Core Claim

The future of AI in education will not be singular but plural—consisting of many different use cases across millions of schools, each situated in local contexts with varying degrees of autonomy. Any framework that promises a universal settlement (either utopian adoption or catastrophic collapse) misunderstands the complexity of the terrain.

The Scale Problem

Any discussion of AI in education must grapple with scale:

• Millions of schools worldwide, each in local and national frameworks of power
• Educators at every level (teachers, support staff, administrators) with varying decision-making autonomy
• Multiple third parties influencing the ecosystem: publishers, edtech providers, religious institutions, military organizations, professional certifiers
• Rapidly changing conditions in all these contexts

Into this complexity comes AI with its own layers:

• Multiple companies and startups
• Competing governments
• Open source projects
• Standards bodies
• Types of applications
• Massive investment flows

The intersection of educational complexity and AI complexity means no single prediction will hold universally.

Bentoism: A Framework for AI Decisions

Yancey Strickler's "Bentoism" (like Japanese bento boxes) offers a framework for considering AI decisions across four quadrants:

Applying Bentoism to AI in Education

Now Me (Intrapersonal, Immediate)

• Personal convenience and efficiency
• "AI can grade these papers faster"
• Self-reflection: What do I gain right now?

Now Us (Interpersonal, Immediate)

• Relationships and community impact
• "How does this affect my students today?"
• Collective benefit in the present moment

Future Me (Intrapersonal, Long-term)

• Personal growth and development
• "What skills am I building or losing?"
• "What kind of educator am I becoming?"

Future Us (Collective, Long-term)

• Human flourishing at scale
• "What kind of education system are we creating?"
• "What does this mean for future generations?"

The Bentoism Insight

AI companies and consultants focus heavily on "Now Me"—personalized learning, immediate efficiency gains. Bentoism pushes us to ask: What about Future Us?

Quick wins that entrench systems may mitigate against human flourishing over the longer term. The framework encourages resistance to short-term optimization that damages long-term goods.

It Is Not the Tool, It Is the Artist

A counterframe from art education:

"It is not the tool, it is the artist who sparks the revolution."

Structural Crisis Framing

Sociologist Zygmunt Bauman argued that modernity is characterized by fluidity and that critical thought must "bring into the light the many obstacles piled on the road to emancipation."

The social and political discourse around AI in education is not new. For centuries, humans have been "blindsided" by technologies that caused structural rupture and shifted entire societies:

• Agricultural settlement
• The printing press
• The steam engine and Industrial Revolution
• Mass media

The Real Forces

AI tools for mass consumption may be a structural touch point, but AI is not the force changing what education is. AI is created by billionaires and fund managers with capital—these are the forces working to change what education means and who has access to it.

The technology is not neutral. It carries the interests of its funders and creators.

Contingency and Pluralism

Against Universal Predictions

Many pronouncements proclaim universal settlements:

• "AI will revolutionize learning!"
• "AI will destroy education!"

Both miss the contingency. What's likely:

• Different schools will integrate AI differently
• Local contexts will shape adoption
• Some uses will benefit learners; others will harm them
• The "same" tool will have different effects in different places

The Plural Future

Educational use of AI will consist of many different use cases:

• Tutoring systems in resource-poor contexts
• Writing assistance in wealthy suburban schools
• Surveillance tools in punitive environments
• Creative tools in progressive classrooms
• Administrative automation
• Research acceleration

Predicting a single outcome ignores this plurality.

Evaluating AI Claims

When encountering claims about AI in education, ask:

1. Who benefits? (Now Me? Now Us? Future Me? Future Us?)
2. Who pays? (Not just money—what do students, teachers, communities give up?)
3. What's the theory of change? (How does this tool create the claimed benefit?)
4. What's the counterfactual? (What if we invested the same resources differently?)
5. What's the structural interest? (Who funded this? What do they gain?)

Why This Matters

For Educators

• Resist pressure for quick wins that lock in harmful systems
• Consider long-term flourishing, not just immediate efficiency
• Remember: you have agency in how tools are implemented

For Researchers

• Avoid universal claims about AI effects
• Study local implementations and contextual factors
• Attend to power, capital, and structural interests

For Policy

• Recognize plurality of contexts and needs
• Resist one-size-fits-all mandates
• Center long-term flourishing over short-term metrics

Open Questions

• How do we make "Future Us" considerations visible in immediate decision-making?
• What institutional structures support long-term thinking about AI?
• How do we distinguish genuine innovation from capital-driven disruption?
• What would AI integration look like if it centered human flourishing rather than efficiency?

Key Formulations (Preserve These)

"The future of AI and education will not be singular but plural, consisting of many different use cases."

"AI is created by billionaires and fund managers with capital—these are the forces working to change what education means."

"It is not the tool, it is the artist who sparks the revolution."

"Quick wins that entrench systems may mitigate against human flourishing over the longer term."

"What about Future Us?"