From AI Art to Housing Justice

How I Write About Emerging Technology Through Stories

What follows is the verbatim text of the talk I delivered live at Medium Day 2026.

Hello, everyone. I'm Amelia Winger-Bearskin. I'm an artist, technologist, writer, and professor of Film and Media Studies at Hunter College in New York City. I'm also an enrolled member of the Seneca-Cayuga Nation of Oklahoma.

Today I want to talk about how I write about AI and emerging technologies through stories.

This is a fitting place for me to think about that question. Years ago, I wrote a series for Medium called Aesthetics of AI. I was thinking about how artists encounter artificial intelligence and what our ways of seeing might add to a conversation that was largely being shaped by the technology industry.

Since then, the technology has changed. The conversation has changed. My work has changed.

But I still begin in the same place.

I like to learn what matters to someone.

What matters to a person gives away their vantage point. It tells me where they are standing, what they can see from there, what they are protecting, and perhaps what they are unable to see yet.

If I disclose what matters to me, I can invite you to walk with me through my mind's eye.

That is often how I begin writing.

I begin with something I think I understand. I take it apart. I try to describe how I believe it works. Then I go about trying to prove myself wrong.

This is also how I approach technology.

I can learn everything I possibly can about a computer system, an artificial intelligence model, or a Homeless Management Information System. I can study the data fields, the interfaces, the rules, and the assumptions embedded in its design.

Eventually, I will brush against a wider field of expertise.

Then another.

I will encounter an entirely different way of measuring the world. I will meet people whose knowledge comes from direct experience, institutional memory, family history, professional training, cultural practice, or simply paying attention for a very long time.

In those moments, I can feel profoundly connected to a universal human experience.

I can also realize that someone with whom I have so much in common is living through a situation I have never experienced and may never experience.

That encounter changes the writing.

It should change the writing.

Curiosity Is Only the Beginning

Curiosity is a wonderful place to begin, but curiosity by itself does not connect us to an audience.

People have written many excellent lists of communication tips. I teach some of them to my students every week. Know your audience. Make a clear argument. Use concrete examples. Avoid jargon. Tell people why the subject matters.

All of that is useful.

But the way I connect my curiosity to other people is by listening to how they are already speaking.

I hope my tone changes slightly every time I move to a new city, make a new friend, or learn a new language.

The people around me, the cadence of their conversations, and the shape of their jokes give me a rhythm through which I can sing to an audience.

If I stop having conversations, I lose that rhythm.

If I stop listening to many voices, my thoughts remain abstract. I lose my ability to carry those thoughts into the vernacular of the moment.

Living in New York City makes this exceedingly easy.

The city is generous with linguistic gems.

You can hear a complete philosophy of life while waiting for the G train. You can hear a perfect description of power while standing in line for coffee. You can learn how an institution actually works by listening to the people smoking outside of it.

I listen while walking through familiar cities and unfamiliar ones. I listen in crowded parks. I listen on airplanes. I listen to students speaking before class officially begins.

I listen for the phrase that contains an entire system.

That is vernacular intelligence.

In a recent interview with The Creative Independent, I described vernacular intelligence as the knowledge that lives outside official systems. It lives with subway performers, DJs, graffiti writers, mutual-aid networks, aunties, organizers, and the people who know how a city actually works.

This intelligence is especially important in an AI-powered world.

AI systems are built to identify patterns. But a pattern is never the full meaning of a situation.

A system might tell us how often something occurs. A person can tell us what it feels like when it does.

A database might show that someone disappeared from a program. A community member may know where they went, why they left, what frightened them, and what might make it possible for them to return.

The official system and the vernacular world are describing the same city from different vantage points.

Writing can bring those vantage points into conversation.

Technology Arrived Broken

A few days ago, someone asked me about growing up between an inventor father and a storyteller mother.

My father brought home broken things from the lab. They were things people were throwing away. A train set. Electronics. Photographic equipment. Synthesizers with missing or damaged parts.

We repaired things together.

Because technology entered my life in a state of disrepair, I never learned to be afraid of it. I also never learned to believe it was complete.

Technology always needed help.

A screen might be broken, but perhaps we could interface with the machine another way. A device might no longer perform its intended function, but perhaps it could become something else.

