humans shrinks, this interrogation and command of technology lend her oeuvre new resonance. “What makes Molnár’s work so important today is that her ability to experiment was aided and amplified by the tools she used,” say Anderson and Bianconi. “This spirit of experimentation allowed these works to be both systematic and humanistic, and has been influential for artists who have worked with computers since.”
An Armored Vehicle For Art, Not War With vehicle attacks and militarized policing on the rise in the U.S., the American debut of South African artist Ralph Ziman’s “SPOEK 1” at this weekend’s 1-54 Contemporary African Art Fair New York could not be more timely. By Min Chen Published May 3, 2018 at s urfacemag.com Earlier this week, South African filmmaker and artist Ralph Ziman had the unique pleasure of watching his 2016 piece “SPOEK 1,” a reclaimed military vehicle, transported through the streets of New York and Brooklyn on the back of a flatbed truck. It was bound for installation at the 1-54 Contemporary African Art Fair New York (running from May 4 through 6 at Pioneer Works in Red Hook, Brooklyn)—a long way from its roots and a far cry from its role in combat. Designed and made in Africa for warfare in the late 1970s, these armored vehicles, known as Casspirs, were extensively used as weapons of terror and oppression in apartheid-era South Africa, and later, by American troops in Baghdad during the Iraq War. Zigman’s rig, however, disrupts that violent legacy. “I wanted to take what was the ultimate symbol of apartheid,” he says, “and turn it into something that is African and beautiful.” For “SPOEK 1,” the artist and his team restored a Casspir, before blanketing its surfaces with intricate, dazzling panels of beadwork. “It was the opposite of camouflage,” says Ziman. Woven by artisans from Zimbabwe and the Mpumalanga province in South Africa, these traditional patterns offer stark contrast to the vehicle’s original army-green body and in turn, its intended purpose. Their vibrancy channels the optimism and spirit of a country emerging out of systemic abuse—Ziman calls it “Africanness” and also, “hope.” Unveiled for the first time in America, the work further echoes this country’s history of police brutality and violence (the Casspirs purchased by the U.S. during the war were later given to American police forces). Reflecting upon Black Lives Matter protests and “heavily armed mostly white policemen dressed in level-three armored vests,” Ziman reckons, “it looks like apartheid-era policing.” Telling the story of the Casspir is crucial to him, if only to underscore the growing militarization of policing and the crippling effects of division. Just as he drove his Casspir to various South African provinces from Soweto to Cape Town last year, Ziman plans to tour his piece across America. “I really want to talk about it and I want people to understand what the vehicle is. “This,” he says, referring to its debut at this weekend’s fair, “is very much the first stop.”
When Art Meets Algorithm How today’s technologies from artificial intelligence to generative scripts are changing the way art is made. By Min Chen Published March 25, 2019 at g litch.com At “New Order,” a newly opened exhibition at the Museum of Modern Art, art and technology are having a major love-in. The show surveys how the time-honored bond between the two fields has evolved in the new millennium, arraying works that explore and expand the creative possibilities of today’s technologies. There’s a self-playing video game by Ian Cheng, a digital simulation of Jeff Koons’ Rabbit by Mark Leckey, and Tauba Auerbach’s series of 116 3D-printed geometric objects. In these and more, the digital has been made physical; TIFF and AVI files are given tangible form. They are machine-generated realities. Of course, it’s not as if art and technology are siloed disciplines. For generations, they have been in collaboration and confrontation, pushing and upending the other’s boundaries. “The two are totally embedded and intertwined,” says Michelle Kuo, the exhibition’s organizer and the Marlene Hess Curator of Painting and Sculpture. “Technology is material and formal in a way that we can’t forget. It’s only by really paying attention to these forms and realities of technology and its effects that we can begin to understand how to change it.” Change is already on its way. Where traditional artists would wield a brush, sculpting knife, or camera, the 21st century affords artists tools from artificial intelligence to 3D printing to virtual reality, enabling them to create in innovative and novel ways. Advancing technologies have dared art to take new risks and art has responded in kind. Once, the interaction between art and technology triggered ethical and moral questions. For example, how can a machine be an artist? Lately though, it’s broaching the richer issue of artistry itself. It asks: can a machine be creative? When Machines Do Art It’s an inquiry sparked by the emergence of algorithmic or AI art, the practice of employing code, data, and machine learning systems to generate pieces of art. These Generative Adversarial Networks have been producing such works for a few years now, but it’s only recently that AI art has found itself smack in the middle of the art (and art-buying) world. Last October, an algorithm-generated portrait, “Edmond de Belamy, from La Famille de Belamy,” went under the hammer at Christie’s and sold for a cool $432,500. Created by French collective Obvious, it was the first-ever AI portrait to go on auction, and its sale spawned headlines variously celebrating and worrying about its implications for art-making. Should artists be worried about their jobs? Not at all, says Obvious’ Gauthier Vernier. “We see AI as a tool to catalyze the artist’s own creativity,” he tells me. “We don't believe that artists’ jobs are threatened, but we believe that a new type of artist could emerge, one that
