Bridging the AI Literacy Gap

Empowering Educators and Students Through AI Literacy Instruction

Since November of 2022, many educators have experimented broadly with Gen AI in their own work and in student-oriented activities. In this second modality, teachers have begun to successfully integrate Gen AI into lessons where students actively use AI as a brainstorming tool, a generator of essential questions, a writing assistant, a debate partner, a translator, a historical contextualizer, just to name a few exciting applications. 

General AI Literacy Instruction

And yet despite these promising leaps forward toward a more AI-responsive mode of education, there is still very little instruction in schools being offered at the level of general AI literacy. Here, by AI literacy, I mean “a set of skills that enable a solid understanding of Gen AI through three priority axes: learning about AI, learning about how AI works, and learning for life with AI” (Casal-Ortero et al.)

Instead, most educators, pressed for time and by other curricular demands, use these impromptu Gen AI appearances in their courses of study as stand-ins for general AI literacy instruction.

Teachers Desperately Need AI Literacy Instruction

At the same time, it is even rarer to find schools or districts that have developed a comprehensive curriculum for AI literacy to assist teachers with this important work. Schools, as we now approach the end of the first semester of this school year, are fortunate if they have a small committee working on issues related to AI Policy and Usage.

Beyond that, most schools do not have the time, money, and energy to create a broader or more systemic approach to the instruction of AI history, practice, and future orientation. And yet, teachers and administrators are desperately in need of such training and grounding. 

Initial AI Policies Lag in Effectiveness

If we are truly being honest, the first round of AI policies, usually written from a posture of deterrence and abstinence, are now proving themselves ineffective or difficult to enforce in light of the fluid surfaces and structures of Gen AI.

Meanwhile, teachers continue to move ahead with great ideas and lessons, but in most cases are not sufficiently preparing the way for their integrations and applications. (There simply isn’t enough time! Do we need to develop special courses to do this work? Perhaps.)

And so, the significant work of reorienting of classroom norms and expectations that a fuller form of AI-Responsive Education necessitates remains a hypothesis—a project for next year. 

Students Are Largely Teaching Themselves How to Use AI

At the same time, students continue to use Gen AI for a variety of different purposes in their personal and academic lives: AI as research tool, AI as text generator, AI as reading summarizer, AI as source synthesizer, etc.

Students do most of this work outside the view of their teachers and mostly in the absence of any AI literacy frameworks or explicit instruction by teachers or administrators.

Students are conflicted about these uses, but feel a need to master these tools in the absence of direct instruction. This use is creating implicit norms that will continue to subvert existing school policies in complicated and unpredictable ways, and until there is more transparency on both sides of the equation, nothing like a lasting and satisfying solution will be achievable.

AI Literacy Work as a Compelling Narrative

And so, if we take a step back from the situation and truly try to observe what is taking place, we will see that AI in Education is actually splintering off in several different directions at the same time, at different rates of development, serving very different audiences and purposes.

But what I hope to suggest in this short post is that even a small amount of “conscious” work on AI literacy curriculum will enable teachers to reconnect with their students in vital and important ways. In essence, through AI literacy, teachers can create compelling new narratives with the power to draw together these disparate trajectories.

In other words, the AI literacy curriculum might be teachers’ best entry point back into the conversation and into students’ circle of influence and relevance.

AI Literacy Step 1: Ask Students Questions about Themselves

So the question becomes: What are the first practical steps towards creating an AI literary program and a compelling narrative about the nature of AI, its applications, and its future development? 

My response is that we as educators need to begin this process as a dialogue and that our first role must be one of listeners. 

In other words, students do not need an initial series of boring lectures about what AI is, how to use it, and what it might be used for in the future. 

Nor do students not need to be thrown in front of an AI application and set loose to experiment to their hearts’ content.

Rather, we first need to ask our students thoughtful questions about themselves and their relationships with computing and AI, and then we need to listen closely to their responses in order to discover how to best shape our AI literacy instruction and curriculum. 

A Cultural Studies Approach: Part 1

In a previous post, I invited my readers into a reflective space where they might consider the causes and conditions that influence their own responses to Gen AI. These causes and conditions included factors like identity, ideology, socio-economic status, educational background, familial upbringing, understanding of and access to Gen AI, and other influences.

No person responds to Gen AI in a vacuum. Every response emerges in a context and is a continuation of a history. All these statements are very much the case for our students.   

As a result, it is difficult for us teachers to gauge ahead of time how our students will respond to a particular integration and implementation of Gen AI. 

Asking Good Questions; Listening to the Answers

In order to honor our students’ histories, identities, cultures, questions, and concerns, let’s center them as the actual subject and prime recipient of our AI curriculum: 

1. What history does your family have with computing and AI? 

2. What is the significance of computing and AI in your culture, society, and personal life?

3. What does it feel like to work on a computer or to use AI? 

4. What are your greatest hopes and fears when it comes to AI? 

In my own conversations with students, I sense both a real interest in AI products and AI futures, and a tangible fear, sometimes bordering on existential dread. Two sources of anxiety keep coming up in these discussions. 

First, students worry about their own job prospects in a world bent toward greater automation. All the talk of job elimination is trickling down not so slowly into the classroom. Students are validly wondering why they are working so hard to learn math, writing, etc. when computers appear to do similar tasks so efficiently and accurately.

