Series: Cultural-Technological Friction: Understanding the Digital Divide in Education

Series Introduction: Why I Wrote This Series

Cultural-Technological Friction: Understanding the Digital Divide in Education

I keep circling back to a question that won’t let me rest: if technology is supposed to democratize education, why does it keep making inequality worse?

That question became impossible to ignore during the pandemic, when everything suddenly went online. Overnight, my classroom fractured. Some students bloomed in digital spaces; others vanished—not for lack of motivation, but for lack of stable internet, quiet space, or even the confidence to navigate new platforms. The divide wasn’t new, but COVID stripped away the illusion that access alone could fix anything.

Teaching in South Korea sharpens the paradox. This is one of the most wired nations on Earth—5G everywhere, digital everything—yet inequality threads through its educational system like a hairline crack you can’t plaster over. The hagwon culture means that “access” depends on how much your family can pay: for AI tutors, for specialized apps, for endless test prep. Everyone is connected, but not everyone is empowered.

Then came AI. When ChatGPT appeared in late 2022, the rhetoric was almost messianic: Free tutors for all! Personalized learning for every child! It sounded like the long-promised equalizer.

But a colleague’s metaphor stopped me cold:

“Everyone can enter the building. You gotta pay to use the elevator. Costs more each floor. Stairs are (almost) free. Can you reach the penthouse?”

That image won’t leave me. It captures how access without equity is just architecture for another hierarchy.

Around that time, I found myself rereading Neal Stephenson’s The Diamond Age—a book I first read decades ago but which now feels prophetic. Its AI-powered “Primer” was designed for an elite child but transforms the life of a working-class girl who gets it by accident. The story feels less like science fiction and more like a mirror: even miraculous technology can’t undo social stratification by itself.

That’s the tension I want to explore here. We have the capacity to build tools that could transform education for everyone. The harder question is whether we have the will to make that transformation collective rather than selective.

This series is my way of thinking through that question. It draws from my classrooms in both the U.S. and Korea, from literacy theory and generational studies, and from the lived textures of teaching in a place where connectivity and inequality coexist. My perspective is shaped by my location—an American woman teaching in Korea, moving between public systems and private economies, trying to hold literacy, justice, and technology in the same frame.

I don’t claim answers, but I believe that questions can be an act of care. And the real question isn’t “How do we give everyone technology?” but “How do we ensure technology deepens learning and belonging, not division and exclusion?”

The four pieces in this series explore:

  1. The Digital Divide: More Than Just Access – How James Paul Gee’s literacy framework reveals that digital inequality is about competency and critical literacy, not just bandwidth and devices.

  2. Generational Tech Gaps: Health, Wealth, and Longevity – How age shapes digital participation and why exclusion increasingly maps onto health and lifespan.

  3. The Diamond Age and Today’s Educational Castes – How Stephenson’s novel helps us read AI’s role in producing educational hierarchies.

  4. AI’s Elevator Problem: Who Gets to the Top Floors? – How AI in education risks mirroring Korea’s hagwon stratifications unless equity is designed in from the start.

I wrote this series because I think we’re standing at a hinge moment. AI in education is still unsettled—still porous enough to shape. We could claim it as a public good, invest in teachers, and demand ethical, equitable design. Or we could let the market decide, and watch as a new hierarchy of digital access quietly solidifies.

I hope these reflections nudge us toward the first path. Because the choice we make now will decide whether AI becomes another staircase of exclusion—or a bridge we actually cross together.

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