Education Futures

Jenny Anderson is an award-winning journalist and author with 25 years in the field, including a decade covering finance at The New York Times — where she won a Gerald Loeb Award in 2008 for her coverage of Merrill Lynch ahead of the 2008 financial crisis. She later pioneered coverage of the "science of learning" at Quartz, and now contributes to The New York Times, The Atlantic, and The Washington Post. She is the co-author, with Rebecca Winthrop (Director of the Center for Universal Education at Brookings), of The Disengaged Teen: Helping Kids Learn Better, Feel Better, and Live Better (thedisengagedteen.com) — the product of five years of research, including a survey of more than 65,000 students and 2,000 parents conducted with Brookings and Transcend, into why so many children lose their love of learning in adolescence. She writes the weekly Substack newsletter How to Be Brave, reaching tens of thousands of educators and parents. She is a senior fellow at the Center for Teen Flourishing and co-host of Ask the Kids, a podcast with Transcend Education. In this episode, Jenny talks with Svenia Busson about:The disengagement gap — why 75% of kids love school in primary years, but only 25% still do by 10th gradeThe Four Modes framework — Passenger, Achiever, Resistor, and Explorer — and why fewer than 4% of students land in Explorer modeWhy phones and AI aren't the root cause of the teen mental-health crisis — academic pressure consistently ranks higherSchool models built for agency — Big Picture Learning's semester-long internships, Red Bridge School, and Valor Collegiate Academies' "school within a school"Assessment in the age of AI — competency-based learning, portraits of a graduate, and why parents resist abandoning high-stakes exams like the GCSEsThe AI silence at home — why most teens use AI regularly while few talk to their parents about itAI, writing, and "cognitive stunting" — what outsourcing the first draft costs a developing thinker, building on Rebecca Winthrop's NYT piece on AI and creativityWhat parents can actually do — testing the tools themselves, and protecting space for productive struggle

Bethany Koby-Hirschmann is a designer, social entrepreneur, and co-founder and Chief Vision Officer of Fam Studio, a research and design practice based in Somerset, England. She holds a BA from the Rhode Island School of Design and an MSc in Responsibility and Business Practice from the University of Bath, and is completing a PhD on youth co-creation and the uses of enchantment. In 2012, after finding a discarded laptop in a skip near her home in East London, she co-founded Tech Will Save Us with her husband, Daniel Hirschmann, on the conviction that children should be producers of technology, not just consumers of it.Tech Will Save Us grew into a STEAM company selling in 97 countries and partnered with the BBC, Microsoft, Samsung, and ARM to design the BBC micro:bit — a pocket-sized computer distributed free to a million UK children that has since reached more than four million users worldwide. After selling the company in 2021, Bethany founded Fam Studio, which co-creates with families and children to build technologies, learning content, and experiences centered on people and the planet. Current projects include a multimodal "Imagination Tool" that uses generative AI to bring children's voices into large-scale co-creation, and a wellbeing-and-AI research partnership with Oxford's Reuben College and its Child-Centred AI Design Lab.In this episode, Bethany talks with Svenia Busson about:Finding a laptop in a skip — the origin story behind Tech Will Save UsDesigning the BBC micro:bit with Microsoft, Samsung, and ARM — reaching four million children across 97 countriesWhy Fam Studio exists to serve "the village," not just the childTechno-optimism versus AI anxiety — holding both at onceWhether AI reinforces the industrial-era school model or finally breaks it openBuilding the "Imagination Tool" — using generative AI to bring children's voices into co-creation at scale"No Tech Sundays" and the house rules her family set for her teenager's AI useMoving from human-centered to life-centered design — what biomimicry teaches educatorsShe closes with future-guest picks: Caroline Essame, author of Why Nature Matters (Routledge); Noan Fesnoux, creative adviser to Dubai's Museum of the Future (LinkedIn); Liz Robinson, CEO of Big Education (bigeducation.org); and Jenny Gibson of Cambridge's PEDAL Centre (pedalhub.net).

