Thank you to Art In America magazine and Jason Bailey for featuring my drawing on their January issue, focusing on Generative Art. This represents a milestone in the industry of Art and Technology, and its an truly an honour to be featured here.
I made this drawing in 2017, during a residency in Tokyo. The project was an experiment; entirely self directed, simply to explore a curiosity. At the time, I was just getting started working with robots after many years of making digital and installation art through code and drawing.
The process of moving beyond what was on-screen was liberating; bringing code into a medium like robotics was a way I could return the physicality of art making back into the work.
It felt like a coming home — my years of drawing, which always felt obscured by software tools, felt like it could be playful, adaptive, and imperfect, in a way that could help me grow as an artist.
I’ve learned a lot about technology through making art with machines — which began over 5 years ago. I learned that the human hand is always present, and “the AI” is always a system that reflects some known and unknown aspects of its designer.
There’s a lot of hype surrounding this idea of “AI Art” at the moment. I think it’s largely driven by a subconscious anxiety of how intertwined in our lives digital technology has become. People appear to really like thinking that the AI is making music, making poetry, making painting. Perhaps this is because if “the AI” can make beautiful art, it might somehow make up for the fact that “the AI” is also taking our jobs, making biased policy decisions, and shaping our society in ways we don’t really understand. The ‘AI as artist’ is an alluring idea that helps soothe, perhaps, a fear of these technologies, but it’s one that does nothing to empower us in the face of technological change.
As an alternative to this, I like to think of the potential for AI systems as collaborators. Why? Because we’ve all had collaborators, good and bad. Collaboration is about making with; it can be about control and dominance, but it can also be generosity and kindness. Ultimately, these AI systems can be created in the service of working together, to make something better for both human and machine.
For me, that’s what is promising and hopeful about working with these technologies - in fact, I think it might be an imperative. We should be designing these technologies to make us, and the world, better. To achieve this goal, art and technology are a very natural pairing; they both reflect the culture in which they are made, and both have the power to profoundly shape the future we want to see.
Sougwen Chung is an internationally renowned multi-disciplinary artist and researcher, whose work explores the dynamics of humans and systems. Chung is a former research fellow at MIT’s Media Lab and a pioneer in the field of human-machine collaboration. In 2019, she was selected as the Woman of the Year in Monaco for achievement in the Arts & Sciences.
Aswin Pranam: You're an artist, researcher, and leading figure in the world of human-machine art & collaboration. For the uninitiated, what is human-machine collaboration?
Sougwen Chung: Human-machine collaboration is a perspective of technology not as a tool, but as a collaborator. What does that mean? It stems from an understanding that the relationship between humans and their tools have changed. Digital tools are different from tools like a hammer, for instance. They are editable, fluid, distinctly fallible, or all the above. Screen-based tools change and receive updates in a way that physical ones do not. Think photoshop vs. a paintbrush.
And today, with the predictive nature of A.I. systems, which are driven by user data, the tools are informed by us. By the user through the data being collected, by the designer's intent, and by technological trends, processing power, and a suite of other factors. I find this interesting because it seems like there is a responsive quality to tools of the modern-day, prevalent in commonplace concepts like autosuggest / autocorrect. This feedback loop of the human/tool/system fundamentally changes the process of making; the canvas is no longer blank. It suggests things to you and nudges you along. It complicates authorship, and it extends beyond creative pursuits to our day to day use of technology. Depending on your perspective, that's either exciting or uncomfortable.
So, human-machine collaboration situates these ideas at the forefront — it recognizes that the dynamic between an artist and her technological tools is more complicated. There is an excitement in culture at the moment about "A.I. art" and "A.I. artists," and I think it stems from an interest in understanding what the promises, potentials, and paranoias of A.I. are and could be. That being said, I find the false premises about A.I. creating art strange. It suggests this relinquishing of human agency and erasure of human labor. Which, for me, is not what is exciting or valuable about the artistic practice.
Also, the data through which the A.I. system's model is trained is not always solely created by the artist or designer. By coming to terms with that, I think we can arrive at a provocative perspective. For me, that's at the heart of human-machine collaboration. A sense of collective authorship — a collaboration between the artist, the data set, the machine, and the dynamics & design of the algorithmic process. Human-machine collaboration has created a place for me to explore the complicated and compelling question of authorship as a working artist today.
Pranam: In your T.E.D. Talk, you described building a robotic prototype (titled D.O.U.G.) that mimicked your hand movements on the canvas. Where did the interest in blending robotics with artwork originate?
