What should schools expect from the companies bringing AI into their classrooms?

Microsoft President Brad Smith joins Dan Fitzpatrick to discuss the new AI Safety and Privacy Standard agreed with the American Federation of Teachers and its New York City affiliate, the UFT.

Their conversation covers enforceable protections, school AI bans, teacher control, independent schools and whether the agreement could extend beyond the United States. Brad also addresses whether stronger safeguards could slow innovation.

Dan then examines the latest PISA findings, the evidence behind Utah’s reported critical thinking gains, AI in special education advocacy and OpenAI’s Learning Lab. The episode closes with three practical actions to help schools check both the protections around their tools and what students are actually learning.

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The two biggest school districts in America pulled students back from AI this week. In the same 72 hours, the AI labs handed teachers everything for free. Dan walks through the five stories that matter and what each one means for your school on Monday.

NYC's one-year moratorium through eighth grade and the carve-outs nobody reported. LAUSD's district-wide restriction. The Royal Society finding that only 14% of teachers are confident with AI, with principals scoring lower than the teachers they lead. IBM's survey showing 77% of parents want input while 20% understand what's happening. OpenAI's 16-state privacy agreement, and why that matters more than the free access. And the Stanford review and Tennessee trial on what AI tutoring actually does.

Plus three things to do this week: separate your staff and student policies, teach the thing before you police it, and redesign one task.

The Educators' AI Guide 2027: theeducatorsaiguide.com

Back to School AI Summit, 8-9 September: summit.aieducator.tools

You can also watch on YouTube at https://www.youtube.com/@IamTheAIEducator

Our new book is out, so this episode is me walking through what's in it and why we made it.

The Educators' AI Guide 2027 runs to 30 chapters from 28 educators across the world, edited with Heather Brown. I talk through the five issues I set out in the introduction: why the chatbot era is already old news, why we have to start designing for when AI enters the learning rather than whether it does, why assessment has run out of road, what serious AI governance looks like now, and what happens when teachers start building their own software.

Along the way: Larisa Black's blunt test for any assessment, Samantha Armstrong on the difference between a shortcut and a tool, a preschool teacher in Türkiye who got 21 hours a month of documentation down to 90 minutes, Heather's chapter on AI companions, and Stuti Mehta's case for going haule haule.

Get the book at theeducatorsaiguide.com

Women gained seven grade points with Mainstay, making chatbot student performance impossible to ignore in AI college courses.

In this episode:

• Women in an undergraduate Microeconomics course saw their final grades increase by seven percentage points due to course-specific chatbot messages, demonstrating how AI improved grades.
• The Mainstay chatbot improved chatbot student performance by providing timely administrative nudges and support links, rather than generating academic content.
• Research at Georgia State University showed that chatbot student engagement was most effective for the middle 80 percent of students, offering vital scaffolding without necessarily building transferable study habits.
• Implementing AI in higher ed for course support requires significant human design, oversight, and existing infrastructure for it to be effective, as evidenced by the NBER working paper.
• To successfully adopt AI college courses, educators should first audit specific student friction points and measure real outcomes and staff workload, rather than focusing solely on claims of AI improved grades.

Chapters:

• 00:00 — Cold open & welcome
• 00:30 — Women gained seven points with chatbot student performance
• 01:00 — Mainstay chatbot: Nudging, not generating
• 01:45 — The invisible administration and chatbot student engagement
• 02:45 — Strongest effects for the middle 80 percent
• 03:45 — Gender effects and the Microeconomics course
• 04:30 — Performance vs. capability: No transfer of skills
• 05:30 — Implementation details for successful AI college courses
• 06:15 — Research credibility and limitations of the NBER paper
• 07:00 — Advice for leaders: Audit the problem first

How can teachers use AI marking safely?
The study suggests AI is best used for administrative nudges like reminders and connecting students to resources, rather than for academic decision-making or grading content directly.

What specific benefits did the Mainstay chatbot provide in AI college courses?
The Mainstay chatbot improved chatbot student performance by sending personalized text messages for deadlines, missing work alerts, encouragement, and links to tutoring, leading to higher grades and engagement, particularly for women.

Did AI improved grades for all students?
While students assigned to the chatbot were generally more likely to earn an A or B, the most significant gain was observed in women in the Microeconomics course, who earned grades seven points higher; men showed no comparable effect in this study.

Featuring: Dan Fitzpatrick, NBER, Georgia State University, Mainstay, Registry of Efficacy and Effectiveness Studies, National Institute for Student Success, Katharine E. Meyer, Lindsay C. Page, Catherine Mata.

