This post was originally published by NEW INC on April 20, 2018 and is based on an interview between Lindsay Howard and Sougwen Chung.
Recently NEW INC, the New Museum’s cultural incubator, and Nokia Bell Labs presented their first exhibition entitled “Only Human” at the Mana Contemporary in Jersey City, New Jersey. The exhibition showcases the work of NEW INC artistsSougwen Chung, Lisa Park and Hammerstep (Jason Oremus and Garrett Coleman) participating in the artist-in-residence program at Bell Labs and their collaboration with Bell Labs researchers to produce new artistic projects inspired or enabled by Bell Labs technologies.
“Only Human” is available to visit Tuesdays - Saturdays at 3PM through June 2nd as part of the Mana Contemporary’s gallery tours. No RSVP is necessary.
On Saturday, May 12th there is a day-long symposium at the Mana Contemporary for a deeper dive into some of the ideas, themes, and technological research that are being explored in the works on view. It will also reflect on the legacy of the Experiments in Art & Technology program (1967–2001), founded by artists Robert Rauschenberg and Robert Whitman, and Bell Labs engineers Billy Klüver and Fred Waldhauer. Please RSVP here.
The interview below with Sougwen Chung provides additional insight into her practice and how her work with Bell Labs researchers has enriched her artistic experience during her year long tenure as an artist-in-residence.
Lindsay Howard: What are some themes you’ve been exploring, and some past projects that relate to the research you’ve been doing at Bell Labs?
Sougwen Chung: I’ve been evolving the theme of human-robot collaboration through the past year at Bell Labs. My work has always centered around the marks made by hand and the marks made by machines—and the machines are constantly evolving. In particular, I’ve been exploring the fields of collaborative robotics, computer vision, and biometrics during my residency. It’s been able to observe how the role of connected machines are expanding in scale and scope through advances in artificial intelligence and the proliferation of mechanical agencies in IOT and in workplace automation. Sometimes it seems like these systems are imbued with a kind of predictive ability that can seem prescient, or at least much higher in intelligence and ability. I have been meditating on some words by Adrienne Rich during my residency:
“We are living in a time of unprecedented complexity, our senses are currently whip-driven by a feverish new pace of technological change. The activities that mark us as human, though, don’t begin, exist in, or end by such a calculus.”
They were written in 2002, when then the activities that mark us as human were much clearer. Now, in 2018, it’s likely more of a space to define, to demarcate. These speculations have driven my curiosity about working with machines—and co-evolving my artistic practice alongside expanding technological complexity. At Bell Labs, I'm exploring computer vision work and the robotic interface as a creative collaborator, from single mechanical unit to robotic swarm.
LH: What is your day-to-day experience like at Bell Labs? Are you in a science laboratory? Are you in a research space? Are you working daily with an engineer or researcher? How do you balance all of that?
SC: I have the privilege of being able to work with a diverse array of collaborators in my practice. This past year at Bell Labs has been the place where it's all come together. I’ve been able to take the divergent influences, ideas, and prototypes that I’ve been working on, and sit and reflect on them in the quiet space of my studio. I’m currently working on the formal prototypes for the robotic units that will make up my commission project. I’ve been working with artists and designers Andy Cavatorta and Scott Peterman, as well as a fabrication studio named Young Buk on the final iteration of the robotic system past the prototype. It’s been a joy to go from making decisions about the design, behavior, and hardware—the organs of this robotic swarm system—to the finished product with this incredible team. I’ve started calling one of the prototypes DOUGLAS because it’s the continuation of my previous drawing collaborations, or drawing with DOUG.
LH: What does DOUG stand for?
SC: It stands for Drawing Operations Unit Generation [1, 2, 3, etc.]. I think we’re on generation four now. ‘LAS’ stands for “Live Autonomous System.” It's definitely a bit of a mouthful and DOUGLAS is a lot friendlier. We’ve been working on design, programming, and fabrication simultaneously, while integrating it with feedback from my collaborator at Bell Labs, Larry O’Gorman, and getting a sense of how it’s starting to move and shape up at Bell Lab’s research facility.
LH: What interested you in Bell Labs Researcher Larry O’Gorman’s work?
