This transcript is generated with the help of AI and is lightly edited for clarity.
//
SOUGWEN:
I’d been converting my brainwave signals into a genomic sequence.
One way in which I’m not interested in being machine-readable—for me, the work that I’m doing is about my own learning, in a way. So I don’t want to be machine-executable.
Why would I want to build a system that takes away the thing I love the most from me? And I can say, to this day, I draw more than I ever have.
For me, it’s about extended authorship. It’s much more Haraway than Hinton.
//
REID:
In the third century, a Chinese court official named Zhong Yao invented a technique that would define calligraphy for the next two thousand years. He called it dùn: the pause. A deliberate moment of pressure, where the brush presses down, holds, and then lifts or redirects. It was a way of encoding intention into the stroke itself—not just where the mark goes, but the weight of the decision before it moves. No original works by Zhong Yao survive. What survived was the technique itself. Passed from hand to hand for eighteen centuries, the pause became a kind of inherited intelligence: embodied, transmitted, alive. Chung recently discovered they are one of Zhong Yao’s direct descendants.
And in RECURSIONS—a 10-meter scroll performed live at Art Basel Hong Kong, with two robotic arms guided by EEG data—the pause returns in a new form: not in the wrist, but in the brainwave threshold that tells the robot when to act. Sougwen has been building toward this for more than a decade. Not in theory—in ink. Raised between Toronto and Hong Kong, trained at the MIT Media Lab, and an artist in residence at Bell Labs and Google, Chung has argued for something more demanding than AI art: that the machine can be a collaborator, that error can be generative, that technology can reveal as much about the human as it does about itself. They believe that to extend agency, we must understand the human sensorium—and how technology changes what humans experience as we move through the world.
In 2022, the Victoria and Albert Museum acquired MEMORY, making it the first AI model collected by a major cultural institution. In 2023, Sougwen Chung was named one of the hundred most influential people in AI. Today’s conversation is less about whether machines can make art than about what artists can teach us about living with intelligent systems. Sougwen Chung is an artist, researcher, and founder of SCILICET.
Welcome, Sougwen. I’ve been looking forward to this since getting exposed to your art when we were in Solomeo, at the Cucinelli event.
SOUGWEN:
It’s a beautiful event.
REID:
Yes. And thank you for joining us on Possible.
SOUGWEN:
My pleasure.
REID:
Your father was an opera singer and your mother a computer programmer. When did you realize that it wasn’t about choosing one part of the inheritance—maybe the kind of parenting—but blending them together?
SOUGWEN:
I love that question, because I think it’s really hard to choose between your parents—and early on, we all realize it’s probably best not to. So we were brought up with both languages in our household. When you learn something from early childhood, from those experiences, they become part of the fabric of how you think about things, how you cognate, how you express. So I don’t think there was ever really a moment in which I chose one side or the other. I grew up playing violin and piano, but also learning how to code. We had computers from a young age, so it always felt really natural.
At the same time, I always thought that maybe through that—and maybe because I’m kind of a quiet person in general—there’s something that art and performance, those mediums, could express that language couldn’t. So I very much veered toward those directions.
REID:
Out of curiosity—because this is one of the things that affected me when I was young—did you ever read Gödel, Escher, Bach?
SOUGWEN:
I’m going to be quite honest with you. I tried.
REID:
Okay, fair enough. It’s like—
SOUGWEN:
Yeah, it’s quite— I weaponized it in different ways. I tried. But I’d love for you to tell me about it.
REID:
Well—Hofstadter, genius book, Pulitzer Prize. He’s writing about human existence and consciousness and whatnot, which is part of where the art and AI and all the places we’re going. But it was also the parallels between, for example, Gödel, Escher, and Bach. So you play music, you do visual art, you think in computer science—the same kinds of parallels between these systems. How you think about the relationship between music and computer programming is kind of a classic. That was the reason it occurred to me that maybe you’d encountered it.
SOUGWEN:
It’s so funny. It’s been so ingrained in my experience. I consider myself an artist and researcher, but I just learn by doing. So I think it’s been playing violin at such a young age, and piano, and learning through instruments—but also understanding that there’s a really interesting world of digitization around sound and visual that happens from a really young age. Those parallels, and that translation, have really been a point of inspiration, of tension, and of curiosity for the work, because they’re readable in many different forms.
REID:
Yeah, exactly. We’ll get to various forms of readability. But it seems that your art practice, and what you’re building, started with the question of what happens when a robot draws alongside you. So what did you expect? And then what did you discover?
