AI can sound human, but it isn’t — and that difference changes how we teach, parent, and prepare kids for a future shaped by AI. On this episode, we dive into AI readiness: the blend of skills, ethics, and technical insight that young people need to question, adapt, and lead in an AI-powered world. We sit down with Philip Colligan of the Raspberry Pi Foundation to unpack layered AI literacy, including what students should know about data, large language models, bias, and the social impact of automation. He shares how Experience AI (co-created with Google DeepMind) equips teachers with free classroom resources so every student can get hands-on practice with training AI models, diagnosing bias, and interpreting results. From “tomato vs. apple” misclassification to image-generation blind spots, Phil shows how simple activities can spark important conversations about fairness, accuracy, and accountability. We also hear from Kenyan teacher Mr. Monyancha Isena, whose students crowd around limited computers yet light up as they test AI models and ask why accuracy never hits 100%. Their curiosity illustrates a bigger point of how access and equity determine who benefits from AI. If you’re a parent, teacher, or curious listener, you’ll leave with concrete ideas on how to build AI-ready habits: teach students how AI systems learn, demonstrate model bias through classroom activities, keep privacy guardrails in place, and emphasize student agency in using AI technology. aiEDU: The AI Education Project aiEDU.org linkedin.com/company/aiedu/

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