Chung: My interest in working with robotics came from my practice of drawing. Working with robotics and drawings brings me back to the body — the mark-made-by-hand, and what things like muscle memory and physical instinct can inform about the creative process.
Drawing and robotics seemed like a natural progression — movement articulated through a mechanical body; in my case, a robotic arm, a collaborator I named D.O.U.G._x after Drawing operations Unit, Generation 1. The robotic arm was an ideal form through which I could explore what drawing could be — drawing as a process of thinking through movement, drawing as a collected data set, and drawing as articulated by an A.I. system.
By drawing with a robotic unit linked to my movements, to my drawing data, and other artists' data sets, it created a creative catalyst and a framework for speculation about technology and its effects.
Pranam: What part of the artistic process takes the longest: brainstorming, building the technology (e.g., neural nets), or creating the final output?
Chung: Drawing Operations has been an ongoing series — since 2014 to today. Like the practice of drawing, I view it as a life-long project, an evolving process experiment. In my talk, I speculate at the nature of creative practice today, and what that means, and that perhaps what defines art-making today is not in the making itself, but how practitioners can synthesize tradition and technology, and the techniques of culture, to explore new ways of making. These ideas manifest as narrative, kinetic sculpture, performance, writing, models of interaction, and visual artifacts.
Pranam: As the fidelity of digital media continues to improve, technologies like V.R. (virtual reality) could eventually enable experiences that command a significant portion of our time and attention. Will this draw focus away from non-digital art?
Chung: I've long been fascinated by V.R. as a medium that facilitates the implanting of memory. That's the 'fidelity' of contemporary V.R. that I'm drawn to, and that which also leaves me unnerved. The simulation of the screen is so closely tied to the participant's spatial orientation, which dissolves the mediation of the screen in traditional digital art.
Non-digital, and our experience of, say, a painting in-person, has become rarefied. I would say that most paintings today are seen as photographs on screen. When was the last time you saw a painting in person? The majority of our consumption is screen-based now, and our attention to non-digital art is still experienced through a photograph of the drawing.
These shifts inform my interest in process — the process of drawing and mark-making through time, is easily distinguishable from the instantaneous capture of photography. Its these processes I feel are being challenged by digital media. The tangibility of raw material, and the "process of making" with materials like graphite that have their own characteristics. I draw attention to these processes because they carry their own historicity, their personal narratives, and, for me, that is a vital part of the creation of the work.
Pranam: The arts and sciences are generally seen as being separate, distinct entities, but you've managed to bridge the gap with your work. Do you see the two as being closely related?
Chung: I've understood the arts and sciences as the pursuits of similar goals utilizing complementary but distinct approaches. A foundational premise of both is developing a framework for understanding, of internal models of experience and external models of the 'world.' I see both as philosophical pursuits — part of the ecosystem that includes design and technology.
Pranam: You recently launched Scilicet, a studio exploring human and non-human collaboration. Walk us through the goals for this project.
Chung: Through the creative work, I've come to see machines not merely as tools but collaborators. And by continuing the work, machines as non-human collaborators. I see great potential there — and I think its a contemporary question. As per every generation, what it means to be 'social' shifts and changes.
It's a big topic, for sure, and one that I think is at the forefront of a lot of people's minds but one that's complicated to work through on one's own. The studio recognizes that the subject of our relationship to the non-human is evolving, and therefore demands a response from the wider community.
Scilicet is a space where anybody can feel welcome to explore these ideas with us — with artists, scientists, designers, and writers who recognize that widening the conversation is essential to exploring these ideas at the depth and breadth that it deserves.
In the immediate term, we're excited about meeting like-minded collaborators to build a space that nurtures new ideas around collaboration and making-with. We provide an evolving network of practitioners to produce projects and research that push the boundaries of what is possible in human and non-human collaborations.
Through this, I'm exploring how the traditional art studio environment can be a locus for community, discussion, and critical thought; how can human and non-human collaboration expand our thinking about cooperation itself, and what it means to create collectively?
Pranam: What ethical boundaries exist in the world of human-machine art? Are there any lines that should not be crossed?
Chung: I see human-machine art as a testing ground for examining human-machine interaction at large, which has broader implications for the relation of technology and society. Through the projects, I work through questions of authorship, of agency and control, of what it means to collaborate with the things you build, and what relationships are built upon the process of co-creation.
I think about hidden narratives behind prevalent work in this space — around the hype of A.I. art. People want something greater than themselves to believe in, and in some ways, art through history has had a relationship with creating sensory experiences of that kind of power. Is that dangerous? Is it the tradition of art? Does it have to be? I find these questions interesting.