SOUGWEN:
That’s such a great question. It started such a long time ago—it’s funny to reflect on something from ten, eleven years ago. I was thinking through this moment in 2015, particularly when I was reading an article about Lee Sedol and AlphaGo. Lee Sedol mentioned, in his defeat to AlphaGo in this landmark competition, that even in defeat he was incredibly inspired, because he saw the beauty of the non-human move. And that was catalytic for me. It was really inspiring, because the context was that he’d been defeated by a computer system—which we didn’t think was possible, because he was the Mozart of the game, which we all aspired to, for a game that’s been played since time immemorial.
There are a few aspects of that I found really interesting. One: as an engineer, how do we unpack this idea? How do we quantify the beauty of the non-human move? Is that even a sensical direction to take artistic or technical development? Secondly—and as I get older, and reflect on these different waves of AI, its conceptualization and culture—he’s talking about seeing beauty after experiencing defeat. That fatalistic-to-awe trajectory was so incisive and really exciting to me.
So at that point in time, I was thinking about being a drawer, a performer, drawing through the interface of the computer and the screen and the mouse—and feeling a lack of embodiment in that translation of my mark into something that happens on screen. So I wanted to think about bringing it back into physical space, and what that would mean. I think it comes from playing violin at a young age and understanding this expressive gesture. I wonder if it comes from my interest in calligraphy as well—this extension of the human subject through the line. So that really was the kernel, from Lee Sedol.
I’m not a very good Go player at all, but that kernel really made me think that I wanted to explore what the beauty of the non-human move was for me. And I could achieve that through learning how to build robots, and taking the one thing I knew—drawing—and seeing what would come from it.
REID:
Most people’s first impression, when they encounter it, is: oh, what’s important is the robot drawing.
SOUGWEN:
Yeah, exactly, right.
REID:
But what’s actually important is the dynamic, and what’s happening with the human.
SOUGWEN:
Yeah.
REID:
So what’s been that lesson—the lesson of the dynamic, in which the non-human move is also incorporated into the human move, into the dance that is your art?
SOUGWEN:
I think there’s so many things I’ve learned from engaging in this process durationally. Ten years is not a short amount of time. We’ve gone through seven generations of robotic and artistic development, where we address different themes and work with different sensors and different algorithms to bring a different type of gesture into the form. That said, I’ve learned that there’s a lot of beauty in the error state, and a lot of truth in the uncertainty of the mark-making. Sometimes people say the work feels really sci-fi—but I always respond that there’s nothing fictional or speculative about any of the work that I do.
It might feel that way, but I’m really trying to get at the materiality of these systems, at the materiality of the art form, of drawing and of performance. So I think there’s something more true about this idea of drawing and not really understanding what the system is outputting. There’s something very interesting about the questions that arise from that: What is machine-readable? What isn’t? What does it mean to draw with one’s own historical archives? All these interesting lessons that I’ve gathered.
REID:
And what’s been part of the journey for you? Because one of the things that makes art really interesting is that personal quality. So what’s the thing you’ve learned on the journey?
SOUGWEN:
What have I learned? Quite a lot. I know people like to think about optimism or pessimism, but one thing I learned—maybe not about myself, but about art in general—is that by engaging with this practice, by building these systems and understanding oneself as data, measuring all these things and trying to make something maybe beautiful or true or gestural from it, it’s been a way for me to hold fear and hope in the mind at the same time. Because there’s a lot of hype and a lot of dystopia around this idea of the human-machine. It’s been in Hollywood, it’s been in contemporary media, it’s been all over. Every major platform is talking.
They have some stance of pure optimism or pure dystopia, it seems. But for me, what I’ve learned is that there are ways to chart out what that actually means for you—how you live with it in your life, and how you integrate, or don’t integrate, the things you really care about into the contemporary systems and models.
REID:
I love that answer. And the blend of thinking about it—there’s a parallel to the yin and yang.
SOUGWEN:
Yeah.
REID:
And that’s what brings the human in. Your work lives in the line between.
SOUGWEN:
Yes, there you go. I like that—it’s the line between.
REID:
Exactly. So, one of my super-weaknesses is pronunciation, so I’m probably going to get this word wrong—but the dùn pause technique.
SOUGWEN:
Yeah, the dùn technique. Yeah.
REID:
That your ancestor—again, Zhong Yao —
SOUGWEN:
Yeah, yeah, that’s great.
