AI From The Ground Up

In this episode, we examine one of Canada's most ambitious efforts yet to prepare its citizens for the age of artificial intelligence: a new national AI literacy initiative designed to reach over 1 million people. The Canadian federal government, in partnership with AIME (the Alberta Machine Intelligence Institute), has launched a comprehensive program targeting 1 million post-secondary students and more than 50,000 K-12 educators. The initiative is built around three core principles: understand AI, use AI, and for those who choose, build with AI. Post-secondary students will gain access to a free three-hour AI literacy course focused on responsible use and workplace readiness. K-12 educators will receive practical training and classroom-ready resources to help navigate AI in education. The program emphasizes critical skills like assessing AI-generated information, recognizing biases, identifying misinformation, and understanding privacy risks. Workers and job seekers will also be able to access short-duration AI training as workplaces transform. Join us as we break down what Canada is doing, why treating AI literacy as a universal skill matters, and the real challenges of implementing national education initiatives when provinces control their own curricula. This isn't just about learning to use AI tools. It's about building the judgment to know when to trust them, question them, and use them wisely. Is AI literacy becoming the next digital literacy?

In this episode, we examine one of the boldest government actions yet on AI in education: Mayor Zohran Mamdani's comprehensive policy banning generative AI for younger students across New York City's public schools. Mamdani's administration is implementing a one-year moratorium on student-facing generative AI for students in grades 2K through 8th, affecting nearly 600,000 public school students. The policy rejects the tech industry's narrative that AI in early education is inevitable and necessary, instead prioritizing human connection, critical thinking, and evidence-based decision making. The policy introduces strict age-appropriate restrictions while allowing limited teacher-supervised AI pilots for high schoolers, with only about 5% of New York City public school students participating. High school students will receive twice-yearly AI literacy modules to learn how AI works, where it can fail, and how to use it responsibly. Teachers will still be permitted to use approved AI tools for lesson planning and administrative work, and exceptions exist for students with disabilities, multilingual learners, and those in career readiness programs like computer science. Join us as we break down what this policy actually does, why it matters, and whether New York City's approach could become a model for how governments navigate AI in schools. This isn't just about technology. It's about whether preparing students for an AI future means making them dependent on AI, or teaching them how to think, create, question, and use these tools with judgment.

In this episode, we examine a striking proposal from Dario Amadei, CEO of Anthropic, one of the leading companies building frontier AI systems. Amadei has just made one of the strongest public arguments for slowing down the pace of AI development. What makes this particularly noteworthy is that Amadei is not anti-AI. He believes artificial intelligence could cure major diseases, accelerate economic growth, and dramatically improve human life. Yet he warns that the risks are becoming more serious, including loss of control, cyber attacks, bioterrorism, and major economic disruption. His central concern is recursive self-improvement: AI systems increasingly helping to build the next generation of AI systems. He argues this could accelerate capability growth beyond our ability to understand or control it. Amadei's proposal has three key parts: embedding independent evaluators inside AI companies with employee-like access to verify safety practices, coordinating pacing among democratic countries, and eventually achieving global coordination. He emphasizes that pacing should be tied to capabilities rather than arbitrary timelines, with checkpoints where more powerful systems must meet higher safety standards before progressing further. Join us as we break down why one of AI's leading figures believes the frontier needs to be paced, what he is proposing, and whether slowing down is actually realistic in a world where companies and countries compete for AI supremacy.

In this episode, we examine the story of Jacob Coxon, a 27 year old AI researcher who just quit Anthropic after spending three years working on pre-training frontier AI models at both OpenAI and Anthropic, two of the companies at the center of the AI race. When Coxon left, he issued an extraordinary warning: the companies building frontier AI are racing towards self-improving superintelligence without knowing how to guarantee that those systems remain under human control. Join us as we examine one researcher's decision to walk away from the frontier, and what it reveals about the forces shaping the future of artificial intelligence.