Alison "Ali" Gellett leads The Big AI Project at the Oasis Big Education Institute. The project aims to give every school in the UK and the Republic of Ireland what it needs to approach AI safely, ethically and strategically. Ali has 30 years of experience in educational leadership across teaching, multi-academy trust (MAT) executive leadership and local government. She is a Fellow of the Royal Society of Arts.

For the past decade, Ali has focused on transforming the education sector by co-designing solutions with schools. She founded and runs the My Future programme, which teaches careers, aspirations and essential skills to primary school children. Since 2021 it has reached more than 35,000 children and enabled over 800,000 encounters between children and employers. It is funded by Essex County Council and has just launched its first London pilot. The Big AI Project grew out of Big Education's Rethinking School programme and is funded by Salesforce. It is free and AI-agnostic, and its materials were designed by teachers and quality-assured by Professor Rose Luckin's team at Educate Ventures Research. After a pilot with more than 230 schools, it is now rolling out nationally. That includes a region-wide partnership with the Liverpool City Region Combined Authority covering its 400–500 schools. Ali co-authored The Big AI Project report (March 2026).

In this episode, Ali talks with Svenia Busson about:

• Why a school's AI strategy should start with vision, purpose and pedagogy, not with choosing tools
• Building a coalition of 50+ partners around shared values, and keeping commercial and political motives out of the room
• A four-hour, AI-agnostic training for heads — and why their confidence rises from 1–2 out of 5 to 4–5 out of 5
• AI literacy from age 3 to 14, with prediction games, bias and stereotyping activities, and class agreements not to share misinformation
• Anthropomorphism, deepfakes and the AI tool that erased the features of a child with Down's syndrome from a nursery resource
• "Truth has gone": misinformation, young people's mental health, and a million 16–25-year-olds not in education, employment or training
• Why human connection and essential skills matter more than ever in a world full of AI
• The Good Future Foundation AI Quality Mark, and why schools that go it alone end up making their job harder

Dr. Ola Ozernov-Palchik is a cognitive neuroscientist who studies how the brain learns to read and, more and more, how AI should (and shouldn't) be used to help it. She is a Research Scientist at MIT's McGovern Institute for Brain Research, a Research Assistant Professor at Boston University Wheelock College of Education & Human Development, and Associate Director of Translational Research in BU's AI & Education Initiative. She got her start in research almost by accident: as an international psychology student, she landed her first research job at the Institute for Reading Research at Southern Methodist University because she spoke Russian.

That job led her to cognitive neuroscience, a PhD in Cognitive Science at Tufts, and early work with Dr. Nadine Gaab at Boston Children's Hospital on some of the first studies to predict dyslexia from kindergarten, followed by a postdoc with John Gabrieli at MIT. She has published 30+ peer-reviewed papers, including a recent Nature Communications study showing the brain's language network is already adult-like by age 4. She received the International Dyslexia Association's Early Career Award, and she is President of New England Research on Dyslexia and Associate Editor of Scientific Studies of Reading.

She founded and directs the Evidence-Based AI in Learning (EVAL) Collaborative, a partnership between BU Wheelock and the Hariri Institute for Computing. EVAL holds AI learning tools to the evidence standard we'd expect of a medical intervention. Its first AI in Learning Challenge drew 35 companies and chose Amira Learning for a free, independent randomized controlled trial. She also co-built KIVA, an open-source AI reading companion that won a 2026 Tools Competition award.

In this episode, Ola talks with Svenia Busson about:

• How the brain learns to read: repurposing circuits for vision and language, the "visual word form area," and why b and d are so hard to tell apart
• What causes dyslexia: phonological processing, family history, and why reading ability sits on a continuum
• Why decades of reading science still don't reach classrooms, with the US as a case study: only ~40% of fourth graders read proficiently on NAEP
• Why no one checks edtech the way medicines are checked: schools buy tools based on user numbers rather than learning outcomes, and some districts are now banning AI outright
• Inside the EVAL Collaborative: pre-registered, open-science RCTs published regardless of outcome, and the first EVAL AI in Learning Challenge
• Can an 8-month trial prove learning? Measurement models, gated technical reviews (including how well speech recognition handles accents and dialects), and evidence that builds up over time
• Advice for edtech founders: collect evidence from day one, and edtech's "5% problem"
• KIVA, skeptical first graders, and the "AI penalty": teachers rated AI tutoring responses higher than human ones until they were told they came from AI