REID:
Invented in 230 CE, survived only because practitioners carried it forward—not necessarily the works. So your RECURSIONS system carries your gestural archive forward through a neural network. What does it mean that this is another line between—another union—one of the oldest techniques with one of the newest? How would you draw those lines?
SOUGWEN:
There’s so much mystery for me in how we connect to our past—how we might, in the words of Audrey Tang, be good ancestors, which I still find very incendiary. So what I’m interested in, in the RECURSIONS system—what I recently showed and performed at Art Basel Hong Kong—is: how do you make decisions within a system? What direction or proposition that is non-cognitive can I give the system that will allow it to draw, or stop? Which is very similar to the pause technique originated by my ancestor. And those developments weren’t developed in parallel, because we live in very different times, to say it mildly.
But when I realized that this was my ancestry, my genealogy—that I’d been developing something quite related without knowledge of his invention—I felt like there was a kind of recursive temporal inheritance happening. My interest in calligraphy doesn’t come from an interest in, or even the knowledge that this was my ancestor; my interest in drawing was almost innate from when I was very young. But when I learned about this overlap, I was excited and kind of nervous to talk about it, because it felt so apt, so layered and interesting. I’ve been working with my own archival data, and bringing up my parentage, when I think about my practice.
And it was exciting to relate something as ancient and as substantive as calligraphy to the marks I’m making with my performative gestures.
REID:
That’s awesome. And one of the things you said recently is that to become a machine collaborator, you’ve had to become machine-readable. I want to come back to this, because you’ve gestured a couple of times at readability. It feels much more like a gesture at modern life, through art. So say a little bit about how you’ve had to make yourself machine-readable—what have been the learnings from that? And how does that go to art, and then to the human experience?
SOUGWEN:
Absolutely. When I do a little bit of mentorship for different artists, I always talk about how there are so many tools, so many opportunities, so many possibilities with how we work—or don’t work—with technology today. And I found: what’s the meaning-making engine for my own work? It’s drawing. It’s the most simple. So when I decided in 2015 to train a recurrent neural network on two decades of my drawing data, I thought, this is the thing I care about, the thing I know, the thing I understand in my bones. What does it mean to digitize that work—from the level of volume? What is the labor involved? What are the challenges?
For instance, in that very specific example, at that point you couldn’t get—maybe that’s why I’m obsessed with time—you couldn’t get the pauses of the gesture. You’d only be able to read the drawing as a finished image that you have to reverse-engineer. So a lot of the decision-making pathways of the data are not available. So from then I developed a tool that allowed me to trace the pauses, to trace the time—to put the time back into the data of drawing.
In that way, it’s been really rewarding to think through the nuts and bolts of what makes art machine-readable and what makes it not—what parts are legible to the system and what parts aren’t, and what parts we want to be legible and what parts we don’t. That’s been really educational, and really grounding, because a lot of the time fear comes from a lack of specificity—you’re just afraid of all of it, especially when it comes to machines replacing artists, that automation cycle.
So it’s given me a real sense of grounding, and also this idea that I can train my own muscle memory by putting what is machine-readable in my drawing back toward the space of the canvas, as a collaborator.
REID:
So you make yourself very machine-readable. Is there anything you want to not make machine-readable? Where is that alternative—I don’t know if it’s negative space—that human space? Anything in that thread?
SOUGWEN:
Yeah. We’ll get to some issues of human presence versus not, later on too. But one way in which I’m not interested in being machine-readable: for me, the work I’m doing is about my own learning, in a way. So I don’t want to be machine-executable—maybe that’s the right word. There are a lot of artists and projects that extend personal data into a drawing machine. We’ve seen that quite a lot; there’s a lot of art-historical precedent for it. And sometimes people think that’s what I’m interested in doing. But for me it’s really about creating the conditions of relation, and the feedback loop between human and machine. So I’m never designing or authoring myself out of the equation.
That’s been my North Star. Because—why would I want to build a system that takes away the thing I love the most from me? And I can say, to this day, I draw more than I ever have. I’ve also worked with these systems maybe a little bit longer than a lot of people. So I think there’s a world where both can exist.
REID:
Well, 2015 is definitely well before most people had realized an AI revolution was coming.
SOUGWEN:
Yeah. People were a little bit concerned when I was making this project, because it wasn’t in the dialogue at the time. It was very different—it was like real-time graphics, maybe starting to be a little bit of gaming interest. But that feedback loop has been at the center of what I’m curious about for a long time.
