The Brooklyn Rail

These days, automation conjures images of algorithms, artificial intelligence, and invisible systems making decisions on our behalf. We imagine computation rather than machinery. But automation is not really about machines. It’s about movement. The machine itself is often invisible; what gives it away is its choreography—the pauses, handoffs, hesitations, and oddly graceful motions through which code becomes action. We recognize automation not by inspecting code or peering inside black boxes, but by noticing the distinctive ways things move and interact. That’s style. A brushstroke can reveal an artist’s hand, a building’s ornament can signal a historical period, and a composition can betray its cultural origins. 

Style matters to art history because it provides a way of recognizing underlying processes through their visible effects. Art historians have long used style to identify artists, trace influences, date objects, and understand how cultural values become embedded in form. Far from being mere decoration, style is evidence—a record of how something was made, by whom, and under what conditions. In an age of automation and AI, that skill becomes newly relevant.

—Charlotte Kent

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We live in a world subsumed by automation—machines that manufacture, package, ship, and deliver our goods; software, algorithms, and artificial intelligence that order our consumption of information. Automation is not static. It is not a gadget or a thing. Its medium is movement: the handing off of things and data from one point to the next in a series of consecutive interventions. To recognize automation, then, is not a question of whether something looks a certain way, but whether it moves a certain way.

In the physical world, automation makes itself manifest just below our perception through styles of movement: it is an aesthetics of pauses and paces; the time it takes for a sensor to reset or a vehicle to advance on a track, the forceful and jerky movements of brakes, the pregnant pauses of computers double-checking their actions. To understand automation, we must learn to perceive the logic of sensors, relays, and computers in the noise—this is a question of style.

Of all places, this lesson was impressed upon me while watching the illusionist Criss Angel’s MINDFREAK show in late 2021. As the world opened after the pandemic, I found myself in a desolate Las Vegas in a desperate attempt to escape my apartment. Despite not being one for magic shows, I was mesmerized by the television magician’s well-known levitation stunt that ends his show. Intrigued by the mechanics of the spectacle, I found few answers in looking for wires or other clues to its manufacture.

Confronting my frustration, I told myself that rather than trying to see something concrete, I should instead look at the style of the movement. Then, I began to see something completely radical: how he floated slowly to avoid any pendulous sways; how fluid motion united with precision stops, handed-off turns, and a speedy fluidity synonymous with machines. I could not see the technology, but I could recognize the style of something deeply familiar.

Letting my gaze float across his movements, I suddenly recognized the aesthetics of automation: the invisible logic of a machine, procedurally undertaking a series of liquid actions. I could not see the machine or its wires, but I didn’t need to. Its style of movement undeniably indexed the existence of an overhead conveyor, programmed with accuracy and precision.

The automation was the magic. People are enchanted by the spectacle of machines and their precise and procedural movements that always result in some uncanny fusion of smoothness and stiltedness, a fluid yet syncopated movement. There is a reason why magic and automation have been so deeply intertwined since the term burst upon the scene in the early 1950s—from the mid-century amusement park to a contemporary Las Vegas magician. To this day, we are entranced by the uncanny movement of machines, whose faultless fluidity and grace startle us with their inhuman elegance.

At Mercer Labs in New York City, self-described as the museum of art and technology, Volvox Labs’s The Beach (2024) is a robotic “arm” that traces patterns in the sand while miming movements that can be projected as emotional and responsive to some psychic state. Viewers are entranced by this industrial machine, sitting in a darkened room, observing its movements behind a glass wall as if some animal at a zoo. The movements are speedy and brash, starting and stopping with meticulous precision. Repeatedly, the machine demonstrates its millimetric control in its positions and the sheer brutal force of its power. Watching it is a masterclass in the aesthetics of automation—of how machines move.

By stripping the machine of its functionality and transforming it into a medium of aesthetic contemplation, the work hypnotically lays bare the machine’s style of movement, cultivating a visual language of recognition and articulation. This KUKA arm is the same industrial robot that screws bolts, solders metal, paints, and undertakes a whole host of other actions in our factories and warehouses. But, in the past decades, they have also become a source of entertainment, precisely because of the kinesthetic experiences they offer. For instance, the same technology produces the magic of flight in Universal Studio’s amusement park ride for Harry Potter and the Forbidden Journey (opened in 2010).

Other applications in the art world have sought to generate a sense of sympathy for these anthropomorphized machines. In Sun Yuan and Peng Yu’s Can’t Help Myself (2016) at the Guggenheim Museum, the same manufacturing arm swept up a red, blood-like fluid issuing from its core amidst dance-like movements. The human-like, life-likeness of this latter work generated a sense of compassion for the Sisyphean labor of the machine, drawing a deep empathic parallel to the monotonous and repetitive movements of humans working under automated systems. There are limits to the efficacy of empathy, but if these works have any true political action, it comes from the aesthetic contemplation of machines that are purposely concealed from our gaze in factories and behind the scenes of amusement parks.

