January 12th, 2026

The Importance of AI Literacy

AI Literacy Relationship to Other Disciplines (page 17) | https://ailiteracyframework.org/wp-content/uploads/2025/05/AILitFramework_ReviewDraft.pdf

​As Artificial Intelligence (AI) becomes increasingly ubiquitous in our world, the importance of developing strong AI literacy programs in K–12 schools has become impossible to ignore. AI has rapidly entered our daily lives, and we cannot simply hope it fades away or choose to avoid it altogether. Instead, we must ensure that students understand what AI is, how it works, and how to use it appropriately. Equally important is helping them grapple with the legal, moral, and ethical dilemmas associated with this technology. At its core, this work requires a return to the foundations of strong digital citizenship so that students and future generations can engage with AI in informed, responsible, and thoughtful ways while recognizing both its opportunities and its limitations.

In my work with educators, I often encounter two dominant reactions to AI. Some lament its use, expressing concern that students will lose the ability to think critically and creatively. Others are optimistic, intrigued by AI’s promise and its perceived ability to do things that “have never been done before.” The reality, however, lies somewhere in between. Most AI applications today function by rapidly identifying patterns and connecting preexisting “dots” to generate new arrangements and configurations of “dots” that can feel extraordinary at first glance, largely due to their speed and scale. Our immediate responsibility is clear: we must create learning experiences that help students understand how AI works, how it is trained, and how it can be used in positive, meaningful, and ethical ways. This reality underscores the need for intentional AI literacy experiences that allow students to explore both the promises and the pitfalls of AI technologies.

AI Literacy Begins with Digital Citizenship
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At the heart of AI literacy is digital citizenship, which is closely connected are media literacy and digital literacy. While these terms each carry distinct emphases, they all reflect ideas about understanding and using digital technologies responsibly and in ways that respect the dignity and well-being of others. Rather than treating these literacies separately, we must prioritize learning experiences that help students make sense of digital tools and prepare them for a world that will continue to evolve alongside technology.
In the work my colleagues and I do to support educators in digital teaching and learning, we are often asked a deceptively simple question: What should we teach about AI? This question naturally leads to a discussion of AI literacy frameworks. While AI tools and applications have proliferated rapidly, frameworks designed to guide AI literacy instruction have emerged at a much slower pace. In many ways, using AI appears far more glamorous than teaching how it actually works. Yet without a clear instructional foundation, meaningful learning is difficult to achieve.

The Digital Promise AI Framework 

In response to these requests for direction for both students and adults, I often rely on two AI literacy frameworks. The first is from Digital Promise and was the first framework I used to design AI learning experiences. This framework is straightforward and organized around three core components: Understand, Use, and Evaluate. Educators often appreciate not having to navigate overly complex terminology, and despite its simplicity, the framework is robust enough to support a wide range of learning activities.

One activity I frequently use involves sharing an AI-generated image of the downtown area when I am facilitating professional learning. I ask the experts in the room, the educators who live and work in that community, to respond to two questions: What do you notice? and What do you wonder? The responses are always fascinating. Educators are typically quick to point out surface-level inconsistencies: “There are no people,” “The streets are too clean,” or “There are no cars.” While these are all good observations, I less frequently hear comments such as “The trees do not have shadows on any side.” This often leads to a conversation about why we gravitate toward what feels like the “low-hanging fruit” when evaluating AI-generated content. I then ask participants to identify which component of the Digital Promise AI Literacy Framework they were using in this activity. This reflection helps them connect the framework to an authentic experience and deepens their understanding of how AI literacy can be embedded in meaningful ways.

Empowering Learning in the Age of AI Framework

The second framework I often reference comes from a joint collaboration between the European Union and the Organisation for Economic Co-operation and Development (OECD), supported by Code.org. This collaboration resulted in the publication Empowering Learning in the Age of AI: An AI Literacy Framework for Primary and Secondary Education, with the most current version available in draft form as of May 2025. This publication makes two particularly valuable contributions to AI literacy.

First, it identifies four key AI competencies: Engaging with AI, Creating with AI, Managing AI, and Designing AI. These competencies encompass the knowledge and skills individuals need to interact effectively with AI systems. The framework also emphasizes the attitudes required for responsible AI use and includes a strong focus on ethics. One aspect of this publication that resonates deeply with me is AI literacy’s connection to other disciplines, including data science, digital literacy, media literacy, design thinking, ethics, and computer science. The visualization illustrating these relationships (found on page 17 of the publication) serves as a powerful reminder of the interdisciplinary nature of AI and what I hope my own son is experiencing in his education.
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Designing Experiences That Lead to Real Understanding

As educators move forward in helping students and others understand how AI works, along with its opportunities and limitations, it is important to remember that this responsibility is shared. While selecting a framework or model can provide helpful structure, what matters most are the learning experiences we design and the opportunities we create for students to deepen their understanding of AI in real-world contexts. As I often share, my son and his peers are very good at telling adults what they think we want to hear. Yet when they are asked to demonstrate their understanding, it becomes clear that many still struggle to apply their knowledge of AI meaningfully. This struggle, however, is not a failure; it is where learning and growth occur. Real-world experiences that challenge assumptions and invite students to consider multiple perspectives are essential. ​

The original post was written entirely by the author with edits and suggestions made by Chat GPT.  The final version considered edits and suggestions with some accepted and rejected.  It is always important to disclose the use of AI as a model for others.