This special episode is a recording of a live panel discussion from the AI & Education Meetup series, hosted by Education Futures at the London Interdisciplinary School (LIS).Svenia is joined by four guests at the intersection of AI and learning: Ash Brockwell, LIS associate professor and lead of the new Education Futures master's; Niccolò Pescetelli, LIS associate professor leading the AI & Collective Intelligence program; Stephen Jull, GeoGebra GmbH co-founder now Global Head of AI Educational Technology at Teach For All; and Bibi Groot, behavioral scientist and Chief Impact Officer at Eedi, who runs large-scale RCTs on AI tutors.The conversation moves through what it means to "learn" when AI can retrieve and summarize anything instantly, the risk of cognitive offloading and "cognitive surrender," and evidence from a 12-week chess RCT on hints and productive struggle. The panel also digs into relationality and embodied learning, how Teach For All is building AI literacy at scale across 63 countries, tools designed to cut screen time while still using AI (like Eedi's QR-code diagnostic system), and closes with each guest's vision of a preferable — not just probable — future for education, including a sharp reminder from the audience that 70% of children globally still lack basic literacy access.Recorded live in London as part of Education Futures' ongoing meetup series exploring desirable futures for education in the age of AI.

We asked 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.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.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 wayWhat the history of web literacy teaches us: it took 25 years to find strategies that actually workWhy domain expertise — not AI knowledge — may be the most critical factor in using AI wellWhat to make of "AI-powered" schools like Alpha SchoolWhat students themselves are saying: two-thirds of US students say AI is harming their critical thinkingWhy "the homework machine" is the most honest name for what's happening in classrooms todayAlso mentioned in this episode:Mike Caulfield's SIFT framework for teaching web literacy: https://guides.lib.uchicago.edu/c.php?g=1241077&p=9082322A 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-aiThe 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 platformGoogle DeepMind's LearnLMLearning Engineering Virtual Institute (LEVI) — created by Schmidt Futures & Renaissance PhilanthropyDavid Yeager, 10 to 25: The Science of Motivating Young PeopleAI Hub for Education (Stanford) — reviewed 800+ papers on AI in education; only 20 had causal evidencePoulidis & 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

The tech industry is building powerful AI tools for children, often without understanding how children actually learn and grow. That's the gap Anne-Sophie Seret set out to close.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 developmentiRAISE 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-.pdfResearch: "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.pdfBook 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 itThe 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, itThe Rithm Project's youth research report identifying nine portraits of how young people relate to AI chatbotsAI sycophancy — and what it quietly does to a generation's capacity to be wrongThe wave of state-level AI safety legislation: California's SB 53, the New York RAISE Act, and Illinois House Bill 315Why the Take It Down Act matters and how non-consensual deepfake imagery is already a crisis in schoolsA 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.pdfCalifornia 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 engineerThe critical shift in information systems engineering from reliability to trustHow the Sorbonne is rethinking assessments in the age of AI — and why students themselves are demanding itThe difference between students who use AI to cheat and those who use it to learnWhat 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 philosophersReferences & links mentioned in this episode:Alex's website: adcphilosophy.comThe Durham Commission on Creativity and Education: https://www.artscouncil.org.uk/sites/default/files/download-file/Durham_Commission_on_Creativity_04112019_0.pdfThe Gartner Hype CyclePISA — now updated to include a creativity assessment (https://www.oecd.org/en/topics/student-performance-pisa.html)Bill Lucas on creativity skills and perseveranceSimone Weil — French philosopher referenced on personalized learningPhilosophy 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 ShaukatLanguage 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/usEIDU (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 aboutWhy, 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 bodyThe Reggio Emilia philosophy — and why she turns to it whenever she feels lost in the noise around AILessons 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 AILinda 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 Rahimhttps://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-companionsBrighteye 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)

