Key points:
While nearly every industry is racing to integrate artificial intelligence, most schools are still teaching high school math the way it’s been done for decades–rooted in instructional material that is abstract, disconnected, and detached from the world students actually live in.
It’s no wonder that so many students decide early on that math “isn’t for them.” The way we’ve structured math instruction makes it hard for them to see why it matters. Our standards were built for a university pipeline, not for the realities of a dynamic economy that values creativity, problem-solving, and the ability to ask the right questions.
To move beyond outdated approaches and materials, the field has leaned heavily into AI as a solution. But efficiency alone can’t replace or cultivate the human relationships and sense of purpose that drive meaning and engagement in education.
In that case, we’ve mistaken rigor for relevance.
What we see in most high school math classrooms is a system built around endurance rather than understanding. Students race through fragmented topics to prepare for exams, while the deeper “why” behind the mathematics remains out of reach. The problem isn’t that we’re teaching difficult concepts, it’s that we’re teaching them as if meaning will magically emerge at some point down the road.
Students move through isolated chunks of algebra, geometry, and calculus without ever hearing the storylines that connect them–the human motivations and the real-world intrigues that gave rise to the math originally. When we teach mathematics without the curiosities that first inspired it, we rob students of the very spark that drove mathematics forward in the first place.
As we look ahead and begin to redefine math education, one thing is abundantly clear: AI won’t fix bad pedagogy.
AI is already being woven into nearly every aspect of education–from generating practice problems to serving as on-demand tutors. But these tools, while impressive, risk amplifying what’s already broken. By mimicking what we already know, AI doesn’t challenge the fundamental assumptions of what or how we teach. It personalizes, but it doesn’t humanize.
Investors and edtech companies see AI as the next frontier–the “holy grail” for scale and efficiency. But pedagogy isn’t an engineering problem. Teaching is an act of connection. Students learn through human storylines, through emotional safety, and through conversations that spark dissonance and exploration. Those are the moments when real understanding takes root–and they can’t be automated.
If we continue to pour AI into the same outdated frameworks, we’re simply pouring concrete on something already flawed, therefore cementing it in.
We want students to thrive in an AI-driven world, so our approach to math education must evolve to emphasize what makes us distinctively human: following our curiosities and reasoning through ambiguity to find clarity, structure, and connection. That means refocusing the student experience to ensure it becomes a human one through two key components:
- Human teachers who guide learning with empathy, context, and real-time understanding of students’ emotions and misconceptions.
- Human storylines that connect math concepts to lived experience–showing not just how we do math, but why mathematics resonates.
Instructional materials should be designed like great plays–with structure, narrative, and a sense of purpose. That requires writers who understand both mathematics and the art of storytelling. It’s not enough to generate more problems; we need to generate more curiosity, and what better way than to bring humans together to share these experiences rather than work independently with a machine.
Take the quadratic formula, for example. Surely that term elicits some sort of emotional reaction or vague memory from high school. When introduced to this formula, you were likely asked to ‘complete the square’–but were you ever actually handed a square with a hole and asked to complete it? Or was there any conversation or demonstration of the way humans solved these types of problems before there was a quadratic formula?
Current math instruction uses words that certainly seem human, such as “complete the square,” and yet we don’t provide the human story for students to make it tangible or relatable. There’s no room in the conversation for curiosity, to ask or pursue a question in order to better understand or attribute meaning.
AI could arguably solve every quadratic equation better than any human. But why is the goal to simply memorize or accurately execute rather than to think, question, and reason together?
The economy our students are entering doesn’t reward rote learning; it rewards adaptability and creative reasoning. We need a generation that is inclined to ask, “Is there such a thing as completing the triangle?”–not just one that can solve for x.
AI will continue to change the landscape of every profession, but its rise should prompt us to double down on the human elements of learning, not abandon them. If we want students to lead in an AI-augmented world, we must design math experiences that build understanding, purpose, and agency–not just automation.
It’s time to stop digitizing old lessons and start rewriting the story of math education itself.
Jill Diniz, CEO and founder of SmartWithIt, is a curriculum innovator, ed-tech entrepreneur, and longtime math educator committed to changing how we think about learning. With a deep background in software engineering, curriculum design, and classroom teaching, Jill brings a rare blend of technical rigor and educational empathy to every product she creates. Her work at Smart With It reflects a passion for joyful, validating educational experiences that are scientifically sound, deeply accessible, and built to last.
