Education Futures

Justin Reich is an Associate Professor at MIT and Director of the MIT Teaching Systems Lab, author of Failure to Disrupt (Harvard University Press), host of the TeachLab podcast, and the force behind The Homework Machine — a landmark 7-part podcast series investigating what's really happening with AI in classrooms across the US.

We asked him, one of the most respected education technology researchers in the world a simple question: how should schools teach students to use AI?

His answer? We don't know yet, and pretending we do is the problem.

In this conversation with Svenia Busson, Justin explores:

• Why "AI literacy" follows the same broken playbook as digital citizenship and computational thinking — and will likely fail students the same way
• What the history of web literacy teaches us: it took 25 years to find strategies that actually work
• Why domain expertise — not AI knowledge — may be the most critical factor in using AI well
• What to make of "AI-powered" schools like Alpha School
• What students themselves are saying: two-thirds of US students say AI is harming their critical thinking
• Why "the homework machine" is the most honest name for what's happening in classrooms today

Also mentioned in this episode:

• Mike Caulfield's SIFT framework for teaching web literacy: https://guides.lib.uchicago.edu/c.php?g=1241077&p=9082322
• A Guide to AI in Schools: Perspectives for the Perplexed — MIT Teaching Systems Lab guidebook (August 2025) https://tsl.mit.edu/wp-content/uploads/2025/08/GuideToAIInSchools.pdf
• "Stop Pretending to Know How to Teach AI" — Justin's article in the Chronicle of Higher Education (November 2025) https://www.chronicle.com/article/stop-pretending-you-know-how-to-teach-ai
• The Homework Machine podcast: https://podcasts.apple.com/us/podcast/the-homework-machine-what-ai-is-really-doing-in-classrooms/id583456652?i=1000747231954 (a must listen)

What does it actually take to know if an AI tutor is helping kids learn? Bibi Groot, Chief Impact Officer at Eedi Labs, has spent her career answering exactly that question — first at the Behavioral Insights Team (aka the Nudge Unit, co-founded with Nobel laureate Richard Thaler), then in classrooms across the UK and Latin America.

In this episode, Bibi walks us through how Eedi's diagnostic engine works — 60,000 carefully designed multiple-choice questions, each distractor linked to a specific misconception — and why understanding why a student gets something wrong matters as much as knowing they got it wrong.

Bibi also introduces a concept that should alarm everyone in edtech: cognitive surrender — the risk that when AI does all the thinking, students stop learning altogether. Her solution is architectural: don't ask students to self-regulate, build the constraints directly into the system. She references a striking study by Poulidis and Bastani on chess students — those who received AI hints at system-chosen moments improved 64% vs. only 30% for those who could ask for help whenever they wanted.

This is a rare, rigorously evidence-based conversation about what responsible AI tutoring actually looks like — and how far most of the field still has to go.

References mentioned in this episode:

• Behavioral Insights Team (the Nudge Unit)
• Eedi Labs — including the free Eedi School platform
• Google DeepMind's LearnLM
• Learning Engineering Virtual Institute (LEVI) — created by Schmidt Futures & Renaissance Philanthropy
• David Yeager, 10 to 25: The Science of Motivating Young People
• AI Hub for Education (Stanford) — reviewed 800+ papers on AI in education; only 20 had causal evidence
• Poulidis & Bastani chess study (system-chosen AI hints → 64% improvement vs. 30% for on-demand help)
• London EdTech Week — Meet Bibi & Svenia at the London AI & Education Meetup on June 18, 2026

Anne-Sophie is the co-founder and Executive Director of everyone.ai, a Silicon Valley nonprofit bridging artificial intelligence and developmental neuroscience. She is also the Chief Program Officer of iRAISE (International Research-driven Alliance for AI Serving Every child), the global coalition she launched at the Paris AI Action Summit alongside 11 governments, UNESCO, UNICEF, and companies including OpenAI, Anthropic, and Google.

In this episode, she and Svenia explore why children's brains are not mini adult brains, and why that changes everything for AI design. They discuss the critical developmental windows AI is currently disrupting (0–6 for language acquisition; 12–14 for social skills development), what the research on teenagers and anthropomorphic AI actually shows, and where the line is between AI as a scaffold and AI as a crutch. Anne-Sophie also shares the story of how iRAISE was built in just three months, what a "proactive" approach to AI safety looks like in practice, and why regulating AI is actually easier when children are the focus.

