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Published Wednesday 8 May 2019 - 10:58 AM Harsh Biyani
She always sees bigger, always more beautiful! Cinzia Sgambati-Colman, president and founder of the “Woman of the Year, Monte Carlo Award”, organized the 8th edition of her annual event on Saturday night at the Oceanographic Museum.
And for this 2019 edition, the theme chosen was “Art & Science”, inspired on the occasion of the 500th anniversary of the death of Leonardo da Vinci. During the evening, sponsored by the Walgreens Boots Alliance, the public discovered the three women who received the awards. It is Sougwen Chung (Chinese-Canadian) Monte-Carlo Award “Woman of the Year” 2019; Elena Rossoni-Notter (Monegasque) Prix Monte-Carlo “Woman of the Year” – Monaco; Special award for her entire career in Orlan (French).
Prince Albert II met with the laureates who told him about their career, alongside Cinzia Sgambati-Colman and Ornella Barra, co-chief operating officer of Walgreens Boots Alliance.
Sougwen Chung won the Monte-Carlo Woman of the Year Award in 2019 for her artistic work. Multimedia artist of Chinese origin, who grew up in Canada and lives in New York. She has been working with robots since 2015, exploring the links between “handmade” and design machines, to understand the relationship between humans and computers. Chung is an artist-in-residence at Google and in the cultural incubator at New Museum, New Inc. and a former academic researcher at MIT Media Lab. In 2017, she was one of three artists selected to participate in a new partnership between Nokia Bell Labs and New Inc. to support artists working with emerging technologies.
Elena Rossoni-Notter, Director of the Museum of Prehistoric Archeology of Monaco, received the Monte-Carlo Woman of the Year Award – Monaco, for her commitment, tenacity, research, discovery and dissemination of archaeological research on the territory of Monaco. Elena Rossini-Notter started working at the museum in 2014 as an archaeologist. She made several excavations in Monaco. She was appointed Director of the Museum in April 2018.
Orlan received the Monte-Carlo Award “Woman of the Year” – special award for her career. Avant-garde, a pioneer in the field of art, science and technology, the artist uses her body as a creative material and source of inspiration. Operated, scanned, remodelled in 3D, virtualized, this body questions, provokes. With a French robotics company, Orlan has designed a robot in her image: Orlanoïde.
Interview with Ken Tan featured on The Creative Independent
Artist Sougwen Chung discusses the joys and complications of working with robotics, the evolving definition of what it means to be an interdisciplinary artist, and creating space for other people to explore.
KT: How did you get into art?
KT: When did the leap to visual art occur?
The first encounter with visual art that felt meaningful to me was when I started making work on the computer. My mother was a computer programmer, so I’d been around technology from childhood, in addition to music. I fell quite deeply into making websites, coding my first website when I was nine, I think. I still recall my first image tag fondly, and that translation from code in HTML to a visual graphic on screen, to a URL that could be shared and experienced on the other side of the world. It was so exciting at the time—looking back, it really changed everything.
KT: You’ll never forget your first image tag.
Yeah, you really don’t, right? You didn’t know that you could have that power to effect technology, especially back then. In the early days of the internet, you had to do everything manually in order to show your work to the world, like hand-coding HTML, setting up your own FTP servers, and uploading to Angelfire. It felt dynamic because not only could you manipulate something on screen, but you could also show it to all of your friends who were geeky enough to be online or have a computer. So, I guess you could say I started exploring visual art through on-screen graphics. Honestly, for a long time the two were synonymous. Visual art was digital art to me.
Sougwen Chung, High Tide Etude Op 2, 2012
KT: When did it become a legitimized art form for you?
As far as my work goes, a lot of what I do today is inspired by creating new forms of collaboration; thinking about machines or environments as creative catalysts. It stems from an interest in thinking about authorship and technology. Because I started so young with computers, after a while I wondered, where was my creative agency in software? As I became proficient with the tools as an expert, I felt there was something missing.
I found that I missed physical gesture when working with computers—specifically the gestural instincts I’ve developed through violin and drawing. Sometimes working with software and code can feel like one is relegated to the screen. So that feeling led me to explore working with robots through the medium of performance, to re-engage with physical spaces. Robots are typically regarded as industrial tools, but I’ve always thought of them as a kind of kinetic sculpture. Being able to invent my own human/machine collaboration processes has been really empowering.
KT: How do you define value for your work? Is it an experience?
There’s an Agnes Martin story that I’m going to paraphrase poorly: a little girl went into her studio. Martin held up a rose and asked if it was beautiful. The girl said it was. Then Martin put it behind her back and asked the child again, if the rose was still beautiful. The child still said yes—positing that the art that is being experienced is actually the aesthetic sensation that happens within the viewer.
I’ve always really liked that, that the value of the work occurs within the experiencer of the work. It’s probably what a lot of artists who started in the digital realm feel, too, and what drew me towards the ephemerality of performance, eventually. Rather than define the value as an authority, why not accept the situatedness of valuation? It’s there and then it’s not. That’s what makes it interesting.