REID:
Well, the other aspect of this—putting the timing back in—is that LLMs, neural networks, are actually pretty bad at concepts of time.
SOUGWEN:
So true. Yes.
REID:
And so say a little bit about the temporal experience, because that’s one of the places where you say: well, what is quintessentially human—in the place between, and the expression, and the dance? Could you say a little bit about that temporal element, and what you’ve learned there?
SOUGWEN:
When I brought this idea of time—and the pause—in, was when I started working with EEG. And that was during the pandemic, because I did not want to draw anymore. It was a dark time for everyone, I think. A lot of creative people, a lot of artists, and just people in general felt quite unmoored, to say it mildly. So I really went to meditation—not as a creative outlet, but as an existential outlet, maybe. And I wanted to train a way to enhance and deepen my sense of the alpha-state threshold, which is the state you’re in when you’re in deep meditation. So I wanted to create a configuration that allowed me to do that.
So I developed the system—the Spectral system paints only when I’m at that alpha-state threshold, and it doesn’t when I’m not. Which, for the tradition of meditation, maybe is somewhat blasphemous. But I found it was a nice way of enacting a non-conscious type of control that wasn’t gestural—and control is not really the right word here, but maybe understanding proprioception. I used that to make a pause meaningful and sensible. I don’t know how it is for you, but I think creativity happens in the silence, in the imagination, and real reflection happens in the quiet and the pauses. I’m not surprised that some of these LLMs don’t really understand that—that even in that feedback loop between human and system, there needs to be a pause.
I was joking with a friend of mine today: wouldn’t it be nice to just sit in silence? There’s so much that can happen in those pregnant pauses. I really wanted to bring that back into the data set, and back into the space of drawing.
REID:
So what have you had to quantify about yourself? And what, if anything, have you deliberately held back—to protect yourself in your work?
SOUGWEN:
I try to restrict myself to movement—whether that’s my own electrical-signal movement or my gestural movement. I do so because it’s a constraint that creates a lot of adaptations that I find really interesting. I like that constraint, because I build my world through movement and line. I’m also interested in writing and speech and image, but that’s a very different thing. I love the focus of seeing what I’m made of in movement.
REID:
And is there anything you’ve begun thinking about—since you’re both a program thinker and an experienced thinker—where a language of that movement—
SOUGWEN:
I’m starting to think about what that might look like, actually. It almost feels like notation. I show the work, and the data set, as its own art piece. I’ve been converting my brainwave signals into FASTA format, like a genomic sequence. So I’m really starting to play with what that encoding looks like. I think it’s super interesting. But maybe I have too much respect for language, and maybe poetry—I like keeping almost to text. I love that inscription version of thinking about text, versus a more verbal version of it.
REID:
Yeah, I look forward to you extending that line—and drawing a line. So you have this Drawing Operations Unit: Generation series—robotic systems trained on your gestural archive, which we’ve been talking about, built to draw with you, not simply execute a command. I don’t know if you refer to it as D.O.U.G. deliberately—is it a personification? What’s with the name, and how does the name become part of that non-human gesture, along with the human gesture?
SOUGWEN:
That has really changed a lot through time. And I miss those playful days sometimes. In the beginning, I was thinking about anthropomorphization quite a lot, because I didn’t know so much about how anything really worked. I have more of a computer-science background, not a robotics background—so a lot of these kinematic levers I didn’t really understand yet. I just projected a lot onto the system. And Drawing Operations Unit: Generation 1—D.O.U.G. 1—sounds a little bit like Sougwen. It felt very cheeky, playful, weird. It brought a lot of strange dimension to the first experiment.
That was such a gift, looking back, because the work can be really serious—but there’s a playfulness to it that sometimes we don’t get to have in our everyday. We talk about these big topics: humanity and machines and the future of work. And there was a playfulness in the very beginning that I still really enjoyed—maybe a playful ignorance, because I did anthropomorphize quite a lot. And everyone joined in. We had gallery curators and museum staff being like, how’s D.O.U.G.? And I still love that it’s given another entry point to robotic development, to this dialogue, that I still really cherish.
REID:
Is there anything in this play? Because—you’re probably familiar—there are multiple theories that it’s not Homo sapiens, it’s Homo ludens: we’re playing. Is there anything in that play that has illustrated for you some aspects of humanity, and some access to machine readability and interaction?
