Education Futures

AI is already in classrooms. The real question is: who is responsible for governing it?

In this episode of Education Futures, Svenia Busson sits down with Clara Hawking, founder of Kompass Education, to explore what AI governance actually means for schools and educators.

As governments roll out new regulations, including the EU AI Act, schools are facing urgent questions around compliance, safety, privacy, and responsibility. But governance is not just about following the law. It is about building trust, protecting children, and making intentional decisions about how AI enters learning environments.

In our conversation, we explore:

• What “AI governance” really means in practice
• How the EU AI Act impacts schools and educational organizations
• Why individual teacher subscriptions to AI tools can create legal and safety risks
• The difference between AI literacy and AI safety
• Why students are hesitant to admit how they use AI
• The growing cognitive dependency concerns for Generation Alpha
• And what a more human-centered, collaborative school of 2040 could look like

Clara makes a compelling case: AI adoption without governance is not innovation, it is risk.

For listeners interested in evaluating AI tools from a child safety perspective, we also mention Kora (https://korabench.ai/), a new initiative that benchmarks large language models on child safety criteria.

Follow Clara on Linkedin for more content around these topics: https://www.linkedin.com/in/clara-hawking-ba9123149/

In this episode of Education Futures, host Svenia Busson sits down with Ken Shelton, a 20-year teaching veteran and global thought leader in educational technology. Drawing from his experience working with schools in over 50 countries, Ken challenges the "all gas, no brakes" approach to AI, as well as the knee-jerk "ban and block" mentality seen in many governments.

Key topics discussed in this episode include:

• The Digital Equity "Quilt": Why digital equity is about much more than just providing a device, it’s about broadband infrastructure, "digital redlining," and the quality of the platforms being used.
• The Problem with Efficiency: A critique of the AI marketing trend that focuses on "grading faster" at the expense of pedagogical efficacy and meaningful feedback.
• AI as a Truth-Teller: How AI hasn't necessarily created "cheating" problems, but has instead highlighted ineffective and antiquated forms of assessment like multiple-choice tests.
• Practical Pedagogy: Ken's "Golden Rule" for AI (More Context = Better Output) and how teachers can use Project Zero thinking routines to "AI-proof" learning.
• Confronting Bias: Engaging activities to help students and teachers identify the human-generated biases embedded in image generators and LLMs.
• The School of 2040: Ken’s vision for a future-ready education system that prioritizes lifelong intellectual curiosity, multilingualism, and media literacy over static curriculum.

Ken reminds us that while the platforms may change, the skill sets required to navigate them: critical thinking, ethical leadership, and human-centered design, are evergreen.

In this episode of Education Futures, we explore the "AI Leap"—Estonia's ambitious national strategy to roll out a specialized version of OpenAI across the entire country. Our guest, Jaan, is a neuroscientist and psychologist at the University of Tartu who is leading the scientific team overseeing and evaluating this project.

Unlike standard implementations, Estonia has collaborated with OpenAI to create a custom, pedagogically driven tutor that prioritizes active learning . Jaan explains why this system is designed to stop and ask questions rather than simply providing answers, ensuring that students continue to construct knowledge in their own brains

In our conversation, we explore:

• The Pedagogical Tutor: Why Estonia rejected the standard ChatGPT EDU in favor of a model that mimics a Socratic tutor .
• Brain Literacy vs. AI Literacy: The importance of teaching students why mental effort and friction are mandatory for long-term learning .
• Teacher Autonomy: How Estonia’s culture of trust allows teachers to lead the AI transition without rigid, top-down supervision .
• Measuring What Matters: Why the research team is moving beyond "overrated" grades to track more granular aspects of the learning process.
• The "Safe to Fail" Environment: How AI can scale the ability for students to make mistakes and receive gentle, honest feedback .

More about the AI leap strategy: https://e-estonia.com/ai-leap-2025-estonia-sets-ai-standard-in-education/

A great interview of Jaan on the OpenAI rollout: https://tihupe.ee/en/ai-researcher-thinking-for-oneself-is-the-only-way-to-be-free-and-in-control/

In this episode of Education Futures, host Svenia Busson sits down with Alex Sarlin, the founder of EdTech Insiders and Global Edtech lead at the ASU GSV Summit . With over 15 years of experience at giants like Coursera and Skillshare, Alex provides a masterclass on where learning is headed in the age of generative AI.

Alex challenges the dystopian view of AI as an isolating force, arguing instead that it will serve as a "motivational translator" and a facilitator for deeper human relationships within schools . We dive into the psychological traits students need to thrive—focusing on metacognition and agility rather than specific technical tools—and discuss the "race against time" the industry faces to prove its value before a significant cultural backlash takes root .

