My Robot Teacher

Ep12 - Querying the Collective Mind - CrowdSmart Co-Founder Kim Polese on Collective Intelligence

How can AI summon the wisdom of the crowd without the stupidity of the mob? In Episode 12 of My Robot Teacher, Sarah Senk and Taiyo Inoue talk with Kim Polese—co-founder of CrowdSmartAI and Common Good AI—about collective intelligence, deliberative tech, and a different vision of AI: not as a machine for generating answers, but as a facilitator that helps groups think better together. From enterprise strategy and citizen assemblies to seminar pedagogy, the conversation explores what happens when AI stops generating answers and becomes a facilitator for collective intelligence: surfacing tacit knowledge, preserving quieter voices, and helping institutions process forms of disagreement that usually disappear into noise. My Robot Teacher is hosted by Sarah Senk and Taiyo Inoue, sponsored by the California Education Learning Lab, and produced by editaudio. 📄 Full transcripts available on Substack: https://calearninglab.org/myrobotteacher/ [https://calearninglab.org/myrobotteacher/] 🌐 More about the show: https://www.myrobotteacher.ai [https://www.myrobotteacher.ai] 📨 Email us! myrobotteacherpod@gmail.com 🔔 Subscribe for Extras: https://www.youtube.com/@myrobotteacher [https://www.youtube.com/@myrobotteacher]

Ep11 - The Opposite of AI Slop: AI, Journalism, and Government Transparency

What does AI have to do with democracy? More than most people realize. In this episode — recorded on My Robot Teacher's one-year anniversary — we're joined by Kim Bisheff (Journalism, Cal Poly SLO) and Emmy-award winning professor Foaad Khosmood (Computer Engineering, Cal Poly SLO), the team behind the Digital Democracy Project, an AI-powered tool that makes state legislative proceedings searchable, transparent, and accessible to journalists and ordinary citizens alike. In this episode: * What the Digital Democracy Project is, how it works, and why it won an Emmy * AI as a civic tool: using machine attention to shine light on the government proceedings nobody has time to read * Why AI didn't start with ChatGPT — and why that history matters              * How Kim uses AI in the journalism classroom to teach story-finding, accountability reporting, and the politics of summarization                    * The hard lessons of the social media era — and how public-interest          technologists are trying not to repeat them                                    * Jargon as an enemy of transparency — and AI as a potential democratizer of dense government language                                                    * The difference between AI built for engagement and AI built for the public good                                                                         * "AI is not a monster to be feared. It's a monster to befriend."                                                                                  My Robot Teacher is hosted by Sarah Senk and Taiyo Inoue, sponsored by the California Education Learning Lab, and produced by editaudio.                                                                                                   📄 Full transcripts available on Substack:                                      https://calearninglab.org/myrobotteacher/ [ https://calearninglab.org/myrobotteacher/] 🌐 More about the show: https://www.myrobotteacher.ai [https://www.myrobotteacher.ai        ]                  📨 Email us! We'd love to hear from you! myrobotteacherpod@gmail.com 🔔 Subscribe for Extras: https://www.youtube.com/@myrobotteacher [https://www.youtube.com/@myrobotteacher ] https://www.youtube.com/@myrobotteacher