That being said, the 'artificial' of artificial intelligence tend to overlook the human element. In my drawings, the models I train require large datasets to be effective. In my case, those data sets are decades of my drawings. Is it uncomfortable to look at one's artwork only as data? Does the digitization of the work capture the essence of the work, or is it just a representation. What is lost in adapting to be machine-readable, of thinking about individual output as data? The philosophical nature of these questions continue to influence and refine my approach.
Deeply grateful to @Lumen_prize, for awarding the Art and Technology Prize to Drawing Operations, a project I started in 2015 exploring human and machine collaboration. Thank you Carla Rapoport, and Jack Addis for your support and welcoming me into the Lumens family. . . In these deeply uncertain times, I find myself thinking of #DonnaHaraway’s writing in Staying With The Trouble 🖤: “It matters what worlds world worlds. We become together or not at all." Collaboration, for me, is a way to steer away from "a technophobic spiral, by conceiving of humans & machines as interacting parts of complex adaptive systems." . . .
LATE LAST YEAR, artificial intelligence made a loud splash in the art world. A trio of French students, calling themselves Obvious, put a smeared, unfinished portrait up for auction at Christie’s. Titled Portrait of Edmond de Belamy, the murky image pictured a suited gentleman with a plain white collar. Rendered in three-quarter profile against an indistinct background, the image mimicked conventions from Renaissance and Baroque portraiture. At the corner of the canvas, a mathematical equation ostentatiously replaced the traditional artist signature. Global media trumpeted the achievement as a stunning first. Obvious oiled its promotional engine by misleadingly claiming it to be the first ever work of art created by AI to go under the hammer. Neither claim turned out to be true: significant human labor went into its making, and a set of AI-generated images had gone to auction at San Francisco’s Gray Area in 2016. Offered at $10,000, the image went to an anonymous buyer for a jaw-dropping $432,000.
This portrait embodies significant problems at the heart of AI’s recent cultural ubiquity. Machine learning is being used across art, science, and industry — from music production to space exploration — but its excursions into the creative economy have ignited the most controversy. Commonly, such works lead to the question, “Can a machine be creative?” But this question misses the mark.
AI is the latest, most intangible incarnation of the automated arts. When it comes to creative automatons, history shows we’ve been rehearsing the same hand-wringing about authorship and authenticity for over a century. The history of photography, for example, famously raised alarms about humans surrendering the arts to machines. While automatons are now largely digital, not strictly mechanical, they, too, seem to imperil the ostensibly humanist essence of art. But Portrait of Edmond de Belamy did not spring fully formed from the neural network’s “mind.” Rather, it emerged out of a complex system where human actors continue to play a crucial role, although the story of their absence — and abdication of the arts — persists.
Obvious worked with an artificially intelligent system known as a generative adversarial network, or GAN. An algorithm composed in two parts, a GAN reproduces an agonistic relationship between artist and critic. The Generator creates new images based on a massive data set, and the Discriminator evaluates that image against a human-made image. Obvious trained their GAN on a data set of 15,000 portraits from the 14th to the 20th century. Ensconced in a gilded frame, and gorged on the Western canon, the image convincingly reproduced the aesthetic conventions of portraiture. By signing the image with a segment of the algorithm’s code, Obvious had, in a clever sleight of hand, cast an algorithm as a stand-in for the absent hand of the artist.
But the artist in question was not, actually, a hypothetical person. Obvious had appropriated their code, as well as the training set, from Robbie Barrat. Then a 19-year-old artist and programmer, Barratt had shared his Old Masters GAN on the open-source sharing website, Github, in 2014. An outcry from the small community of AI artists punctuated the auction. They not only emphasized Barrat’s erased contribution but also expressed disbelief that the amateurish image was representing their years of creative experimentation with GANs to the world at large. In their rush to crown the algorithm as the work’s author, Obvious obscured the central roles played by humans in the conception, coding, and curation that yielded the image. If this was an aesthetic Turing test, then we have willfully failed it. But why?
The equation at the traditional site of the artist’s signature offers some clues. This staging culminates a centuries-old conversation about the agency of creative automatons. Signatures boast a special connection to the human hand. Historically, they have imprinted the heft of the human body upon an object, whether artwork or legal contract. They index the identity of the signer: they affirm that someone was really there. By displacing a human signature with an algorithm, Obvious manifested an obscured predecessor in the history of automated art — not the camera, but the player piano. Yes, that classic piece of ragtime furniture.