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 districtThe "Swim, Snorkel, Scuba Dive" metaphor for AI literacy across K-12Why human and durable skills (not prompt engineering) should be the foundationWhy we should flip the script: "soft knowledge, hard skills"His top 5 skills for the age of AI: discernment, compassion, interest, relational intelligence, and creativityThe "blockbuster vs. Netflix" moment facing public education todayHow to design assessment in the background of meaningful work, not as stop-and-test examsWhy de-skilling is real, and why the answer is redesigning learning and not banning AIA 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.orgGwinnett County Public Schools (where the AI Readiness Framework was developed): https://www.gcpsk12.orgThe 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/futureeducatorTeach for all: https://teachforall.org/ & Teach For America: https://www.teachforamerica.orgMcKinsey 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-wagesIsabel 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 relationshipPlato's Theaetetus and Sophist — on knowledge, truth, and the sophist as pretenderPlato's Phaedrus — on writing, memory, and dialogueTulane University — where our guest completed his doctorateSt. John's University, New York — where he will be teachingThe 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-allWe explore:How GeoGebra scaled to 500M+ users with no ads, no data collection, and a mission-driven business modelWhy Teach for All's 2-year fellowship model is more relevant than ever in the AI eraWhat the AI Literacy and Creator Collective actually looks like in practice — and why it rejects the traditional top-down training modelWhy working exclusively with free AI models is central to ensuring equity and scale across 60+ countriesWhether 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/B0GG9TMHC2Forward College – https://forward-college.eu/London School of Economics (academic partner) – https://www.lse.ac.ukKing's College London (academic partner) – https://www.kcl.ac.ukAn Avalanche is Coming report (Michael Barber, IPPR, 2013) – https://www.ippr.org/articles/an-avalanche-is-coming-higher-education-and-the-revolution-aheadNoise 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.comMcKinsey "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 safetyWhat 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 dangerousWhy sycophantic, "I care about you" chatbot behavior can blur the line between human and machineThe rise of emotional over-dependency and even romantic relationships between adolescents and AIPilyoung's Social and Emotional AI Literacy Framework for teachers, parents, and school psychologistsConcrete prompts you can use right now to make AI chatbots safer for kidsWhat Pilyoung learned at OpenAI and on Capitol Hill about the future of AI policy for childrenA 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-kimPilyoung Kim at the University of Denver: https://liberalarts.du.edu/about/people/pilyoung-kimCenter 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-respondPilyoung's Capitol Hill briefing on AI & youth mental health: https://pilyoung.substack.com/p/bringing-ai-safety-and-child-developmentSociety 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 advocateThe three non-negotiables every AI system should meet before reaching childrenWhy conversational AI is fundamentally different from social mediaThe risks of AI companions, AI tutors, and chatbots in classroomsRaising children in an AI world: practical advice for parentsThe Meta accountability case and the shifting tide in US courtsWhy "inevitability" is the biggest trap — and what collective action can still achieveResources & links mentioned:Safe AI for Children Alliance → https://www.safeaiforchildren.orgFree guide for schools and educators (on the Alliance's website) → https://www.safeaiforchildren.orgThe 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 siteRecent 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.Links mentionedKORA (the benchmark)Introducing KORA (blog)Open-source benchmark on GitHubLaunch post by Mathilde CollinDeep-dive on KORA (EdTech Partnerships)Conversation with Mathilde Collin about KORA (Opportunity Knocks)People mentionedMathilde Collin (co-founder of KORA)Isabelle Hau — Stanford Accelerator for Learning · personal siteLove to Learn by Isabelle Hau (Hachette) · Stanford Report featureJonathan 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 KurzweilSubstack writers recommended by Wess:Mike Taubman — AI WaypointsStephen Fitzpatrick — Teaching in the Age of AIMike 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 processesWe 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/

What does it mean to assess learning in a world where AI can generate answers instantly?In this episode of Education Futures, Svenia Busson is joined by Alina von Davier, Chief of Assessment at Duolingo, and Elie Bechara, who works on institutional partnerships for the Duolingo English Test.Together, they bring a rare combination of assessment science, product innovation, and real-world university dynamics.As AI tools become widely accessible, traditional forms of assessment, especially high-stakes exams, are being fundamentally challenged. If students can generate answers with AI, what are we actually measuring?In this conversation, we explore:• Why AI is putting pressure on the validity of traditional exams • How universities are responding to new questions around academic integrity and admissions • The shift from testing knowledge → competencies and skills • Why assessment needs to become more continuous, contextual, and embedded in learning • How the Duolingo English Test is rethinking language assessment using AI • The importance of designing assessments that reflect real-world performance, not artificial test conditionsWe also discuss how assessment can evolve from a moment of evaluation into a tool for learning itself — providing feedback, guiding progress, and supporting long-term skill development.The challenge ahead is about redefining what we value, what we measure, and what we trust in education.To explore further what was discussed in the episode:https://englishtest.duolingo.com/ https://blog.duolingo.com/video-call/

What should universities teach in the age of AI?In this episode of Education Futures, Svenia Busson speaks with Art Markman, Chief Academic Officer at Minerva University and a leading expert in cognitive science, decision-making, and learning.With a career spanning academia, research, and applied learning design, Art brings a powerful perspective on how education must evolve — not just to keep up with AI, but to remain relevant in a rapidly changing world.In this episode, we explore:• Why education should focus on “far transfer” — the ability to apply knowledge across contexts • The shift from teaching content → developing durable skills (reasoning, communication, empathy, systems thinking) • Why most universities are still structured like they were centuries ago • How Minerva Project is redesigning higher education from first principles • Why grades and transcripts fail to capture real learning • How AI is reshaping the role of assignments, assessment, and feedback • Why trying to ban AI in universities is the wrong approach • How AI can be used as a tutor, feedback engine, and learning acceleratorTo go further:Minerva University: https://www.minerva.edu/UT Austin’s Homegrown AI Tutor Platform: https://tech.utexas.edu/news/ut-austin-and-aws-launch-ut-sage-ut-austins-homegrown-ai-tutor-platform

