Podcast
Kinwise: AI Insights for Educators
Hosted by Lydia Kumar · EN
AI is reshaping education—fast. The question is: how do we use it well?
Kinwise: AI Insights for Educators is a podcast about how teachers, schools, and districts are actually using AI in real classrooms.
Kinwise is an AI-powered instructional coaching platform for teachers. Through this podcast, we explore the real stories, decisions, and challenges shaping AI in education today.
Each episode features conversations with educators, leaders, and innovators navigating:
• Real classroom use cases (what’s working and what’s not)
• Practical strategies for teachers and school leaders
• Ethical questions about AI, learning, and human development
• How schools are preparing students for an AI-powered future
Season 1 explored AI and the future of work.
Season 2 focuses on AI in education: how teaching, learning, and leadership are changing right now.
If you're a teacher, school or district leader, or education professional trying to use AI with clarity and purpose, this podcast is for you.
Subscribe and learn more at https://kinwise.ai
15episodes
Episodes
Newest firstAll episodes
The Skeptic and The Optimist: Navigating AI in Higher Education
Jan 800:41:36Tap to summarizeJoin us for a candid debate between two colleagues who view the future of AI in education through very different lenses. We are joined by Dr. Jason Margolis, an AI skeptic who worries about the atrophy of critical thinking, and Dr. Nicole Schilling, an AI optimist who sees these tools as essential scaffolds for complex problem-solving. Together, they model the concept of "Critical Friends," engaging in respectful but challenging dialogue on a polarizing topic. We dive deep into the ethics of the "8-minute dissertation," the tension between efficiency and the learning process, and why we might need flexible guidelines rather than rigid policies in this rapidly changing landscape. Whether you are an educator, a leader, or just someone trying to figure out where the human ends and the machine begins, this conversation offers a roadmap for navigating the grey areas of innovation. Key Discussion Points: Skeptic vs. Optimist: Jason’s concern about "outsourcing our brains" versus Nicole’s vision of AI as a partner in social constructionism. The "8-Minute Dissertation": A critical look at what is lost when we prioritize the product (the degree) over the process (the struggle of learning). Ethical AI Use: Examples of high-level use, such as training an AI model to act as a rigorous dissertation committee rather than writing the paper for you. Bias and Power: Addressing the "racist undertones" in algorithms and questioning whose interests are really served by the rapid adoption of AI. Policy vs. Guidelines: Why creating rigid policies for fast-moving tech is often futile, and the argument for developing ethical "guidelines" instead. The Critical Friends Model: How to disagree productively and maintain professional relationships in an era of polarized viewpoints.
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Redesigning the Syllabus for Deeper Learning: AI, Empathy, and Assessment
Dec 1700:42:29Tap to summarizeJoin us for an insightful conversation with Dr. Dana Riger, UNC's inaugural Faculty Fellow for Generative AI, as she guides us through the rapid paradigm shift brought on by AI in higher education. Dr. Riger shares her journey from a "fear-driven" assessment redesign, after discovering ChatGPT, to developing a nuanced, values-driven framework for integrating and avoiding AI in the classroom. We dive into practical strategies, like redesigning traditional research papers into creative, AI-avoidant multimedia projects, and intentionally integrating AI for skills development, such as using chatbots for practice dialogues on polarizing topics. Dr. Riger also addresses the institutional challenge of avoiding "one-size-fits-all" AI policies and underscores the importance of fostering an open dialogue. Ultimately, this episode offers a compelling vision for the future of teaching, emphasizing that the human educator's unique value lies in fostering empathy, presence, and critical dialogue, not just imparting knowledge. Key Discussion Points: -The AI Paradigm Shift: Dr. Riger's initial reaction to ChatGPT and her immediate, fear-driven assessment redesign in 2022. -The Nuanced Approach: Distinguishing between AI-avoidant (experiential, creative) and AI-integrated (intentional skill-building) assessments. -Practical Examples: How a multimedia project replaces a traditional paper, and using AI to practice difficult, emotionally laden conversations. -Leading with Collaboration: Why policing AI use is ineffective and the importance of respecting student autonomy and ethical objections. -Institutional Guidance: The missteps of mandated, uniform AI policies and the need for a thoughtful "middle ground" approach. -The Value of Process: Shifting assessment focus from the final product to the process of learning (drafts, revisions, process logs). -The Core Question: What are the unique, human-centered qualities (empathy, presence) that educators must prioritize in the age of AI?