Ep10 - Teaching without a Script: Improv Pedagogy in the Probabilistic Classroom

What does improv have to do with teaching in the age of AI? More than you might think. In this episode, we’re joined by Julie Simons (Applied Mathematics, UC Santa Cruz) and Pedro Morales (Mathematics, UC Santa Cruz) to talk about improv not as performance, but as pedagogy - and, more broadly, a philosophy of classroom life. In this episode: * Why active learning may be a stronger response to AI than surveillance or detection tools * The case for improv as a philosophy of teaching, and why being wrong out loud might be the most important skill we can model for students * The difference between productive struggle and demoralizing struggle * Equity concerns around AI access, opt-out students, and who shapes these systems * The "broken bottom rung" problem: as AI absorbs entry-level jobs, how do students build the experience to eventually reach senior ones? * The remediation crisis in California: what happened when the CSU and community college systems  My Robot Teacher is produced with support from the California Education Learning Lab. My Robot Teacher is hosted by Sarah Senk and Taiyo Inoue, sponsored by the California Education Learning Lab, and produced by editaudio.  📄 Full transcripts available on Substack: https://calearninglab.org/myrobotteacher/ [https://calearninglab.org/myrobotteacher/] 🌐 More about the show: https://www.myrobotteacher.ai [https://www.myrobotteacher.ai] 📨 Email us! We'd love to hear from you! myrobotteacherpod@gmail.com 🔔 Subscribe for Extras: https://www.youtube.com/@myrobotteacher [https://www.youtube.com/@myrobotteacher]

Ep09 - Resilience Over Right Answers: Rethinking Science Education in the Age of AI (with Biophysicist Jon Sack, UC Davis)

Science education after ChatGPT: what happens when students can outsource the thinking, and still turn in something that looks right? In this episode of My Robot Teacher, CSU professors Sarah Senk and Taiyo Inoue talk with UC Davis biophysicist Jon Sack about AI literacy, scientific thinking, and how LLMs are reshaping both the classroom and the day-to-day reality of research. If the most available “mentor” in a student’s life is an LLM optimized to validate, what happens to the virtues science depends on: tolerating disconfirmation, staying curious through failure, and separating confidence from evidence? And if AI can generate the output, what exactly are we teaching - especially when the point is conceptual understanding, not polished answers? In this conversation, we explore: * What AI literacy should mean in science classrooms (beyond “don’t cheat”) * How to resist the reward of feeling right when LLMs produce fluent, plausible explanations on demand * How to redesign assessment so students can’t simply outsource the thinking * What “good” use looks like: prompting for falsification instead of praise, plus habits of verification and iteration * What AlphaFold and protein design teach us about hypothesis overload, “hallucinations,” and selection under uncertainty * The bigger meta-question: if we’re co-evolving with AI, how do we keep student agency intact? Ultimately, Jon argues that resilience isn’t a soft skill in science—it’s the method: reality-testing what sounds plausible (including AI-generated ideas) and iterating without outsourcing the thinking. Sponsored by the California Education Learning Lab. 💬 Drop your perspective in the comments. We may feature listener takes in a future episode. ✅ Subscribe for more “in the wild” classroom experiments and AI literacy for educators. CHAPTERS * 00:00-6:27 - Chapter 1 - Introduction: Claude Code Built My Canvas Course (Winter Break Experiment)  * 6:28-10:14 - Chapter 2 - Jon Sack’s First ChatGPT Moment (and the “Too-Positive” AI problem) * 10:15-12:44 - Chapter 3 - Resilience is the Core Skill in Science * 12:45-16:08 - Chapter 4 - Scientific Method = Falsification: “Kill Your Darlings” and Reality Testing * 16:09-19:26 - Chapter 5 - Conceptual Understanding vs. Outsourcing: When the Thinking is the Assignment * 19:27-25:25 - Chapter 6 - AL Literacy for Students: Use Every Tool, Track Limits * 25:26-28:22 - Chapter 7 - Inside Jon Sack’s Lab: Ion Channels and Stochastic Decisions * 28:23-30:36 - Chapter 8 - Stochastic 101: Probability, Sampling, and Why LLMs Vary * 30:37-38:55 - Chapter 9 - Are We Stochastic All the Way Down?  * 38:56-44:07 - Chapter 10 - AlphaFold & Protein Design: Cheap Hypotheses, Hallucinations, Verification * 44:08-53:30 - Chapter 11 - Co-evolving with AI: are tools optimizing around us, and are we changing around them? * 53:31-1:01:22 Chapter 12 - Education After ChatGPT: Epistemic Virtues, Judgment, and Student Agency