What happens when students start trusting AI more than their teachers?In this episode of Education Futures, Svenia Busson speaks with Mary Burns, researcher at the Brookings Institution and co-author of the report “A New Direction for Students in an AI World: Prosper, Prepare, Protect.”With over 40 years of experience in education — from classroom teaching to advising ministries of education across more than 100 countries — Mary brings a rare, global perspective on how AI is reshaping learning systems.In this episode, we explore:• The “web of distrust” emerging in education systems• Why students may begin to trust AI more than teachers• The risks of cognitive, emotional, and social offloading to AI• Why AI feels more reliable, neutral, and emotionally safe than humans• The rise of teacher over-reliance on AI — an under-discussed risk• Why AI literacy must be holistic (not just tool usage)• The dangers of sycophantic AI systems and emotional attachment• The growing gap between AI adoption and regulationA key framework from the episode:Mary co-authored a major report proposing a 3-pillar framework for AI in education:👉 Prosper, Prepare, Protect• Prosper: Use AI to improve learning and opportunity• Prepare: Equip students, teachers, and systems to use AI responsibly• Protect: Safeguard learners from risks (cognitive, emotional, data-related)📄 Read the full report:Brookings Institution – A New Direction for Students in an AI Worldhttps://www.brookings.edu/wp-content/uploads/2026/01/A-New-Direction-for-Students-in-an-AI-World-FULL-REPORT.pdfDistance education for teacher training: modes, models and methods - http://go.edc.org/07xdRead "eyes wide open" the chapter Mary wrote in "Que educação nos exige – hoje − o porvir? Se não agora, quando. Universidade de Lisboa: Centro de investigação e de estudos em belas-artes, p. 50-69"English version here: https://static1.squarespace.com/static/5fac2fdb0da84a28cc76b714/t/67b56f484fc8d51dd5546fa4/1739943752612/Mary+Burns-Eyes+Wide+Open+What+We+Lose+from+Generative+AI+in+Education.pdf

What if we asked children how to design the future of education?In this special episode of Education Futures, Svenia Busson is joined by Selena Marwaha, an 11-year-old builder, coder, and speaker who has already presented at global events such as COP28, COP29, and WISE Summit Qatar.She is joined by François Taddei, co-founder of the Learning Planet Institute, whose work focuses on collective intelligence, learning ecosystems, and the future of education.Together, they explore what education could look like if it were co-designed with the next generation.In this episode, we explore:• Why children should be actively involved in shaping the future of education • Selena’s vision for a school that prioritizes creativity, mentorship, and problem-solving • Why AI should be used as a co-creator, not a shortcut • The importance of art, curiosity, and human expression in a tech-driven world • How to balance AI acceleration with human development • Why schools should help students navigate emotions, relationships, and purposeSelena also shares her project Planetary Stories — a platform where children from around the world can share their dreams, challenges, and visions for the future, creating a collective dataset of youth perspectives to inform decision-making.Go further with these ressources:Selena's initiative "Planetary Stories" will be launched on April 22nd (Earth Day), we will share these here in the show notes.Mara Mintzer TED Talk "How kids can help design cities" https://www.ted.com/talks/mara_mintzer_how_kids_can_help_design_citiesAlison Gopnik's work: research on child creativity and learning https://alisongopnik.com/Kiran Bir Sethi's work: creator of the Design for Change framework (“Feel, Imagine, Do, Share”) - https://dfcworld.org/SITE

Are we building educational technology faster than we can prove it actually works?In this episode of Education Futures, Svenia Busson speaks with Natalia Kucirkova, professor at the University of Stavanger and co-founder of the International Centre for EdTech Impact.Natalia has spent years researching how children learn, and how digital tools can (or cannot) support that process. Her work sits at the intersection of learning science, AI, and impact evaluation.As AI tools rapidly enter classrooms, one question becomes critical:Where is the evidence that these tools actually improve learning?In this conversation, we explore:• Why engagement is not the same as learning• The risk of deploying AI tools without evidence of impact• How EdTech companies can collaborate with researchers to design better products• Why we need to slow down before scaling untested technologies• The difference between efficacy, effectiveness, and real-world impact• Why traditional evaluation methods (like RCTs) need to evolve in the age of AI• How teachers and schools can make more informed, evidence-based choicesWe also discuss concrete tools and initiatives aiming to bring more transparency to the field:Natalia's Centre for Edtech Impact: https://foreduimpact.org/AI safety benchmark Natalia has contributed to:https://korabench.ai/Edtech Certification Natalia is affiliated with & recommends: https://eduevidence.org/Other Certifications that exist:https://www.1edtech.org/https://edtechimpact.com/https://iste.org/edtech-product-selectionhttps://www.edtechtulna.org/Natalia also explains how EdTech evaluation works in practice — from early-stage testing (A/B testing, rapid cycles) to large-scale studies like randomized controlled trials (RCTs).The takeaway:In education, good intentions and high engagement are not enough. If we want technology to truly support learning, we need to measure it well.

