How Should We Live With A.I.? A New Group Show Probes Our Ties With Technology

From hand-drawn QR codes that may or may not actually work to an A.I.-assisted coffee-ground reading—a new show at MASS MoCA dives into our ever-present and growing relationship with technology and artificial intelligence. “Technologies of Relation” also offers many surprising connections, insights, and fresh approaches to engagement with science and our related devices.

“We’re not just focusing on the dark side of technology,” curator Susan Cross told me. “It’s acknowledging that, but also saying: ‘Moving forward, how can we change it? How can we have agency over it and feel more familiar with it?’”

Cross emphasized the non-binary approach as we walked through the cavernous former industrial factory-turned-contemporary art venue in the Berkshires. As she noted in an essay for the show: “It was artists who raised the alarm” about A.I., before the wider public became more cognizant and engaged. “They identified the colonialist logic, racism, and violence embedded in corporate-produced technologies… Just as crucial as understanding these problems is visualizing a technological future that can be inclusive and liberatory.”

The 12 artists who contributed to the show—among them Morehshin Allahyari, Kite, Taeyoon Choi, and Lauren Lee McCarthy, among others—pose serious questions, and push back against oppressive systems that threaten our collective privacy, while also advocating for inclusion and representation.

An Invitation to Slow Down

Most of the featured works meditated on how our lives have become entwined with technology. In the case of Nairobi-based artist Neema Githere‘s , that entanglement is literal. Her large installation features two suspended hammocks stitched with phrases like: “log on” and “log off” and “data” and “healing.” It was inspired, in part, by Githere’s realization that the word for hammock, or “net” in Portuguese is “” (pronounced HEH-jee), the same word used to describe a network.

That impulse to slow down is carried over in Roopa Vasudevan‘s (2021-2022), a series of 100 hand-drawn QR, or “quick response,” codes. Some of these codes are active—directing viewers to a series of pithy, poetic “reflections”—while others simply present as designs. They almost mimic textiles, said Cross.

“I love artists for making us pay attention to these things,” she said. “I love that Roopa saw the QR code as a design. She saw that it was a machine so she wants to try to replicate it. But of course she’s adding color and she’s also adding her hand.” Indeed, many of the works reference the connection between modern day science and “ancient technologies,” such as the jacquard loom setting the stage for binary code and other tools, techniques, and engineering achievements developed by early civilizations.

And speaking of “earlier” technology, Vasudevan’s tongue-in-cheek series (2022/2026) nods to the dial-up modem days of AOL and the first internet browsers. The clear acrylic plaques that are peppered throughout the show include her tribute to MySpace as “as place for friends that gave us a place to shine.” Another reads “In Loving Memory of the Dial-Up Modem,” an homage to the device that made online connecting a “special occasion.”

Time Traveling Artists

But what of our tomorrow? A number of artists in the exhibition also looked at how technology informs our future by looking at the past.

New Zealand-born Pelanakeke Brown’s installation, (2025–26) was not the only work to reference this notion but it was certainly one of the most poignant. As an artist with a disability who is also engaged with Crip Theory (a way to explore the theory of disability, often through a queer lens), she mixes elements of her Samoan heritage—specifically tapa, a heavily treated bark paper—with her own treatment of symbols including keystrokes and mythological marks that are rendered in perfect symmetrical patterns with the aid of A.I.

Brown also references Mafuiʻe, the god of earthquakes who lives underneath the ground and is “also disabled,” since he has one arm, Cross pointed out. “Pelanakeke is really invested in finding disability stories in precolonial Samoa,” said Cross.

I also spent time with Mashinka Hakopian and Danny Snelson, who, along with Dahlia Elsayed and Andrew Demirjian, are behind one of the most thought-provoking and prominent projects in the show, (2024–26). It merges “artificial intelligence with ancestral forms of knowing,” according to the catalogue description, through the art of tasseography or “coffee reading.” Hakopian, who grew up watching her aunt perform these readings at their kitchen table, points out it’s a far earlier form of “predictive technology.”

Inside an elaborately designed kitchen space with traditional Armenian textile designs—a tribute to Hakopian’s heritage and a reminder that technology pervades even the most intimate of our domestic lives—visitors, who must sign up in advance for 10-minute slots, are invited to select an overturned coffee cup on a saucer. Participants place a thumb in the cup bottom to smudge the grounds, then place the cup under a reader and press a button which whirs to indicate the reading has begun.

The 10-minute prediction or reading process is also meant to invite slowness (deliberately chosen books of Armenian feminist poetry are provided) as well as to conserve energy. Snelson told me the small machine, which runs on CPU (as opposed to GPU) takes “1/10 the amount of power it takes to heat a cup of coffee.”

Hakopian, an associate professor in technology and social justice at ArtCenter College of Design in Pasadena, trained an A.I. on this particular method of “divination.” The training corpus included readings that Mashinka previously conducted in Glendale, where the artists reside. “So nothing that you find in this project is being live-generated,” Hakopian said. “There is no text being written by an algorithm. It’s very intentional on our part, we didn’t want to cede or surrender authorship future to an algorithmic agent.”

Another intentional feature that Hakopian included is the output of the prediction in both Armenian and English, a pushback against A.I. models that heavily favor English.

“I knew from the very start we wanted a multilingual model of A.I. and what I discovered is that there were no rich base models in Armenian… which speaks to the questions of whose languages are algorithms.”