Margin of Thought with Priten

Priten Soundar-Shah
  • 5.0 (12)
  • EDUCATION
  • UPDATED SEMIWEEKLY

Margin of Thought is a podcast about the questions we don’t always make time for but should. Hosted by Priten Soundar-Shah, the show features wide-ranging conversations with educators, civic leaders, technologists, academics, and students. Each season centers on a key tension in modern life that affects how we raise and educate our children. Learn more about Priten and his upcoming book, Ethical Ed Tech: How Educators Can Lead on AI & K-12 at priten.org and ethicaledtech.org.

  1. How Might Schools Make Sustainable AI Policies? - Joel Sohn

    1D AGO

    How Might Schools Make Sustainable AI Policies? - Joel Sohn

    In this episode, Priten speaks with Joel Sohn, Deputy Head of School at Head-Royce, a K-12 independent school in Oakland serving roughly 920 students, about how a school can build a coherent approach to AI without retreating into a rulebook. Joel walks through the two-year arc of arriving in fall 2023, identifying early teacher champions, taking them to the Schools of the Future Conference, and using Leon Furze's framework to land a philosophy statement rather than a granular policy. The conversation covers why originality has always been a puzzle, how students have shifted from experimenters to skeptics, and why a simplified nine-word mission is doing more work than any rulebook could. Key Takeaways: Build a philosophy, not a plagiarism policy. Joel draws an analogy to dress codes: the more granular the rule, the more the only thing you see is the violation, not the person. AI use is too varied across math, history, and English classrooms to codify the way schools codified plagiarism a generation ago, and a philosophy gives educators the room to make case-by-case judgments.Trust the team first, accelerate later. Joel chose a two-to-three year change trajectory anchored in building educator trust rather than racing to be first. His worry was falling behind by 2027, but the trust groundwork is what made the eventual rollout move quickly and made families comfortable with the rollout.Originality has always been a puzzle, and AI just forces the question. Joel pushes back on the assumption that pre-AI student writing was somehow more "original," pointing out that Shakespeare cribbed too and that brain science still cannot pin down what original thought really is. Schools have been asserting certainty they never had, and AI is making that hard to avoid.Students are no longer the experimenters they were two years ago. Joel sees the current generation as more anti-AI than in 2023, citing concerns about energy use, corporate ethics, and privacy. Teachers using AI sloppily and shipping obviously machine-generated lessons has accelerated that skepticism, which is why he tells teachers to disclose their AI use and how they checked it.Strident anti-AI students need to be interrogated too, not just validated. Joel argues schools should push back when students refuse to engage with AI, not to override their values but to ask whether their stance is rooted in privilege, fear, or genuine principle. The work of school is teaching kids to handle complexity, not to handle any specific tool.

    44 min
  2. What Does Faithful Teaching Look Like in the Age of AI? - Chuck Parish