What should we protect in education, as AI transforms how we learn, think, and work?In this episode of Education Futures, Svenia Busson speaks with Nick Krichevsky, a high school teacher and Head of Digitalization at the German International School Johannesburg in South Africa.With over 15 years of teaching experience across Germany and South Africa, Nick brings a grounded, classroom-based perspective to one of the most pressing questions of our time:What should education hold onto, and what should it let go of, in the age of AI?In this conversation, we explore:• Why AI should serve a clear educational purpose, not drive it• The limits of a one-size-fits-all education system across different contexts• What Nick calls the “promise — and misspoken promise — of education”• Why many students still lack practical skills and opportunities, despite access to schooling• The importance of effort, friction, and cognitive rigor in real learning• How AI can support education by freeing up time and resources, not replacing thinking• Why students must develop ownership of their learning process• The growing concern among students about AI, self-efficacy, and their futureNick also shares a powerful vision for the school of the future:Not one centered on technology, but one built around human relationships, social learning, mentorship, and responsibility.

In this episode of Education Futures, Svenia Busson speaks with education entrepreneur Ed Fidoe, founder of London Interdisciplinary School and co-founder of School 21 in London.Ed has spent the last decade building new kinds of educational institutions from the ground up. His work challenges one of the core assumptions of higher education: that students should specialize in a single discipline.Instead, the London Interdisciplinary School is built around a radically different idea: teaching students to tackle complex real-world problems using knowledge from multiple disciplines.In this conversation we explore:• Why universities are facing a structural crisis• Why the traditional single-discipline degree may no longer make sense• How AI is reshaping what students need to learn• Why universities should teach students how to identify the right problems to solve• Why innovation in education requires experimentation and new institutionsWe also discuss the Education Futures Master’s at LIS, a new interdisciplinary program designed for educators, learning leaders, and anyone interested in how education systems must evolve in an AI-driven world.Ed also shares lessons from School 21, including the development of oracy education, teaching students how to think and communicate effectively through speech.We mentioned:https://www.lis.ac.uk/https://school21.org.uk/https://voice21.org/

In this episode, Svenia Busson speaks with Guila Clara Kessous, a UNESCO Artist for Peace and Harvard teacher, about the intersection of art, education, and peace-building. They explore how performing arts and literature can heal trauma and how "diplomatic entrepreneurship" can help the next generation navigate a world shaped by AI and social media.Key Topics Guila’s Journey: From performing arts conservatory to a PhD with Nobel laureate Elie Wiesel.Art Therapy & Bibliotherapy: Understanding how drama and reading (recognized by the WHO) can increase serotonin and well-being.Education in the Age of AI: Why we should teach kids how to "prompt" like the game Jeopardy to find neutral information and overcome biases.Diplomatic Entrepreneurship: Using culture and art to reconcile communities in conflict, such as through Israeli-Palestinian youth summer camps.Non-Violent Communication (NVC): The importance of teaching children to "agree to disagree" and express views respectfully.The School of the Future: A vision of an open school in nature that connects the "heart, head, and body".Resources MentionedWorld Art Day International Forum: An annual event at UNESCO every April 15th focusing on arts, health, and activism. (Website: worldartdayforum.com)Faber and Mazlish Technique: Practical methodology for communication between adults and children ("How to Talk So Kids Will Listen").Femina Vox: An international forum at UNESCO dedicated to Women’s Rights.Movements for Peace: "Women Wage Peace" and "Women of the Sun," including the "Prayer of the Mothers" song.Bibliotherapy: Mention of the power of reading as recognized by the World Health Organization (WHO).