She also previews the AI Safety Builder, a new science-backed tool launching at VivaTech that helps EdTech founders evaluate how their conversational AI interacts with children, detecting anthropomorphic, interactional, and relational risk cues based on the work of 30+ researchers.

Resources mentioned:

• everyone.ai — nonprofit at the intersection of AI and child development
• iRAISE Coalition — launched at the Paris AI Action Summit (February 2025) https://parispeaceforum.org/initiatives/beneficial-ai-for-children-coalition/
• Research: "Adolescents & Anthropomorphic AI: Rethinking Design for Wellbeing" https://everyone.ai/wp-content/uploads/2026/02/Adolescents-Anthropomorphic-AI-Rethinking-Design-for-Wellbeing-.pdf
• Research: "Mapping of generative AI impacts on child development" — mapping of risks and opportunities by age group, contributed to the G7 agenda https://everyone.ai/wp-content/uploads/2026/05/Mapping-of-GenAI-impacts-on-child-development-1.pdf
• Book recommendation: Love to Learn by Isabelle Hau (Stanford) https://www.isabellehau.com/

Kashyap "Kash" Rajesh is 20 years old, a Junior at Cornell University studying Information Science and Government with a minor in AI, and he's been working in AI policy since he was 14.

He supported the founding of Encode, a non-profit originally founded by young people, focused on how AI is impacting the public and particularly the next generation, which grew to 40 states and every inhabited continent. As VP, he helped lead and grow the organization, which advised the White House Office of Science and Technology Policy's AI Bill of Rights and filed an FTC complaint against AI companion app Replika. He now supports the Rithm Project, a research and movement-building org focused on pro-social AI and human connection, and is involved in research at the Cornell Brooks Tech Policy Institute and the JEM Lab for Generative AI at Work.

In this episode, Kash talks with Svenia Busson about:

• Why entry-level jobs may outlast middle management in the AI transition — and what Gen Z should do about it
• The Game Plan playbook Encode created to help Gen Z navigate the future of work (four archetypes: the Sleeper, the Anchor, the Tactician, and the Shaper)
• The loneliness crisis that preceded generative AI — and how AI is amplifying, not creating, it
• The Rithm Project's youth research report identifying nine portraits of how young people relate to AI chatbots
• AI sycophancy — and what it quietly does to a generation's capacity to be wrong
• The wave of state-level AI safety legislation: California's SB 53, the New York RAISE Act, and Illinois House Bill 315
• Why the Take It Down Act matters and how non-consensual deepfake imagery is already a crisis in schools

A rare, honest, and deeply informed voice from inside the generation most affected by AI.

Links mentioned:

• ENCODE https://encodeai.org/
• The Rithm Project: https://www.therithmproject.org/
• Cornell Brooks Tech Policy Institute: https://publicpolicy.cornell.edu/btpi/
• Surgeon General's Advisory on Loneliness and Isolation (2023): https://www.hhs.gov/sites/default/files/surgeon-general-social-connection-advisory.pdf
• California SB 53 / Illinois House Bill 315 / New York RAISE Act

What if AI education wasn't just for engineers and computer scientists, but for every student, regardless of their field? That's exactly the bet Camille Salinesi is making at one of the world's most iconic universities.

Camille is a full professor of computer science at the University of Paris 1 Panthéon-Sorbonne, where he has been based since 1999. A specialist in requirements engineering and applied AI, he has published over 250 peer-reviewed papers. He heads the university's AI Observatory alongside legal scholar Célia Zolynski.

This autumn, he co-launches the Collège de l'IA — France's first undergraduate-level AI diploma designed not for STEM students, but for students in law, history, philosophy, economics, and the arts. The programme, backed by France 2030, will give bachelor students 200 hours of AI training layered on top of their existing degree.

In this conversation with Svenia Busson, Camille discusses:

• Why AI literacy is as urgent for a law student as for a software engineer
• The critical shift in information systems engineering from reliability to trust
• How the Sorbonne is rethinking assessments in the age of AI — and why students themselves are demanding it
• The difference between students who use AI to cheat and those who use it to learn
• What the future of software engineering jobs actually looks like

In this episode, Svenia Busson sits down with Dr. Alex Carter, Associate Professor at the University of Cambridge, Fellow of Fitzwilliam College, and Director of Creativity Research at the Centre for AI Interaction. Alex holds a PhD in philosophy from Essex — with roots in Wittgenstein and the philosophy of language — and has become one of the UK's most provocative thinkers at the intersection of philosophy, creativity, and AI.