    6D AGO

    What Does Faithful Teaching Look Like in the Age of AI? - Chuck Parish

    In this episode, Priten speaks with Chuck Parish, an English teacher at a private Christian school in El Paso, about what it looks like to build an AI elective from scratch inside a community that is still deciding whether to be afraid of the technology or learn it. Chuck's path runs through pastoral ministry, teaching at the bachelor's level in Papua New Guinea, and a year of sixth grade before landing in high school English. The conversation moves between the practical questions he is sorting out for his fall semester and the deeper one he keeps returning to: whether schools are forming the kind of judgment students need to use powerful tools well, or whether they are only writing policies. Key Takeaways: Policy can legislate behavior but it cannot form character. Chuck argues that a clean ban or a strict acceptable-use document is the easy move, and the wrong one. Without a foundation underneath it, students will either ignore the rule or comply for the wrong reasons. The school's one-sentence AI policy treats the question as plagiarism, which misses most of what the technology actually changes.A Christian worldview has to address AI the same way it addresses every new tool. The Bible does not name AI any more than it names calculators or television, so the work is in applying an existing foundation to a new technology. Chuck wants students to be able to reason from that foundation themselves rather than relying on him to legislate each case, especially because they will leave the school and lose the legislator.Writing instruction was already in trouble before AI arrived. Texting has shifted how students communicate so far that sixth graders submitting "OMG" and "TY" in their papers is no longer surprising. AI does not start the decline in written reasoning; it accelerates a slide that started with the way students already talk to each other. Chuck plans to use handwritten baseline essays to anchor what each student can actually do without help.Demonstrating the tool in class is more honest than hiding it. Chuck plans to put ChatGPT on the classroom screen, show how fast it can produce an essay, walk through prompting, and surface the hallucinations and fabricated citations directly. The argument to students is that cutting and pasting cheats them out of the learning, and that integrity has to be taught, not assumed.The AI conversation has to include companions and cyberbullying, not just essays. Chuck wants the elective to cover Replika-style companions and image-manipulation tools alongside academic use, because those are the parts students are already encountering outside class. Putting head in the sand, especially in a Christian school context, leaves students to form a worldview about these tools on their own and usually badly.

    45 min
  3. How Do We Catch Higher Ed Up For Age of AI? - Tina Austin

    MAY 12

    How Do We Catch Higher Ed Up For Age of AI? - Tina Austin

    In this episode, Priten speaks with Tina Austin, an AI educator and professor of biomedical ethics who helps institutions rethink assessment and teaching in the age of generative AI. As ChatGPT disrupted the assumption that polished output reflects student thinking, Tina moved beyond academic integrity concerns to ask a deeper question: what if we redesigned learning around when and how thinking happens, rather than what gets produced at the end? Key Takeaways: Bloom's Taxonomy breaks down because AI collapses the distinction between output and thinking. The old model assumed a polished answer proved learning; AI now makes that assumption untenable, forcing educators to make thinking visible through process rather than relying on products as evidence.UnBlooms treats learning as recursive, not hierarchical—and starts with intentional friction. Rather than inverting Bloom's or banning AI, Tina's model requires students to show their initial thinking, engage critically with AI output, and revise with judgment; the shape shifts from a ladder to a spiral where learners don't return to the same place twice.Different disciplines protect different kinds of thinking, and AI policy should honor that variation. STEM faculty worry about problem-solving integrity; humanities faculty about voice and nuance; effective AI policy emerges from asking each discipline what thinking they need to safeguard, not from imposing one rule across all fields.The most productive AI use in classrooms builds critical skepticism, not efficiency. Having students critique AI-generated lecture summaries or debate where AI diverges from expert knowledge creates genuine engagement; offloading listening itself (via AI note-takers) removes a central learning function and trades visibility into thinking for marginal convenience.Higher education's crisis is not new, but AI has made it visible and urgent. Tenure and research incentives protect teaching practices that no longer serve; the opportunity now is to ask honestly whether courses are helping students develop judgment and prepare them for genuine uncertainty—not to add AI on top of unchanged structures.Tina Austin is an AI educator, researcher, and policy advisor working at the intersection of education, healthcare, science, and emerging technology. Recognized as one of ASU+GSV's Leading Women in AI (2025), featured by OpenAI Academy, and interviewed by CNN, she is one of the most prominent voices guiding institutions toward responsible, human-centered AI adoption. She has led courses at UCLA, USC, CSU, and Caltech spanning critical thinking with AI, biomedical research, regenerative medicine, and ethics.