Second, some of my students are speaking quite eloquently about their perception of the diminished value of human experience and perspective in the face of machines trained on massive datasets. Perhaps the role of human beings in the not so distant future will be as caretakers or guardians of massive machine intelligences that help guide and improve the world we live in and depend on. There is an element of both hope and despair in these student imaginations that at once intrigues and frightens me as an educator.  

These Fears Strangely Reinforce Each Other

Therein, the relationship between these two sources of anxiety is complicated, dynamic, and quasi-symbiotic. On the one hand, students fear the potential loss of jobs, and yet at the same time, have an increasing trust in the authority of the machines that may be replacing them. 

The Power of a Narrative to Untangle These Fears

In the larger scheme of things, a solid AI literacy curriculum could address both kinds of fear and anxiety, revealing that job loss may lead to many new kinds of careers and professions hitherto unimagined, and that AI “authority” is just one kind of limited view and human feedback on that viewpoint is a vital part of grounding these systems effectively, efficiently, and ethically in the world we live in.

Developing such counter-propositions will become a key part of the narrative-process at the core of our AI literacy programs. 

AI Literacy Step 2: Examining Societal Frameworks and Perspectives

Again, before sitting students down in front of an AI application, it is worth having another framing conversation. 

What are the dominant approaches or perspectives on Gen AI in today’s society?

Here, the educator moves the student skillfully from self-reflection to reflection on society at large. 

A Cultural Studies Approach: Part 2

Cultures and societies rarely have monolithic responses to technological advancements. Usually, cultures and societies fractalize around the introduction of new technologies. Opposing camps take strong stances. Pragmatists work in the middle ground. Time passes. Compromises develop. New paradigms emerge even as the technology continues to change. Nothing is static even as particular adherents espouse “rock solid” beliefs about different states of affairs. 

The explicit goal of a detailed overview of the emerging approaches to AI and its future is to establish a larger societal framework for a more technical study of AI’s history, functionality, and future development (the traditional components of an AI literacy course).

The implicit goal of this overview is to both relativize and contextualize the heated opinions about AI that circulate around school, on social media, in film and television, at home, etc. By the end of this second stage of AI literacy work, students should feel better equipped to categorize different “hot takes” on Gen AI as representative of different approaches or schools. 

Three Orientations on Gen AI and Related Technologies:

Techno-Idealism: Embraces all Gen AI developments, believing AGI is imminent or achieved. Prioritizes gains over risks and sees human-AI interactions as enhancing creative evolution, trusting humans to handle ethical challenges.

Techno-Realism: Evaluates Gen AI developments on their merits and in context. Cautious about AGI labeling, focuses on short-term gains and risks, and recognizes humans' historical ability to navigate technology's impact.

Techno-Pessimism: Distrusts Gen AI developments, often with the belief that AGI is imminent. Prioritizes risks over gains, sees human-AI interactions as distorting creative evolution, and doubts humans' ability to handle ethical challenges posed by AI systems.

The teacher can bring in several different articles, posts, and videos, and ask students to categorize them in terms of the above orientations. 

The teacher can then open up the floor to discuss what perspectives on AI are not captured by these categories.

Conceptual and Rhetorical Analysis:

If students are open and receptive, the teacher can ask them to discuss the relative strengths and weaknesses of these different positions. Or can frame the conversation more rhetorically: What are each of these perspectives “good for”? What kind of work does each perspective “do in the world”?

First Two Steps of AI Literacy: Triangulating around Gen AI

This AI literacy curriculum offers students a chance to get a little distance from the heat of the verbal and visual rhetoric of AI-oriented media. Inside this space, they will have the opportunity to start to develop their own beliefs and knowledge about AI and its future.

After completing these first two steps, students will be in a better position to engage with specific information about how AI works, how to use it, etc. We can conceptualize these moves in terms of an “AI Literacy Triangle” through which the educator and student are creating a contextual framework the study of AI, its use, and its future. Having now established the points of SELF and SOCIETY, the student is ready to fully engage with the subject of AI proper.

Moving Forward: Teachers Need Help Developing AI Literacy Curriculum

Needless to say, students are not the only people in schools who need such instruction and training. As I am writing this, I am acutely aware of how many of my colleagues need a very similar course of study before they can effectively bring Gen AI into the classrooms. Recent studies have shown that teachers are desperate for AI literacy courses, and schools and districts are just not responding fast enough. 

Be Brave; Have Conversations; Create Narratives

In order to help with this situation, I plan to use some of my future posts to continue to explore this issue of AI literacy. Really, a school just needs 2-3 interested teachers or administrators who can dedicate some time to developing a program, and the courage to commit to training staff and faculty on that program in some kind of holistic manner. Be brave, my readers. Have some good conversations in the next couple weeks. Help create a narrative through which you can affect lasting change.

Thanks for reading Educating AI!

Nick Potkalitsky, Ph.D.

P.S. I highly recommend that my readers check out Eric Hudson’s Substack

Learning on Purpose

. He is writing some of the best educational content on AI and Education on this site. Check out this post in which Eric reports from his experiences on the road and offers his insights about AI literacy instruction and training.