KT: How important do you think it is to be interdisciplinary today?
On some level, we are all interdisciplinary today, don’t you think? Digital technology is so embedded in our everyday culture. Even if you are a painter, you still check your email and use your phone, or have some sort of online presence, and are influenced by other mediums and disciplines. When I think about being interdisciplinary under the umbrella of art and technology, I can see the value of being able to experience your practice in ways that you experience your regular life.
In my studio, you can still find paints, canvases… material mess. But there’s also robotics, intangible codes, and deep learning. I think that’s why I like to show my process as part of the work—it’s important to communicate that one can engage in technologies without feeling necessarily like they are losing some inherent spirit of their practice.
I’ve become more comfortable not just occupying one space, but traversing different environments. Drawing, however, is still one of the foundations of my practice and still continues to feel like safe harbor no matter how my work evolves.
KT: How does it feel working with non-sentient collaborators?
I often perform with either multiple robotic painting linked units (20, in one instance), or one to several robotic arms. Part of what interests me in my performances is the exploration of the rawness of that interaction between myself and the machines. It’s a process of negotiation, wayfinding, and tension. When you watch the edited footage of these performances, they can look rather elegant or serene. That’s really an incomplete picture.
It’s not always comfortable, working with a non-sentient unit, even if I’ve designed the system of interactions myself. It can sometimes feel like staring into the void. It’s not exactly as straightforward as verbal communication might be with a human collaborator, and you become very aware that empathetic cues in body language do not exist in the same way.
KT: How does a programmed robotic unit respond to you? How much expression is you versus the machine?
The units respond to a variety of inputs that have developed over time. It began as a gesture-based approach, using a recurrent neural network. My line is recorded in real time, either through an overhead camera or a sensor on the tip of the brush that turns my positional data into something that can be read by the system.
The system as articulated by the robotic units then outputs a set of positions based on an interpretation of my own drawing archives from the past 20 years. It’s a multi-step process that constructs a feedback loop of my own drawing style.
During this last year, I’ve been integrating my own biometrics: data of my heart rate or brain waves. I’m trying to think about ways that humans connect to mechanical and artificial systems, and vice versa, and ways that can function as a creative catalyst.
KT: How can you be creative within a programmed set of rules?
KT: So much can go wrong in reality. For example, even something as simple as voltage could be a problem if you are traveling to different countries. And that opens up creative opportunities?
“Opportunities” is definitely a disposition. I have so many stories from my experiences. One time I debuted a work in which the wheels of several of the robotic units slipped off their paths due to the viscosity of the paint on the canvas. The digital trial simulation did not register the physics or the materiality of the medium.
KT: I love that. It feels human, too, because you’re dealing with practical concerns.
When you see these robotic units slipping in that way, it creates a different kind of artistic activation. The audience sympathizes with the robotic units in a humanizing moment of the fallibility of the machine, but also of the human who tried to work with it. Live and learn.
KT: Do you then work with humans?
Working with the robotic units has made me more interested in collaborating with humans. I’m constantly working with other collaborators now in defining what algorithmic drawing can be today. It’s become broader in scope in a way I didn’t anticipate. It’s far more than just me drawing in a performance. It’s enabled me to take on different roles in the creative process. Behind the scenes, there’s an interconnectedness of various collaborators in an interdisciplinary ecosystem, each bringing a different perspective and skillset to the table.
KT: What’s a day in the studio like for you?
I was actually on the road for years and didn’t have a studio. I found the city then to be a little bit anxiety-inducing. In true samurai style, I worked through my mobile studio setup, traveling with a bag and a robot. That was actually a formative time for me.
That’s one mode of the studio; the other is sanctuary. Sometimes it’s just me working in isolation, essentially just drawing for days on end. I really enjoy drawing and pushing what’s achievable with the machines through that feedback loop, the open-endedness of it.
Sometimes I invite visiting artists in as residents to focus on their practice when I’m traveling on projects. We live in New York where it’s hard to find a sense of sanctuary and calm, so this latter mode is essential, and it’s been a privilege to invite practitioners I respect into a space of my own making.
KT: Do you ever feel like you need gallery representation?
I feel if you’re doing something new that’s maybe a bit uncharted, galleries might not know how to work with you yet. I’ve found that being solely reliant on a gallery becomes too great of a risk—one that doesn’t make sense if you’re doing something that doesn’t sit comfortably anywhere.
And also for someone who had an itinerant practice for years, my practice has been shaped by a poly-geographic sensibility. I aspire to be as comfortable making this work in New York as I am in Berlin or Shanghai. I’m interested in that kind of autonomy—I’ve found it to be an asset when working in the space I’m in, and trying to define a territory for myself, both literally and metaphorically. As there isn’t yet a genre or industry for human-robotic-drawing performances, a certain fluidity is essential in making one’s own way in the world.
KT: As an independent artist, how do you get your projects out there?