Popular in the early 20th century, player pianos are a mechanical incarnation of the absent human hands in AI-generated art. Anyone who has seen a player piano in action can attest to its uncanny nature. Once in motion, one can almost imagine an invisible player sitting at the instrument. Piano keys seem to play themselves in cheerful ragtime. Now largely a relic of a different time, the player piano stirred many of the same kinds of questions and debates that AI art does now.
Inventor Edwin Votey built a prototype of his automated player piano system in 1895. It took the form of a large wooden cabinet, and was powered by suction generated by two foot pedals. It was designed to stand in front of an existing piano, where mobile fingers at its rear would orchestrate its keys. Astride the piano, this cabinet of curiosities contained a small paper roll patterned with tiny perforations representing notes to be played. As a roll moved over the tracker bar, a reading device with a row of evenly spaced holes, a valve would open and trigger a pneumatic motor. This would then fire a felt-covered finger on the external player, causing it to hit the corresponding piano key. Though these functions soon entered the instrument itself, with the introduction of the Apollo line of pianos by the inventor Melville Clark in 1901, these operational principles remained the standard for nearly all roll-operated player piano systems.
In the next decade, the machine developed into a ghostly rendition of human performance. In 1904, German organ builder Edwin Welte and his school friend Karl Bockisch launched a new kind of player piano, the Welte-Mignon. Otherwise known as a reproducing piano, these were able to record and reproduce individual performances by replicating the dynamics, rubato, and pedaling of living players. In its heyday, music roll manufacturers recorded the performances of many famous 20th-century pianists, George Gershwin, Liberace, Jelly Roll Morton, Myra Hess, and Thomas “Fats” Waller among them. Specters of performances past, these rolls conjure the apparitions of nearly every major early 20th-century pianist.
For all its commercial success, the automated instrument drew its share of criticism. In 1906, John Philip Sousa published “The Menace of Mechanical Music,” a screed against the sweeping popularity of player pianos and gramophones. Sounding the alarm about these poor copies, Sousa fretted that these “talking and playing machines” “reduce the expression of music to a mathematical system of megaphones, wheels, cogs, disks, cylinders, and all manner of revolving things, which are as like real art as the marble statue of Eve is like her beautiful, living, breathing daughters.” For Sousa, these creative automatons substituted cogs and wheels for the ineffable human soul.
Creaky in their physicality, the player piano seems a far cry from the digital machines so ubiquitous today. However, the rolls that powered their spectral movements form a bridge with the artificially intelligent systems that generate such images as Portrait of Edmond de Belamy. After all, with the sleek miniaturization of contemporary computing, it is easy to forget that the early computers of the 1940s and ’50s were massive calculators operated by punch cards with holes in them. In these pockmarked landscapes, the automated arts, from player pianos to algorithm-generated portraiture, took root.
As William Gaddis decried in Agapē Agape, his 2002 swan song on the ruination of art by technology, “There was the beginning of key-sort and punched cards and IBM and NCR and the whole driven world we’ve inherited from some rinky-dink piano roll.” The narrator of Gaddis’s pseudo-autobiographical novel lies dying in his hospital bed. He pores over his notes in a desperate rush to finish his magnum opus, a history of the player piano. Paralleling his deteriorating body with the decay of culture, he rages against a commercialized world where art has become mere entertainment, and imitation has displaced authenticity.
Gaddis is not alone in placing the player piano in the history of computational creativity. The recent TV show Westworld also winks at this past. The show envisions a world where guests pay to play in a live-action simulation of the Wild West, replete with cowboys, gun battles, and damsels in distress. Euphemistically named “hosts,” androids in period boots and hats, are at the mercy of the human “guests” who come to ravish, maim, or kill them. In the saloon where guests down whiskey and manhandle artificial women, a player piano sits. Phantom hands alight on the keys; tinkly covers of contemporary songs serve as a soundtrack for gun battles and seduction. As robotic copies of humans cavort among originals, these mechanized cover songs evoke the longer lineage of artificial others.
Despite the century that has passed since their debut, player pianos, like androids, remain eerie, ghostly objects on the brink of life. In a pantheon of creative automatons, the player piano endures for the existential questions it provoked. How have these automated instruments transformed the landscape of creativity? And at what cost?