In this episode of Education Futures, we speak with Kristen DiCerbo, Chief Learning Officer at Khan Academy, where she leads the teams responsible for content, product design, assessment, and learning science.With a PhD in educational psychology, Kristen brings a rare perspective to the AI conversation: learning science first, technology second.We explore how Khan Academy is building Khanmigo, its AI tutor and teaching assistant, and what it takes to design AI tools that support real learning rather than shortcuts.In this conversation, we discuss:Why screen time is a poor proxy for learningHow AI tutors can support practice and feedback at scaleWhy foundational knowledge still matters in the age of AIThe growing concern around cognitive offloading and students delegating their thinking to machinesHow Khan Academy designed guardrails and safety mechanisms for AI used by childrenThe tension between gamification, motivation, and real learningWhy human relationships with teachers remain the strongest driver of learningWhat the school of the future could look like, combining technology with project-based learningKristen also shares how Khan Academy applies a risk-management approach to responsible AI, identifying potential harms early and designing safeguards directly into their systems. (more on this: https://blog.khanacademy.org/khan-academys-framework-for-responsible-ai-in-education/)The takeaway: AI may transform education, but learning will always require effort, curiosity, and human guidance.Read this to go further:National Study in Top Journal Finds Khan Academy Learning Gains After Accounting for Key Unmeasured Factors : https://blog.khanacademy.org/national-study-in-top-journal-finds-khan-academy-learning-gains-after-accounting-for-key-unmeasured-factors/

By 2050, Sub-Saharan Africa will be home to nearly 1 billion people under 18.Today, 90% of 10-year-olds in the region cannot read a simple paragraph (according to the World Bank)What happens when artificial intelligence accelerates, but foundational literacy remains out of reach for millions of children?In this episode of Education Futures, Svenia Busson speaks with Paul Atherton, founder of Fab AI, about the future of AI in low- and middle-income countries, and whether it will close or widen the global learning gap.Paul’s mission is to ensure that the world’s best technologies serve children who lack access to foundational literacy and quality schooling.We explore:Why foundational literacy is the non-negotiable starting pointHow AI could help leapfrog infrastructure gaps in Sub-Saharan AfricaWhy most AI funding focuses on short-term pilots instead of long-term system architectureThe risk that high-income countries experience exponential productivity gains while others fall further behindHow rapid, decision-ready RCTs could modernize evidence in edtechThe difference between AI as autopilot vs co-pilot in learningWhy friction and effort remain essential to deep learningWhy Paul worries more about today’s 15-year-olds than 5-year-oldsThis conversation is about infrastructure, inequality, and the billion young people whose future will shape the global economy, and whose literacy will determine whether AI becomes a tool of opportunity or a force that widens the gap.Try Fab AI's new web app which can help evaluate the quality of foundational literacy and numeracy materials for low- and middle-income countries: https://fab-content-curation.web.app/Read the latest Fab-AI Research Paper: "Context counts: Measuring how AI reflects local realities in education" : https://www.fab-ai.org/initiatives/ai-for-education/edtech-quality/resources/research-paper/measuring-how-ai-reflects-local-realitiesSubscribe to Paul's Substack: https://paulfabai.substack.com/

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 practiceHow the EU AI Act impacts schools and educational organizationsWhy individual teacher subscriptions to AI tools can create legal and safety risksThe difference between AI literacy and AI safetyWhy students are hesitant to admit how they use AIThe growing cognitive dependency concerns for Generation AlphaAnd what a more human-centered, collaborative school of 2040 could look likeClara 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 brainsIn 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 .Key Highlights: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.Key Themes & HighlightsThe 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.Notable Quotes"I tend to try to weave ethical dreams, which are dreams that are a nightmare for no one, neither today nor tomorrow." — François Taddei"The last thing we can afford to lose is hope. Because if you lose hope, then you cannot do anything. But if you have hope... you can rebuild and you can reinvent." — Francisco Vera (via François Taddei)Resources MentionedLearning 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-makingHow the speed of AI creates noise, confusion, and decision paralysisThe persistent research-to-practice gap, and why it’s even harder with AIWhat current evidence actually tells us (and doesn’t) about AI in K–12Why most research today shows promise, not certaintyHow leaders can think in short-cycle experiments instead of long-term predictionsThe difference between using AI for efficiency, outcomes, and reimagining schoolWhy personalization has too often turned into isolation, and how AI could help reverse thatA vision of future schools built around collaboration, real-world learning, and apprenticeship-like experiencesChris 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/aiThe 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 outdatedHow AI systems are becoming cognitive rivals, not just toolsWhy humans are especially vulnerable to anthropomorphizing conversational AIThe concept of asymmetric relationships between humans and AIWhy photorealistic, conversational AI represents a new and far more powerful form of influenceHow AI may reshape education, work, relationships, and childhood itselfWhat skills children actually need to develop in a world of rapid, continuous changeWhy banning AI in schools is not a solution — but neither is naïve adoptionLouis 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.📚 Essential reading — Louis Rosenberg on AI denialThese 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-realhttps://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 itThe crucial difference between formative and summative uses of AIWhy authenticity and motivation matter more than ever in educationHow peer-to-peer learning reduces reliance on AI shortcutsWhy meetings, dialogue, and facilitation are learned skills, not inefficienciesWhat it means to educate for stewardship of the commonsWhy responsible technology requires people who can govern togetherHow education could shift from credentials to lived, cooperative experienceSeth 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 centuriesHow AI is accelerating the exposure of slow, inefficient, and misaligned systemsWhy “AI transformation” is often the wrong framing, and why betterment matters moreWhat universities misunderstand about students, industry, and the marketplaceWhy entry-level work, credentialing, and degree length must be rethoughtHow innovation is more likely to come from outside universities than withinWhat the future of higher education could look like in a plural, AI-enabled worldMichael 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 misguidedHow “existential hope” differs from blind optimismWhy agency matters more than prediction when thinking about the futureHow world-building and scenario planning can help rethink educationWhy education may be the most powerful lever for long-term changeHow AI could make learning more humane — not lessWhat skills and mindsets future education systems should prioritizeWhy plural, diverse futures matter more than one “perfect” visionBeatrice 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?”