SC: Larry started out in the privacy sector. Turns out that he was one of the major contributors to the fingerprinting technology that is ubiquitous in the world now. I thought he was such an interesting person to have a conversation with. From our conversations, I learned more about his career. Currently, he works on designing visual algorithms for public cameras that extract optical flow data from surveillance footage.
LH: When did you decide to formalize this collaboration and partnership?
SC: I think I always knew I would be working in some form with Larry’s research, in part because of the aesthetic qualities that his system could extract from a camera. There were visual features that shared similarities with my work—my gestural abstract work. I felt like there was a lot of harmony there. He actually sent me a paper after our first meeting about his work, and the paper was titled "Towards A Kinder Camera," which I thought was such an unusual sentiment to come from a research facility.
LH: Sounds like he was anticipating, whether or not he knew [it], some sort of ethical responsibility.
SC: In general, the willingness for Larry and for Bell Labs to be a part of that conversation is something I found to be really inspiring and compelling. They have this future human idea which, I think, on some level, is central to the contemporary artistic imagination as well.
LH: What is the future human idea?
SC: It’s not complicated. Very universal, and, again, a privileged dialogue to have. It concerns itself with questions like: What do people want society to look like in ten years? Our generation and the generation before ours have seen the internet turn into what it is today, from dial-up to Uber. We’ve been able to see the internet evolve, and we’re only just starting to reflect back on the past twenty years of this invention and how it’s influenced how we interact with each other, how we communicate, how we move around. Facilities like Bell Labs have an inside view into how digital technologies have shaped our culture, so the awareness that the decisions we make today can have a significant impact on society ten years from now comes naturally to their legacy and vision moving forward. The same can be said for artistic institutions—the idea of shaping the future through community and artistic artifacts while maintaining a cultural archive, a record of what was.
LH: What have you learned about yourself, or what has most shaped your practice by collaborating with robots, and by collaborating with the technologies that you are describing?
SC: Drawing, I think is one of the most humble art forms. Being able to engage with mark-making in collaboration with a robot means not always knowing what I’m doing—and that has been really enlightening. It’s helped me work through and question what narratives we tell when we engage in collaboration with mechanical agents, and technologies in general. In the conversation of AI, that gets really broad—dystopian, utopian, occasionally fraught with controversy. When people think about AI there is a tendency to ascribe, or imagine, considerable agency. Something like an artificial consciousness, however far-reaching that might be. I’m compelled by the human capacity to anthropomorphize our relationship to machines, particularly to robots, and how that can end up being a mirror for how we view ourselves and our own interactions with others. There are didactic models that are encouraged by developments in IOT and voice interfaces. But the collaborative models are more interesting to me. It’s a new stage for examining authorship and agency. It starts to question, who is in control? Who do we want to be in control? Is that the point?
The proliferation of computation is bringing about a paradigm shift. From marks made by hand toward marks made by machine, we invite the question: if machines are able to execute actions traditionally performed by humans, will the human hand be replaced?
Contemporary artists with a forward-thinking approach are responding to this question by imagining new pluralities, rejecting the simplistic binary of human or machine. Through explorations of machine automation as an artistic medium, artists are defining paradigms of human and machine as intertwined agencies informing each other. Through co-authorship of organic and computational intelligence, an expanded notion of collaboration sets the stage for vital new inter-subjectivities. Thus, we investigate how might the conception of human agency need to evolve.
Allegories of Human & Machine in Art
Art, by necessity, provokes speculation. Artistic movements have long helped shape a cultural understanding of historical epochs through allegorical lineage, linking the role of the artist to conceptions of agency — from Michelangelo’s hand setting an angel free from marble, to omniscient arm of SEEK that shape the environment of its citizens, to the works of today, exploring the emergent possibilities of human and machine.
During the renaissance, the artist’s hand was considered God’s vessel by religious institutions. Michelangelo's Angel of Arca di San Domenico was a valorized motif, an idealized form waiting to emerge from its captivity in stone – he artist’s skill was secondary. Michaelangelo’s role as an artist was that of a facilitator of religious wonder – an intermediary between the commonality of man and the sublime.