SOUGWEN:
Sure. This particular projection has taught me a lot more about art than about developing robots, actually—because these systems are us in another form. So much of that early conception of D.O.U.G. as a discrete unit was very much my own projection. And that’s what people bring to the work as well. I feel like that’s a deeply human trait—one that comes from empathy, one that comes from imagination. So much of the work is this machinic other that’s of my design and authorship and creation, and that can be a really beautiful thing. I think that’s what art is. That’s what artists bring to their mediums. And the same can be said for robotics as well.
REID:
And so one of the beautiful expressions—and maybe I’m overusing the gesture metaphor, but I love it—
SOUGWEN:
I’m here for it.
REID:
Yes—but one of the things is, the earliest D.O.U.G. introduced some deviations. And your response was to say: no, this is poeticizing error. Say a little bit more about that. And that phrase—poeticizing error—is something I think I may plagiarize.
SOUGWEN:
Please do, please do—you heard it here first. I really do think it was such a gift, that first generation, because I don’t think I really knew what I was doing when I first started performing this interaction—this drawing with D.O.U.G.—in 2015, in a dark basement, with a quite janky robot, actually. When I think about poeticizing the error, it was a gift that came from the fact that I performed it live in one of its first iterations. And it was a gift that came from the audience—because in tech development, you don’t poeticize error. It’s always a bug, not a feature. But in that performative moment, I knew I wanted to explore something very real and gestural and responsive.
When things didn’t work according to the simulation I had on the side, people really responded to that moment, that error, with a lot of empathy, a lot of delight. And that was a really strange spectacle in the moment, as a performer, because we were all kind of hallucinating through this machinic other, in a way. But as a visual artist and as a developer, I realized that if there wasn’t error in that interaction, it would be really uninteresting—because I’d have nothing to adapt to, and the first generation would just be a mirroring of my own gestures. So without that error, that distortion—it was sort of like an artistic style of the robot at the time. It made it quite dynamic.
And that really gave me a lot of permission to develop more ambitiously and widely—because if something that’s barely working can spark all these creative ideas, for myself and for an audience, then there’s really something here that’s really potent.
REID:
And how—if you’ve given any thought to this—would you help other people generalize, using art as a lead? Whether it’s human interaction with chatbots, maybe with hallucinations—which is what labs are trying to do in alignment training. How would you say: hey, echoing forward this art, this gesture, poeticizing error—here’s a good way for people to think about how to approach their own interactions with AI?
SOUGWEN:
I think a lot of that comes from building from the ground up. There’s a lot of optimization that can happen when you use more of these proprietary, off-the-shelf tools. But when you really think from the ground up, you can think about more sustainable materials for different types of sensory development. You can think about low-cost, low-compute models. And you can have a stronger dialogue with the artistic intent. I’ve been saying lately that artists are great at breaking things—and when you break things, you separate what’s really essential from what’s necessary, and find new directions. So there’s something about building from the ground up, and working with people who think quite outside of an engineering format, which can sometimes be artists.
REID:
Oh, exactly. So if you had one afternoon with the heads of the frontier AI labs, what’s a habit or a practice from the art studio that you’d want them to try?
SOUGWEN:
I really believe in embracing uncertainty. I think there’s something much more true in not knowing what you’re doing, in a way. And: build something that’s made to be broken, and interesting at the same time.
REID:
So most AI teams optimize for capability, speed, engagement, depth of knowledge. What’s another interesting metric—from a human-machine-system, artist’s perspective? Is it more agency, more attention, more of that dynamic of mutual readability? What would you say: put these in your feedback functions?
SOUGWEN:
That’s a great question. And maybe it’s so organically coming from our conversation—thinking about reduction, thinking about pauses. When you feel, as a developer, that you can build anything, then you may not really know where you’re going. You don’t have that intention. I think there’s something about reduction, pauses, silence, that can be its own feature—its own characteristic of how we build these loops. A pause, a moment of silence, or even a reduction of functionality, in order to get the user to input differently. Because right now it feels like everything’s vast. It’s a magic machine. But there’s something really powerful and unexpected in that reduction.
REID:
Yeah. And something also—in the kind of dance—I could see is: there’s probably some pattern where it isn’t just, take a chatbot, you prompt it and it gives you an answer, like a vending machine, but it does something else that adds a little bit of variability, a little bit of difference, a little bit of a dance move into the equation.
SOUGWEN:
And sort of—what’s a low- or no-stimulation response that can initiate or instigate something really surprising in the—I don’t like the term user—the partner, or whatnot? I think it’s unexplored, because it’s not the temporal register we really exist in, in 2026. But I think it’s something we’re all craving.