understands and works with AI models.” The products of this union will naturally be curiosities, half-manmade and half-machinemade. After all, in making “Edmond,” the AI model, like the human that built it, acts as producer and creator, significantly blurring the lines between artist and technology. Here and elsewhere, AI doesn’t just facilitate the artist, but also, imitates. That’s not to say it can create. “Creativity is a notion that is hard to define,” says Gauthier, “so we like to say that an AI can be inventive, in a way that it can invent something new, unique, and relevant.” What these algorithms and machines do, inventively and unpredictably, is generate. My Generation Generative art is not new: art, music, and poetry created by an independent system has been around long before computers existed. In the 1950s, the likes of Vera Molnár and Ellsworth Kelly were devising strict procedures with rules and instructions that determined how their visual art turned out. The ‘60s ushered in computer art pioneers from Frieder Nake to Manfred Mohr to Roman Verostko, who latterly coined the term algorists, as in algorithm artists. And notably, from the ‘70s, musician Brian Eno began experimenting with generative music—what he called “putting in motion something and letting it make the thing for you”—yielding 1991’s Neroli, 2017’s Reflection, and apps like Bloom and Trope. Eno has not only been visionary and perceptive about the field, but is drawn to the questions it raises: “Who actually composes music like this? Can you describe it as composition exactly when you don’t know what it’s going to be?” At the same time, he remains in thrall to generative music’s promise—likening its vast “multi-centered” nature to the internet, and urging a reconsideration of the artist’s function. “If you move away from the idea of the composer as someone who creates a complete image and then steps back from it,” he’s said, “there’s a different way of composing.” Making good on that inheritance, today’s generative artists understand how their role is shifting alongside technology. Digital artist Sean Catangui tells me, “With generative art—creating the algorithms that generate art, but also selecting which of the results to present—the ability to create thousands of compositions in less than a second shifts the role of an artist to that of a hybrid artist-editor-curator.” His generative work, such as Line Tree, C-mum, and Randomized Form, emerged from his desire to enhance his ideas through programming. In the process, they gleaned him an appreciation of code and computer as expressive mediums. These projects, he says, “made me feel like the machine was alive.” And the machine is alive all over Glitch. You’ll find it in other generative art works such as Matt DesLauriers’ Retro Album Covers, n–schedé’s algorithmic objects and landscapes, and Anders Hoff’s many interactive forms. With these pieces, the artists may have constructed the machines and models, but as they stir and run, it’s their generative efforts that exceed expectations and hold unending surprises. “I might be just as happy to discover some
unexpected behaviour and explore that instead,” writes Hoff. “Overall, this means that the process is continuous, exploratory, and never really complete.” Art Encoded In the lo-fi, early days of computer art, practitioners endeavored to define and describe what exactly it was they were doing. Just observe how the 1976 anthology Artist and Computer offers a trove of phrases such as “creative processing” (from Mohr) or “scientific aesthetics” (Hiroshi Kawano). Whatever they were, all pretty much suggested that the alliance between art and science works both ways. If technology is made a part of art, art might also be embedded into technology to realize what Kawano termed “the science of human art.” Or to arrive at Jenn Schiffer’s Piet Mondrian generator. Marrying art and code, the application does as it says on the tin and produces iterations of the painter’s post-Impressionist compositions. (As she also points out, Mondrian’s logical, progression-based pieces are ripe fruit for programming languages.) This is just one part of Schiffer’s broader var t; project, a series of similar generators emulating the works and styles of artists including René Magritte, Henri Matisse, and Mary Cassatt. In doing so, she’s turned material art into intangible Javascript—a process directly opposite of that happening at MoMA’s “New Order”. That script, then, might itself serve as an art form. Chad Weinard, Mellon Manager of Digital Initiatives at Williams College Museum of Art, dubs it “code as its own form of creative writing.” He arrived at that idea after witnessing poet Lillian-Yvonne Bertram’s adaptation of Allison Knowles’ computer poem “A House of Dust.” Originally built with FORTRAN language, the piece is a constantly shifting entity, its lines randomly generated and connected. Weinard responded with his own iteration, populated with collection data from the museum. Representing an interaction between data, algorithms, and chance, his quatrains are also woven with a collected history and a history of collecting. “I’ve been fascinated with the accumulated textures, biases, artifacts and quirks of that data as it’s been passed on over the years,” he says, “and thinking about what legacy we’ll leave in the data for others to find in the future.” And future humans will find not only art in our code, but art criticism, particularly in Omayeli Arenyeka’s creation, Art Connoisseur. The Twitter bot raids Artsy for images of art, then generates commentary on each with hit-or-miss accuracy and a snarky, knowingly pretentious tone. “Ooh, it’s minimalism without mortality,” is just one brassy example. Though somewhat tongue-in-cheek, the app underscores the abiding gap between art and its interpretation, if not the pitfalls of allowing a machine to evaluate art. But is it art? So how should we deal with such machine-generated realities? Generative and AI art are awesome to behold, but neither are intended to be measurements of any machine’s creativity. Rather, as Kawano once wrote, their immense potential and varied products offer
only an “artificial creativity.” Perhaps computer-generated works do more by simply broaching and challenging notions of creativity and authorship, presenting a tension between artist and tool that resolves nothing, but offers us the opportunity to interrogate everything. Which, really, is the point of art anyway. Just like the open-ended nature of generative art, the ever-evolving relationship between art and technology can only continue to astonish as it brings forth yet more revelatory artifacts, arguments, and possibilities. “Technology can change us, the way we think and look and relate to each other,” says Weinard. “I hope art can make technology more self-conscious, mindful of the future, more personal and textured, more humane, more reflective, more vulnerable, more inclusive, more creative.” That exchange bodes well for the future of both fields. All we have to do is set it in motion.