In the case of SEEK, the machine’s hand was omniscient. The machine’s prescient use of computer vision technology introduced a synthetic mode of sensing that contrasted the organic sensory apparatus of its gerbil subjects. The project simulated computational sovereignty via a robotic entity that was responsible for maintaining order in an environment based on a predetermined set of rules that determined environmental changes informed by its population’s response to previous iterations. SEEK was an early example of automation and computational governance provided by a simulation of a self-organizing and self-referential system. SEEK provided a metaphor for how technological systems could potentially govern behavior.
Allegories in art reflect and shape the social values of their historical context. Michelangelo's works in the renaissance can be seen as glorifying religious iconography with the scope of supporting the church’s governing dogma. SEEK and comparable works in media art effectively simulated the regulating influence of systems, a prescient concept in 1969 and a precursor to the networked systems of today. On one side of the spectrum, the fictive machines as a consummate offspring of humankind (combining the tendency towards pareidolia with imaginative delusions of grandeur). On the other, machines that render humankind obsolete affirm a fatalistic mindset. While such ideas might satisfy the tendency towards utopian and dystopian fantasies about technology, they emphasize a reductive binary of human or machine.
Man or Machine
Throughout time, we have witnessed the ways in which cultural shifts provoke anxiety and how, beneath the tectonic plates of the establishment, they dismantle structures. With that in mind, it can be tempting to mythologize the utopian belief in a hypothetical emergent intelligence within the computational operations of the machine as a seraph enclosed within the substrate of bits and bytes. To seek sublime within sublimation. These myths provide comfort and a stabilizing, yet perhaps naive, optimism. But if we operate under this assumption, what becomes of human agency, as embodied by the artist’s hand? Is it no longer required?
The reality of today’s technological landscape is more complex. What is a representative microcosm of the overall megastructure? As alluded to in prescient works like SEEK, the effect of computational governance is at once non-neutral, ubiquitous and invisible. Systems link to form an interconnected network that sees and yet is unseen. The anatomy of the network, its sensors, its data collection and influence, are rarely in the frames of mind of the users it governs. It is these conditions that have contributed to the intractable effect of technology in the ebb and flow of modern life. It is “an accidental megastructure, one that we are building both deliberately and unwittingly and is in turn building us in its own image.”
Man and Machine
Today, artists are caught in a cacophonous feedback loop as they ricochet between the tradition of art (manifesting social consciousness and reflecting on human experience) and the increased presence of machine automation (proliferated in tools, software, sensors, and robots). The modern psyche is on a transitional edge. We are charged with constructing intellectual and philosophical frameworks alongside the technologies that are simultaneously shifting perceptions of human agency.
Take AARON, a computer program designed in 1973 by artist Harold Cohen, as an example. Trained as a painter long before AARON began, Cohen’s project translated singular artistic intention through computers. In this project, the machine operated as an extension of the artist’s vision. Cohen defined the system according to his own aesthetic sensibility. The machine’s rule-based system used familiar motifs within the genre of painting such as people and plants, which eventually shifted towards abstraction in later years. In this project, Cohen programed the machine to paint a series of novel images and acted as the overseer of the work – absolving him from contributing physically to the painting and privileging didactic over dialogical methodology. Cohen prefered to extend his agency through a machine by translating his artistic vision into computational language. AARON executed permeations on a style, but did not invent its own original style beyond Cohen’s predefined set of rules. Thus, the limitations of the output were predetermined. The artist, for Cohen, was a designer of systems and an interrogator of authorship.
The creativity described in Cohen’s work is linear, as it begins with the artist and ends with the machine. The human and machine gestures remain separate because the mechanical operations are executional. Cohen creates the rules for AARON to follow and they never occupy the same space in time. With this approach, Cohen occupies a privileged space in the interaction with the machine because his vision is absolute, perfect, unchallenged, non culpable. While the authorship may be in question, the roles occupied by human and machine are not. Now, Cohen is able to produce posthumously through automated agency. In questioning authorship, we challenge the definition of creativity. But what of collective authorship?
Drawing Operations: Towards Collaboration
Since 1969, it could be said that we are all living in a Blockworld described by SEEK, overseen by an accidental megastructure fed by memes, gps data, satellite imaging, reddit threads, remix culture, and unfortunate flash mobs. The “landscape” of human extension through networked devices has contributed to the widespread digitization and regurgitation of culture.
