Education Futures

What if education wasn't about delivering content, but about preparing young people for human flourishing in the age of AI?

In this episode of Education Futures, Svenia Busson sits down with one of the earliest visionaries on AI in K-12: Babak Mostaghimi. Back in 2019, long before ChatGPT, he convinced one of the largest school districts in the US that AI would be a Netflix-style disruption for education. The result: an AI Readiness Framework rolled out across 142 schools and 180,000 students.

Today, he's pushing the boundaries even further, working to re-architect the entire American public education system around human development.

In this conversation, we explore:

• How a McKinsey Global Institute report sparked an early AI bet inside the 11th-largest US school district
• The "Swim, Snorkel, Scuba Dive" metaphor for AI literacy across K-12
• Why human and durable skills (not prompt engineering) should be the foundation
• Why we should flip the script: "soft knowledge, hard skills"
• His top 5 skills for the age of AI: discernment, compassion, interest, relational intelligence, and creativity
• The "blockbuster vs. Netflix" moment facing public education today
• How to design assessment in the background of meaningful work, not as stop-and-test exams
• Why de-skilling is real, and why the answer is redesigning learning and not banning AI

A hopeful, deeply systemic conversation about the architecture we'll need to build the future of learning we actually want.

Links & references mentioned in this episode:

• Learner Studio (where Babak now works alongside CEO Kim Smith): https://learnerstudio.org
• Gwinnett County Public Schools (where the AI Readiness Framework was developed): https://www.gcpsk12.org
• The Forest School (Atlanta) & Institute for Self-Directed Learning, founded by Tyler Thigpen: https://www.theforest.school. Their last report can be found here: https://www.selfdirect.school/futureeducator
• Teach for all: https://teachforall.org/ & Teach For America: https://www.teachforamerica.org
• McKinsey Global Institute report on automation & jobs (referenced from 2017): https://www.mckinsey.com/mgi/our-research/jobs-lost-jobs-gained-what-the-future-of-work-will-mean-for-jobs-skills-and-wages
• Isabel Hau (Stanford) on relational intelligence (cited as inspiration for one of his top 5 skills): https://isabellehau.com

What does education need to become when AI can replicate most of our cognitive abilities, and what human skills must we protect, develop, and teach now, before it's too late?

In this episode, Svenia Busson sits down with Delphine Le Serre, engineer turned behavioral scientist, founder of EdHu 2050 and creator of the MOON Pedagogy.

After starting her career in microelectronics, Delphine gave her first university lecture in 2005, and never looked back. When COVID-19 hit, she realized education needed a radical rethink and founded EdHu 2050, a non-profit think tank based in Montreal that guides universities, school boards, and ministries of education through the AI transformation.

At the heart of her work is the MOON Pedagogy, a holistic educational framework built around four pillars: Me with Myself (intrapersonal socio-emotional intelligence), Me with Others (empathy, non-violent communication, and collaboration), Me with Intelligent Objects (AI literacy, often taught without any screens), and Me with Nature (reconnecting children with the natural world).

They also discuss how the shape of organizations is shifting, why human skills are the real currency of the future, and what parents and teachers can do today to raise children ready for 2050.

Delphine is building the first Moon School, set to open in Toronto in 2027.

🔗 edhu2050.com

🔗 HUMANES education summit in Montreal: https://www.humaneducationsummit.com/

🔗 Delphine's Linkedin: https://www.linkedin.com/in/delphineleserre/

What can Socrates teach us about artificial intelligence? In this episode, Svenia Busson sits down with Alexander Montag, a scholar of ancient Greek philosophy finishing his doctorate at Tulane University, and soon to teach at St. John's University in New York as well as to conduct research at the New School for Social Research. Together they explore the concept of Socratic dialogue.

We unpack what Socratic dialogue actually means, drawing on some of Plato's most important texts, the Lysis (on friendship and the teacher-student relationship), the Theaetetus and its sequel the Sophist (on knowledge, truth, and the pretender to wisdom), and the Phaedrus (on the dangers of writing itself).

Together, they ask: Is AI the new sophist — a convincing pretender to wisdom that can mimic the form of dialogue without ever truly seeking the truth?

What does AI sycophancy do to our capacity to think?

Can AI ever occupy the role of a teacher we admire and want to emulate?

