Generation to Generation: Conversing with Kindred Technologies, Nathaniel Stern

Interview with  artist Nathaniel Stern about his collaborative exhibition titled Generation to Generation: Conversing with Kindred Technologies. By Selva Ozelli Esq, CPA, Author of Sustainably Investing in Digital Assets Globally

The Museum of Art + Light (MoA+L) presents Generation to Generation: Conversing with Kindred Technologies, a traveling exhibition by artists Nathaniel Stern and Sasha Stiles, from September 4, 2026, through February 14, 2027, in the museum’s De Coded Digital Gallery.  The exhibition approaches artificial intelligence (AI) as more than a recent invention or isolated digital tool. Stern and Stiles place AI within a much longer history of human beings developing systems to extend thought, language, memory, labor, and imagination. Their work examines the reciprocal nature of that relationship: people shape technology through their language, values, biases, and decisions, while technology, in turn, influences how people create, communicate, and understand the world.

Insights with Nathaniel Stern

Stern is an artist, writer, educator, and researcher whose work connects art, technology, engineering, embodiment, and environmental concerns.

Tell us about your journey to become an artist and your interest in Artificial Intelligence and how it interacts with art.

Both my parents were English teachers; my father is a poet. Naturally, I rebelled by attending an engineering high school.

After a serious car accident at seventeen, performance, writing, and art helped me find my way back into the world. I studied fashion and music, then discovered Photoshop in 1997 and became obsessed with combining code, engineering, performance, and poetry.

I wound up doing a graduate degree in art and technology at NYU, followed by six years making digital art in South Africa. That period profoundly influenced my personal and embodied approach to computing. I then completed a PhD at Trinity College Dublin, supervised in Electronic and Electrical Engineering by Linda Doyle, now Trinity’s Provost. Across more than 25 years, my work has explored how humans and technologies co-evolve: how we shape our tools, and how they shape us in return.

AI is the latest chapter in that same story: using technology not to replace human expression, but to unsettle and expand it.

How did you come up with the idea for your collaborative traveling exhibition titled “Generation to Generation: Conversing with Kindred Technologies”?

Sasha and I met online during the pandemic and began chatting because of a mutual respect for each other’s work. The original collaboration came out of those conversations, leading to online poetry and code, and eventually embodied interaction.  We saw a big question emerging: what might future generations want us to understand about the technologies we are building now? We wanted to bring this into a physical space and kept going from there.

Where else has your exhibition been shown and will be shown in the future?

It premiered at Krasl Art Center in St Joseph, Michigan, in 2025, then travelled to Milwaukee’s Kenilworth Gallery in February 2026. The Museum of Art + Light run is through February 2027. After that, we shall see! We are open to more full exhibitions, or to showing elements from it in group exhibitions or in smaller spaces.

Generation to Generation : Conversing with Kindred Technologies brings together across 6 installations hybrid sculpture, prints, poetry, artists’ books, sound, movement, haptic experiences, discarded electronics, and recovered metals. Each installation gives physical or interactive form to a poem co-created by Stiles and her AI alter ego, Technelegy and Stern’s, poetic dialogue that runs throughout the exhibition. The works emerge from an ongoing exchange between human intention and artificial intelligence, asking visitors not only what technology can produce, but also what people transmit through the technologies they create. Tell us about your artistic dialog in these six installations that explore the evolving relationship between art, technology, and human experience.

Oh, we have had so many conversations, and our goal is to inspire more! We hope to complicate relationships with AI and technology and bring the stakes of those relationships into the room. Each piece is a poem made material: electronic waste becomes memory; recovered metal carries ecological weight; bodies write with machines; speech, image, and typography mutate across generations.

For our Neural Network Font Type (also playfully called our Feral Font), we trained diffusion models on 30 public-domain examples of each alphanumeral. It generated a strange, child-like typeface that feels hand drawn. Visitors are invited to practice with it, completing the journey from human hand, through machine, and back to human hand.

For Weighing (Mother Computer), our poetic exchange became a concrete poem, hand-forged from metals recovered from discarded technologies. Its language emerged through computation, but its weight—ecological, historical, physical—is unmistakably real.

Here, AI is not a window and a prompt; it is earth and metal, heat and work. The inputs are historical and deliberately chosen; the outputs are curated and materially transformed by us. Everything is opened up and made to be felt in the space itself.

Did you use any AI to create any of the pieces of this work?  And to what extent?

AI is present throughout, but nothing was “made entirely by AI.” We used language models, machine learning, generative systems, and custom software alongside writing, editing, coding, forging, printing, composing, fabrication, and performance. AI is one participant in a much larger studio ecology.

With your work you place AI within a much longer history of human beings developing systems to extend thought, language, memory, labor, and imagination by examining the reciprocal nature of that relationship: people shape technology through their language, values, biases, and decisions, while technology, in turn, influences how people create, communicate, and understand the world.  Tell us more about this.