I share the process… maybe I live a little bit in it. The projects exist in their own world online; it looks, sounds, smells, feels like something. It’s part of the exploration, which I really do enjoy sharing as a kind of meta narrative. I think that impulse comes from my background as an early internet user. If you can communicate in a way that everyone feels they’re being spoken to, maybe they will feel like they can contribute to your story and get behind what you’re doing.
KT: You have many projects. How do you decide which to take on or decline?
I’m interested in many different things, and I’m a believer in randomness. Generally, I’m trying to say yes to people and projects I feel some connection with. I recognize when people are also trying to be inventive in their own respective gambit. I find it energizing when that dedication and value system is evident… Ultimately it’s an intuition which has done right by me so far.
I’ve been thinking about how I can align with projects that support a culture that I want to see thrive. Not only am I going to say yes to those things, but I’ve been actively seeking them out. I’m trying to be more judicious in what I say yes and no to, which is still really hard as everything, to a degree, is interesting to me.
KT: How did your TED Talk come about?
TED was unexpected and still a bit surreal, probably because it happened rather quickly after they reached out. That’s the thing about putting things on social media, right? They found my work and felt that it was creating a space for things that hadn’t been said, centered around collective authorship and collaboration.
That being said, I knew when I was preparing the talk that I didn’t want it to be focused solely on me. Accessible to everyone; sure. But with the opportunity of such a large audience in front of me, I wanted to talk about the larger idea of collective collaboration. The talk actually inspired me to launch my studio, Scilicet (which is Latin for “permitted to know”). That’s the thing about opportunity; it empowers you to assume a bigger identity.
KT: In a way, you are an entrepreneur…
There’s this idea that in order to make art or to have an art practice, you have to have a gallery, or you need to have a trust fund, or institutional support. I don’t have any of that, and I think that keeps people afraid of making the work they are meant to make. I’ve definitely felt that at various stages in my life. Nowadays, for my part, I’m just trying to share my work and interests with as many people as possible. I guess on some level that looks like entrepreneurism.
I’ve been steered by this notion of “going where you are rare,” of trying to not limit myself to one discipline, approach, or industry. It takes a bit of focus, and the practice has evolved into what I’m doing now. It is far more than I could have imagined when I started.
Sougwen Chung Recommends:
Arts of Living On a Damaged Planet: Ghosts and Monsters of the Anthropocene, 2017 Anna Lowenhaupt Tsing, Heather Anne Swanson, Elaine Gan, and Nils Bubandt
#GOTHSCREENSHOTS - existential screenshots – remember me on this computer -
World’s first classical Chinese programming language by Lingdong Huang
“Diving into the Wreck” by Adrienne Rich
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.
It’s thrilling to see the artists featured here, & to be part of an evolving canon of experimentation and collaboration. @annaridler @LIAsomething @glagolista @quasimondo @aaronkoblin @flight404 @goodfellow_ian @ben_fry @REAS @johnmaeda @_joelsimon @c_valenzuelab @joshuadavis
( See the full article showcasing our work here )
At my studio, we have so many exciting projects in the works that aim to expand the collaborative potential of art and technology.
We’re looking for likeminds to work with, so please get in touch if any of these ideas resonate with you.... and as always, so much more to come ~~
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.
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?
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.
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.
What happens when humans and robots make art together? In this awe-inspiring talk, artist Sougwen Chung shows how she "taught" her artistic style to a machine -- and shares the results of their collaboration after making an unexpected discovery: robots make mistakes, too. "Part of the beauty of human and machine systems is their inherent, shared fallibility," she says.
This talk was presented at a TED Institute event given in partnership with BCG. TED editors featured it among our selections on the home page. Read more about the TED Institute.
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." .
Thank you to the early support of Drawing Operations Unit: Generation 1 by @juliaxgulia Karen Wong and Lisa Phillips through @NewMuseum’s incubator project @NewInc. And the continued development of Generation 2: Memory by CG-Arts NTT InterCommunication Center @japan_media_arts_festival and @firstname.lastname@example.org@takahikoazami. Was a pleasure to have iterations researched at Pier Nine @sherryingw and @salvagione.
Currently developing forthcoming generations, focused on Collective Collaboration with the support of @googleartsculture@dh7net
Thankful for the contributions of friends and collaborators @hardmaru@YotamMann, @MaryFranck, @_frnsys & musical collaborator @aquarianyes.
So much more to come. 🌹
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.
Vanessa Chang is senior lecturer in Visual & Critical Studies at California College of the Arts, and lead curator with CODAME Art + Tech. Her writing has appeared in Wired, Slate, in media res, Journal of Visual Culture, among other venues.
〰️ 🌊 daydreaming in blue 🌊〰️
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).
Where does "I" end and "we" begin? .
Thank you to @artnet for including me and Doug in their article on 9 Pioneering Artists working with AI. I spoke a bit with @Naomikrea about the potential I see in working with this new medium.
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.”
Delighted to be in the company of @quasimondo, @genekogan, Anna Ridler, Helen Sarin and more. https://news.artnet.com/
Copyright Sougwen Chung