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Trailblazing AI Literacy: Connor Mulvaney’s Rural Classroom Revolution (Rebroadcast)
Nov 1900:39:53Tap to summarizeIn this episode from the archives, Montana science teacher and district AI lead Connor Mulvaney joins host Lydia Kumar to share how he turned fishing photos, traffic-light rubrics, and a healthy dose of curiosity into AI leadership in Montana and across the nation. Fresh off announcing aiEDU’s largest Trailblazers Fellowship expansion, Connor shares stories about leading students and educators to responsible AI adoption. In this episode, you’ll learn: Break-the-Ice Questions – Three questions that instantly surface student misconceptions (and enthusiasm) about AI. Fake Fish, Real Ethics – Using deepfake trout to spark serious debate on consent, bias, and digital citizenship. Trailblazers 2.0 – What’s inside the 10-week fellowship (virtual sessions, $875 stipend, national recognition) and why rural teachers asked for it. This episode is for K-12 educators, district leaders, and mission-driven education organizations who want to shift AI conversations from fear and plagiarism to possibility and purpose.
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Danelle Brostrom on Leading AI: Privacy, Humanity, and Progress in Schools
Nov 1200:36:48Tap to summarizeK-12 EdTech coach Danelle Brostrom joins us to talk about bringing curiosity, guardrails, and humanity to AI in schools. We dig into what we should learn from the social-media era, how librarians are frontline partners for information literacy, the real risks inside edtech privacy policies (and how districts can negotiate them), and concrete ways AI can expand access, like instant translation, reading-level adjustments, and executive-function supports. If you’re a district leader, principal, or teacher trying to move from paralysis to practical action, this conversation is your on-ramp. Key Takeaways Don’t repeat social media’s mistakes. Protect in-person connection; teach students how to spot manipulated media and deepfakes. Librarians = misinformation SWAT team. Pair EdTech with media specialists to teach reverse-image search, corroboration, and bias checks. AI is already in your stack. Inventory tools teachers use; many “non-AI” products now include AI features that touch student data. Equity in action. Real-time translation, leveled texts, and scaffolded task breakdowns can immediately widen access—offer to all students. PD that sticks. Start with low-stakes personal uses (meal plans, resumes), then ethics, then classroom workflows—build a safe space to wrestle. Listen first. Talk to students about how they’re using AI; invite skeptics to the table. Leadership mindset. Curiosity, grace, and progress over perfection.
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Duke's Ahmed Boutar on AI Alignment: Ensuring Users Get Desired Results
Nov 500:43:49Tap to summarizeIn this episode, we’re joined by Ahmed Boutar, an Artificial Intelligence Master’s Student at Duke University, who brings a rigorous engineering focus to the ethics and governance of AI. Ahmed’s work centers on ensuring new technology aligns with human values, including his research on Human-Aligned Hazardous Driving (HAHD) systems for autonomous vehicles. This conversation is an urgent exploration of the practical and ethical challenges facing education and industry as AI progresses rapidly. Ahmed provides a critical perspective on how to maintain human judgment and oversight in a world increasingly powered by Large Language Models. Key Takeaways The Interpretation Imperative: The most critical role of an educator today is to ensure that students move beyond simply accepting AI output to interpreting it, explaining it, and wrestling with the material in their own words. This is the ultimate guardrail against outsourcing thinking. The Alignment Problem: AI failures often stem from misalignment between the intended goal (outer alignment) and the goal the AI actually optimizes for (inner alignment). The chilling example provided is an AI that solved the objective of "moving the fastest" by designing a tall structure that immediately fell down to maximize speed. Transparency is Governance: For high-stakes decisions like loan applications or hiring, users and regulators must demand transparency into why an AI made a prediction. Responsible development requires diverse perspectives on design teams to prevent innate biases in training data from causing discrimination. Adoption Over Abandonment: As humans, we cannot stop AI's progress. Instead, we must adopt it to augment productivity, while simultaneously creating policy and guardrails that ensure fair and responsible use. A Hope for Scientific Discovery: While concerned about the concentration of AI development in a few large companies, Ahmed remains optimistic about AI's potential in scientific fields like drug discovery and proactively addressing global crises, as seen during the COVID-19 pandemic.
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