Tools are not something on the outside. We make them from our language, labor, politics, materials, and desires, and in turn they reorganize how we think, communicate, and act. Humans and technologies do not merely interact. They co-evolve. Fire, speech, carrier bags; desktops, social media, AI. For better or worse. This calls for accountability across the tools we produce, how we use them, where we regulate them, with what power, and more.

How do inherited language and cultural memory influence what AI generates?

AI generates from cultural inheritance: archives, clichés, prejudices, metaphors, omissions, and acts of imagination. But what gets counted as data? And what gets left out? Whose language is preserved, digitized, and amplified, and whose is absent or illegible to the machine?

Researchers, artists, archivists, and communities are working to address these gaps through more representative datasets, local and Indigenous language models, careful documentation, and new forms of cultural stewardship. AI can amplify what a culture remembers, but also reveal what it has forgotten, or chosen not to see.

Can emerging technologies deepen human connection and creative possibility rather than diminish them?

Absolutely. This is why we use language as our core example. The spoken word enabled richer communication and connection between people. The written word extended that communication across time and distance, and the printing press brought it to a mass scale. AI brings much of that history to our fingertips. And examples of “good” and “bad” uses of each can be seen daily. A technology’s possibilities depend upon how we design it, use it, regulate it, and relate through it. Curiosity and responsibility, wonder and criticality, must develop alongside capability.

How might people build relationships with technology founded on curiosity, reciprocity, and care?

Begin by treating technology as neither magic nor an enemy. Ask where it came from, whose labor and values it carries, what it asks of the world, and what relationships it makes possible.

I think through three scales. First, the intimate: how do I use AI every day, and how might I do so with greater care? Second, the systemic: what laws, research, and energy policies should shape it, and how can I promote these? Third, the imaginative: what can I make, think, or do now that I could not before?

Care means attending to all three.

Text to image tools use massive amounts of energy.  Most of that energy comes from coal and gas which create global warming impacts including melting ice, wild fires, torrential rain storms etc.  This high energy cost creates a major problem for the earth as AI use grows.  What are your thoughts in regard to this while creating your art piece?

First, we did not use any text-to-image tools for this exhibition. We are both climate activists and pay close attention to energy use in our practices. And the show’s only diffusion model (image-to-image) was used for our alphabet; we trained it ourselves on “small data,” just 30 images per model.

The larger energy question is real and deeply concerning. Machine learning continues a much broader trajectory of rising energy consumption, from streaming video and AI to shipping and transport. We need rapid investment in both nuclear and renewable energy, greater transparency and accountability from AI companies, and meaningful liability when these systems cause harm, intentionally or otherwise.

That is precisely the kind of conversation we hope the exhibition encourages: moving beyond simple good-or-bad binaries, acknowledging complexity, and working towards actual solutions.

Under US law text-to-image AI creations generated entirely by a machine without human expressive input do not receive copyright protection. The U.S. Copyright Office and federal courts maintain a strict human authorship requirement, meaning raw outputs from prompts fall directly into the public domain.  What are your thoughts in regard to this and its impact on AI generated art?

US copyright law makes an important distinction: purely machine-generated material is not protected, while human selection, arrangement, editing, and transformation may be. The best of AI-assisted art still involves substantial human authorship, and collaboration with a machine does not erase the artist. Honestly, the debates are very similar to those around the time of photography’s emergence. The boundary between us and our tools, between technology’s “work” and ours, is always a question.

On the other hand, copyright promises a balance between protection and creative remixing. But in practice, those who can afford lawyers on retainer often enjoy far more freedom than those whose work is being remixed. We need rules that protect artists’ livelihoods without closing down experimentation, collaboration, and cultural exchange.

Taking this further still, I don’t believe copyright alone is the best fit for the current debates. We need something akin to “derivation rights”: enforceable consent, credit, and compensation when artists’ work materially shapes commercial systems or outputs. Artists should be able to opt out of training; datasets should be transparent and auditable; and AI could itself help build provenance systems that identify the works and visual traditions contributing to what it produces. Collective licensing and affordable dispute mechanisms would protect artists better than requiring each individual to battle a corporation.

Anything else you would like to add

Think of Generation to Generation as a series of questions, and concepts and materials to think with around them. It does not ask visitors to be pro- or anti-AI, but to spend time with these systems. To move, listen, touch, read, and wonder, as well as criticize, before deciding what our relationships with them could and should become. We hope people leave with still better questions, and a stronger sense that they have agency in answering them.

How can people reach you?

Dr. Nathaniel Stern

Director of Research, College of Arts and Architecture

Director of Academic Engagement & Creative Impact, Lubar Entrepreneurship Center

Professor of Art and Design / Mechanical Engineering

University of Wisconsin-Milwaukee

https://nathanielstern.art/

See more breaking stories and interviews here.