    38 min
  4. What Happens When School Is Not Enough? - Laura Schroeder

    MAY 7

    What Happens When School Is Not Enough? - Laura Schroeder

    In this episode, Priten speaks with Laura Schroeder, an 18-year-old student in Germany who spent a year at an American high school and now participates in the Knowledge Society, a global innovation program for ambitious teens. Laura's dual experience across two education systems reveals a critical tension: while schools provide foundation and structure, ambitious students increasingly find their most meaningful learning happening outside formal classrooms, driven by curiosity and real-world project work rather than standardized curricula. Key Takeaways: American schools excel at fostering belonging and passion; German schools prioritize academic depth. The US system's emphasis on extracurriculars, personalized classrooms, and elective variety created a strong sense of community and identity, while Germany's more rigorous curriculum moved students through material years ahead—showing that schools can optimize for different values but rarely achieve both simultaneously.Technology in classrooms creates distraction rather than learning gains. Whether Chromebooks or iPads, digital devices enable both research efficiency and constant off-task engagement; Laura's choice to prioritize TKS work over classroom attention reveals that access to devices lets ambitious students opt out, while less motivated students simply drift.Project-based learning and standardized structures cannot coexist. Rigid schedules, subject silos, and grades as numbers fundamentally conflict with the flexible, exploration-driven learning Laura values—and attempting to layer PBL onto existing structures, or adding AI without rethinking foundations, misses the deeper architectural problem.School provides maturity and awareness that independent learning cannot. Laura credits high school with giving her the lived experience of education's shortcomings, which then motivated her own solutions; skipping formal education earlier wouldn't have accelerated her impact because she lacked the contextual understanding to see the problems that mattered.The students most prepared for the future are building it themselves alongside school, not through it. TKS, her project Passion Fruit, and her conference attendance are where Laura develops judgment, iteration, and genuine stakes—school becomes optional context rather than the primary engine of growth for students who have found their direction.Laura Schroeder is a high school student driven by curiosity and a desire to create meaningful impact. As an Innovator at The Knowledge Society, she builds projects at the intersection of AI, project-based learning, and student agency. Laura is on a mission to reimagine secondary education by returning to first principles and the 'why' behind education - advocating for personalized, interdisciplinary, and foundational education that equips students to thrive in today’s world and the one ahead.

    50 min
  5. Is Using Tech the Same as Understanding It? - Melvin D. Smith II

    MAY 5

    Is Using Tech the Same as Understanding It? - Melvin D. Smith II

    In this episode, Priten speaks with Melvin D. Smith II, a digital learning specialist and computer science teacher at an all-girls school in Maryland where he teaches a required ninth-grade course called Digital Thinking. Smith challenges the assumption that today's youth are automatically tech-savvy and doesn't shy away from restricting access—his school has a no-phone policy—while simultaneously teaching students how to think and communicate with intention in digital spaces. His perspective cuts through both extremes: neither "let them use everything" nor "technology is bad" but rather "understand what you're actually doing and why." Key Takeaways: Being surrounded by technology is not the same as understanding it. Students who've grown up with devices don't automatically know what cookies are, how algorithms predict behavior, or what happens to their data—the access itself teaches nothing without deliberate instruction on how the systems actually work.Removing phones from the classroom improved student focus, and students embraced the restriction because it came from them. When administration asked students what they thought about a no-phone policy rather than imposing it, students volunteered the idea and enforced it themselves—suggesting that transparency and student agency can matter more than the rule itself.Communication is the foundational skill that makes everything else—including AI use—work. Whether students are writing essays, coding, or prompting AI, the core challenge is knowing how to articulate what they actually want; bad communication produces poor results regardless of the tool.AI should be a sparring partner that pushes back, not a butler that does the work. The distinction between using AI to clarify thinking through dialogue and using it to bypass thinking entirely shapes whether it's a learning tool or a shortcut, and teachers need to model and enforce that distinction explicitly.The "digital native" myth obscures what students actually need to learn. Today's students need basic digital literacy—not just access to technology—and they need adults to show them responsible use in real time, because peer pressure and the competitive advantage of shortcuts remain powerful forces.Melvin D. Smith II’s path to tech instruction has been all but a clear one: first planning to be an astronaut to pilot the space shuttle, then changing to become a physician, then neuroscience researcher... 27 years ago he started his career in teaching (formal and informal) science. Adopting the philosophy of STEAM instruction before it became a thing, he fully embraced and utilized the disciplines for the learning environment- in and outside the classroom. Fast forward to his current position at Garrison Forest School in Maryland, Melvin still maintains that practical learning is the most salient and beneficial to developing soft skills and transferable knowledge. Whether in the Digital Thinking class, discussing and practicing the uses of technology to maintain a positive digital footprint; AP Computer Science Principles, where application development coincides with block and text coding; or a brand new course on the history and pedagogical use of AI, his coursework is still rooted in the idea that each student can be reached and succeed if they are given the correct tools, are willing to put forth the effort, and granted a little patience.