His central claim: AI is not creative in the same way we are. Not because it lacks power, but because "AI does not think like us, it thinks like we think we think", it is a mirror of human thought, not thought itself.

In this conversation, we explore:

🔹 Why AI is fundamentally incapable of creativity — and the philosophical argument behind it

🔹 The "race to the middle": as we outsource our thinking to AI, humans get slightly worse while AI appears slightly better, and we meet at mediocrity

🔹 Why education systems have been "teaching algorithmically" for decades — long before ChatGPT. AI didn't create the problem; it just made it impossible to ignore

🔹 Why AI should make problems for students, not solve them — and what "friction maxing" means for learning

🔹 The Gartner Hype Cycle and why reaching the "plateau of productivity" requires a complete rethink of education

🔹 The Durham Commission on Creativity (2001) — and why 25 years later, nothing has changed in the UK 🔹 What consciousness really is — and why even the engineers building AI don't fully understand what they've made

🔹 Why philosophy should be the connective tissue of every discipline — and why we need more philosophy, not more philosophers

References & links mentioned in this episode:

• Alex's website: adcphilosophy.com
• The Durham Commission on Creativity and Education: https://www.artscouncil.org.uk/sites/default/files/download-file/Durham_Commission_on_Creativity_04112019_0.pdf
• The Gartner Hype Cycle
• PISA — now updated to include a creativity assessment (https://www.oecd.org/en/topics/student-performance-pisa.html)
• Bill Lucas on creativity skills and perseverance
• Simone Weil — French philosopher referenced on personalized learning
• Philosophy for Children (P4C) by Thoughtful and the PLATO organization

Dr. Asyia Kazmi, OBE spent 12 years teaching mathematics in some of London's toughest schools, and she loved every minute of it. She went on to advise the UK government, work at PwC, lead Global Education Policy at the Gates Foundation, and is now CEO of WISE (World Innovation Summit for Education, https://www.wise-qatar.org/), a Qatar Foundation initiative that convenes the world's leading minds to solve education's hardest problems.

In this conversation with Svenia Busson, recorded live in Paris, Asyia shares what the classroom taught her that no policy document ever could and how that foundation shapes every investment decision, every programme she designs, and her vision for the school of the future.

We explore:

— What it really means to measure learning, and why waiting 2–3 years for impact evaluations is simply unacceptable

— How she built an AI and EdTech portfolio at the Gates Foundation that significantly improved the learning of 2.5 million children across India and Sub-Saharan Africa, working with partners like Central Square Foundation, Fab Inc, and EIDU.

— What she looks for when evaluating an EdTech product (from pedagogical rigour to data protection for children)

— Why teachers are irreplaceable (and how AI might free them to do what only humans can do)

— Why motivation may become the new inequity divider in an AI-powered world

— Her instinctive vision of a future-proof school, built for the most underserved communities

— The WISE Prize — a $1M+ prize open to established education organisations ready to test bold new ideas. Applications close 27 June 2026 (go check it out here: https://www.wise-qatar.org/innovation/wise-prize-for-education)

Organisations & people Asyia recommends exploring:

The Citizens Foundation, Pakistan — CEO: Zia Akhter Abbas (2,500+ schools for underserved communities)

Pratham Education Foundation— Rukmini Banerji

Madhi Foundation — Merlia Shaukat

Language and Learning Foundation — Dr. Dhir Jhingran

Human Capital Africa — Dr. Oby Ezekwesili, former Minister of Education of Nigeria and co-founder of Transparency International

EEDI (for maths) https://www.eedischool.com/us

EIDU (foundational literacy and numeracy in Africa) https://www.eidu.com/

Linda Liukas spent her early career surrounded by engineers in Silicon Valley, working at Codecademy and dreaming of a different kind of computer science education — one that felt tangible, joyful, and human. In 2014, she launched a Kickstarter for Hello Ruby, a children's storybook teaching the big ideas of computer science through characters and storytelling. She asked for $10,000. She got nearly $400,000 — and a community of 10,000 believers.

Since then, Linda has been doing exactly that: making computer science accessible to children through picture books, drawing workshops, and — most recently — computational playgrounds. The first one, a six-meter-tall computer you can actually crawl through, opened in Helsinki two years ago. More are being built across Europe, each one locally designed, intensely participative, and built to last 20 years.

