My Robot Teacher

Students move across California’s public higher education systems all the time. Their access to AI tools, training, and infrastructure does not necessarily move with them.

In this episode of My Robot Teacher, Sarah Senk and Taiyo Inoue talk with David Goldberg of San Diego State University, Michelle Fischthal of the San Diego Community College District, and Dan Suchy of UC San Diego about the “Equitable AI Alliance” a regional partnership working across institutional boundaries to address that gap.

The conversation explores what equity means when students at neighboring institutions may have very different access to generative AI, AI literacy training, faculty support, and advanced computing resources. The Alliance’s response includes a shared AI micro-credential, coordinated faculty development, student surveys, and partnerships that extend access to computing infrastructure across the region.

But the episode is also about what makes that kind of coordination possible. David, Michelle, and Dan describe institutions sharing resources instead of duplicating them, using common data to understand student needs, and building the personal relationships that allow collaboration to continue across three different higher education systems.

At the center of the conversation is a simple problem: if colleges and universities increasingly expect students to understand and use AI, what happens when access to those opportunities depends on which institution a student happens to attend?

CHAPTERS

0:00-7:02 Chapter 1 - Introduction

7:03-11:01 Chapter 2 -  Introducing the Equitable AI Alliance

11:02-13:00  Chapter 3 -“Is It Something You’d Be Willing to Share?”

13:01-16:49  Chapter 4 - Access to AI Literacy Training and AI Tools

16:50-20:54 Chapter 5 - Chapter Surveying Students

20:55-29:56 Chapter 6 - How Many Students Use ChatGPT?

29:57-35:58 Chapter 7 - The Future of Work and the Promise of Collaboration

35:59-43:06 Chapter 8 - The AI Microcredential

43:07-48:33 Chapter 9 - AI-Ready California Workforce

48:34-52:20 Chapter 10 -  Sharing Institutional AI Infrastructure

52:21-55:02 Chapter 11 - Stop Competing, Start Collaborating

55:03-1:01:29 Chapter 12 - What’s in the Water in San Diego?

My Robot Teacher is hosted by Sarah Senk and Taiyo Inoue, produced by editaudio, and funded by the California Education Learning Lab, incentivizing innovation in teaching and learning in California’s public higher education.

Video Editing by Starline Hodge, Audio Editing by Megan Hayward, and our Production Manager is Kathleen Speckert.

📄 Full transcripts available on Substack: https://calearninglab.substack.com/s/my-robot-teacher-podcast

🌐 More about the show: https://www.myrobotteacher.ai

📨 Email us! [email protected]

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Applied category theorist and Topos Institute co-founder David Spivak joins Sarah and Taiyo to explore the mathematics of thinking together. They begin with a question that runs through the episode: when does a resemblance between two fields become useful enough to carry knowledge from one into the other? From epidemics and information to the institutional conditions for adopting AI, they explore how recognizing shared structures can open up questions we would not otherwise know to ask.

David explains why he helped build an independent research institute around teaching, interdisciplinary work, and practical applications; how “ontology logs,” or Ologs, make our mental models explicit; and why two eyes offer such a useful analogy for collective intelligence. In the closing conversation, Sarah and Taiyo show how they put these ideas to work: recording their discussions, using AI to examine the transcripts, and correcting its interpretations together. A lengthy disagreement about learning becomes a concrete example of how people can hear the same word, mean different things, and gradually learn to understand each other.

Also in this episode:

• What disease transmission and information spread can teach us about borrowing models across disciplines

• AI adoption as a phase transition: early adopters, connected groups, and institutional conditions

• When an analogy becomes useful—and why mathematical isomorphism is a more precise idea

• Why optimizing individual parts can create friction across a system

• Functors and ologs: translating between mental models and making their structure visible

• The practical difficulty of turning everyday relationships into formal models

• What gardening can teach us about abstraction and cultivating learning

• “Always be recording”: using a conversation archive to trace assumptions and revisit disagreements

• Why AI mediation becomes useful through shared review, correction, and iteration

CHAPTERS

00:00-11:58 - Chapter 1 Introduction: Same Shape, Different Domains

11:59-16:31 - Chapter 2 Topos Institute and a Different Model for Research

16:32-25:01 - Chapter 3 What Is Applied Category Theory?

