Why I think AI literacy is necessary (Part 1)

What does “AI literacy” mean?

Once you get past July 4th weekend as a teacher, last year recedes and next year appears — a long way off, thankfully — over the horizon. As I look ahead to next year, I want to get more clear with myself about why I believe high school students should have AI literacy experiences. The arguments around AI in high schools are only going to get more vigorous this fall, so the calm of the summer is a good time to gather our thoughts.

I’m sharing my current thoughts in case they’re useful to others wrestling with similar questions in their contexts. In this post and some future ones I’ll engage with key questions I think AI literacy advocates need to answer. Today’s question, to start this off:

What does the phrase “AI literacy” even mean?

When I use the term, I’m thinking about the literacy I explored with students for many years as an English teacher. I understood my primary goal to be teaching reading, writing and discussing. By the end of high school, this mostly meant helping students solve a kind of puzzle, albeit one that can be assembled many different ways.

Teaching reading meant helping students put together the pieces of a story, the events of the narrative and the words the author uses to describe them, so we could see the broader picture the author was creating — and so students could later do that again on their own. Teaching writing and discussing meant helping students find their own words for the ideas about a text or about life (or ideally about both) that they wanted to convey. In other words, students would write and talk about the process of putting together the puzzle of a book and what they learned about the book and themselves during that process.

Some of my most powerful literary experiences, as a teacher and a reader, were working through the novels Another Country by James Baldwin and The Women of Brewster Place by Gloria Naylor in a 12th grade English course I designed and taught for several years. In both books, the authors weave together symbols and images to help readers confront truths about America and about themselves.

Baldwin’s characters listen to and perform classic blues songs throughout his book, and we would play the original audio in class, annotating the lyrics and listening to the melodies and asking why Baldwin would put that song in this story at that time. Then we’d consider whether we might still need that kind of music — literally or figuratively — in our time and if so, how to make it. Naylor uses the idea and image of a phoenix to launch her book, so in each character’s chapter we looked for the moment a phoenix would appear, sometimes as a reference to sunlight and sometimes as a pigeon taking flight. We’d then discuss the implications of Naylor’s narrative, whether we should be looking for phoenixes in our lives, around us and inside us, and if so how to go about finding them.

In both cases, learning to read, write and discuss better also meant learning to live better, and live together better — the text providing a kind of secular spiritual training for both the individual student and the classroom as a whole.

When I think about AI literacy, the translation I realize I’m making is to treat AI as a text. The technology of books, as it were, is something we barely notice any more. But when I think about reading, I’m thinking about engaging with structures and conventions that have become almost subconscious in their ambience. When we read Naylor and Baldwin, we would flip between different chapters to see the threads the authors tied to hold their story together. We would zoom in on specific words and phrases the authors put down on the page. We’d ask, over and over again, “Why did the author make this decision?” We’d consider the world they were writing within, what they thought of that world and what they wanted to change, and also consider the world we were reading them within and what we might want to change.

In English class, the book creates an occasion for us to work together to understand ourselves, each other and our moment, and then ask what should happen next. In AI literacy lessons, I understand AI to be doing something similar.

A key move in both cases is to see the “text” as full of human decisions.

In English class, that aspect of literacy is easier to convey. The author’s name is on the cover. The publication date is given a few pages before the story even starts. We know right away who made this and when, so we can move on to the question of why.

In AI literacy lessons, we need to help students see the authors. For example, as we redesign our AI literacy class for 26-27, Scott Kern and I want to spend more time introducing students to the leaders and researchers shaping AI systems. We want to give students a sense of who those people are, how they think, and what their formative life experiences seem to have been, in the same way I’d always devote a lesson or two in that English class to background on Baldwin and Naylor, including videos of interviews with them. In both cases, the goal is to help students see that there are people who made decisions about the experience they are having, about how the “text” in front of them was built.

(It’s also important to remember that authorship is a more complicated concept when it comes to AI. The incentive structure surrounding this technology is an author too, as are the many people involved in training AI models, as are we in the form of the training data we collectively created.)

Once we make the decision makers visible, we need to teach how to identify their decisions and consider the implications of those decisions. Baldwin keeps alluding to the blues — what does that do to our experience as readers, and why do you think he decided to do that? Naylor keeps alluding to phoenixes — what does that do to our experience as readers, and why do you think she decided to do that? AI leaders and their UX teams designed AI conversations so that they look a lot like a text message exchange — what does that do to our experience as users, and why do you think they decided to do that?

Part of the point is to help students wake from the dream we can all fall into when reading, or when using AI. In both cases, we can quickly forget we are living in a world someone else created and start to feel like things were always going to be this way. Another Country was inevitably going to be full of music; LLMs were always going to respond using the first person. When we remember the authors, though, we wake ourselves up, which is to say we remember who was doing the dreaming in the first place. (Obligatory former English teacher note: The narrative dream is a wonderful one! I just wanted students to know how to make it a lucid dream from time to time.)

A second key move is to see ourselves as decision makers too.

That’s why our English classes ideally landed on questions like, “If Naylor designed her book to make an argument about the importance of personal rebirth, what would it mean for you to rise from your own ashes? What would it mean for us to collectively do the same?” The point was for students to read books and write about them until they realized they could also read and revise reality.

In AI literacy lessons, the questions look like this: “If AI companies designed LLMs so it seems like you’re talking with an all-knowing, infinitely patient conversation partner, not just prompting a probability machine, what would it mean to use AI in a more lucid way? What would it mean for us to collectively argue for different AI design choices?”

That’s why I think the term “literacy” works for the kinds of AI lessons we should be teaching. In the way I understand it, “literacy” means practiced awareness and analysis that leads to increased agency.

In both kinds of classes, though, the literacy edifice rests on a potentially fragile foundation.

When I designed that 12th grade English course, I built in mechanisms to hopefully ensure students did the reading before class. We had “reading tests” on Mondays, where students answered questions about the plot of the weekend’s reading (and could use notes to do so, which they then had to turn in with their test). But in addition to extrinsic measures like that, I also hoped our classroom conversations were so intrinsically interesting they became another motivation for doing the homework. The larger point here, as any English teacher will tell you, is that we need everyone to do the reading.

And that’s the most basic reason I believe we need to bring AI into high schools, in the same carefully and professionally curated ways that we bring in novels like Another Country and The Women of Brewster Place. Both were explosive texts in their time and still are in ours, based on the way students carried our conversations out into the hallway after class. AI is a new kind of text we need to help our students engage with, one that is powerful, exciting and dangerous. AI raises new — and old — questions students need to grapple with, and their teachers are some of the people best equipped to help them do that. But they can’t do that grappling, and we can’t help them do it, if we leave them alone to encounter AI at their bus stop, on their couch, or in their bedroom. We all need to be doing this reading together.