And what happens to philosophical education — and the sacred long-form essay — in a world where students have access to LLMs around the clock?

We also dive into the question of teaching philosophy from an early age, the value of interdisciplinary thinking over disciplinary silos, and what every technological revolution — from writing to agriculture to AI — forces us to confront: what does it mean to be human?

A rich, timely, and genuinely Socratic conversation.

References & Resources mentioned:

• Plato's Lysis — on friendship and the student-teacher relationship
• Plato's Theaetetus and Sophist — on knowledge, truth, and the sophist as pretender
• Plato's Phaedrus — on writing, memory, and dialogue
• Tulane University — where our guest completed his doctorate
• St. John's University, New York — where he will be teaching
• The New School for Social Research — where he will be a visiting researcher

What if teachers stopped being passive consumers of AI, and started shaping how it's built?

In this episode, Svenia Busson sits down with Stephen Jull a true EdTech veteran who started his career teaching in the remote woodlands of Northern Canada, went on to co-found GeoGebra GmbH — the free dynamic mathematics software that reached over 500 million users worldwide — and now leads EdTech and AI strategy at Teach for All, the global 60+ country network founded by Wendy Kopp, who also founded Teach for America over three decades ago.

At the heart of this conversation is the AI Literacy and Creator Collective (AI LCC) — a program launched in partnership with Anthropic — that brings together nearly 2,000 educators from across the world to move from being "done to" by AI, to actually co-architecting how frontier models are developed and deployed in classrooms.

More about the AI LCC here: https://www.anthropic.com/news/anthropic-teach-for-all

We explore:

• How GeoGebra scaled to 500M+ users with no ads, no data collection, and a mission-driven business model
• Why Teach for All's 2-year fellowship model is more relevant than ever in the AI era
• What the AI Literacy and Creator Collective actually looks like in practice — and why it rejects the traditional top-down training model
• Why working exclusively with free AI models is central to ensuring equity and scale across 60+ countries
• Whether our guest is, at heart, an optimist about AI's impact on children's ability to learn and think

What does it actually look like when a higher education institution takes AI seriously, as something to integrate into the very design of how students learn, are assessed, and grow?

In this episode, Svenia Busson sits down with the founder of Forward College, Boris Walbaum, who walks us through one of the most concrete and thoughtful AI-in-education frameworks we've encountered. From an in-house AI Hub giving students access to all major models, to an AI Mirror dashboard that maps how each student is using AI (memorising, getting feedback, or — the red flag — offloading higher-order thinking to the machine), to an AI Journal where students log and defend their AI strategy on every assignment, this is what AI-integrated learning can actually look like in practice.

We also dig into the bigger philosophical shift behind it: why "excellence" itself is being redefined in a world moving from certainty to uncertainty, why the appetite for learning is collapsing among teenagers, and why investing in deep skills — cognitive, social, emotional and practical — is the only no-regret move in a world where technical skills become obsolete every few years.

A must-listen for anyone in higher education.

Resources & references mentioned in this episode:

• Boris's book Excellence Isn't What You Think – https://www.amazon.com/Excellence-Isnt-What-You-Think-ebook/dp/B0GG9TMHC2
• Forward College – https://forward-college.eu/
• London School of Economics (academic partner) – https://www.lse.ac.uk
• King's College London (academic partner) – https://www.kcl.ac.uk
• An Avalanche is Coming report (Michael Barber, IPPR, 2013) – https://www.ippr.org/articles/an-avalanche-is-coming-higher-education-and-the-revolution-ahead
• Noise by Daniel Kahneman, Olivier Sibony & Cass Sunstein – https://www.hachettebookgroup.com/titles/daniel-kahneman/noise/9780316451383/
• Paul LeBlanc (President of Forward College's Academic Council, former SNHU President) – https://www.paul-leblanc.com
• McKinsey "no-regret moves" framing – https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/strategy-under-uncertainty

In this episode of Education Futures, Svenia Busson sits down with Pilyoung Kim, Professor of Psychology at the University of Denver and Director of the Center for Brain, AI, and Child (BAIC). Pilyoung's research bridges developmental science and AI design to understand how generative AI is shaping the social, emotional, and neural development of children.