Ambiguous authorship has introduced incredible complexity into the network. Inspired by Cohen’s AARON, artists have continued to create visual systems that can produce infinite permutations upon a theme. The linearity of Cohen’s human and machine has extended to form a loop. Now, the conversation has grown to explore what happens to agency, originality, and authorship after we extend ourselves through machines, spawning a new generation of artistic inquiry. Notably, the Hong Kong international exhibition Ubiquitous Humanity explored the boundary between human and the mechanical through collaborative and interactive pieces, such as D.O.U.G.
Drawing Operations Unit: Generation 1 (D.O.U.G.)
I introduced Drawing Operations Unit: Generation 1 (D.O.U.G.) as a performance piece investigating automation, autonomy, and collaboration in 2015. In Generation 1, the robot (D.O.U.G_1) and I draw together. The machine mimics my gestures in real time via computer vision, which results in a synchronous collaboration between human and machine. Set as a 20 minute performance, the demonstration of co-creation builds upon the mechanical extension proposed by Harold Cohen’s AARON and suggests a metaphor for human machine symbiosis through behavioral empathy.
In Generation 1: Mimicry, both human and robotic agent are creatively implicated through the act of performance. As D.O.U.G._1 mimics my movements, we create a visual language and cohesion manifested through a sustained awareness of mechanical and human marks. The project is primarily concerned with ambiguity and interoperability in a machine and computer mediated creative process. We create a feedback loop within the performance that allows for a fluid dialog between the mark made by a human hand and a mark made by machine.
Through this work, I suggest that separation between collaborators is inconsequential. The producer and the impersonator are indistinguishable, and there is no leader or follower as they endlessly follow each other. Ultimately, the authorship of the resulting artwork is un-ascribable. The folie-a-deux’s binding creation may only be attributed by compulsory collaboration, a shared (polycentric) improvisation. In Generation 1, my improvised gesture is an extension of experience, emotion, subjective, moment, impulse control, dexterity, and rhythm translation over time. The robot’s movements are circuitry and servos, with its vision in pixels and coordinates, and electricity driving its movement, but also sight, interpretation, “understanding”, “parsing”, “learning”, and “data sets”.
In an evolutionary progression, Generation 2 of Drawing Operations matures the interaction model of artist and machine from mimicry to memory via machine learning. Gestural data extracted from my archives are fed into training models, simulating a neural network. The training models interpret archives of images, which provide a foundation of a rudimentary understanding of style. Effectively, the robotic arm begins to learn from the style of the artist’s hand throughout time. The system learns the stylistic patterns of its human counterpart, and, in a sense, interprets the history of the artist’s archives, learning to “independently” produce its own conclusions. The performance can be thought of as a collaborative simulation between an artist and her own mechanical doppelgänger. By doing so, Drawing Operations embraces indeterminacy in the age of mechanical production by implicating the machine as artistic collaborator, or possibly, originator. Not only does this place the authorship of the artwork in question, but it also speculates on the necessary evolution of our existing conception of collaboration.
Generation 2 teases at future applications of machine learning intertwined with artistic production – not limited to a single artist, but inclusive of a wider breadth of artistic sources. The machine as collaborator may invent a range of styles beyond the imagination of the human artist, as digitized archives of drawing take on a new life. By cataloguing art history as training data, the machine may be able to forecast, produce and thus originate future movements and styles by tracing and speculating the provocation of artistic development over time.
Overall, the pursuit of multi-threaded agency is poised to stimulate new ways of seeing, sensing and decoding the artistic process.In this framework, the process of creation is as much a part of the artwork as the visual outcome, if not more so. In a sense, the artistic agency questioned within the Drawing Operations project is a composited interoperation. It embraces creative ambiguity in the work, rendering full credit beyond the grasp of human or machine, suggesting the obsolescence of the distinction. In exploring a continuously blurring of distinction between self and machine, Drawing Operations fuels speculation upon inclusive models of radical inter-subjectivities.