New technologies demand new visions of how we might use them. AI technologies have been accused of reproducing the invisible human structures that inhere in the data from which they learn, including the best and worst of us. Take Portrait of Edmond de Belamy. Not only did it regurgitate musty art historical conventions, but its success affirmed the gatekeeping function of the auction house, as well as the conflation of monetary worth with artistic value. Where Obvious’s image replicates some of the least compelling elements of the art world, other AI artists imagine other ways we might relate to these creative machines.
Against a narrative of imperiled human creativity, some artists working with AI instead frame these new technologies within an ecology of human and machine collaboration. In Drawing Operations, the artist Sougwen Chung stages a series of collaborative drawing performances with a robotic arm. In three chapters, “Mimicry,” “Memory,” and “Future Speculations,” Chung showcases an evolving robotic behavior based on her research with art and AI. Ongoing since 2015, the work highlights the complexities of assigning authorship to AI.
In Generation 1 of the project, Chung explored robotic mimicry in real time. By capturing her drawing gestures with an overhead camera and analyzing them with computer vision software, the robotic arm replicated her movements. The robot precisely duplicated the pace, shape, and style of the original performer. In many ways, we might understand this arm as a 21st-century version of Votey’s player piano, the mechanical fingers of his wooden cabinet playing the keys in the absence of a human performer. But Chung turns this dynamic on its head. After all, her body was actually present, the robotic arm a proxy for her in the same moment. Their gestures synchronized as they made marks on paper, Chung and her robotic double formed a strange duet.
In Generation 2 of Drawing Operations, the robotic arm was linked to a neural network trained on a database of Chung’s extracted gestures from previous drawings. As a result, the robotic arm was able to generate new movements and drawings in Chung’s style, without duplicating them exactly as it had prior. In improvised performances, Chung draws in tandem with the arm, creating abstract line drawings that blur her marks with those of her robotic collaborator. Speculating on artificial creativity, Drawing Operations suggests a more complicated entanglement of human and machine actors than prevailing media narratives suggest. Through these performances, Chung systematically imagines a creative future where automatons might extend human intelligence.
As the perforated rolls of the player piano prefigured the punch cards of early computing, so, too, have they shaped how we talk about creative machines. Like the ghostly hands that played upon pianola keys, AI art stokes deep cultural anxieties about the risks automation poses to human activity. Ultimately, we fear that they will replace us, whether at the factory or at the canvas.
While the story of absent human hands lingers from the heyday of the player piano, the stakes have changed. For all the controversy it stirred, the player piano was ultimately only a reproducing musical robot, unable to deviate from its punched script. It was also an industrial invention, symptomatic of rapidly changing modes of production. In a creative economy, where factory jobs are all but gone, creativity is just another commodity. The risk is not that humans will stop being creative but that they will cede the signs — and compensation — of their labor to algorithmic signatures.
By demonstrating AI artworks’ commercial viability, Portrait of Edmond de Belamy sparked a gold rush. Shortly after the notorious auction, computer scientist Ahmed Elgammal debuted the creative output of AICAN, his GAN variant, in a Chelsea gallery. Unlike Edmond de Belamy, these pieces, collected under the title Faceless Portraits Transcending Time, were pitched as a joint effort between man and machine. While many images from the show ostensibly sold for five figures, AICAN’s financial ambitions are far higher. Based on its success identifying the chronology of the images in its data set, Elgammal and his investors believe it could be used to anticipate — and produce — future art trends. Unchecked, these virtual automatons could theoretically cut human artists out of the art market entirely. The fears of Sousa and Gaddis could, in fact, be realized.
But rather than allow this threat to send us into a technophobic spiral, we could instead, like Sougwen Chung, conceive of humans and machines as interacting parts of complex adaptive systems. Whether creative duet, industrial partnership, global economy, or internet, these complex systems have marked all of human history. So imagined — and so designed — intelligent machines can serve to amplify and augment human activity. It is neither us nor them, but both.
My (re)search and art practice featured in Issues in Science in Technology: Future of Work Special Edition.
In Omnia per Omnia, I paint with a multi-robotic system connected to the flow of a city. It is a meditation on the porous relationship between self and world; individual agency within a collective body (intelligence).
Sougwen Chung, Drawing Operations (2017). Courtesy the artist.
WHO: Chung is a Canadian-born, Chinese-raised, New York-based interdisciplinary artist and former research fellow at MIT’s Media Lab. She’s currently E.A.T.’s artist-in-residence in partnership with the New Museum and Bell Labs. Her work, which spans installation, sculpture, drawing, and performance, explores mark-making by both hand and machine in order to better understand the interactions between humans and computers. She has exhibited at institutions including The Drawing Center in New York and the National Art Center in Tokyo.