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Randi Weingarten AI policy pairs an elementary ban with training 100,000 teachers as Los Angeles Unified School District cuts screens.

In this episode:

• Randi Weingarten, president of the American Federation of Teachers, proposes banning student-facing AI in elementary schools to protect young children's foundational thinking skills.
• The American Federation of Teachers plans to train approximately 100,000 teachers in AI this year through the National Academy for AI Instruction, prioritizing adult readiness.
• The episode highlights a critical distinction: AI in elementary schools should be carefully considered, distinguishing between tools that offload cognition and those that remove barriers for students.
• Developing AI skills for students means fostering critical thinking, context evaluation, and fact-checking, rather than just showing them how to type prompts.
• Effective AI in education policy needs to move beyond blanket bans, focusing instead on developmentally informed, tightly controlled applications and teacher involvement from the outset.

Chapters:

• 00:00 — Cold open & welcome
• 00:15 — Randi Weingarten AI policy: Ban for young, train for adults
• 00:45 — The concern: AI and cognitive debt in elementary schools
• 01:15 — Defining 'student-facing AI' and policy nuances
• 01:45 — Beyond bans: AI for accessibility vs. offloading cognition
• 02:15 — Essential AI skills for students in secondary education
• 02:45 — Teacher training as a key part of AI in education policy
• 03:15 — Unions' role in ethical AI deployment and professional development
• 03:45 — Balancing protection and progress in AI policy
• 04:00 — Conclusion: Protected thinking vs. challenged thinking with AI

What is Randi Weingarten's stance on AI in elementary schools?
Randi Weingarten advocates for banning student-facing AI tools in elementary schools to prevent children from offloading foundational thinking skills they need to develop.

How is the American Federation of Teachers addressing AI skills for teachers?
The American Federation of Teachers, led by Randi Weingarten, aims to train approximately 100,000 teachers this year through the National Academy for AI Instruction, using a peer-led model.

What challenges does AI in education policy face regarding student use?
AI in education policy must navigate the tension between preventing cognitive offloading in young learners and leveraging AI for accessibility or developing critical AI skills for older students.

Featuring: Dan Fitzpatrick, Randi Weingarten, American Federation of Teachers, National Press Club, Charter, ChatGPT, Los Angeles Unified School District, National Academy for AI Instruction, AFL-CIO.

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Retention jumped from 67% to 83% in Ayisha Irfan's AI for student thinking pilot at Forging Opportunities for Refugees in America.

In this episode:

• An AI Socratic method increased learning retention from 67% to 83% for students at Forging Opportunities for Refugees in America (FORA) compared to AI summarization.
• Student confidence in using AI tools like Gemini or ChatGPT showed almost no relationship with their actual learning, emphasizing the need for robust AI literacy in schools.
• The real value of AI for student thinking lies in how students respond to questions, retrieve information, and explain concepts, not just in the AI's output.
• For professional development, educators should compare an AI's instant summary with a carefully designed questioning dialogue to understand its impact on delayed learning retention.
• Ensuring AI in refugee education or any diverse context means demanding accessibility as a foundational design element, including language support and suitable reading levels, not an optional setting.

Chapters:

• 00:00 — Cold open & welcome
• 00:15 — FORA pilot: AI for student thinking improves retention to 83%
• 00:45 — Ayisha Irfan's research at Forging Opportunities for Refugees in America
• 01:15 — Gemini's Socratic method vs. ChatGPT's direct answers
• 01:45 — Why productive struggle is key for AI learning retention
• 02:30 — Rethinking AI literacy in schools: beyond confidence and usage
• 03:15 — Addressing equity and accessibility for AI in refugee education
• 03:45 — Essential questions for school leaders on AI engagement and data privacy
• 04:30 — Measuring what matters: delayed learning retention over activity

How can teachers use AI marking safely?
Teachers should prioritize AI tools that prompt students to explain and retrieve information over those that simply summarize, and always ensure robust data governance regarding identifiable student information.

What is the best way to measure AI literacy in schools?
Measuring AI literacy should go beyond self-reported confidence or usage figures; instead, focus on students' ability to reason, explain, and retain information without the AI tool, and how they understand AI's influence on their thinking.

How can AI help students in refugee education?
AI in refugee education can narrow learning gaps if systems provide usable instructions, suitable reading levels, language support, and careful teacher oversight, ensuring accessibility is a foundation, not an afterthought.

Featuring: Dan Fitzpatrick, Gemini, ChatGPT, Forging Opportunities for Refugees in America, FORA, The 74, Augmented Intelligence Advisory, Ayisha Irfan, Google Privacy Policy.