What’s to come
Beyond the adversarial binary of human versus machine lies a spectrum of intertwined conceptions of biological and mechanical agencies. In this pursuit, emerging themes will be shaped by emergent interconnectivity. Developments in brain computer interfaces are heralding a generation of responsive prosthetics as cognitive extensions of the mind.In competitive gaming through online communities, human players are competing with learning systems inspired by their own playing styles. By doing so, players are evolving new strategies for competing with machines, as well as extending notions of beauty within gameplay.In tandem, by capitalizing on recent advances in audio codecs and digital signal processing, researchers are exploring ways that haptic feedback can be used to restore perceptions, and perhaps create new ones. Multi-player virtual reality may eventually lead to the normalization of post-geographic communal spaces and extend the idea of co-presence within an abstracted space. Works that are manifold and cooperative, inspired by shared sensorial and spatial experiences, will espouse the imagining of complex new inter-subjectivities.
By examining the co-authorship of human and machine in the context of building, artworks offer allegories for how we can potentially navigate technological change, providing models for how the multi-sensorial data collected from humans, machines and the environment applies to the human experience. Beyond adversarial binaries, towards a promiscuously inclusive, multi-species array of cognizing agents — mechanical and biological, singular and composite, discovered and soon-to-be discovered. We are moving from a mark made by hand and a mark made by machine toward a mark made of something else entirely.
 Harari, Yuval N. Sapiens: A Brief History of Humankind. Toronto, Ontario: Signal, McClelland & Stewart, 2016. Print.
 “Io intendo scultura quella che si fa per forza di levare: quella che si fa per via di porre è simile alla pittura.” a basis for the interpretive translation "I saw the angel in the marble and carved until I set it free." "Lettera a Messer Benedetto Varchi." Lettera a Messer Benedetto Varchi - Wikisource. N.p., n.d. Web. 20 June 2017.
 Vardouli, Theodora. "Nicholas Negroponte: An Interview." Open|architectures. N.p., 26 Oct. 2011. Web. 20 June 2017.
 "Angel (Michelangelo)." Wikipedia. Wikimedia Foundation, 11 June 2017. Web. 20 June 2017.
 Vardouli, Theodora. "Nicholas Negroponte: An Interview." Open|architectures. N.p., 26 Oct. 2011. Web. 20 June 2017.
 Kranzberg, Melvin. "Technology and History: "Kranzberg's Laws"." Technology and Culture27.3 (1986): 544. Web.
 Bratton, Benjamin H. The Stack - On Software and Sovereignty. Massachusetts: MIT, 2016. Print.
 "The Further Exploits of AARON, Painter." The Further Exploits of AARON, Painter. Stanford, 22 July 1995. Web. 23 June 2017. SEHR, volume 4, issue 2: Constructions of the Mind
 The 2016 Hong Kong group exhibition Ubiquitous Humanity comprised of a selection of works curated by Takahashi Mizuki addressing the role of technology in expanding human sensitivity (physical, emotional and behavioral), examining the boundaries between the human and mechanical through visual, collaborative, and interactive experiments.
 Metaphorically, “shared psychosis”, is a psychiatric syndrome whereby its symptoms are shared by more than two people by transmission. Berrios, G. E. & Marková, I. S.. “Shared Pathologies”. In Bhugra D & Malhi G (eds) Troublesome disguises. Managing challenging Disorders in Psychiatry. 2nd Edition, London, Wiley, 2015. pp.3-15.
 DOUG’s mechanical mode of production becomes the same tool as the artist’s tool for expression.
 The readability of massive quantities of data is the focus of the field of machine learning, which has been thriving on the mass data sets generated by humans, and the advancement of processing speeds. Machine learning algorithms are being trained on this data, and the techniques are improving in sophistication. The machine learning of today utilizes neural networks to glean behavioral patterns from the collected data of humans through images and text, which, en masse, form encoded impressions of the collective as a whole.
 DOUG heeds an imagining of machine and human that transitions beyond the conventional species-specific binary of human vs machine, by presenting a ulterior model of interaction derived of multiple artists.
 Xu, Zhe, and Emanuel Todorov. "Design of a Highly Biomimetic Anthropomorphic Robotic Hand towards Artificial Limb Regeneration." 2016 IEEE International Conference on Robotics and Automation (ICRA) (2016): n. pag. Web.