Technology needed human imagination to find its way back into the world.

My mother was a storyteller. Her work involved gathering stories and understanding where each story came from. A story might belong to this side of a river because this side could see a particular vista. Context was part of the story. Relationships were part of the story. The responsibility of carrying it was part of the story.

Those two inheritances meet in my work.

I take the machine apart to understand how it works.

I follow the story to understand where it belongs.

This is how I write about AI.

I want to understand the mechanics of the technology, down to the smallest point I can reach. I also want to understand the creation story we are using to explain it.

Who appears in that story?

Who is missing?

Who is the hero?

Who is expected to be saved?

Who is cast as inevitable damage?

AI's Creation Story Is Unfinished

In technology, we often speak in a strangely confident future tense.

A product is announced as if the future it promises has already arrived.

This will transform education.

This will revolutionize health care.

This will make organizations more efficient.

This will solve homelessness.

This will change everything.

People outside the technology industry may not realize how aspirational this language is. People inside the industry sometimes forget, too.

A demonstration is presented as a functioning system. A functioning system is presented as a solution. A solution is described as inevitable.

But the creation story of AI is unfinished.

An engineer's story about AI is one version.

A company's story is another.

A writer, artist, teacher, social worker, organizer, or person navigating a public benefits system might tell a completely different story.

Each person is encountering the technology from a particular vantage point.

The language of inevitability tries to erase those vantage points. It suggests that the technology simply arrived and that our task is to adjust ourselves around it.

But emerging technologies are emerging.

They are unfinished.

They can still be challenged, shaped, refused, repaired, misused, and reimagined.

That unfinishedness is where writers belong.

Our role is not simply to report what a technology claims it will become. We can investigate the gap between the claim and the lived experience.

We can ask what kind of world must exist for the promise to come true.

We can ask who will perform the hidden labor.

We can ask what the system needs to know about us.

We can ask what happens to the people who do not fit its categories.

We can ask what values have already been woven into its design.

Most importantly, we can ask what values we want to weave into it now.

Stories Are a Form of Technology

I often say that stories are among our oldest technologies.

A story can preserve knowledge. It can carry instructions across generations. It can warn us about danger. It can encode relationships, responsibilities, agreements, and ways of understanding the world.

My project Wampum Codes began with a question about whether ethical values could be carried inside software.

Wampum belts are sometimes displayed in museums as decorative objects. But wampum can record agreements and collective decisions. The belt and the person carrying its meaning work together. It is a material record held within a living practice of interpretation and accountability.

With Wampum Codes, I began asking: What if software worked that way? What if ethics were woven into technology from the beginning?

What if people building a system had to name the values they believed they shared?

What if those values traveled with the code?

What if we treated technology as an agreement for which someone remained accountable?

When I brought these questions into rooms with developers, I discovered that many had been taught to think of ethics as someone else's job.

Artists rarely have this hesitation.

Ask an artist about the ethical stakes of their work and you are likely to receive a complicated answer. Artists are accustomed to locating themselves within the work. We are expected to think about history, power, material, interpretation, and consequence.

Developers are often trained to complete a task whose values have already been established elsewhere.

But the people building a system make ethical decisions constantly.

Which mistake is considered acceptable?

Who gets to appeal a decision?

Who is visible?

Writing about technology means making these decisions visible.

Learning Through Play

There is another part of my practice that may sound less serious.

I play.

I believe play is one of our most rigorous methods for understanding technology.

When my students encounter a new coding language, software platform, or piece of hardware, I tell them to capture their first three hours with it.

During those first hours, they have not learned the correct way to use the tool. They may misunderstand what it wants. They may ask it to do something no experienced user would attempt.

Those misunderstandings can be extraordinarily generative.

The first encounter with a technology is a little like falling in love. Those initial imprints can shape how you understand the relationship from then on.

I use tools according to their intended purpose, and I also use them incorrectly.

In my artwork I WOULD LIKE TO BE MIDNIGHT / I WOULD LIKE TO BE SKY, I used AI inpainting to remove human architecture from landscape footage.

Inpainting is generally described as a process of restoration. A section of an image is missing or damaged, and the system generates material to restore it.

But what counts as restoration?

In my film, restoration meant removing power lines, buildings, and other architecture. It meant allowing the land to breathe.