25:01-28:10 - Chapter 4 Collective Sensemaking and Translating Perspectives

28:11-35:44 - Chapter 5 Ologs: Making Mental Models Explicit

35:45-40:04 - Chapter 6 Seeing Analogies More Easily

40:04-47:31 - Chapter 7 Always Be Recording: Revisiting Conversations and Learning to Think Together

My Robot Teacher is hosted by Sarah Senk and Taiyo Inoue, produced by editaudio, and funded by the California Education Learning Lab, incentivizing innovation in teaching and learning in California’s public higher education.

📄 Full transcripts available on Substack: https://calearninglab.substack.com/s/my-robot-teacher-podcast

🌐 More about the show: https://www.myrobotteacher.ai

📨 Email us! [email protected]

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Tags/Keywords:

David Spivak, category theory, applied category theory, Topos Institute, cross-disciplinary analogies, cross-domain isomorphisms, collective intelligence, AI in education, higher education, AI adoption, diffusion of innovation, phase transitions, abstraction, ontology, ologs, mental models, AI mediation, conversation transcripts, Codex, ChatGPT, Claude, My Robot Teacher, Sarah Senk, Taiyo Inoue, California Education Learning Lab

What kinds of struggle are essential to learning and what kinds of drudgery should we be happy to hand off to AI?

Leah Belsky, who leads education at OpenAI, joins My Robot Teacher to talk about one of the hardest questions facing educators in the age of AI: where to draw the line between productive friction and work that technology can usefully remove. Drawing on her work at OpenAI, her experience at Coursera, and her own life as a parent, Belsky makes the case for preserving the forms of difficulty that actually build understanding while using AI to make learning more accessible, personalized, and manageable.

The conversation then widens beyond the individual student to explore what AI might enable at the level of classrooms and groups: collective intelligence, project-based learning, new forms of critique and collaboration, and learning environments in which students become builders rather than spectators. They also discuss age-appropriate guardrails, why secondary education may need to become more interdisciplinary and maker-oriented, what the United States might learn from Estonia’s approach to technology and teacher agency, and why educators who are worried about AI need to engage with it rather than retreat from the conversation.

Also in this episode:

• Where the line falls between productive struggle and educational drudgery

• Columbia’s CAiSEY project and using AI to make case-based learning more interactive

• OpenAI’s new tools for study planning, flashcards, quizzes, and other student workflows

• Why Belsky would not put general-purpose chatbots in the hands of young children

• The case for teaching high school students to build and create with AI

• Moving the unit of AI design from the individual learner to the classroom and collective intelligence

• How AI can make project-based and collaborative learning possible at much greater scale

• Using AI as a “seminar secretary” to understand how groups think and learn together

• Why AI may blur traditional professional roles and push education toward greater interdisciplinarity

• What Estonia’s approach to privacy, teacher empowerment, and student responsibility might teach the United States

• Why treating AI only as a productivity or cost-cutting tool could undermine education

• Why educators need firsthand experience with current AI systems before they can meaningfully shape their use

CHAPTERS

0:00-6:40 - Chapter 1 Introduction: What Should We Delegate to AI?

6:40-10:23 - Chapter 2 Leah Belsky’s Journey to OpenAI and the Promise of Accessibility

10:23-16:58 - Chapter 3 Drudgery vs. Productive Struggle

16:59-20:35 - Chapter 4 Age-Appropriate AI and Rethinking Secondary Education

20:35-29:59 - Chapter 5 From Individual Agency to Collective Intelligence

30:00-40:05 - Chapter 6 Estonia, the United States, and Two Cultures of Educational Technology

40:07-44:28 - Chapter 7 Risk, Equity, and Why Educators Have to Engage

44:29-50:34 - Chapter 8 Reflections: Codex, Canvas, and the Faculty AI Epiphany

My Robot Teacher is hosted by Sarah Senk and Taiyo Inoue, produced by editaudio, and funded by the California Education Learning Lab, incentivizing innovation in teaching and learning in California’s public higher education.

📄 Full transcripts available on Substack: https://calearninglab.substack.com/s/my-robot-teacher-podcast

🌐 More about the show: https://www.myrobotteacher.ai

📨 Email us! [email protected]

🔔 Subscribe for extras: https://www.youtube.com/@myrobotteacher

UC San Diego Chancellor Pradeep Khosla joins My Robot Teacher to explain why large public universities need to move faster on AI, and why “mandated coordination” may be the wrong way to get there.