 Clark, Andy, and David J. Chalmers. "The Extended Mind." The Extended Mind (2010): 26-42. Web.
 Metz, Cade. "The Rise of Artificial Intelligence and the End of Code." Wired. Conde Nast, 01 May 2017. Web. 20 June 2017.
 Metz, Cade. "The Sadness and Beauty of Watching Google's AI Play Go." Wired. Conde Nast, 03 June 2017. Web. 20 June 2017.
PROPS: What is the role of images in your research?
Sougwen Chung: The role of images in my research is linked to ways in which interface design shapes image-making. For years I've had an interest in exploring how an interface operates as a layer of mediation in creative process.
My practice is motivated by a curiosity regarding this layer of mediation, of “being on the boundary”.1 This approach is part of a philosophy of making that speaks to the aesthetics of the near-future, inherently and by extension. It does so through the mediums of performance, installation, and moving image.
The fields of human-computer interaction, artificial intelligence, and machine learning are complex, involving layers of computational abstractions and a technical lexicon often inaccessible to people outside of their respective research areas. As such, the fields benefit from a narrative context to communicate their significance to a wider audience.
One such context has been in the arena of competitive game-play. The narrative of games provides cultural reach as well as defined parameters of success. Watson, AlphaGo, and Libratus are centerpieces around which computational abstractions of human computer interaction, artificial intelligence, and machine learning can assemble.2 However, the easy communicability of competition reinforces the adversarial dynamic of human vs machine already prevalent in popular cultural discourse.
My recent project, Drawing Operations, presents an alternative. In Drawing Operations, I engage in a drawing performance with a robotic arm as an exploration of human and machine collaboration.
The co-creation of an image between human and machine reframes the conventional narrative assigned to artificial intelligence. It sets the stage for a broader cultural understanding of the field and posits a different set of research goals. Conceptually, collaboration extends the interaction of human and machine to that of a creative partnership (however aspirationally). Additionally, it invites the subjective assessment of an audience as well as inspiring research goals defined by aesthetics, interaction, and craft. The role of images, in this case, creates space for comprehensive exploratory narratives to emerge. (Sometimes counterpoint, sometimes polyphony.)
AI Researcher Fei-Fei Li says that if we want machines to think, we need to teach them to see.3 In addition to teaching machines how to see, as we speculate upon modes of vision and cognition dissimilar to our own, we are also teaching them what to see.
Drawing Operations In Drawing Operations, the role of images is two-fold. As input, they are firing the synapses of the machine which cause it to move. As output, they are objects of aesthetic inquiry.
Input: Behaviour & Process The behavior of the machine is driven by learning algorithms trained on images from a variety of sources. These images are derived from art historical archives as well as the works of contemporary artists. By using computer vision, video analytics, and machine learning, I interpret contemporary and historical image sets to glean meaningful gestural behavior. From there, these behaviors are taken into the context of a collaborative performance. Within this collaboration, Drawing Operations aims to showcase a confluence of biological and mechanical modes of sensing, cognizing, interpreting, and mark-making.
Output: Aesthetics “When the image is new, the world is new.”4 The speculative nature of the project is advanced by the interoperability of visual artifacts as concrete representations of research, sites of aesthetic comprehension, and objects within themselves. (The wreck and not the story of the wreck, the thing itself and not the myth.)5
As aesthetic inquiry: what forms emerge as a result of human and machine collaboration? What new types of information can be encoded in a single image? How do unfamiliar aesthetics stimulate new ways of seeing, sensing and decoding in the viewer?
Conclusion Today, the interface is not simply a mediating apparatus for creation but a speculative agent of co-creation. As a result, in projects like Drawing Operations, the role of the image is multifaceted. The image functions not only as an aesthetic object, but a visual artifact showcasing the intersection of artistic practice and machine learning.
For me, the project's continued evolution teases at some creative possibilities of the near-future. Beyond traditional anthropocentrism, and towards a promiscuously inclusive array of cognizing agents — mechanical and biological, singular and composite, discovered and soon-to-be discovered.
