Real learning is rarely a single event but an ongoing process in which new discoveries are made and ideas developed.

When an assignment can be completed quickly, with little resistance or challenge, we must question whether a meaningful learning experience has truly occurred. This concern existed long before AI entered classrooms. More importantly, the regurgitation of information—masquerading as real-world application—does not constitute creativity.

Creativity exists at multiple levels. At one level, creativity emerges when a student discovers something new that is appropriate to a specific content area. This might occur when a student connects a historical event to a contemporary social issue, or constructs an understanding of why leaves change color in the fall. Creativity continues as the student works out how best to express these ideas and apply them to projects. 

This experience helps make learning more visible to others and, in some cases, can further elevate creativity by gaining appreciation and value from an audience. In this sense, creativity is inseparable from learning itself: it is the act of forming novel connections and applying them to meaningful, real-world contexts in the classroom.

At this level, it is easy to see how AI can support learning. AI can simplify complex information, personalize instruction, and help students explore different ways to express their understanding. It can elevate writing mechanics, suggest organizational strategies, and provide customized feedback. Used thoughtfully, these affordances can strengthen learning and improve the overall quality of student work. So long as students are making genuine discoveries and developing their own ideas, they are engaging in creativity—with or without AI support.

In these situations, instructional efficiency may also improve, potentially freeing teachers to focus more on social-emotional needs and human connection. When we consider diverse learning preferences, students with disabilities, and the ongoing challenge of differentiation, it is difficult to ignore the genuine opportunities AI offers to support access and inclusion in the classroom.

However, creativity also exists at a higher level—the level at which individuals produce outcomes that have never existed before. This form of creativity drives radical change in human experience and fuels breakthroughs in medicine, climate science, and social progress. From what we understand, this level of creativity does not appear within AI’s capacity. 

AI operates by recombining existing knowledge; it cannot generate what is fundamentally unknown, even if it seems unknown to the untrained or novice learner. And this is where things get dicey!

In my experience, student work increasingly sounds remarkably similar from one submission to the next. While some may celebrate improvements in efficiency, fluency, or surface-level quality, the originality of ideas is diminishing when viewed beyond the individual level. 

Even when students engage with AI ethically and responsibly, new challenges emerge that are only beginning to be understood.

Consider using AI to generate ideas for writing topics. While this practice may help an average student access more appropriate and advanced ideas than they could generate independently, it removes the struggle of identifying something personally meaningful. That struggle is often the very process through which unique ideas emerge—ideas shaped by a student’s background, experiences, and individual ways of making sense of the world.

As more students rely on AI-generated idea sets, creativity increasingly becomes an act of selection rather than generation. Students choose from variations of the same ideas, slightly reworked, rather than constructing original perspectives. Over time, this narrows the range of ideas expressed in the classroom, even within open-ended assignments designed to encourage originality. This is how I see lower levels of creativity emerging.  While they are important, they do not compare to what goes into higher levels of human creativity that build on human knowledge and experience. 

Since the widespread adoption of generative AI. I have observed a noticeable reduction in the higher levels of creativity among my students.  Even when students intend to write their papers independently, the topics, connections, and arguments often mirror those of their peers. This pattern has emerged rapidly—within the first year of ChatGPT’s release—and continues to intensify. Students are making identical connections across assignments that explicitly invite personal interpretation and real-world application.

It’s like all sense of originality and uniqueness has been lost.

This represents one of the central challenges at the intersection of AI and creativity in education. Even guided or well-intentioned uses of AI may unintentionally encourage students to offload creative thinking to technology. While idea evaluation and refinement remain important cognitive acts, they are not equivalent to the sustained struggle required to pursue something genuinely new and meaningful to the student at the individual level.

For this reason, creativity must be intentionally safeguarded. This requires a shift in priorities—from the submission of polished content toward the process of learning and creative development. When students are required to generate their own outlines, articulate initial ideas, or draft early versions of their work before engaging with AI, the creative responsibility remains with the learner. Even if AI is used a little to clarify the assignment and converge on ideas, its most effective use in education is to provide feedback, support revision, and assist with refinement—without replacing the core creative work.

This manifesto reflects the very approach to AI and creativity it promotes. As a dyslexic academic, I began by clarifying what I wanted to share and how I wanted to share it—grounding the discussion in different levels of creativity and centering it around a writing task. With my audience in mind—educators and others engaging with this work—I drew on my knowledge of AI and creativity to shape the ideas on the page, choosing my own words and voice to express these beliefs. AI was then used deliberately to support the mechanics of writing—assisting with spelling, grammar, and clarity—without replacing the thinking, meaning-making, or creative intent behind the work.

I made further revisions throughout the process, some that strengthened the manifesto and others that reintroduced familiar writing tics. Nevertheless, what remains is unmistakably my ideas, my voice, and my perspective on AI and creativity formed and shaped over the past few years of reading and learning on this topic.

When the process is prioritized in this way, educators can be confident that the learning and creativity expressed in final products emerged through meaningful student engagement.

Ultimately, high-level, real-world creativity requires deep expertise. Breakthroughs—such as curing disease or addressing the climate crisis—are built on mastery of existing knowledge. We must therefore continue to strengthen how students develop content expertise, which is perhaps where I see the most value in AI. However, at the same time, radical creativity—the ability to imagine what does not yet exist—remains a uniquely human capacity. And this higher-level creativity is only applicable to the workplace after we have acquired such knowledge.

These points are why I am highly cautious of claims that we must teach AI simply because it will be used in the workplace. Obviously, but this frames schooling in the same context as industry, but the latter centers on the end product, whereas learning is (or should be) defined by everything that happens before it.

This is why education must resist reducing creativity to efficiency or output alone. We need both deep knowledge and imaginative thinking. AI complicates this balance, and without intentional design, it risks diminishing the very forms of creativity that education should cultivate. The responsibility, therefore, is not to reject AI—but to use it deliberately, in ways that preserve and strengthen human creativity rather than replace it.

So, to educators and administrators: be cautious of the many AI platforms that claim to streamline learning, improve efficiency, or address equity. Likewise, question claims from experts whose authority rests primarily on experience with AI tools and technologies, when that experience is not accompanied by knowledge from the learning sciences or an understanding of how students actually learn.

This approach requires your own creative and critical thinking as you consider how these tools interact with existing teaching and learning approaches in your classrooms and schools. Just as importantly, AI use should be approached contextually—by asking what problem a tool is intended to address, which aspects of the learning experience it supports, and whether, along the way, it risks hampering or undermining original thought and meaningful connection to the material.