    38 min
  6. How Do You Teach Responsibility if Students Don't Care? - Lorin Koch

    APR 30

    How Do You Teach Responsibility if Students Don't Care? - Lorin Koch

    In this episode, Priten speaks with Lorin Koch, an educator who has taught across high school, online, and college settings after starting his career in journalism. Koch brings perspective from multiple vantage points—as a classroom teacher navigating AI integration, an online instructor confronting assessment challenges, and a parent of soon-to-be teenagers. Together they explore what happens when students understand the difference between learning and shortcutting but choose the shortcut anyway, and whether responsibility can be taught when the incentive to take a quick way out has never been lower. Key Takeaways: Understanding responsibility is not the same as practicing it. Students conceptually grasp that using AI to do their work for them is wrong, but when faced with pressure to get things done, they often choose the shortcut anyway—suggesting that knowing what you should do doesn't guarantee you'll do it.Self-paced, online environments create new accountability problems that have nothing to do with AI. The absence of in-person interaction makes it harder to detect cheating and easier to rationalize it, which means AI hasn't created the problem of student disengagement—it's simply made it more visible and more scalable.Your teaching intuition about whether something is AI-generated will become less reliable. As students grow up reading AI-generated text, their own writing will be shaped by those patterns, making it harder for teachers to distinguish between authentic voice and AI assistance based on stylistic markers alone.Presenting work through dialogue forces different stakes than submitting text alone. Requiring students to explain their thinking through presentations or discussion boards creates accountability that's harder to fake, even if the source material was AI-generated.The gap between high-achieving and struggling students will likely widen because of how students think about time. Students with short-term vision—those thinking about the next 24 hours rather than long-term consequences—are the most vulnerable to AI shortcuts, and they're also the ones who need human attention most.Lorin Koch is an educator with 21 years experience teaching high school and 3 years as a college instructor of education. He holds an Ed.D. degree from the University of South Carolina. Lorin currently teaches online and in person from Washington state, where he works at Walla Walla University. He also writes and presents on Artificial Intelligence in education, focusing on integrating generative AI into the classroom.

