Prologue

What We Can Make Possible

Years before I wrote about artificial intelligence, I wanted to write songs. There were a few practical problems with this plan. I couldn’t sing, and I couldn’t play an instrument. But I could write lyrics, and for a while, growing up in rural North Dakota, that was enough to keep me going.

I filled pages with words I hoped someone might someday sing. Eventually, I started writing about the music industry instead. I became interested in how technology changed the way people discovered songs, built audiences, and made a living. The lyrics stopped coming as often. The essays took their place.

Then, in 2024, I opened an old Google document, found a set of lyrics, and gave them to a music-generation tool called Suno. Within seconds, I could hear them as a hard rock song. The words belonged to a younger version of me, but I was hearing them performed for the first time.

I knew enough about the music industry to have a hundred questions about what this meant. What had the model learned from? What would these tools mean for the people who made music for a living? What, exactly, had I created? Those questions mattered. So did the fact that I had just heard something I had wanted to hear for years.

That tension runs through this book. I keep encountering technologies that make something possible for me, then wondering what happens when the same opportunity becomes available to millions of other people. A personal discovery becomes a question about an industry. An experiment becomes a question about education. And sooner or later, I find myself asking who will get to participate.

I grew up with access to computers because other people made decisions that put them in my school and home. Someone decided that kids in a small North Dakota town should learn how to use them. My dad connected our farm to the internet. Teachers taught us to type. We were later called digital natives, as if knowing our way around a computer had been included with our birth certificates. But access, encouragement, and practice had something to do with it.

I think about that whenever someone assumes that today’s students will simply figure AI out. Some will. Some will get help from a parent, a professor, or a friend who has already spent months experimenting. Others will have access to the same text box without much sense of what to ask it, what to believe, or how it could connect to something they care about. Being surrounded by a technology and learning to use it well are different experiences.

This is one reason I became an academic librarian. While studying at the University of Michigan, I began to see AI literacy as part of the work I wanted to do. My internship at the Shapiro Design Lab gave me another piece of the picture. A room full of creative tools could open possibilities, but people still needed help imagining a project, working through a problem, and figuring out what to try next. The people alongside the equipment mattered.

That lesson followed me into teaching. I expected an AI fluency class to involve a great deal of explaining tools and helping students write better prompts. It did involve those things. But students also started making websites, games, and applications, and the conversations became more interesting than the tool demonstrations. Who would use this? What were they trying to accomplish? Had anyone asked them?

One student wanted to build something for her mother’s hairstyling business. She could begin generating a prototype almost immediately. The more useful conversation concerned how her mother actually worked, what she found frustrating, and why the software already available had not solved the problem. Suddenly, learning AI involved learning how to listen to another person.

That is where my understanding of fluency keeps expanding. You can learn to make a chatbot produce a convincing answer. You can learn to make an app appear on a screen. But you also need to understand what you are looking at, how to examine it, and what would give you a reason to trust or change it. A research answer needs evidence. A website needs someone to try it. A song asks something different of us: does it express what we hoped it would, and what choices made it ours?

As educators and librarians, we face a fascinating challenge. We are learning these things while helping other people learn them. We have to make room for curiosity and creative ambition while taking questions about accuracy, access, authorship, and harm seriously. I want a student to feel that an idea is worth exploring. I also want that student to be able to explain why a result deserves confidence, where it falls short, and who might be affected by using it.

You will see my thinking change across these essays. Some begin with excitement about a new capability. Others follow that excitement into questions about work, institutions, and increasingly powerful machines. I have made predictions, worried about possible futures, and revised my understanding through things I tried myself. Bringing the essays together lets me see how often the same question has followed me from music to technology to libraries: what becomes possible for people, and what will it take for them to make something of the opportunity?

I hope this book gives you room to pursue a question of your own. You may want to teach a class, help a colleague, investigate a claim, or finally make something you have carried around in your head for years. The place to begin could be a problem in your community or an old document you had almost forgotten.

I still think about those lyrics. Hearing them did not settle my questions about the future of music. It gave me a reason to keep exploring. I would like to help you find a reason of your own.