What does school look like through the eyes of a 15-year-old who actually uses AI to learn, not just to finish homework faster?In this episode of Education Futures, Laurent & Svenia sit down with Hudson, a high school student from San Diego who is already doing computer science education research, and working with a UCSD mentor on learning science–informed approaches to teaching.Hudson shares a strikingly clear perspective on what’s broken in today’s education system, and what could be rebuilt in the age of AI.Rather than focusing on AI literacy, tools, or prompt engineering, he argues for something deeper: teaching students how to think.People & institutions mentioned:Art of Problem Solving for Math education - https://artofproblemsolving.com/Carnegie Mellon University – LearnLab - Kenneth Koedinger & John Stamper (intelligent tutoring systems) https://learnlab.org

Is learning how to code still relevant when AI can generate code for us?In this episode of Education Futures, we sit down with Dora Palfi, founder of imagi, to explore what computer science education should become in an AI-driven world — and what must not be lost along the way.Dora has a background in computer science and neuroscience and has spent years working at the intersection of education, technology, and equity. Her core conviction is clear: AI should not become a shortcut that removes understanding, agency, and critical thinking from learning.We discuss why coding still matters — not as a job guarantee, but as a way to understand how the world works — and why telling students they don’t need to understand technology anymore is not only wrong, but patronizing.Check out "hour of AI" a Loveable x OpenAI x imagi initiative: https://imagilabs.com/pages/hour-of-codeWe discussed the book "IF ANYONE BUILDS IT,EVERYONE DIES" - Eliezer Yudkowsky & Nate Soareshttps://ifanyonebuildsit.com/

(EPISODE IN GERMAN - FOR THE ENGLISH SUBTITLES CHECK OUR YOUTUBE CHANNEL: https://youtu.be/tiLh9Jq1ApU)In dieser preisgekrönten Folge der Podcast-Serie "A youth dialogue on keeping the future human" spricht Gastgeberin Svenia Busson mit drei Schülern aus Berlin und Hamburg: Flor (13), Luca (15) und Sofia (15). Während sich die globale Debatte oft auf zukünftige Risiken konzentriert, leben diese Schüler bereits heute mit der Realität von KI im Klassenzimmer.Sie geben einen offenen Einblick, wie KI die Bildung schon jetzt verändert – von Lehrern, die mit Drohungen auf ChatGPT-Aufsätze reagieren, bis hin zur sehr realen Angst vor Deepfakes, die die Gesellschaft spalten. Sie argumentieren, dass Verbote keine Lösung sind; stattdessen fordern sie, dass Schulen kritisches Denken und KI-Kompetenz von Anfang an vermitteln.In dieser Episode diskutieren wir u.a:Ungleichheit und die "Superreichen": Flor (13) stellt eine brutale ethische Frage an die Entwickler: "Unterstützt es viele Menschen oder hilft es nur den Superreichen, noch reicher zu werden?" Dies ist eine direkte Kritik an der Konzentration wirtschaftlicher Macht, einem zentralen Thema in Aguirres Essay.Datensouveränität: Luca (15) äußert eine sehr klare Sorge, nicht über die Intelligenz der KI, sondern über die Privatsphäre.Das "Her"-Syndrom (Soziale Isolation): Flor und Luca betonen die emotionale Gefahr. Sie erkennen das Risiko, dass KI Freundschaften ersetzt, nicht nur Arbeit.KI als "Super-Tutor" (Positive Nutzung): Im Gegensatz zu der Vorstellung, dass Schüler KI nur zum Schummeln nutzen, erklärt Flor, dass sie personalisierte KI-Assistenten (die ihr Vater via Fobizz erstellt hat) nutzt, um Debatten zu üben oder ihre Aussprache zu korrigieren.