    31 min
  7. What If Our Pedagogical Goal Was Curiosity? - Mary Shawn Newins

    APR 28

    What If Our Pedagogical Goal Was Curiosity? - Mary Shawn Newins

    In this episode, Priten speaks with Mary Shawn Newins, a computer science teacher in Greensboro, North Carolina, who arrived in the classroom at sixty with decades of corporate and sales experience but no coding background. Her unusual arc gives her permission to build AI literacy alongside her students rather than ahead of them. What emerges is a classroom culture where curiosity itself—not mastery or fear—becomes the pedagogical goal. She uses practical structures like a "quack" incentive and peer questioning to shift how students see AI: not as a shortcut to avoid, but as a tool that works best when you know what you actually want to learn. Key Takeaways: Curiosity as a pedagogical aim changes everything about how students use AI. When learning for its own sake is the standard—not grades or compliance—AI becomes a catalyst for deeper exploration rather than a means of dodging work. A student asking AI about birds of prey out of genuine interest learns far more than one copying homework.Making AI use visible and gamified shifts students from hiding it to owning it. Mary's "quack quack" jar and peer accountability turn using AI into something worth discussing openly. Social transparency works where rules do not.Three non-negotiable standards replace prohibition: name the tool, share the prompt, explain the output in your own words. This mirrors citation practices students already know. It's not about policing—it's about maintaining the chain between question, resource, and understanding.Strict phones, generous computers reflects a deeper principle about attention and agency. Banning personal devices while enabling desktop computers creates a bounded space for learning. The boundary isn't about rejecting technology; it's about who controls the environment.Late-career teachers bring a rare asset: they remember how knowledge worked before AI. Mary's corporate background means she can model learning alongside students without needing to be the expert first. That permission ripples through the classroom.Mary Shawn M. Newins is a Marketing and Computer Science educator at Southern Guilford High School in Greensboro, North Carolina. She has been a full-time faculty member since Spring 2023 and proudly serves as the school’s AI Champion, supporting innovative and responsible technology integration in the classroom. Mary holds a Bachelor of Science in Education from Bowling Green State University and is an Ambassador for the CodeMonkey High School curriculum, advocating for accessible and engaging computer science education for all students. Before transitioning into education, Mary spent 30 years in the business sector, working across business-to-business sales, retail, direct sales, and operations management. Outside the classroom, Mary is a wardrobe stylist at Chico’s Friendly Center, a denim upcycler, and a creative at heart who enjoys painting.

    32 min
  8. Are We Building AI Literacy or AI Dependence? - Alyssa Muhvic

    APR 23

    Are We Building AI Literacy or AI Dependence? - Alyssa Muhvic

    In this episode, Priten speaks with Alyssa Muhvic, a high school history teacher in Indiana navigating AI's reshaping of her classroom. With experience on her district's AI task force and deep expertise in both AI literacy and equity concerns, Alyssa demonstrates how educators can lead rather than resist technological change. She challenges the assumption that AI's presence signals either inevitable dependence or straightforward disruption, arguing instead that the work is fundamentally pedagogical: helping students develop the judgment to use these tools responsibly while still engaging with core historical thinking skills. Key Takeaways: Treating AI as a search engine reframes citation, sourcing, and critical thinking as one unified practice. Students must learn to evaluate AI outputs with the same skepticism they'd apply to any source—examining bias, verifying claims, and contextualizing information. This makes digital literacy inseparable from historical literacy.The equity issue isn't access; it's reliability and responsibility at different price tiers. Paid AI plans produce output 20% more accurate than free versions. When affluent students get more reliable tools, the learning gap widens. Teaching responsible use becomes a justice issue.Academic dishonesty with AI reflects overwhelm, not moral failure. High-achieving students risk-taking for perfection; struggling students disengaging entirely. Neither group benefits from prohibition. Both need to understand why checking your work still matters.Transparency about your own AI use gives students permission to use it thoughtfully. When teachers hide their tool-use, students either view AI as forbidden or adopt it covertly. Showing your process—and its limits—normalizes critical engagement over sneaking.Districts need protected time, not more mandates, to equip teachers as active learners. Asking educators to master AI literacy while managing diploma rewrites, state standards shifts, and dual-credit pipelines is unsustainable. The bottleneck is time, not will.Alyssa Muhvic is a Social Studies Teacher at Noblesville High School in Indiana, where she has been shaping young minds since 2021. She teaches United States History, Pre-AP World History, and Indiana Studies, and was the driving force behind launching the school's Ethnic Studies course — designing and implementing the curriculum from the ground up. Alyssa earned her degree in General History and Secondary Social Studies Education, with a minor in African American Studies, from Ball State University in 2021.

    42 min
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About

Margin of Thought is a podcast about the questions we don’t always make time for but should. Hosted by Priten Soundar-Shah, the show features wide-ranging conversations with educators, civic leaders, technologists, academics, and students. Each season centers on a key tension in modern life that affects how we raise and educate our children. Learn more about Priten and his upcoming book, Ethical Ed Tech: How Educators Can Lead on AI & K-12 at priten.org and ethicaledtech.org.

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