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ChatGPT makes a silent character speak, while AI in literature education shows why Emile Bernard’s Madeleine in the Bois d'Amour defeats pattern matching.

In this episode:

• AI in literature education should focus on critical thinking AI, enabling students to directly confront the limitations of tools like ChatGPT in literary analysis.
• ChatGPT made specific errors when analyzing Carson McCullers' *The Heart is a Lonely Hunter*, including changing a bus to a train and giving dialogue to the silent character, John Singer.
• Southern Gothic AI analysis reveals that AI struggles with the nuanced contradictions and 'grotesque' elements in authors like Flannery O'Connor, highlighting AI limitations in humanities.
• Effective teaching AI literary analysis involves students annotating AI responses for textual support and then revising them, fostering a 'productive struggle' that deepens understanding.
• Rather than simply dismissing AI for lack of 'feelings,' educators should guide students to critique AI interpretations based on textual evidence, coherence, and insight.

Chapters:

• 00:00 — Cold open & welcome
• 00:30 — Exploring AI in literature education with ChatGPT
• 00:52 — ChatGPT’s errors in *The Heart is a Lonely Hunter*
• 01:15 — Why Southern Gothic AI analysis challenges pattern matching
• 01:52 — Critiquing AI interpretations: beyond 'no feelings'
• 02:30 — ChatGPT ignores John Singer’s silence
• 03:00 — Practical teaching AI literary analysis: annotation and revision
• 03:45 — Rethinking assessment: product, process, and live understanding
• 04:15 — Professional development for critical thinking AI
• 04:45 — AI in literature education makes close reading essential

How can teachers use AI in literature education without students misusing it?
Teachers can foster critical thinking AI by allowing students to directly identify AI limitations in literary analysis, such as ChatGPT's errors when analyzing *The Heart is a Lonely Hunter*.

What are the specific AI limitations in humanities subjects, especially literature?
AI's linguistic fluency can create the appearance of understanding without genuine insight, missing nuanced textual details, contradictions, and character specificities, as seen in Southern Gothic AI analysis.

How can teachers develop critical thinking skills using AI tools for literary analysis?
Teachers can have students annotate AI-generated literary analyses, identifying supported claims, areas needing more evidence, and overlooked details, then requiring them to rewrite sections with their own defended interpretations.

Featuring: Dan Fitzpatrick, Emile Bernard, Madeleine in the Bois d'Amour, Carson McCullers, The Heart is a Lonely Hunter, Flannery O'Connor, Spiros Antonapoulos, John Singer, ChatGPT.

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Screen time is a poor proxy for learning. AI in education policy should judge thinking, access, ethics and student data.

In this episode:

• The United States Department of Education outlines five core principles for AI in education policy: technology must be educator-led, ethical, accessible, transparent, and protective of student data.
• Evaluating education technology guidelines means shifting focus from mere screen time in schools to the quality of student thinking and the learning outcomes produced.
• Responsible AI education emphasizes rigorous edtech procurement, requiring independent evaluations and a focus on evidence of impact, not just vendor popularity or brand recognition.
• Accessibility features like text-to-speech and captioning are critical equity components of effective edtech procurement, ensuring all students can access grade-level content.
• Effective AI in education policy balances evidence, professional judgment, and local context to ensure technology genuinely enhances learning rather than becoming an expensive, unproven addition.

Chapters:

• 00:00 — Cold open & welcome
• 00:25 — United States Department of Education's 5 principles for AI in education policy
• 01:00 — Why screen time in schools is a poor metric for learning
• 01:50 — Balancing duration with educational value in education technology guidelines
• 02:35 — The critical difference between passive consumption and active thinking with an AI chatbot
• 03:15 — Raising standards for edtech procurement: evidence and independent evaluation
• 04:15 — Leadership responsibility in implementing new education technology guidelines
• 05:05 — Equity and accessibility as a foundation for responsible AI education
• 06:00 — Balancing evidence, professional judgment, and local context in AI in education policy

What are the United States Department of Education's five principles for AI in education policy?
The five principles are that technology should be educator-led, ethical, accessible, transparent, and protective of student data.

How should schools evaluate education technology guidelines beyond just screen time in schools?
Schools should focus on the quality of student thinking, the learning outcomes produced, and the cognitive tasks students are engaging in, rather than simply measuring screen exposure.

What evidence should districts look for during edtech procurement to ensure responsible AI education?
Districts should seek independent evaluations, randomized controlled trials, and evidence that considers the specific conditions under which the technology proved effective, not just brand popularity or basic usage numbers.

Featuring: Dan Fitzpatrick, United States Department of Education, Elementary and Secondary Education Act, Every Student Succeeds Act, Apple Podcasts, Spotify, Google, AI chatbot, Linda McMahon.