REID:
Well, speaking of words—you describe your work as operational art. And not AI art.
SOUGWEN:
I do, yeah.
REID:
Say a little bit about why the naming difference is important—and what someone should see from that.
SOUGWEN:
Sure. I’ve been thinking through this—I’m building it out as I go, like I do everything. It really comes from Drawing Operations, and the ten-year journey. Knowing that it’s been this set of protocols, different types of data, different experiences, that have gone into building a much wider system, or operation, that really drives what I think of as operational art. You can thread it together—it’s a little bit like Systems Art for 2026, in that we recognize there are so many different loops that all artists and people interweave to author their work.
There’s research, with different agents; there’s drawing; there’s programming; there’s robotics. All these spheres layer onto a wider practice. So I’m still trying to figure out the language for this—thinking of operational art—but it’s one that’s meant to be inclusive of, and a rejection of, these traditional-versus-technological differences. Just thinking about it all as a series of operations.
REID:
So in Spectral, the robot is not just responding to you, but participating in the production. So it’s much more co-regulation than assistance. What is that a preview of—where we think AI systems might be going? And I think your answer is going to be both: whether we should be excited or alarmed by it. Given the earlier things, my guess is you’re going to say some version of both.
SOUGWEN:
Yeah. I love that you use the word co-regulation, because I think there’s this intertwining of these systems in our nervous system that we may not be fully aware of yet. I’m exploring that in how I link my robotic system to my EEG. There are ways in which we can co-regulate, but there are ways in which working with these feedback loops can also really disrupt. So it’s a little bit from column A, a little bit from column B. But I do think that’s the direction we’re heading, and it’s useful to be mindful of it—while also understanding that we can create configurations that deepen the experiences we want. Like meditation, and like drawing.
REID:
Well—like the alpha state for the drawing. So is there anything—some people say, oh, AI is just a tool. Is there anything you’d say: no, no, this is the important thing you need to understand, beyond just the tool?
SOUGWEN:
We’ve always, as a species, evolved through our practices and our tools. Our tools are not just tools—and that’s something artists know. A paintbrush is not just a paintbrush. It’s something we profoundly become through, and express through; we create our reality through these paintbrushes, and through these words, and through these conversations. So I see a vast horizon of possibility when it comes to breaking apart and exploring our own ways of making tools. There’s the making component, which I’m quite bullish on—because when you work with any tool, you work with someone else’s system. And I really love building my own systems and tools for expression, because that’s where all the meat of it is. That’s where all the curiosity is, for me. It’s not shifting from platform to platform because of the promise of automating certain tasks that really makes for creative excitement for me.
REID:
And one of the things—the co-regulation, when it’s a dance, when you have the joint participation—has a kind of beauty in your own work. Do you ever worry that that creates missteps in the dance? Maybe it’s just poeticizing error. And two: given that most people are going to use AI systems they’re not creating, what is the nature of that dance? People worry about whether it’s manipulation, et cetera. Any thoughts or reflections on that?
SOUGWEN:
I found it really fascinating that presenting the work through the lens of performance brings a lot of projection from other people. Sometimes people think I’m in love with the robot; sometimes people think I’m its mother. But those are all reflections that people bring onto the work. I don’t know if I think about it as a dance, really—I think of it as a gestural co-negotiation, in some ways. There’s a lot of tension in the performance of the work; there’s a lot of error in the performance of the work. And that, I think, really communicates more of what it actually is to work with some of these tools—which is: it’s not always harmony. Sometimes it’s psychosis, you know. And I think it’s good to keep that in mind—for me, in the work, it’s a way to remind myself of that. In performance, there’s a lot at stake within that frame. So part of what the work brings is that kind of reality.
REID:
What do you think is the most challenging thing people get wrong when they think about AI as just a tool?
SOUGWEN:
People think AI tools are static, but they’re not—they’re adaptive. And we’re also adapting to this tool that’s constantly changing. So it’s about understanding that process of mutual adaptation and dynamism, toward the future we want.
REID:
Awesome. I totally agree. One of the things I’ve been very curious to ask you about: you’ve said that working with AI has made you aware of the limits of the human sensorium—and that things like climate solutions may require a broader, more interconnected way of sensing than our bodies alone provide. Say more.