• The School of the Future: How AI will facilitate small group instruction and peer matchmaking rather than just individual screen time .
• Survival Skills for 2036: Why "learning how to learn" is the only durable skill in an asymptotic technological curve .
• Founder Wisdom: Why entrepreneurs should avoid "frothy" markets like generic AI language apps and look for underserved niches like accessibility compliance or specialized education .
• ASU GSV Summit: A preview of the "meeting of the minds" happening in San Diego this April.

In this episode, we sit down with François Taddei, Chief Exploration Officer of the Learning Planet Institute, to discuss the radical shifts needed in global education. François shares his vision of "ethical dream-weaving"—the process of building futures that are a nightmare for no one—and argues that in a world of polycrisis, hope and collective wisdom are the only tools that can truly scale.

• The Ethical Dreamer: François describes himself as a weaver of ethical dreams. He explains how we must balance the "nightmares" built by those in power by meeting fellow dreamers to co-create a better world.
• Intergenerational Co-design: Why should decisions about the future be made only by those who won't live to see them? François points out that while 50% of the population is under 30, they hold only 1% of decision-making power. He advocates for involving students in co-designing everything from their buildings to their curricula.
• Education as the "Midwife" of Democracy: Drawing on John Dewey, the discussion explores how education must help democracy be born anew in every generation. We look at the history of democratic "fractals"—from city-states to nations—and why we now need a planetary democracy to manage our shared commons.
• AI and the Humanity Loop: Rather than delegating thinking to machines, François suggests we use AI to analyze complex "dream spaces" and find consensus among 10 billion people. However, he warns that the most vital human skills—managing emotions, mourning, and finding hope—cannot be learned from an algorithm.
• The Power of Hope: Referencing young activist Francisco Vera, François concludes that hope is the last thing we can afford to lose. Even if systems collapse, hope allows a generation to rebuild, reinvent, and co-create alternatives.

• Learning Planet Institute: An interdisciplinary center co-designed by students.
• The UN Pact for the Future: A commitment to making decisions in the best interest of future generations.
• Planetary Commons: The three types of commons we must protect: Natural, Human-made, and Digital.
• Aristotle's Three Forms of Knowledge: Episteme (science), Tekne (technology), and Phronesis (the ethics of action).

AI in education is evolving at a pace that often overwhelms teachers, school leaders, and policymakers. New tools appear weekly. Research lags behind practice. Hype fills the gap.

So how do we make good decisions when certainty is impossible?

In this episode of Education Futures, Svenia is joined by Chris Agnew, who leads the AI Hub for Education at the Stanford Accelerator for Learning.

Chris brings a rare perspective to the AI conversation. With a background in environmental and experiential education, from outdoor classrooms to apprenticeship-based learning, he has spent decades trying to bridge relevance, rigor, and access. Today, his role is to translate cutting-edge AI research into practical guidance for superintendents, state leaders, and education systems making decisions right now.

In our conversation, we explore:

• Why the biggest challenge is not innovation, but sense-making
• How the speed of AI creates noise, confusion, and decision paralysis
• The persistent research-to-practice gap, and why it’s even harder with AI
• What current evidence actually tells us (and doesn’t) about AI in K–12
• Why most research today shows promise, not certainty
• How leaders can think in short-cycle experiments instead of long-term predictions
• The difference between using AI for efficiency, outcomes, and reimagining school
• Why personalization has too often turned into isolation, and how AI could help reverse that
• A vision of future schools built around collaboration, real-world learning, and apprenticeship-like experiences

Chris also shares why banning AI from schools is unrealistic, but blindly adopting it is equally risky, and why adult judgment, not student technical skill, will matter most in the years ahead.

This episode is not about finding definitive answers, it’s about building the capacity to learn, adapt, and decide well, even when the future remains uncertain.

Learn more about the hub here: https://scale.stanford.edu/ai

The report The Evidence Base on AI in K-12: A 2026 Review is out now:

https://scale.stanford.edu/sites/default/files/The%20Evidence%20Base%20on%20AI%20in%20K-12%20Report.pdf

In this episode of Education Futures, we welcome Louis Rosenberg — technologist, entrepreneur, and long-time researcher in virtual reality, augmented reality, and artificial intelligence.

Louis has spent decades building technologies designed to augment human intelligence and warning about the risks when we fail to understand what we are building.

In this conversation, we focus on a phenomenon Louis has recently written extensively about: AI denial: society’s tendency to underestimate AI’s capabilities as a way of avoiding an uncomfortable truth.