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Nine neighbouring districts set different rules for the same technology, showing why AI policy school districts adopt must be clearer.

In this episode:

• Nine Central Florida school districts demonstrate varied AI policy school districts are adopting, from outright prohibition to specific allowances for tools like Google Gemini and ChatGPT.
• Student AI use policy must clearly define 'permission' to avoid six teachers setting six different boundaries for the same student, ensuring consistent instructional guidance.
• Orange County Public Schools and Brevard Public Schools correctly avoid relying on AI detection software as definitive proof of cheating, requiring supporting evidence like writing samples or student conversations.
• Effective AI guidelines for teachers should integrate AI tools for education into learning design, emphasizing human judgment and student cognitive engagement over simple machine production.
• Districts like Flagler Schools offering enterprise access to AI tools for education can provide stronger privacy controls, but policy language needs technical precision to avoid vague terminology.

Chapters:

• 00:00 — Cold open & welcome
• 00:30 — AI policy in Central Florida schools: Nine districts, different rules
• 01:00 — Foundational AI guidelines for teachers
• 01:30 — Variations in student AI use policy
• 02:45 — Why AI detection software isn't definitive proof of cheating
• 03:45 — Procurement and governance of AI tools for education
• 04:30 — The problem of access and equitable provision
• 05:15 — Beyond training: measuring impact and designing professional development
• 06:15 — Characteristics of good AI policy in school districts

How can teachers use AI marking safely?
Teachers should use AI tools for education with permission, protect sensitive student data, disclose AI involvement, check outputs for errors or bias, and rely on human judgment, especially for grading and high-stakes decisions.

What are common challenges for AI policy in school districts?
Challenges include varied student AI use policies across classrooms, over-reliance on AI detection software for cheating, and the need for technically precise language in procurement to ensure privacy and security with tools like Google Gemini and ChatGPT.

How can schools ensure equitable access to AI tools for education?
Schools must design AI provision to be accessible for all students, addressing needs related to homes, disabilities, and languages, rather than treating accessibility as an afterthought to purchasing decisions.

Featuring: Dan Fitzpatrick, Maria Salamanca, Orange County School Board, Brevard Public Schools, Katye Campbell, Flagler Schools, Don Foley, Google Gemini, ChatGPT.

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A school AI policy reversed an AI ban two days before term, leaving teachers to define supervised student AI use.

In this episode:

• The Shawnee Mission School Board's last-minute reversal of an AI ban, two days before term, created immediate uncertainty for educators defining student AI use.
• Effective district AI guidelines must clarify 'teacher-guided access' for students, distinguishing between productive struggle and outsourcing thinking to AI tools.
• The PICRAT framework is a useful tool for teachers to consider student engagement with AI, but it doesn't replace the need for clear school AI policy and operational guidance.
• Assessment strategies for teaching with AI should prioritize student process, explanation, and live performance over relying on AI detection software to gauge understanding.
• A credible school AI policy requires genuine community workgroups, cross-departmental collaboration, and funding for professional development to support consistent student AI use.

Chapters:

• 00:00 — Cold open & welcome
• 00:15 — Shawnee Mission School Board reverses AI ban two days pre-term
• 00:45 — Challenges of 'teacher-guided access' for student AI use
• 01:15 — Defining acceptable student AI use vs. cheating
• 01:45 — PICRAT framework for teaching with AI
• 02:15 — Superintendent Schumacher's call for balance in AI in schools
• 02:45 — Parent concerns and AI policy governance
• 03:15 — Community workgroup and measures of AI success
• 03:45 — Rethinking assessment in the age of AI
• 04:15 — Funding the reality of school AI policy

What are the immediate challenges when a school AI policy changes right before term starts?
When a school AI policy changes last-minute, teachers face significant challenges in interpreting new rules, preparing for classroom scenarios, and communicating effectively with families due to a lack of time and consistent district AI guidelines.

How can schools define 'teacher-guided access' for student AI use effectively?
Schools can define 'teacher-guided access' by clarifying what counts as direct supervision, specifying approved tools and contexts (e.g., brainstorming vs. drafting), and distinguishing between AI reducing friction and removing productive struggle for students.

How can educators adapt assessment when students are using AI?
Educators can adapt assessment by focusing on the student's process, live performance, and ability to explain decisions or defend sources, rather than relying solely on the final product or unreliable AI detection software.

Featuring: Dan Fitzpatrick, Shawnee Mission School Board, PICRAT, Dr. Mike Schumacher, Center for Academic Achievement, KCTV.

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