We dive into:

• Why general-purpose chatbots were never designed with children in mind — and what that means for safety
• What happens inside a kindergartener's brain when they talk to ChatGPT (spoiler: the same brain region that lights up when they talk to another human)
• The paradox of AI as mental health support: accessible, affordable… and quietly dangerous
• Why sycophantic, "I care about you" chatbot behavior can blur the line between human and machine
• The rise of emotional over-dependency and even romantic relationships between adolescents and AI
• Pilyoung's Social and Emotional AI Literacy Framework for teachers, parents, and school psychologists
• Concrete prompts you can use right now to make AI chatbots safer for kids
• What Pilyoung learned at OpenAI and on Capitol Hill about the future of AI policy for children

A must-listen for educators, parents, researchers, and anyone building technology for the next generation.

Links & references mentioned in the episode:

• Follow Pilyoung Kim on Linkedin: www.linkedin.com/in/pilyoung-kim
• Pilyoung Kim at the University of Denver: https://liberalarts.du.edu/about/people/pilyoung-kim
• Center for Brain, AI, and Child (BAIC): https://www.baic.center/
• Pilyoung's Substack newsletter "Brain, AI, Child" (with prompt examples for teachers): https://pilyoung.substack.com/
• Pilyoung's study on kindergarteners' brain activation during storytelling with ChatGPT: https://pilyoung.substack.com/p/how-do-young-childrens-brains-respond
• Pilyoung's Capitol Hill briefing on AI & youth mental health: https://pilyoung.substack.com/p/bringing-ai-safety-and-child-development
• Society for Research in Child Development (SRCD): https://www.srcd.org/
• The Rithm Project – "Youth, AI, and the Relationships That Shape Them" report: https://www.therithmproject.org/research

In this episode of Education Futures, Svenia Busson sits down with the founder of the Safe AI for Children Alliance, Tara Steele, a former intelligence officer who spent a decade assessing long-term risks before turning her attention to one of the most urgent and least-discussed issues of our time: the impact of AI on children.

From conversational AI optimized for intimacy (not just attention) to deepfakes, AI companions, and the tragic real-world harms already documented, our guest walks us through what parents, educators, and policymakers need to understand right now. She shares the Alliance's three non-negotiables for AI design, explains why schools shouldn't have to shoulder this responsibility alone, and offers a surprisingly hopeful message: the sense of "inevitability" around AI harms is itself the biggest obstacle to change.

A wake-up call and a roadmap for anyone who cares about how children grow up in an AI-saturated world.

In this conversation:

• From intelligence officer to AI safety advocate
• The three non-negotiables every AI system should meet before reaching children
• Why conversational AI is fundamentally different from social media
• The risks of AI companions, AI tutors, and chatbots in classrooms
• Raising children in an AI world: practical advice for parents
• The Meta accountability case and the shifting tide in US courts
• Why "inevitability" is the biggest trap — and what collective action can still achieve

Resources & links mentioned:

• Safe AI for Children Alliance → https://www.safeaiforchildren.org
• Free guide for schools and educators (on the Alliance's website) → https://www.safeaiforchildren.org
• The Alliance's three non-negotiables campaign: AI should never produce sexualised images of children, create emotional dependency, or encourage self-harm, full campaign on the Alliance's site
• Recent US legal cases on big-tech accountability for harms to children (referenced around the 28-minute mark, including the Meta case) https://www.bbc.com/news/articles/c747x7gz249o

What happens when millions of children start talking to LLMs every day and no one knows whether it's safe?

In this episode, Laurent Jolie sits down with Stéphie Herlin, co-founder and Research & Product Lead at KORA, the first independent, non-profit, open-source benchmark measuring how safe LLMs are for children. Before KORA, Stéphie spent 8+ years as a government economist, then moved into education as a policy analyst and teacher — spending nearly five years in a French public classroom with 6- to 10-year-olds while retraining in neuroscience, developmental science and pedagogy.

