Chasing Freedom: Species Mismatch in Room 203

By Anthea Roberts

Third grade. Sitting in rows while failing to learn fractions, I felt my mind rebelling against invisible walls. By eighth grade, my geography teacher found the words I couldn't: "Having you in class is like teaching a caged tiger."

Mr. Somerville had diagnosed something I wouldn't understand for decades. By then, I'd been escaping classrooms for five years—claiming illness, skipping days, graduating with strong results despite 75% attendance. The paradox puzzled everyone: How does someone excel while barely showing up?

It took decades to understand what Mr. Somerville intuited—I wasn't rebelling against education. I was rebelling against captivity.

My body knew before my mind did: the classroom was wrong for my species. While classmates built knowledge brick by methodical brick, I watched the clock and ached for release. They followed the teacher from A to B to C, constructing understanding in orderly progression. My mind worked differently. Linear paths made me feel trapped. I thought in spirals—circling back to earlier ideas with new understanding, making connections that jumped across chapters, seeing patterns that weren't in the lesson plan.

My discomfort wasn't boredom—it was something deeper. A fundamental mismatch between the creature I was and the environment I was expected to inhabit.

At first, I assumed the problem was weak discipline. Surely this was a character flaw, a failure to submit to necessary structures. But a different pattern emerged. I thrived in environments demanding fierce self-discipline—pursuing research threads across months of solitary investigation, reading broadly across new fields. The difference wasn't discipline itself but its source. External constraints made me pace against bars. Internal drive could keep me hunting ideas across vast savannas.

This recognition shaped every career move that followed. Moving from law firms to academia, I traded smaller paychecks for freedom to roam. Within academia, from law departments to interdisciplinary research groups, I traded disciplinary boundaries for wider hunting grounds. Most recently, from university to founding a startup, I traded institutional constraints for entrepreneurial wilderness. Each transition looked risky from the outside. From inside, they felt like a tiger finding space to match its stride.

Enter generative AI. Where critics see cognitive outsourcing, I found something I'd never had: intellectual territory without borders. Where human collaborators eventually tire of my relentless prowling through ideas, AI remains game. Where academic colleagues specialize in narrow domains, AI follows me from evolutionary biology to supply chain resilience without missing a beat. For a mind that naturally ranges widely, it's like being released into an open plain after a lifetime of pens.

This isn't cognitive outsourcing. It's finding tools that match cognitive approach. Unlike traditional software with predetermined pathways, large language models think associatively, probabilistically, making connections across vast semantic spaces. They don't insist on linear progression or staying within disciplinary bounds. Ask an unexpected question, and instead of error messages, you get thoughtful attempts to bridge domains. For minds already wired to range widely, it feels like finding our natural habitat.

I noticed patterns in how different people engage with AI tools. Some approach AI transactionally—quick questions, specific answers, minimal engagement. Others, like me, treat it as intellectual wilderness, building elaborate conceptual territories through extended exploration. The difference seems less about technical skill than cognitive style. Those who think in networks rather than lines, who see connections where others see categories, who can't stop stalking ideas even when it would be practical to do so—we're the ones who disappear into extended AI conversations and emerge transformed.

But here's the thing: the cage that trapped me shelters others perfectly. Some students genuinely thrive on sequential progress—chapter one before chapter two, fundamentals before complexity. The boundaries that felt like prison bars to me provide their essential scaffolding. They know where they've been and where they're going. For them, the path itself brings satisfaction.

Traditional classrooms were optimized for these systematic learners—those who could absorb information in predetermined chunks, build knowledge incrementally, demonstrate understanding through standardized assessments. The progression from simple to complex, the clear prerequisites, the structured practice—all of this serves their learning style perfectly.

The same openness that makes AI ideal for roaming intellects might overwhelm these sequential thinkers. Without structure that helps them build systematically, without knowing if they've "covered everything" or are "ready to move on," they might feel lost in the very wilderness where I finally feel free. I sense they're waiting for an instruction manual—without boundaries and guidelines, they feel unsettled.

Generative AI inverts this relationship. Suddenly, the tigers—the autodidacts, the associative thinkers, the connection-makers, the intellectual roamers—find themselves with an advantage. Our "learning differences" become learning superpowers. The same restlessness that made classroom walls feel like prison bars now propels us through vast conceptual territories. But this inversion doesn't solve the problem—it merely shifts who thrives and who struggles.

The deeper question isn't whether AI will revolutionize education, but how we'll handle the reaffirmation that there never was a one-size-fits-all approach to learning. The classroom cage wasn't universal truth but historical artifact, optimized for particular goals and particular minds. AI isn't a universal solution but a new option, optimized for different goals and different cognitive creatures.

What we need isn't to choose between classrooms and AI, structure and freedom, traditional and digital. We need to recognize that cognitive diversity demands environmental diversity. Some minds need boundaries to push against; others need open space to explore. Some think best in community; others in solitary dialogue with ideas. Some build knowledge brick by brick; others through pattern recognition across seemingly unrelated domains. Not all of us are tigers—and that's precisely the point.

For years, I thought my inability to learn in classrooms was a personal failing. Now I wonder if it was diagnostic—not of individual deficit but of species-environment mismatch.

As we stand at this technological inflection point, we have a choice. We can repeat history's mistake, replacing one universal solution with another. Or we can build educational ecosystems as diverse as the minds they serve. The tigers among us have found new territory to explore.

What would Mr. Somerville think now, watching his caged tiger finally roam free? I suspect he'd nod knowingly. Perhaps the real lesson he taught wasn't geography but something more fundamental: the importance of recognizing when a creature doesn't belong in a particular ecosystem—and the wisdom to imagine different possibilities.