WHAT: For her current project, Drawing Operations, Chung uses Google’s TensorFlow, an open-source software library used for machine learning, to classify archives of her own drawings. The software then transfers what it has learned about Chung’s style and approach to a robotic arm that draws alongside her. She’s also working on a few new projects using pix2pix (a neural network trained to produce variations on an image, like the nighttime version of a daytime photo) and sketch-rnn (which tries to continue or complete a digital sketch based on where the human leaves off) to expand on this idea of human and machine collaboration.
WHY: “As an artist working with these tools, the promise of AI offers a new way of seeing,” Chung explains. “Seeing as self reflection, seeing through the ground truth of ones own artworks as data. There is a lot of talk about biases evident in AI systems and that is absolutely true within AI systems trained on art. You could describe visual language as a kind of visual bias, a foregrounding of the subjective view of the artist. By translating that into machine behavior, I am attempting to create a shared intersubjectivity between human and machine.”
I always like to start with talking about an artist’s background. Can you talk a bit about your early life and how you came to visual art?
I grew up in an immigrant family in Canada, my parents are originally from Hong Kong. Hong Kong is a place that I fantasize about -- feel this deeply unearned nostalgia and longing for; I wonder if that’s typical for children born into the east asian diaspora.
My father was a classically trained opera singer and my mother a computer programmer, so those influences were always in the background. I always considered my upbringing to be quite normal, growing up with rigorous musical training and access to technology before everyone else, but I recognize it now as a very distinct privilege.
I grew up playing several instruments. I didn’t know it at the time, but learning to communicate through music, through the apparatus of an instrument, probably shaped my outlook on everything. Playing the violin was what resonated me the most.
I look back and think of my time as a violinist as one of my first experiences of artistic escapism -- learning a feedback loop of internalization and externalization through gesture that was at once improvisational and abstract. At the same time, it wasn’t really subjective. You either had the skill and intent to communicate the emotion or you were asleep at the wheel. Or in my case, the bridge.
In tandem, we were among the first to have computers and access to the internet. As a child I was very active in the building of online culture and digital identity, which as a result still fascinates me. Nostalgia is overrated, but I indulge in it a bit when I think about those early internet days. I like what Andre Nusselder says about digital space as a projection of one's desire and fantasy -- especially back then before online spaces were so regulated and before communication became so reliant on platforms. The fantasy before the deep fake. When talking to someone from another continent still felt like magic -- it probably still is, we just forget that it is.
My early life was mostly about learning how to communicating through instruments, musical and technological. Growing with that practice, sharing through performance. In that sense, nothing much has changed.
What’s different is that now these instruments, these tools, are part of much more complex systems. So there’s a feedback loop, a cycle of learning and adaptation through the promise of AI and an evolution of the digital object. In that sense, everything has changed.
How long have you been interested in exploring the relationship between robots and humans? What led you to explore this relationship through visual art?
I’ve been exploring this space for almost 5 years now... Maybe more? It seems like a long time and also a split second in the scheme of things.
I’ve always considered the relationship between robots and humans as a proxy for exploring the broader scope of technology’s influence on our lives. One specific influence is that of AI systems in the world today. My robots bring AI generated behaviours into physical space -- out of the digital simulation. You could say that it’s about bodies, as well as bytes.
I work alongside the AI system to make drawings, creating a feedback loop on a single canvas in real time. I was surprised that by translating these behaviours physically and working alongside them it changed what drawing meant for me. Working with prototypes and behavioral experiments; it’s a reminder of the vitality and fallibility of the process at the same time -- I guess that’s what I’m drawn to. The uncertainty, the unlearning, the unknowing of it all.
When I think of robot production, I think of functionality, and not so much artistic expression and collaboration between robots and humans. What do you believe about the future of human and robot communication? How do technological advancement and artistry intersect?
That’s such a big question. It could go so many different ways, really. I will say that working with robots has contributed to my own thinking and fluency with deep learning systems, rapid prototyping, physical computing. It’s intimidating at first, but rife with aesthetic and conceptual inspiration.
Its further affirmed that technology in general isn’t inherently good or bad, but it isn’t exactly neutral either. However, the stories we tell about technology, especially in pop culture and tech media tends to be pretty reductive and sensationalized. It’s not all Terminator, Tesla, or Twitter.
We probably think of functionality when we think about robots as they were a prominent icon of the industrial revolution -- we associate them with assembly lines and factories. It lends itself to a didactic perception of the role between human and machine, with humans in control.