We talk about why education hasn't had its scientific revolution yet and what precision education could look like; Stéphie's earlier ed-tech project Brio and the tension between engagement-first investors and outcomes-first science; how KORA works (generating conversations between synthetic child profiles and real LLMs, judged against a taxonomy of 25 risks / 8 categories co-built with ~30 experts); the first results (average safety ~44%, ranging 13–78%, with some models regressing over time); why educational integrity is the industry's biggest blind spot (about a third of US kids use LLMs every day); a simple tip for parents (telling the model your child is a child improves safety by ~10 percentage points across every model tested); why LLMs still hallucinate ~20% of the time; and how any ed-tech builder can run KORA on their own conversational product today, for free.

KORA (the benchmark)

• Introducing KORA (blog)
• Open-source benchmark on GitHub
• Launch post by Mathilde Collin
• Deep-dive on KORA (EdTech Partnerships)
• Conversation with Mathilde Collin about KORA (Opportunity Knocks)

People mentioned

• Mathilde Collin (co-founder of KORA)
• Isabelle Hau — Stanford Accelerator for Learning · personal site
• Love to Learn by Isabelle Hau (Hachette) · Stanford Report feature
• Jonathan Banon — Ed.ai

In this episode, Svenia Busson sits down with Wess Trabelsi, a Tech Integration Specialist at Ulster BOCES in New York, where he supports eight rural school districts. Wess is neither a cheerleader nor a doomsayer when it comes to AI in education, he's something rarer: an evidence-driven practitioner who actually read the research.

Wess shares his deep dive into the science (or lack thereof) behind AI in K-12. After reviewing over 100 studies, he found that the vast majority are noise, glorified surveys, opinion pieces, and what he calls "dead horse studies" that prove the obvious. His findings closely mirror those of the Stanford AI Hub for Education's newly released 2026 Review, which started with 800 studies and kept only 20 with strong causal evidence, and found zero conducted in U.S. K-12 settings.

Together, Svenia and Wess unpack the two most significant studies to date: the Harvard RCT showing a custom AI tutor significantly helped motivated physics students, and the landmark Wharton/Turkey study showing that AI-assisted practice gains completely disappeared when AI was removed at test time. Neither provides a clear playbook for the average classroom.

But the conversation goes much deeper. Wess makes the case that AI didn't create a problem in educatio, it merely exposed one that was already there, putting "the final nail in the coffin of the traditional model." He advocates for process-based and project-based learning (citing the inspiring model of High Tech High in California), and for rethinking assessment entirely, away from written essays as proxies for thinking, toward conversation, video, and authentic real-world problem-solving through work-based learning.

If you've been overwhelmed by AI headlines in education and wished someone would just tell you what the evidence actually says, this episode is for you.

Resources mentioned in this episode:

• 📄 The Evidence Base on AI in K-12: A 2026 Review — Stanford AI Hub for Education (PDF)
• ✍️ The Good, the Bad, and the Ugly Science of AI in Education — Wess Trabelsi (Substack)
• 🎓 High Tech High — San Diego, California (school that does PBL)
• 📖 Superintelligence by Nick Bostrom · Works by Ray Kurzweil

Substack writers recommended by Wess:

• Mike Taubman — AI Waypoints
• Stephen Fitzpatrick — Teaching in the Age of AI
• Mike Kentz — How We Frame Machines

In this episode of Education Futures, Svenia Busson is joined by Michaela Horvathova, founder of Beyond Education and former policy analyst at the OECD.

For more than a decade, Michaela has worked on an important and misunderstood challenge in education: how to define, develop, and assess metacognition and soft skills.

As AI makes knowledge abundant and easily accessible, these competencies are becoming essential. Yet across most education systems, they remain poorly defined, inconsistently taught, and rarely measured.

In this conversation, we explore:

• Why we still lack a shared definition and taxonomy of soft skills

• Why what gets measured and graded still determines what gets taught

• The gap between policy ambition and classroom reality

• How the Four-Dimensional Education Framework (knowledge, skills, character, meta-learning) helps structure these competencies

• Why metacognition (learning how to learn) is becoming a foundational skill

• The risks of cognitive offloading and the emergence of a “cognitive divide”

• Why assessment must shift from outputs to thinking processes

We also discuss how schools can move toward competency-based models, drawing on Michaela’s work at Beyond International School.

The challenge is not just to talk about soft skills, but to define them clearly, prioritize them, and measure them in ways that truly reflect how humans learn.

To explore further what was discussed in the episode:

https://beyondeducation.tech/

https://curriculumredesign.org/4-dimensions/