We explore:

• Why dismissing AI as “just slop” or “just autocomplete” is dangerously outdated
• How AI systems are becoming cognitive rivals, not just tools
• Why humans are especially vulnerable to anthropomorphizing conversational AI
• The concept of asymmetric relationships between humans and AI
• Why photorealistic, conversational AI represents a new and far more powerful form of influence
• How AI may reshape education, work, relationships, and childhood itself
• What skills children actually need to develop in a world of rapid, continuous change
• Why banning AI in schools is not a solution — but neither is naïve adoption

Louis argues that we are repeating the same mistake we made with social media: regulating yesterday’s risks while ignoring tomorrow’s.

He also shares a radically different vision for AI’s future — inspired by swarm intelligence and biomimicry — where AI is used not to replace humans, but to connect groups of people into collective intelligence, keeping human values, judgment, and responsibility at the center.

This episode is a call to move beyond fear and denial — and to educate the next generation with clarity, realism, and agency.

These recent articles are directly referenced in the conversation and provide crucial context:

https://bigthink.com/the-present/the-rise-of-ai-denialism/

https://venturebeat.com/technology/ai-denial-is-becoming-an-enterprise-risk-why-dismissing-slop-obscures-real

https://bigthink.com/the-future/what-happens-the-day-after-humans-create-agi/

What is education actually for, in a world where AI can increasingly do things for us?

In this episode of Education Futures, recorded at the Learning Planet Institute in Paris, we sit down with Seth Frey, professor at UC Davis working at the intersection of computer science, social science, and self-governance.

Seth’s work focuses on a rarely discussed question:

what skills do humans need to run things together — responsibly, collectively, and democratically?

Rather than framing AI as a tool to accelerate productivity or replace learning, Seth argues that AI is an uncomfortable gift: it strips away the superficial parts of education and forces us to confront why we learn in the first place.

In this conversation, we explore:

• Why AI is often used as a substitute for learning, not a support for it
• The crucial difference between formative and summative uses of AI
• Why authenticity and motivation matter more than ever in education
• How peer-to-peer learning reduces reliance on AI shortcuts
• Why meetings, dialogue, and facilitation are learned skills, not inefficiencies
• What it means to educate for stewardship of the commons
• Why responsible technology requires people who can govern together
• How education could shift from credentials to lived, cooperative experience

Seth introduces the idea of a “commoning standard”: a framework for the basic literacies required to steward shared resources — from classrooms and organizations to technologies and communities.

This episode is about re-centering education on agency, responsibility, and collective capacity, and asking what kind of people we need to cultivate before deciding what role AI should play.

What if artificial intelligence isn’t the real threat to higher education?

In this episode of Education Futures, we speak with Michael Burgess, a sharp and uncompromising voice on the future of higher education, to unpack a provocative idea:

Universities don’t have a technology problem, they have a strategy problem.

Michael argues that AI isn’t breaking universities.

It’s revealing what has been broken for a long time.

Together, we explore:

• Why higher education’s operating model hasn’t fundamentally changed for centuries
• How AI is accelerating the exposure of slow, inefficient, and misaligned systems
• Why “AI transformation” is often the wrong framing, and why betterment matters more
• What universities misunderstand about students, industry, and the marketplace
• Why entry-level work, credentialing, and degree length must be rethought
• How innovation is more likely to come from outside universities than within
• What the future of higher education could look like in a plural, AI-enabled world

Michael also explains why most institutions fall in love with shiny tools, layer them onto broken processes, and then wonder why nothing changes, and why real progress starts with courage, clarity, and a willingness to cannibalize parts of the existing model.

Are we really living through the worst moment in history, or are we actually in the best position ever to build a better future?

In this episode of Education Futures, we welcome Beatrice Erkers, Existential Hope Program Manager at the Foresight Institute.

Beatrice works at the intersection of technology, long-term thinking, and societal progress, helping people move beyond doom narratives to imagine desirable futures — and take responsibility for shaping them.

Together, we explore:

• Why pessimism about the future is historically misguided
• How “existential hope” differs from blind optimism
• Why agency matters more than prediction when thinking about the future
• How world-building and scenario planning can help rethink education
• Why education may be the most powerful lever for long-term change
• How AI could make learning more humane — not less
• What skills and mindsets future education systems should prioritize
• Why plural, diverse futures matter more than one “perfect” vision

Beatrice also shares inspiring examples — from AI tutoring models like Alpha School to progress-oriented movements — and explains why hope is inseparable from action.

This episode is an invitation to stop asking “what will happen?”

and start asking “what future do we want to build — and how do we begin now?”