What if it wasn’t about control? What if it could that be another way? I wonder what would that look like. I think control is interesting only when its incomplete -- and most of the time it is.
On the same vein, the future of human and robotic communication is pretty porous. It’s not so linear or one-way. It’s not really clear who’s at the wheel, sometimes literally. It raises some interesting questions about agency.
At the risk of sounding like a foghorning media theorist, I’ve been thinking of the parallels between technological and artistic processes, in that they both foreground human bias. One process translates the bias of the dataset and the human engineer into the AI system and the other the visual bias of the artist and her visual style onto a canvas.
By intersecting artistic and technological processes, I’ve been working towards discovering particularities about both. They’re just ways of seeing and shaping the world at the end of the day, after all.
In Omnia per Omnia, you reframe the idea of a landscape as a documentation of movement throughout a space––particularly the ebb and flow of bodies throughout a city. This data is gathered through the interplay of technology or surveillance with the organic and improvisational movement of life. How are these robots taught to move––i.e. Is their movement improvisational? What does it mean to reverse the documentation––by having the human hand follow the robot, as opposed to the other way around?
The movements of the robots are linked to urban flow as captured through public cameras. They move according to motion vectors extracted from pre-existing surveillance feeds in New York City. The movements are improvisational in the way that how we move through cities is improvisational… sometimes chaos, sometimes flow. The mechanical units, which I call D.O.U.G._L.A.S. (Drawing Operations Unit Generation 4, Live Autonomous System) start on predictable paths which, by translating the data through physical space, eventually veer off course, creating space for emergent, random behaviours as the composition unfolds on the canvas. When performing with these units, they resemble to me, a swathe, a broad stroke of the brush on by a multi-agent robotic body.
It’s interesting that you describe it as a reversal, I’m not sure if I see it that way. I think culturally we’re moving beyond the linearity of human following machine or vice versa, to something more cyclical.
As the initial movements of the robots in Omnia follow human movement, and I in turn am creating alongside these translated positions, the marks made between human and machine function as a feedback loop. It’s been described as it’s a rhythmic duet, evoking a sense of push and pull; of coexistence. Alternatively it could be seen as meditative, and sometimes disturbing and chaotic. For me, the performance demands a vital focus on the movements of my robotic collaborators. It requires a kind of ego dissociation. Like being part of a collective.
You ask “are we on the onset of a new, collaborative imagination––of radical new intersubjectivities?” What does this mean? What do you foresee this world, in which humans and technology collaborate, looking like?
The promise of some of these new technologies, like computer vision and deep learning, offers an alternative way of seeing. In my work I explore the particularities of that vision by turning it on my drawings, my environment, myself, to see from another perspective.
Seeing can be an act of self reflection, but self-reflection is a closed loop. Learning to see as a machine sees is a vantage point that requires mediation between symbolism and data. In deep there is the concept of ground truth, that which is objective and not derived from inference.
There is a lot of conversation about biases evident in AI systems and that is absolutely true within AI systems trained on art. In that vein, you could describe visual language as a kind of visual bias, a foregrounding of the subjective view of the artist, like I said before. Bias is another form of subjective view. For my part, by translating visual style as bias as subjectivity into machine behavior, and collaborating with machines as an aspiration, I am attempting ask certain questions. What might the ground truth of an artistic practice be? Is that something we want? What might a shared intersubjectivity between human and machine look like?
For my project, Omnia per Omnia, I elaborated on this “intersubjectivity” and expanded it to the idea of a collective. In the work, I painted alongside a system of painting robots whose movements were linked to the flow of New York City. The movement was extracted using an optical flow algorithm trained on surveillance cameras around New York City. The performance is a trio of sorts between myself as a performer, the 20 multi-robotic units and the collective movement of the city, improvising a hybrid choreography. It’s a performance of human and machine and city, an emergent creative process.
With Omnia, the act of improvisational painting takes place through a heightened sense of awareness of the machines. It’s flow is site-specific. The movements are linked to the movements of a crowd, who aren’t aware of their position as catalysts of the robotic swarm.
But what if the crowd were aware of being all watched over by these machines? That’s what I mean by being at the onset of this collective imagination and intersubjectivity. It’s inspired the idea of a collaborative space between multiple bodies that is physical, digital, telepresent, and most importantly, shared. It’s a representation that isn’t about control, but something else.
