The machine does not need to be divine to occupy a godlike position. Machines have become our favorite performers of certainty. Before prediction became computational, people turned to one another and to systems of divination to make uncertainty feel interpretable. The tools we use to navigate uncertainty have changed but the impulse has not. We invent new ways to make uncertainty feel measurable.
I had the pleasure of speaking with Jane Lu recently about the systems humans have established to predict what comes next, from older, ancient divination practices, to contemporary computational models that seep in to organize everyday life. The distance between these systems is small. Both begin with the desire to read the present and create comfort around the future¹.
Jane Lu is a Los Angeles–based multidisciplinary designer, researcher, and prototype builder. She studied graphic design at California College of the Arts before moving into Media Design Practices at ArtCenter, and her work has increasingly occupied the space between old systems of knowledge and new forms of computation. Divination, biometric data, ecological sensing, physical interfaces, AI.
Her latest work, Moled to Gold, stems from 痣相, a Chinese tradition of reading moles on the face and body for clues about personality and fate². In Lu’s work, a participant places a rhinestone mole somewhere on their own face. A computational system reads that placement and generates a fortune.
The setup is playful, but its premise is familiar. We have never stopped looking at bodies for information about how to speculate the future. Lu came to this partly through previous commercial work involving the biometric data market. “We haven’t really stopped reading the body as a predictive surface,” she told me. “We’ve just developed different ways of extracting from it.”
Ancient mole readers contemplate birth marks on the face; in contrast, a machine converts the face itself into measurable data. Both begin with the belief that something visible can help us reason with, or predict something invisible. The machinery around prediction evolved, yet our appetite for abstracting the unknown is important to note as something that remains consistent across ages. Lu calls both ancient and contemporary predictive systems “technologies of their time.” Part of what interests her is interrogating the legitimacy we assign to each. The phrase she uses for this is “evil fun”. There is irony in placing an ancient divination practice beside machine learning and asking which one has earned the authority to tell us who we are.
“To predict is to read,” Lu says, “and to read is, in some sense, to prepare.”
Lu has become particularly interested in this version of soft control. It is not imposed from machinery or an unknown source, sometimes we do it to ourselves. That is also why she resists treating soft control in technologies and abstraction models as something sinister. Prediction can make us feel prepared. The more interesting threshold for Lu is the point where preparation becomes an inability to tolerate not knowing.
Moled to Gold plays with this anxiety while giving the participant an unusual degree of control over the exchange that we don’t often see in automation. You enter the encounter with the piece with knowledge that your face will be read, receive the prediction you asked for, then your fortune and its accompanying data disappears. Lu was deliberate in the ephemerality of this encounter. The participant’s face is not stored or accumulated into a dataset after the reading. “You can offer yourself to the machine for a moment without becoming its property,” she says.
It is a small decision in the design of the work, but helps change the relationship to our idea of being digitally optimized and captured. Most digital systems are built around the opposite assumption; information should remain accessible after the original interaction ends. An image can become training data, an opt-in click can become an advertising profile to be sold, even location may contribute to popularity heatmaps and patterns. The value of data frequently outlives the moment in which we opted into something.
In Lu’s work, there is a boundary around what the exchange is able to become. Of course, this kind of selective legibility is much easier to construct inside an artwork. Meaningful consent assumes that we understand the choice being offered, and are able to refuse it. In daily digital life, refusal means losing access or making navigating different platforms harder for yourself. Moled to Gold gives the participant an artificial version of the agency that contemporary platforms increasingly make difficult. At some point, “opt in” stops describing a decision and instead becomes the benchmark for how we gain accessibility and information³.
Her earlier work Osmosis of Touch approaches extraction differently by working with ecological systems, Lu noticed how easily the logic she had encountered through biometric data intersects with bodies, land, information, and resources. This point is where her work enters Ctrl+Save, Kive Studio’s upcoming group exhibition on systems of control and the possibility of navigating them with greater awareness. Across the exhibition, technologies and institutional structures that tend to remain invisible are made legible through artworks visitors can co-author, multiple floors to navigate freely, and seminars which invite participation from the collective and the institution itself. In both Lu’s work, and the larger exhibition, people are asked whether perceiving systems of control give them any room to renegotiate them.
Artists like Jane situate machines, bodies, and ecologies within a larger entangled network. Folding older forms of divination into contemporary prediction models articulate the recurring human impulse to navigate the discomfort of uncertainty by placing interpretation elsewhere, once in the hands of the divine and now in that of the machine.
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Conducted & Written by Isabel Lotus
All images, diagrams, and renderings courtesy of Jane Lu.
Explore Jane's work: janeludesign.work
Follow her Instagram: @jianhan.design