Removed from the domain of the machine alone, artists have recognized the dance-like poetics of automated movement. In Revital Cohen and Tuur Van Balen’s 75 Watt (2013), workers at the White Horse Electric Factory in Zhongshan, China engage in a choreographed mimicry of the assembly line, inspired by the indication that humans can sustain a seventy-five watt output over the course of an eight-hour workday. As stated by the artists, “In 75 Watt, a product is designed to be made in China. The object’s only function is to choreograph a dance performed by the labourers manufacturing it.” At once, the piece translates human labor into dance, while also alluding to the dance-like choreographies of machines, robotic arms, and materials. In Cao Fei’s Whose Utopia (2006), these ideas are inverted whereby dancers in a Chinese factory interrupt their mechanized labor through dance breaks that capture their individualism against the monotony of the factory.

Transforming automation’s movements to embodied choreographies confronts us with how our privileged world is built on the graces of workers who must dance as machines. Through the anthropomorphizing of industrial machinery, artists embrace ideas like choreography and dance as monikers to articulate what is most vividly present in automation: the stylized movement.

Now, having meandered through factories, labs, exhibition spaces, and such, let us try a little thought experiment:

Imagine you are a robot.

Go ahead, do it. What’s it like?

Imagine you are a robot.

Did your spine straighten, did your shoulders go back, did your arms lock at ninety degrees? Now, move, like a robot. Did your head cock to the side as you stiffly turned, trying not to move your neck while your arms moved angularly?

Now, imagine that you are a slightly more advanced animatronic, like the ones you might see at the Hall of Presidents at Walt Disney World. Better than Rosie from The Jetsons, but not as good as the Terminator.

Did your arms move in and out in graceful gesticulations, repeating in various pre-determined loops? Your movements were probably somewhat stiff but desperately trying to show off their natural eloquence.

Finally, imagine that you are the latest, most advanced animatronic on the market. (Think: the Na’vi River Journey animatronic at Disney’s Animal Kingdom or one of those Boston Dynamics dancing robots)

What changed? Perhaps your arms moved grandiosely in hyper-fluid gestures. You probably are moving a little too much, and in ways that feel somewhat unnatural as you try to show-off how real you seem.

In each of these cases, you performed a certain style of movement. In none of these cases were you ever inclined to just move like yourself, no matter how advanced that machine might become. There’s an aesthetics of movement that automation has taught us across the past century.

No matter how new, how high-tech, or how advanced of a robot you might try to be, there is still something distinctly mechanical in one’s gait. These movements are so distinct that one TikToker has a whole account dedicated to acting like different animatronics across various theme parks. The popularity of his posts is not because they are ridiculous, but because these characters are instantly recognizable by how they move. In each case, the machine has a particular aesthetic.

This little thought experiment performed some of the major transitions in animatronics across the twentieth century: starting from a simple cam-and-level system, where a rotating disc with incision cued up a series of predetermined actions and movement. Then, we moved on to the era of pneumatic and hydraulic animatronics, which used electrical impulses recorded as sound on magnetic tape to synchronize a series of dedicated actions. This brought about greater complexity, while still limited by a certain number and forms of movement. And, finally, we come to the present where electrical actuators of an increasingly small size allow for fluid and precise movements that can sinuously curve and undulate a body. It is the most hyperreal form of movement—one that exceeds the rather motionless stances and twitches of ordinary people that lack this level of finesse.

Each of these movements has its own style, one associated with its technology and programming system, as well as with contemporaneous ideas of what constitutes life-like motion. This all might seem trivial, but there is a lesson here about the aesthetics of automation—not just in an amusement park but in our world. It is a lesson about how we use stylistic judgments to recognize and define systems of automation and even the underlying principles that govern them.

Style is a squishy concept. Even as an art historian, style is a dinosaur—a much maligned and antiquated concept by which connoisseurs would attribute paintings to an artist’s hand or date a work to a certain time and place. These assessments were often based on little else than a subjective list of formal associations and a feeling—by experts, of course, but a feeling, nonetheless.

Style is not a perfect system. But, as has been pointed out, even when we make the judgement that something is human made rather than a mere rock or an unworked piece of matter, we are making a stylistic judgment about our world. We make stylistic judgments constantly without knowing it: deciding whether something is new or old, recognizing different houses on a street block, or distinguishing between the real and the fake.

In the era of generative AI, style isn’t just about referencing prior artists or an art movement’s design qualities, but is becoming critical to how we judge the veracity of the world around us. AI texts have that eloquent nothingness with punchy, contentless statements. AI images have that bulbous, smoothed-out sheen that makes them look a bit like an off-brand Pixar cartoon. AI videos share similar characteristics, but even in the most realistic videos, shadows and light bear their own signature handling. How people move, how they walk in these videos is often a dead giveaway because once again movement has a distinct style. We already notice these signatures instinctively, but what we continue to lack is the vocabulary to describe what we are seeing.

In this capacity, art history has a critical role to play in mediating our relationship to automation and artificial intelligence. Art history teaches us how to see and think about processes that might easily elude our recognition or slip by unnoticed. It provides us with terms and vocabulary through which to express our thoughts and observations about the vicissitudes of style. In a moment where so much of the workings of technology are invisible to us (or the product of black box systems), art historical looking provides us a way of dragging back onto the surface all the logics that have been sublimated under our view.

When we cannot see the wires, the tech, the code, the black box’s workings, do not despair—just observe the movements of data and things. And remember: style is the answer to everything.