Humans have an innate need to adapt and improve what surrounds them. The strong desire to create a better, more meaningful future can be seen through each culture’s artistic and technological developments. Though we as a species are programmed to aspire, grow, and create, the invention of something truly novel—whether it takes the shape of a groundbreaking artwork or a new technology that revolutionizes daily life—is rare. One, therefore, has to wonder: what are the circumstances that enable creativity and invention?
In the 1950s, Mervin Kelly became the president of Bell Labs, the New Jersey research facility, and set out to transform it into an “institute of creative technology,” an initiative that ultimately led to the invention of the laser, transistor, and solar cell, to name a few.1 He enacted social and architectural strategies to empower researchers, including a mandatory open-door policy that encouraged interactions between engineers, chemists, and mathematicians in a collaborative, interdisciplinary environment. Kelly also offered researchers the latitude to delve into self-directed inquiries for years at a time without a specific result in mind. He even designed some of the hallways at Bell Labs to be exceptionally long so that, in walking from one place to another, one would come across acquaintances, who might inspire fresh ideas or diversions. This synergistic, go-for-broke mindset became firmly embedded in the Bell Labs culture and laid the groundwork for radical breakthroughs and collaborations across disciplines between employees and others beyond the walls of Bell Labs.
Billy Klüver talking about E.A.T. and 9 Evenings to group of artists and engineers in Toronto. Artists requests to the engineers for their 9 Evenings performances are projected on the wall behind him. Photographer Unknown. All rights reserved. Courtesy of E.A.T. and Broadway 1602.A SENSE OF POSSIBILITY EXPANDED ON BOTH SIDES, AND THE ARTISTS GAVE KLÜVER WISH LISTS FOR NEWLY AVAILABLE OR NOT YET IMAGINED TECHNOLOGIES
Billy Klüver joined Bell Labs as an electrical engineer during Kelly’s tenure. He was encouraged to follow his passion for cinema and regularly attended film screenings and exhibitions in New York. Before long, Klüver met Robert Rauschenberg at the Museum of Modern Art, followed by John Cage, Merce Cunningham, Jasper Johns, Yvonne Rainer, and Andy Warhol. Over the course of their conversations, Klüver and the artists realized that their combined skills and resources could lead to the creation of works that merge artistic vision with cutting-edge research at Bell Labs. A sense of possibility expanded on both sides, and the artists gave Klüver wish lists for newly available or not yet imagined technologies. Klüver and the engineers at Bell Labs went into production mode, developing inventions such as modified TV sets and projectors that displayed abstract images in response to a musical tone, a Doppler sonar that translated movement into sound, and FM transmitters that relayed sounds from the human body to loudspeakers. The resulting artworks were not only ambitious but also the first of their kind, pushing both sets of collaborators to consider the creative possibilities and implications of emerging technologies. In October 1966, they were introduced to the public in a performance series, called 9 Evenings: Theatre and Engineering, at the 69th Regiment Armory. A few months later, Klüver and Rauschenberg, in collaboration with Fred Waldhauer and Robert Whitman, launched Experiments in Art and Technology (E.A.T.), a nonprofit organization established to support collaborations between artists and engineers.
Through these seminal collaborations and the decades of partnerships that followed, both artists and engineers experienced the advantages of multidisciplinary collaboration. While engineers tend to address challenges in a reductive, linear way, artists generally create artworks using a broader, more divergent approach that can also inspire tangible contributions to a technologist’s research. The engineer will often take a general or universal question and break it down into small components while an artist can observe something that’s seemingly simple and create a whole universe froman it. Though different, the approaches are complementary because both parties are working in an abstract way toward new discoveries. The goal of ascertaining some new or deeper understanding of the world is a commonality between them.