Ep08 - How to Teach AI (Not Just Use It) - with UC Berkeley’s Eric Van Dusen

What would it look like to teach AI literacy the way UC Berkeley teaches data science? hands-on, interdisciplinary, and open? In this episode of My Robot Teacher, Sarah and Taiyo talk with Eric Van Dusen from Berkeley’s College of Computing, Data Science, and Society about how the wildly successful Data 8: Foundations of Data Science course became a scalable model for modern computing education. Eric explains how connector courses and Jupyter notebooks help students from every major learn to code, work with real datasets, and think computationally. Then the conversation turns to small language models (SLMs) and what it means for students to actually “touch the model” - changing parameters, inspecting weights, and understanding tokens and temperature from the inside. Together, they sketch a vision for AI education in public universities: shared “AI sandbox” infrastructure, open tools, and a plan for teaching AI basics.  Chapters [0:00-4:05] Chapter 1 - Introduction: Is UC Berkeley's Data 8 the Blueprint for AI Education? [4:06-13:52] Chapter 2 - Inside Berkeley’s Data Science “Connector Course” Ecosystem [13:53-18:03] Chapter 3 - Jupyter Notebooks: Breaking the Textbook Paradigm with Live Code [18:04-26:12] Chapter 4 - SLMs vs. LLMs: Why Smaller is Better for Teaching [26:13-28:45] Chapter 5 - If AI Does the Work, What Skills Are Left? [28:46-34:04] Chapter 6 - Why Public Universities Need an AI Sandbox [34:05-37:44] Chapter 7 - on “Touching the Models” and Public Infrastructure [37:45-40:20] Chapter 8 - Hey Nvidia! We’re not just consumers.  [40:21-46:43] Chapter 9 - How AI Can Actually Make Teaching Better [46:44-50:37] Chapter 10 - A Model for AI Literacy Education: Applying the Berkeley Data Model to AI Studies [50:38-52:09] Chapter 11 - Join the Conversation on AI in Higher Ed My Robot Teacher is hosted by Sarah Senk and Taiyo Inoue, sponsored by the California Education Learning Lab, and produced by editaudio. Video Editing by Starline Hodge, Audio Editing by Megan Hayward, and our Production Manager is Kathleen Speckert. 📄 Full transcripts available on Substack: https://calearninglab.org/myrobotteacher/ [https://calearninglab.org/myrobotteacher/] 🌐 More about the show: https://www.myrobotteacher.ai [https://www.myrobotteacher.ai] 📨 Email us! We'd love to hear from you! myrobotteacherpod@gmail.com 🔔 Subscribe for Extras: https://www.youtube.com/@myrobotteacher [https://www.youtube.com/@myrobotteacher] 🎧 Listen on Apple: https://podcasts.apple.com/us/podcast/my-robot-teacher/id1818032413 [https://podcasts.apple.com/us/podcast/my-robot-teacher/id1818032413] Follow us on: * Instagram: https://www.instagram.com/myrobotteacher/ [https://www.instagram.com/myrobotteacher/] * YouTube: youtube.com/@myrobotteacher [http://youtube.com/@myrobotteacher] * X: x.com/myrobotteacher [http://x.com/myrobotteacher] * Bluesky: https://bsky.app/profile/myrobotteacher.bsky.social [https://bsky.app/profile/myrobotteacher.bsky.social] * Facebook: facebook.com/myrobotteacher [http://facebook.com/myrobotteacher] Tags/Keywords AI in Education, Higher Education, Data Science, UC Berkeley, Data 8, Eric Van Dusen, Small Language Models, Jupyter Notebooks, EdTech, Artificial Intelligence, Python, SLM vs LLM, Connector Courses, AI Literacy, Public Education, Computational Thinking, Cal State University, CSU, My Robot Teacher Podcast, Sarah Senk, Taiyo Inoue, California Education Learning Lab, AI Infrastructure, Open Source Education, editaudio