The project really stemmed from a curiosity -- a willingness to de-privilege the western conception of the individual towards an entangled, intersubjective, radical ecosystem. I’ve been inspired by this reconfiguration of the “I”, through theorists like Yuk Hui’s who explore a new cosmotechnics, and the philosophies of media centred around eastern concepts of relation.
The act of painting in Omnia per Omnia appears as a meditative practice, in which the lines between the maker and the final product are blurred––that is to say, the act of making seems to be more important than the actual outcome. It reminds me of Allan Kaprow’s “Happenings” in that way. Would you say that the making is more about the act than the product?
Yes, I think I would. Perhaps it’s my upbringing in music. The performance vs the recording of the performance, for instance. My approach to making is grounded in my background as a musical performer, as an instrumentalist. Making through collaboration as folie a deux; a shared hallucination between collaborators. Sometimes harmonious, and sometimes discordant, but always intertwined, and relational. Counterpoint.
You speak about the Japanese Gutai art movement, in which “matter never compromises itself with the spirit; (and) the spirit never dominates matter.” Can you talk a bit about this movement’s influence on your work, and how your work builds upon these theories of making?
I love that particular excerpt of the Gutai manifesto. “matter never compromises itself with the spirit; (and) the spirit never dominates matter.” Its deceptively complex and.. Beautiful and provocative.
In my view, Gutai’s theories of making reframed the human’s relationship with the matter of the day. It sought to recentre the human body (as a channel to spirit) as their artists engaged with painting and sculpture (matter) towards freedom of expression. It stemmed from Jiro Yoshihara’s rejection of contemporary propagandistic trends of art, which were supportive of the political contexts that supported the Japanese involvement in WW2.
For me, their group shows represented a collective action in a time of uncertainty. Gutai artists engaged in radical artistic gestures, through a range of media, performances, and sculptures. Their approach to making was focused on a liberation from the past -- an uncoupling from the cognitive patterns derived from a post-war social order. They worked towards creating new meaning and pathways through these artistic gestures, towards “engaging with the uncompromising spirit of matter itself”.
I’m quite inspired by this approach, though the Matter I’m working with today, you could say, differs from the Matter used by Gutai artists in the 60s.
Technology as matter is interactive; it can be linked, sensate, responsive, interactive, intelligent, interconnected in a way which has never existed in human history. The technology of media art like cameras, sensors, computers, for instance. Technology can serve a propagandistic function all the same and work against our best interests all the same, and our relationship to it must be reframed.
While Gutai emerged from the political and psychic disillusionment of war, it’s important to note that it wasn’t a movement that ended on a sense of nihilism. In the face of uncertainty, the movement demonstrated artistic strategies for uncoupling and unlearning, in service of cultural extension, collective action, and hope in the dark. My work builds on, and is inspired by, these Gutai traditions.
We made a film for #OmniaPerOmnia and it was a wild ride. (This is the teaser ~) .
Thank you to @mynameiscutter for sharing the vision, lending your talents to the project, and assembling the star team for our film. @tshung@cleggm @arianne_alizio .
Original score by @aquarianyes and Mickey Partlow @v3rysaid .
Omnia per Omnia pays homage to the flow of cities. This first chapter begins in NYC, my home of a decade and birthplace of the Experiments in Art and Technology initiative.
Sougwen Chung, Omnia Per Omnia Performance. Photo by Irina Abraham.
"In Omnia Per Omnia Sougwen Chung explores collaborating with robots as opposed to using them as a tool. As I enter the room, the artist and the engineer Andy Cavatorta are fussing around little machines with exposed hardware, which seem to roam free around a white platform. Sougwen and Andy look like two caretakers with the little robots being their wards.
When Sougwen first contacted Andy about the project, he jokingly asked if she wanted him to build her an army of painting robots. To his surprise it was exactly what Sougwen who had designed, coded and engineered the prototypes, intended. The robots are using surveillance footage and have the collective movement of the city power the movement of their swarm. Sougwen is painting the portrait of the city together with the robots. When asked what the difference is between collaborating with humans and robots, Andy and Sougwen laugh and say that humans cooperate. Their hope is that the robotic swarm will keep learning and evolving.
On the day of the performance, Sougwen is surrounded with audience and journalists. Once the robots start moving and the music fades in, everyone turns quiet. The slow and seemingly purposeful movement of the robots, the traces of the blue paint they leave behind, the motion of Sougwen's brush and the expression of total concentration on her face create an atmosphere of a ritual, a spiritual action. The audience is affected by the magic happening in front of them. Watching the artist paint with the robotic swarm creates a true emotion, the way only art can. "