In this episode, Linda and Svenia discuss:

• Why "learn to code was never about learning to code" — and what it was really about
• Why, in the age of AI, teaching the foundations of computer science matters more than ever (not prompting, not tools — the underlying ideas)
• How she designs computational playgrounds that make technology learnable through the body
• The Reggio Emilia philosophy — and why she turns to it whenever she feels lost in the noise around AI
• Lessons from the Finnish education system — its rise, its PISA scores, and the worrying trends (Pasi Sahlberg's work for those who want to go deeper)
• What three things the French education system is teaching her son that will serve him well in the age of AI

Linda also recommends a future guest: Annabel Blake, an Australian researcher who has done fascinating PhD work on young people and AI companions — neither pessimist nor optimist, but deeply nuanced: https://www.annabelblake.com/

If you missed it, we also refer to our Episode 37 with philosopher Alex Montag on Socratic dialogue — well worth a listen: https://podcasts.apple.com/us/podcast/socratic-dialogue-in-the-age-of-ai/id1847420474?i=1000767131871

What skills will remain irreplaceable as AI takes over more and more of the work we do? That's the question that led Rahim Hirji to write SuperSkills — a book about the human capabilities that will define who thrives in the age of AI.

Rahim has spent over two decades at the intersection of technology and education. He ran Maths Doctor, one of the UK's first online tutoring businesses. He co-founded EtonX, which brought soft skills education to students across China and beyond. He then joined Quizlet to lead its international growth, and served as Executive Vice-President at Avallain, a Switzerland-based learning platform. He is now advising AI and EdTech businesses. He is also a school governor at Channing School in North London.

In this episode, Rahim walks us through his SuperSkills Ladder, a framework that goes from survival skills all the way up to what he calls the 7 super skills: curiosity, change readiness, big picture thinking, principled innovation, empathy, global adaptability, and the augmented mindset. His research draws on the findings of the World Economic Forum and McKinsey on the future of work. He explains why the "specialist skills" layer — the vocational knowledge we've spent careers building — is the one being disrupted hardest by AI, and why developing super skills is now an urgent priority for anyone in the workforce.

We also explore what it means to raise teenagers in the age of AI (including Rahim's own hard rule with his 14-year-old), why school curricula need a fundamental redesign, and why the augmented mindset — knowing when to use AI versus when to think for yourself first — may be the most important skill of all.

Go further:

https://superskillsbook.com/ - Rahim's book, pre-order it now!

https://www.thesuperskills.com/about - more about Rahim

https://www.linkedin.com/pulse/what-i-tell-kids-ai-rahim-hirji-bs5re/ - His article "What I Tell Kids About AI"

https://www.linkedin.com/pulse/what-i-tell-parents-ai-rahim-hirji-mcurf/ - His article "What I Tell Parents About AI"

https://boxofamazing.substack.com/ - Rahim's substack

What separates an AI companion from an AI agent? And when does a "sticky" learning app actually make you smarter?

In this episode, Svenia Busson sits down with Rhys Spence, Head of Research & Platform at Brighteye Ventures — one of Europe's leading EdTech and future-of-work VC funds, with over €220 million under management.

Rhys shares the key insights from Brighteye's report Me, Myself and My AI: The Rise of AI Companions, exploring how AI companions are reshaping education, health, and finance — and why vertical, regulated tools are safer and more defensible than general-purpose AI. They also dig into the role of behavioral science in making people genuinely want to learn, the tension between product stickiness and real learning outcomes, the rise of VR and smart glasses in vocational training (cutting qualification times by up to 99%), and Rhys's "Fix the Pothole" thesis: why AI should rebuild broken systems from the ground up, not layer efficiency gains on top of them. Rhys also shares what Brighteye Ventures is actively looking for from early-stage EdTech founders today — and what it means to invest for impact without being an impact fund.

To go further:

Me, Myself, and My AI - the rise of AI companions: https://www.brighteyevc.com/sidekick-posts/me-myself-and-my-ai---the-rise-of-ai-companions

Brighteye Ventures: https://www.brighteyevc.com/

Rhys Spence on Linkedin: https://www.linkedin.com/in/rhys-spence/

https://www.brighteyevc.com/sidekick-posts/fix-the-pothole (Blog post about the Fix the Pothole reference)