An internationally renowned electrical and computer engineer and co-chair of the University of California’s AI Steering Committee, Khosla has pushed one of the world’s leading public research universities to build its own AI infrastructure and experiment with new forms of teaching and student support.

Khosla takes My Robot Teacher co-hosts Sarah and Taiyo inside UC San Diego’s approach to AI innovation, from building TritonGPT on university-owned computing infrastructure to developing AI tutoring that dramatically reduced failure rates in gateway math courses. He makes the case for shared institutional goals paired with decentralized experimentation: giving faculty, students, and staff the freedom to test ideas, fail quickly, and circulate what they learn.

Also in this episode: 

• Skunkworks,” rapid experimentation, and the value of failing quickly

• How AI could make personalized education available at a scale universities could never previously afford

• Why public universities may need to rethink degrees, short-term credentials, and workforce reskilling

• What residential education still offers when individualized instruction can happen anywhere

• How AI could become both a great equalizing force and a driver of new inequality

0:00-6:08 - Chapter 1 Introduction

6:09-12:20 - Chapter 2 Triton GPT

12:21-16:43 - Chapter 3 Buy or Rent?

16:48-22:07 - Chapter 4 UCSD’s AI Skunkworks

22:08-24:39 - Chapter 5 Workforce Upskilling

24:40-27:46 -  Chapter 6 Residential Life in Education

27:47-32:48 -  Chapter 7 Elite but Not Elitist Education

32:49-41:31 - Chapter 8 College Preparedness Gaps

41:32-45:33 Chapter 9 Remaining Questions

45:33-55:52 Chapter 10 Reflections on Mandated Coordination 

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.substack.com/s/my-robot-teacher-podcast

🌐 More about the show: https://www.myrobotteacher.ai

📨 Email us! [email protected]

🔔 Subscribe for extras: https://www.youtube.com/@myrobotteacher

Follow us:

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AI can write code, and it writes it well. So what remains worth teaching? UC Berkeley computer scientist John DeNero joins Sarah and Taiyo to make the case for computational thinking — abstraction, decomposition, and the intuition that tells you when an output is wrong — as general education rather than vocational training. Along the way: why programmers get more out of AI coding tools than non-programmers, what an “AI agent” actually is, and why a CS degree is becoming less like a trade and more like a discipline.

C. Edward Watson, Vice President for Digital Innovation at AAC&U and coauthor of Teaching with AI, joins Sarah and Taiyo to ask how colleges can prepare students for an AI-shaped workplace when both the technology and the workplace itself are still changing. They discuss curricular agility, discipline-specific AI literacy, cognitive sovereignty, and why institutional context should shape how universities teach with AI.

When universities adopt AI at scale, do students learn to treat tools like ChatGPT as authoritative and trustworthy? Dr. Julie Carpenter joins Sarah and Taiyo to unpack AI in education through a sociotechnical lens and ask whether AI literacy can keep up with systems that invite our trust, emotional disclosure, and attachment.

What are faculty and students actually saying about AI when they are given a structured space to speak honestly? In this episode of My Robot Teacher, Sarah and Taiyo talk with April Lawson, co-founder of Insight Debate & Dialogue, about what she has learned from facilitating structured conversations about AI across colleges and universities. Her work brings faculty, students, staff, and administrators into rooms where the debate can move past pro-AI and anti-AI camps and toward collective sensemaking. Together, they discuss why AI conversations on campuses so often collapse into straw-man versions of “the other side,” how those caricatures make sensible AI policy harder, and what becomes possible when disagreement becomes a source of collective intelligence rather than institutional fracture.

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/ 🌐 More about the show: https://www.myrobotteacher.ai 📨 Email us! [email protected] 🔔 Subscribe for Extras: https://www.youtube.com/@myrobotteacher

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/

🌐 More about the show: https://www.myrobotteacher.ai

📨 Email us! [email protected]

🔔 Subscribe for Extras: https://www.youtube.com/@myrobotteacher

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/

🌐 More about the show: https://www.myrobotteacher.ai                 

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