Early in 2017, Bell Labs partnered with NEW INC, the art, technology, and design incubator founded by the New Museum, to reinstate the E.A.T. program with a year-long artist residency. The artists are granted traditional Bell Labs privileges: access to the company’s research, tools, resources, and fabrication studios as well as the freedom to explore countless avenues of research in order to identify relationships and areas of interest, open collaboration with researchers who are exploring everything from machine learning to multi-touch sensors, and a long-term scope to try, perhaps fail, learn, and try again.IN ORDER TO REACH OUR GREATEST POTENTIAL, IT’S IMPERATIVE THAT WE SUPPORT THOSE WHO ARE OPERATING AT THE EDGE OF POSSIBILITY
Two artists and one artistic collaboration—Sougwen Chung, Lisa Park, and the dance duo Hammerstep—are working with engineers to propel their practices forward. Chung began the residency after years of participating in a drawing collaboration with a robotic arm; through her discussions at Bell Labs, she is increasing the robot’s intelligence and multiplying it in order to study crowd behavior, influence, and empathy. Park is building upon her past work with brainwave sensors and heart-rate monitors to create a holographic installation that responds to human touch. Hammerstep is turning their futuristic dystopian written narrative into an immersive theater experience using interactive projections, motion- and biometric sensing, and low-latency locational technology. While these alternative and often poetic interpretations diverge from the engineer’s initial intentions, they have the ability to reveal aspects of technology—and our relationship to it—that wouldn’t have existed any other way.
On a daily basis, artists and engineers seek original ideas, processes, and devices for the benefit of humankind. Through close examination of past successes, we learn that the ability to take creative or intellectual risks without fear of failure, to participate in multidisciplinary collaborations, and to have freedom to develop seeds of ideas over a long period of time are essential for nurturing invention. Art and technology will define the future of humanity. In order to reach our greatest potential, it’s imperative that we support those who are operating at the edge of possibility.
I love the point you bring up in your discussion about "image-making," specifically teaching machines how and what to see. In many ways, I feel that's often the role of the visual artist for people, as well—to show us what to "see" or how to look at something in a new way. Is that something that motivates you?
In some ways, yes. I’m curious about what is unique about image-making today, and why?
How can it be taken apart?
These concerns are not new, and have precedents in the history of visual art. However, our methods of producing and disseminating images have changed pretty significantly, even over the past 15 years. Our generation has a relationship with images quite different to previous generations, and it continues to evolve quite rapidly.
One example is that images today are captured en masse, and filtered in a way to become part of a collective visual memory, which shapes our collective thinking and behaviour.
This cycle of sensing, capturing, and mediating is implicitly addressed in the collaboration with the robotic arm.
The drawing process is recorded, algorithmically parsed, and then reintroduced as behaviour for a collaborative performance. The experiment is ongoing. I’ve found that the project is generating a curious set of visual experiments that also facilitate my deeper understanding of images, creative process, and self-directed tools.
I’ve found that by evolving this workflow, I’m starting to understand drawing in new ways.
Do you see yourself or technology leading your work? Does the prospect of new technology encourage you to try new things or do ideas formulate and then you find the means to create them?
I’m sensitive to the mediating effect of technology; I try to be very aware of the framework which is presented by whatever technology I am engaging with at the time.
My process is about finding ways to understand the tools available more deeply but also break them apart a bit. Maybe it started from a reaction to perceived constraints and questioning preconceptions of interfaces.
In some earlier works, my leading the form has been a central tenet of my interest in it — but in more recent explorations, I’ve been loosening my grip on that idea of control, so to speak.
The question of control in technology today deeper than simple determinism.
Often the frustration of technology is that we expect it to do one thing and then it inexplicably does another. Either out of human error or some internal problem. Does that ever complicate your work? Does it ever elevate it?
Projects that challenge what is expected of that dynamic — the false binary of intuition and computation, excite me.
As technology advances through machine learning, what keeps the artist and machine separate? The computational and algorithmic nature of technology “learning” new modes means that, at some point possibly in the near future, it could create something functionally no different than “organic” work. Is there a line you draw between what the machine can do on its own and what has to be manipulated?
Our definitions are becoming more elastic, some would say gradually and others too rapidly. As with most things, its a matter of perpspective. Imaging technologies are already pretty advanced, so the authenticity of the form is no longer defined by the perfection of the representation. Put another way, a computer can already replicate a painting, and its already difficult to distinguish a photo of an object from the “real thing”. This is pretty established ground.
What I’m curious about is how these new ways of seeing and learning evolves a creative process. To your question — does the artist and machine need to be separate? What does a composite creative process look like — and what precedents does this evolving hybridity have in art history? In this space, there is a strain of speculation that leads to real invention. We’re living in an unprecedented time, the interplay between speculation and invention is sparking like a live wire. My curiosities are driven by that energy.