SOUGWEN:
I have to credit Ed Yong a little bit with this. Working with these tools, and understanding that different cameras can see in infrared—and we can’t, but so can dogs. There’s a vast sensorium that we can sense synthetically, that also exists in non-human animal species. And I think that’s a really humbling way of thinking about our own faculties, our own sensory apparatus—knowing our limitations, knowing that we only see the world in a really specific way as a species, even beyond the cultural lenses that divide us. I think that’s really humbling. It’s really exciting. But also, as a person—not even as an artist or engineer—knowing that we want to uncover and explore radically different ways of sensing and sense-making, in order to have a broader view of what it means to be in this present moment.
REID:
And so, if you were saying: here’s the way policymakers, other folks—would you have them come do a performance like the ones you do, watch a performance, do almost participatory theater, and take part? What would be the way to broaden that human sensorium toward this interconnectedness?
SOUGWEN:
It’s quite imaginative. Some of these suggestions—even thinking about the human sensorium—are incredibly meta, and I love it. And I really believe this, as an artistic practitioner: artists are also trying to pull the threads of our reality a little bit, to extend that sensorium in their own ways. This is going to sound like such a cop-out because of my position, but: really, really engage with art and artistic practice. Because I think artists are already existing on kind of a different plane—it makes artists be thought of as outliers, or divergent, or deviant, or whatever. But that way of thinking beyond what is known is very much a mandate of the practice. And engaging with that is a way to expand that a little bit.
REID:
Exactly. And one of the other things about your work is the focus on empathy and care. Obviously, with machines, people find that a little strange—because they go, well, the machine doesn’t have empathy, the machine is mechanical. What’s the surface of this, where this co-regulation helps the lens on empathy and care?
SOUGWEN:
I sometimes think it’s really about the development of the human subject, in a way. You don’t care about something only because you want to affect a change in that entity. You create these loops to enact that sense in you. And I think we need more mechanisms for enacting that empathy engine in ourselves. I genuinely believe we need more systems like that—because we have a lot of anxiety-producing engines already. There are alternatives that can be about empathy, care, awareness, expanding the sensorium. There are a lot of ways to engage.
REID:
You bring a number of different fusions together in your art. It’s not just drawing, it’s time. It’s not just human, it’s a-human—it’s a question between human and machine, and what the non-human, or human, gesture is in this. And part of it is also performance. But there are a number of different places where your practice ends up—the museum, the fair, et cetera. Is there anything in the shift of modalities where something gets lost? Where is that sense of that lost space, and what’s the thing people should pay attention to there?
SOUGWEN:
It’s really interesting, because I’m thinking through that exact question a lot, and I don’t have an answer. But how I’d frame what I’m interested in exploring is this idea of the human presence as something that is felt without the human—my presence—being there. I talk about collaboration; I talk about co-aesthetic systems, and this relational mode I’ve been building with the system. It almost demands that the person be kind of standing in my shoes, inside the loop. We’re still figuring out how to bring that into the space of installation—because I can’t be there all the time. One person, one body. But the system is built for it.
That might be the next ten years of thinking—how we can bring the human presence into the work a little bit more, that sense of time a little bit more. And there’s a type of fragility there too, because human bodies are inherently fragile. So I don’t necessarily think of it as a problem to solve—but if it is, it’s not one we’ve solved quite yet. We’re working on it.
REID:
So—if I’ve gotten this right—one of the things you’ve said is that these systems don’t possess agency in a mystical sense, but they reflect back our choices, our biases, and knowledge. Do I have that right? And how would you elaborate, or change, what I just said?
SOUGWEN:
When I started using the phrase human and machine collaboration, a very long time ago, it didn’t mean what people maybe think it means now. When people think about collaboration—you talked about mysticism—they think the implication is robotic or machinic sentience. That’s not my implication; that’s not how I’m evoking the word. For me, it’s about extended authorship. It’s much more Haraway than Hinton, if you would. It’s this idea that we are not just single authors of our own journeys—we are a collection of all that came before and all that will come. Not at the risk of sounding too poetic, but I’m a product of two parents, with these interests, of two cultures. And that’s really informed how I think of everything. So that’s how I think about collaboration, and this extension of authorship in the work.
REID:
One of the things I was particularly interested in: how does that change either your sense of agency, or how we should think about human agency?
SOUGWEN:
It links back to this idea of the human sensorium. Because our agency comes from our ability to sense the world and make sense of the world around us. Those ideas are really linked. So if we can expand our own sensorium, we can expand our sense of agency, because we have more information to work with. We’re fundamentally changing beings when we expand what we can perceive.