(EPISODE IN FRENCH - ENGLISH SUBTITLES AVAILABLE ON YOUTUBE: https://youtu.be/iR5IhYTjYA4)Dans cet épisode de la série primée "A youth dialogue on keeping the future human", Svenia Busson s'entretient avec trois élèves français : Alaïs (11 ans), Sarah-Léa (15 ans) et Arthur (16 ans). Alors que beaucoup craignent une IA dangereuse ou "méchante", ces jeunes redoutent quelque chose de plus subtil : qu'elle nous rende inutiles.Ensemble, ils débattent du "problème du plateau d'argent" — l'idée que si l'IA nous facilite trop la vie, nous perdons notre capacité à penser, à fournir des efforts et à grandir. Dans cet épisode, nous abordons :Le "Plateau d'Argent" : L'avertissement d'Arthur sur la commodité qui tue notre curiosité.La Valeur de l'Effort : Pourquoi Sarah-Léa pense que la difficulté est essentielle au bonheur humain.La Connexion Humaine : La définition d'Alaïs d'un "futur humain" : un monde où l'on se rencontre encore dans la vraie vie, pas juste derrière des écrans.

In this episode Svenia sits down with Hudson (15), Joseph (15), and Violet (17), high school students in San Diego and members of their high school’s AI Club.She decodes Anthony Aguirre’s "Keep the Future Human" essay and ask these high school students burning questions around AI. Moving far beyond surface-level tech talk, they tackle the hardest ethical questions facing Silicon Valley today.In this episode, we discuss:The "Bystander Effect": Violet’s powerful challenge to tech CEOs who claim they are "just following the market."Optimization vs. Agency: How the recommendation algorithms they grew up with have shaped—and potentially hijacked—their cognitive freedom.The "Danger Triangle": A technical debate on whether adding Autonomy to General Intelligence inevitably leads to loss of control.Optimism for "Tool AI": Why Hudson believes AI should remain an "exoskeleton for the mind" (like AlphaFold) rather than a replacement for human thought.Violet shared a podcast by David Fajgenbaum (on repurposing medicine) listen to it here: https://www.youtube.com/watch?v=YWIft9yiHAo

In this special award-winning series for the Future of Life Institute's Keep the Future Human contest, host Svenia Busson sits down with teenagers from across Europe and the US.In this episode, host Svenia Busson sits down with three international students based in Paris and Barcelona: Emma (13), Jack (14), and Hector (16). Moving between metaphors of movies and video game controllers, they tackle a fear that isn't about Terminator robots, but about something much quieter: human atrophy.Together, they debate the "Wall-E Scenario"—a future where AI solves every problem so efficiently that humans forget how to walk, think, or care. They argue that our imperfections, our slowness, and our need to make an effort aren't bugs to be fixed by an algorithm—they are the very features that make life meaningful.In this episode, we discuss:The Wall-E Scenario: Jack’s fear that comfort will lead to cognitive laziness and the loss of critical thinking.The "Off" Button: Why retaining an "overriding capacity" is non-negotiable for the next generation.Profit vs. People: Hector’s call for AI that prioritizes equality over efficiency.The Beauty of Imperfection: Emma’s argument that a "human future" is one where we are allowed to make mistakes.

In this episode of Education Futures, Svenia & Laurent speak with Erin Mote, Co-Founder and Executive Director of InnovateEDU, about the urgent intersection of AI safety, youth online protection, and the future of learning systems. Erin, a leading technologist and policy voice — and a mother of two — explains why safety must come first in the EDSAFE AI Alliance framework and why protecting children means safeguarding not just their data, but their experience with AI systems.Erin breaks down the risks of biased predictive systems, engagement-optimized consumer chatbots, and AI companions — and shares emerging U.S. legislation, including a groundbreaking package of 19 federal bills focused on kids’ online safety.Together, they explore the coming disruption of the workforce: the disappearance of entry-level jobs, the difference between automation vs displacement, and what young people must learn now to thrive in an AI-shaped economy.Erin also outlines what a future-ready school must look like: human-centered, deeply relational, grounded in learning science, and designed to build judgment, discernment, dialogue, and metacognition — skills AI cannot replace.A powerful and urgent conversation for educators, policymakers, and parents navigating this arrival technology.