I removed these structures from every third frame, so they did not disappear cleanly. They flickered. The human-built world became unstable.

The mechanics of the technology became a metaphor inside the work.

The algorithm was part of the message.

This is something writers can do, too.

Before writing about what a tool supposedly does, play with it long enough to discover its logic.

Notice what it assumes.

Notice what it refuses.

Notice when it becomes confused.

Notice what it considers a mistake.

Notice what it tries to complete on your behalf.

Then ask yourself whether the tool's mechanics resemble anything else in the world.

A classification system may remind you of a border.

A confidence score may remind you of someone pretending to be certain because uncertainty is not rewarded.

A missing-data field may remind you of a person who could not safely answer the question.

This is where a technical mechanism begins to become a story.

From AI Art to Housing Justice

For many years, I worked with AI through art, storytelling, climate justice, and Indigenous approaches to technology.

That work eventually led me toward housing loss.

I am now working with researchers, technologists, housing organizations, and communities to understand how AI and data systems might help identify housing instability earlier, improve access to services, and support efforts to make homelessness rare and brief.

The technical systems involved are complicated.

Homeless Management Information Systems collect information about people receiving homelessness services. Cities and organizations use this data to coordinate care, measure outcomes, and make decisions.

AI might help people recognize patterns across those systems. It might reduce administrative labor. It might help identify a person at risk of losing housing before they enter a shelter.

Every one of those possibilities contains an ethical problem.

Who decides what risk looks like?

What happens when a prediction is wrong?

What information must a person surrender to receive help?

Does the system direct resources toward people, or does it simply direct surveillance toward them?

Can an automated tool distinguish between a person who needs assistance and a person whom an institution has decided to manage?

The closer I look, the less this resembles a purely technical question.

It is a question about what we believe people deserve.

It is a question about whose knowledge counts.

It is a question about whether we see homelessness as an unavoidable fact of modern life or as the result of decisions that can be changed.

I often describe housing justice as an imagination problem.

Ending homelessness is possible. But first, we have to stop treating housing loss as inevitable.

Art, data, storytelling, and collective design can help us rehearse a different future.

I have also been thinking about homelessness as the opposite of belonging to the land.

My work has long been about belonging to the land, rather than the land belonging to us.

To belong to the land is to be held within relationships. It is to have responsibilities and connections. It is to know that your presence has meaning.

Housing loss is produced by a deeply broken system that severs those relationships and then treats the severing as a personal failure.

When I write about AI and homelessness, I need the technical language. I need to understand models, systems, databases, measurements, and administrative processes.

But technical language alone cannot tell us what home means.

For that, I have to listen.

Writing as an Invitation

So, how do I write about AI and emerging technology through stories?

I begin with my vantage point.

I tell you what matters to me so you know where I am standing.

I take the technology apart.

I learn its mechanics because I want to understand the metaphors already living inside it.

I try to prove myself wrong.

I look for expertise wider than my own.

I listen for vernacular intelligence, especially the knowledge that institutions have failed to record.

I play with the technology before its intended use becomes fixed in my imagination.

I ask who is present in its creation story and who has been left outside it.

I resist the future tense of inevitability.

I look for the values woven into the system.

And then I ask the most important question I know:

Does this help humans thrive?

Human thriving sounds abstract until we ask people what it means to them.

It might mean having a door that locks.

It might mean remaining in the neighborhood where your children attend school.

It might mean being able to care for an elder.

It might mean making art.

Writing about technology is a way of translating between systems and lived experience.

Writers can become interpreters of the spaces between them.

We can say: I see a connection here that has not yet been named.

I see how this design decision becomes an outcome in someone's life.

I see the story this technology is telling about the future.

And I can imagine another one.

The story of AI is unfinished.

That means we are still inside its creation story.

We still have time to ask what matters.

We still have time to listen.

We still have time to change the ending.

Thank you.

This was my talk for Medium Day 2026, Medium's free virtual gathering for writers, readers, and people curious about ideas. I presented From AI Art to Housing Justice: How I Write About Emerging Technology Through Stories live on Zoom at 1:00 p.m. Eastern today. Thank you to everyone who joined and asked such thoughtful, awesome questions. I'll add a video of the talk to this post as soon as Medium releases it.

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