What Eye-Tracking Research Shows About Spotting AI Deepfakes

Why Districts Across the US and the World Are Pumping the Brakes on School AI

In this episode we explore why schools, districts, governments, and families are beginning to slow down AI adoption in education. From Norway’s restrictions on generative AI for younger students to policy delays in New York City, governance concerns in Portland, safety questions in Broward County, and parent-led calls for a pause across the Washington, D.C. region, a broader pattern is emerging: education leaders are asking whether schools are moving faster than they can responsibly govern. Topics covered: • Norway’s ban on generative AI for elementary-age students• New York City’s delayed AI guidance and calls for a moratorium• Portland’s decision to pause AI expansion until oversight is established• Broward County’s concerns about privacy, cybersecurity, and student safety• Parent-led efforts to pause student-facing AI in the Washington, D.C. area• The tension between innovation and responsible governance• What district leaders should consider before approving new AI tools• The growing gap between school policy and students’ everyday AI use Sources: https://www.reuters.com/technology/norway-imposes-near-ban-ai-elementary-school-2026-06-19/ https://www.chalkbeat.org/newyork/2026/06/24/nyc-education-department-delays-ai-guidance-after-backlash/ https://www.oregonlive.com/education/2026/06/amid-concerns-that-ai-is-infiltrating-its-schools-portland-school-board-hits-pause.html https://www.cbsnews.com/miami/news/broward-school-board-meeting-ai-in-classrooms-june-2026/

When Chatbots Create False Fluency

In this episode we explore “the magenta line of learning” — a powerful metaphor borrowed from aviation to understand what happens when students become too dependent on AI tools before they have built real expertise. Topics covered: * The “Children of the Magenta Line” aviation metaphor * What Air France Flight 447 can teach us about automation dependency * Why students may feel confident without actually understanding * The difference between performance and real learning * Cognitive load theory and why struggle matters * How chatbots can give students fluency without schema * How teachers can test whether students truly understand Dan.CoganDrew@newsela.com Source: https://carlhendrick.substack.com/p/children-of-the-magenta-line

Ask Your Students

In this episode we explore what happens when teachers ask students directly whether AI belongs in the classroom. We look at a classroom conversation led by English teacher Marcus Luther, who asked his students whether he should integrate AI tools into his teaching. Their responses were striking. Topics covered include: * Why student voices are often missing from AI-in-education debates * What one teacher learned by asking students whether AI belonged in his classroom * How students think about accomplishment, effort, and authentic learning * The difference between using AI in school and learning about AI for future work * Why teachers’ own perspectives on AI may shift after listening to students Dan.CoganDrew@newsela.com Source: https://thebrokencopier.substack.com/p/i-asked-my-students-about-ai-again

Teaching Into the Messiness

In this episode we explore what AI-generated fiction can teach us about human storytelling, student writing, and the value of literary messiness. We look at a new study on StoryScope from researchers at the University of Maryland and Google DeepMind, which compares the narrative structure of human-written short stories with stories generated by several major AI models. Topics covered: * What the StoryScope study reveals about AI-generated fiction * How human stories differ in ambiguity, time, and unresolved meaning * Tim Requarth’s concern that AI may homogenize imagination before writing begins * How English teachers can help students notice narrative complexity * The risk of “closed-loop” thinking in both storytelling and education technology Sources: https://arxiv.org/pdf/2604.03136 https://substack.com/home/post/p-200818672

Where the Answers Actually Come From

In this episode we explore the surprising relationship between Wikipedia, AI chatbots, and the way students learn to trust information online. We look at how Wikipedia’s commitment to verifiability can actually make it more disciplined than many AI-generated responses. We also explore how teachers can use Wikipedia’s gaps as a powerful classroom demonstration of the difference between a grounded answer and a fluent one. Topics covered: * Why Wikipedia still matters in the age of AI * How AI tools may rely on public, well-sourced information * What happens when a chatbot encounters gaps in its source material * The difference between confidence and verification * How educators can teach students to question AI-generated responses * What “verifiability” means for research and writing instruction * How Wikipedia-based assignments can make student writing more authentic * A simple classroom activity for comparing Wikipedia and chatbot responses Source: https://aiedusimplified.substack.com/p/i-can-put-all-the-statements-i-want