REID:
Awesome. So—rapid-fire section. Is there a movie, song, or book that fills you with optimism for the future?
SOUGWEN:
There’s a book by Emanuele Coccia about metamorphosis. I’m reading a lot about metamorphosis these days, because I’m doing a project on silkworms. Coccia extends metamorphosis to all creatures beyond the caterpillar, and really makes this claim—it’s almost kind of Buddhist—that we are all experiencing metamorphosis, all part of this larger metamorphic cycle. It’s really grounded in science, but also really exciting philosophy.
REID:
That doesn’t surprise me, given the human-and-machine co-regulation. And—first time I’ve ever heard of that book. I’m going to go get it.
SOUGWEN:
Yes, please. I’d love to send it to you, actually.
REID:
Awesome. What’s a question that you wish people would ask you more often?
SOUGWEN:
I wish people would ask me what happens when things go wrong. Because a lot of times people believe it’s only about the good days—only about when there’s harmony in the interaction. A lot of what the work has come from has been a sense of tension, this error state, this groundedness in the reality of co-creation, that I wish people would ask me about more.
REID:
And where do you see progress or momentum outside of your industry—let’s call that art, robotics, and AI—that inspires you?
SOUGWEN:
I’m doing a lot of research into silk proteins, and the discovery that they allow for technology to be biocompatible with the human body—which raises a lot of really interesting existential questions about where the human begins and the machine ends. There’s a layer there that we’re really uncovering. I’m also really interested in robotics and medicine. There’s a lot of really powerful work in robotic surgery that has saved a lot of lives—a really good example of allowing the specificity of robotic movement to enact human intention, which is saving lives. I thought that was really beautiful.
REID:
I completely agree. So—can you leave us with a final thought on what you think is possible to achieve if everything breaks humanity’s way in the next fifteen years? And what’s our first step to set off on that journey?
SOUGWEN:
It’s a really beautiful question. I was thinking about another piece of media that I really love—this film based on a short story by Ted Chiang called Story of Your Life—Arrival. I love that movie because in it, when Amy Adams—fellow Canadian—when her character learns the language of the aliens, it expands her conception of time, and gives her this expanded awareness and gift that she then teaches to the rest of the world. There’s something about education, and learning, and inhabiting practice, that I would love to see: learning the language of different species and technologies, that allows for a broader worldview.
REID:
That is really awesome. And by the way, I also love that work. I made a point—I was at a conference last month that Ted was at, so I made a point to go meet him.
SOUGWEN:
Oh, really? Incredible. So—is he cool?
REID:
He’s cool. Totally worth it.
SOUGWEN:
That’s very cool. I have to meet him one day as well.
REID:
Well, easy enough to facilitate. So—it’s been an honor and a pleasure. And it’s, call it, our first gesture at a conversation.
SOUGWEN:
Sounds wonderful. Looking forward to the next one. Thank you.
REID:
Possible is produced by Palette Media. It’s hosted by Aria Finger and me, Reid Hoffman. Our showrunner is Shaun Young. Possible is produced by Thanasi Dilos, Katie Sanders, Spencer Strasmore, Yimu Xiu, Aman Suri, Danny Garrison, Trent Barboza, and Tafadzwa Nemarundwe.
ARIA:
Special thanks to Surya Yalamanchili, Saida Sapieva, Ian Alas, Greg Beato, Parth Patil, and Ben Relles.
REID:
A big thanks to Natalie Stone, Tessa Nijdam, Arina Ermakova, the SCILICET team, Fellowship, Reece Straw, Sam Osborn, Nick Capezzera, Maximilian Andereya, Peter Butterworth, Haruka Wang and the team at Mosaic Ventures for hosting the conversation.
Additional Credits:
MIMICRY (Drawing Operations Unit: Generation_1), 2015. Footage: Sam Osborn and Nick Capezzera.
MEMORY (Drawing Operations Unit: Generation_2), 2017. Footage: NTT InterCommunication Center Tokyo.
COLLECTIVITY (Drawing Operations Unit: Generation_3), 2018. Footage: New INC & Nokia Bell Labs.
SPECTRALITY (Drawing Operations Unit: Generation_4), 2020. Footage: Maximilian Andereya.
ASSEMBLY (Drawing Operations Unit: Generation_5), 2022. Footage: Peter Butterworth.
GENESIS Process Film, 2023. Courtesy of the artist and Studio SCILICET.