Why AI is So Hard (For Education)

What habits of inquiry, dialogue, and courage can we cultivate now so our students are ready to design the next civilization?

The transition to an AI World is hard, and it isn’t just because we don’t know exactly how to prepare students for it.

It’s hard because economic gains are not distributed even close to fairly in the current world, and it is likely that this maldistribution will get substantially worse in the AI World.

Currently, while the markets roar, 42 million Americans depend on government payments to eat. Twenty-four million rely on the government for significant health care subsidy.

As Emad Mostaque, founder of Stability AI, observes,

OpenAI knows how big of a problem this is.

[the blog]

Currently, human intelligence, which will arguably be inferior to artificial intelligence, is applied in a way that distributes benefits upward. When we apply substantially greater intelligence to the economy, we will mostly distribute the gains of that upward. That’s just simply our economy distributes wealth.

It will, of course, be magnified by the fact that a limited number of companies that control the foundation models underlying this transformation. In AI 2027, the optimistic scenario suggests approximately 10 companies and their leaders will control all of the technology.

In many cases this technology will simply replace people, including people who are well-educated by current definitions of what well-educated means.

This will only get worse:

To summarize, there basically three possible paths.

1. Do nothing and muddle through, with a massive concentration of wealth flowing to the top. This will likely create an unstable society (to say the least).

2. The system collapses. Sam Altman (CEO of OpenAI/ChatGPT) has claimed that AI will collapse capitalism. Mostaque is making the same argument. Many others have made it.

3. We learn to live and thrive in a post-capitalist world where most people are entrepreneurs (Diamandis et al), create, and thrive.

Learning to thrive in a post-capitalist world where most people are creators and entrepreneurs will require a radical overhaul of our educational systems.

According to Sabba Quidwai, students must be positioned not merely as consumers of knowledge but as agents—leading teams of humans and machines, designing their own challenge spaces, and building AI-augmented ventures. Her work on Designing Schools emphasizes that education must develop the capacity to lead human-AI collaborations, not simply learn facts.

Meanwhile, Dan Fitzpatrick argues that educational systems rooted in industrial-era models are already obsolete in the face of generative AI: we must shift from knowledge transmission to innovation ecosystems and equip learners for entrepreneurial environments (Fullmind Learning).

Tim Dasey adds that students need adaptive expertise: not just different content but new ways of thinking, assessing, and acting in rapidly changing contexts. And they need to develop judgment and wisdom.

Together, these thinkers suggest that the education system must evolve from preparing students for predictable employment toward supporting them to launch, lead, iterate, and scale—to become creators of enterprises, designers of their own careers, and collaborators with AI rather than passive recipients of instruction.

According to Bauschard & Quidwai in Humanity Amplified: Understanding the AI World and Augmenting Our Students’ Intelligence with Human Deep Learning (2024), the modern education system must shift toward “deep learning”—a pedagogical approach focused not simply on content acquisition, but on cultivating human-machine collaboration, reflective agency, and adaptive intelligence. They argue that learners must be empowered to lead “AI teams” and to think of machines as partners in creation and entrepreneurship, not just tools to consume or follow. In their view, to thrive in any economy, education must help students develop the mindset and skills to ask: What can we create together with AI? rather than What can we learn from AI?

The Real Debate

In this light, the public arguments about whether students should use AI to brainstorm or write a paper seem almost trivial. They are symptoms of a system that still measures learning by compliance, not creativity; by authorship, not agency. The fundamental question is not how much AI a student uses, but how education helps them understand and shape the world that AI is creating.

This struggle will be as consequential as the founding of nations or the birth of democracy itself. Just as earlier generations had to rebuild the moral and civic foundations of their worlds, this generation will face its own constitutional moment—the moment when humanity must decide how intelligence itself will be governed.

When the American founders like Madison, Hamilton, and Jefferson designed checks and balances to restrain political power, they were grappling with the same question our students will face in digital form: how do we keep power—now algorithmic and automated—accountable to human values?

When the framers of the U.S. Constitution, or revolutionaries in France and Haiti, challenged inherited systems of monarchy and slavery, they imagined new rules for who counted as a citizen, who had agency, and who could speak. The same questions echo now, as AI reshapes who has a voice in shaping truth, labor, and opportunity.

When Mary Wollstonecraft, Frederick Douglass, and John Stuart Mill demanded that education and rights be extended to all, they were not just expanding access—they were redefining what it meant to be human in an industrial age. Our students will be asked to do the same in an age when machines can perform acts once thought uniquely human.

When Karl Marx and Adam Smith tried to explain how capital transformed labor, or when Bismarck and Roosevelt built welfare systems to stabilize societies torn apart by industrialization, they were inventing new economic and governance models to cope with technological upheaval. Today’s generation will have to build new equivalents—models for distributing intelligence itself, ensuring that compute, data, and algorithmic power do not concentrate in the hands of the few.

Just as Franklin D. Roosevelt’s New Deal, Gandhi’s independence movement, and the postwar architects of the United Nations sought to humanize the forces of capital, nationalism, and conflict, this generation will need to humanize artificial intelligence.

What if the purpose of education is no longer to prepare students for the world we grew up in, but to prepare them to lead the transformation into a world we can barely yet imagine?

What if one of the students in your class will help shape the moral, economic, and political foundations of the post-capitalist, AI-driven era?

Then the questions change: What values will they need to hold when intelligence itself is no longer human-exclusive? What forms of empathy, creativity, and discernment will guide their decisions when code becomes a form of governance? What habits of inquiry, dialogue, and courage can we cultivate now so that they are ready to design the next civilization?

Education’s ultimate role is to ensure that AI amplifies our humanity rather than replaces it—to teach discernment, imagination, and empathy in a time when intelligence itself is becoming automated. If we can align ethics, economics, and education toward that end, we will not only adapt to the AI World—we will lead it.

Which of our students will lead the accompanying social, economic, and political transformation?