The conversation highlights a key shift: while AI can handle the heavy lifting—like resume building, interview prep, and research—it also raises the bar for what makes candidates stand out. Adam emphasizes that storytelling, self-awareness, and communication are becoming even more important as AI-generated content becomes more common. In this new environment, the “human edge” is what differentiates students.

The episode also explores practical ways institutions can support this transition, from building safe spaces for interview practice to helping students develop “AI agility.” For educators and leaders, this is a thoughtful look at how AI can serve as a co-pilot—freeing up time for deeper mentorship while equipping students with the skills they need to navigate the future of work.

Drawing on his background in data and assessment, Matthew introduces the importance of systems thinking when working with AI. He explains how clear inputs, clean data, and thoughtful design can prevent the common trap of producing polished but unreliable outputs. The conversation highlights how educators can move beyond using AI for efficiency alone and begin to use it as a tool for deeper learning and problem-solving.

The episode also showcases how students can become creators with AI, not just users. From building custom study tools to collaborating across generations, Matthew shares examples that point toward a more active, hands-on model of learning. For educators navigating where to start, this conversation offers a simple but powerful message: begin with curiosity, start with what matters to you, and build from there.

The conversation traces a familiar journey many educators are experiencing—from fear of replacement to curiosity sparked by practical use. Elizabeth emphasizes that successful adoption doesn’t come from isolated efforts, but from shared ownership across campus. By bringing together faculty, IT, HR, and leadership, institutions can create environments where AI is explored responsibly and collaboratively.

The episode also highlights a critical shift in what it means to be “literate” in an AI-driven world. Beyond using tools, students and educators must develop the ability to question, verify, and interpret information with skepticism. For higher-ed leaders, this is a grounded conversation about how to start small, build confidence, and create systems that support both innovation and trust.

Drawing from his background studying technological disruption, Mike brings a balanced perspective on AI’s dual potential—its ability to expand access and efficiency, while also introducing new risks and ethical challenges. In the classroom, he’s experimenting with AI tutors and simulation environments that help students engage with opposing viewpoints, practice civil discourse, and develop stronger critical thinking skills.

The conversation highlights a broader shift in education: as AI automates more technical tasks, the value of uniquely human skills—judgment, communication, and ethical reasoning—becomes even more important. For educators and leaders, this episode offers a thoughtful look at how to use AI not as a shortcut, but as a tool to deepen learning and prepare students for participation in a rapidly changing civic and technological landscape.

Ann shares her journey from skepticism to advocacy, offering a grounded perspective on how educators can thoughtfully adopt AI without losing sight of what matters most. Rather than positioning AI as a replacement, she frames it as a tool that can create space for deeper human connection—freeing up time for mentorship, communication, and meaningful engagement with students.

The conversation also highlights the importance of intrinsic motivation, curiosity, and vulnerability in both teaching and learning. Ann emphasizes that educators don’t need to have all the answers—they just need to be willing to explore alongside their students. Through practical examples and personal stories, this episode offers a reassuring and actionable perspective for educators navigating the pace of change.

Rather than viewing AI as a simple tool, Adam introduces a more complex idea: AI as an extension of human capability. The conversation dives into how large language models change our relationship with knowledge, language, and problem-solving—while also raising important questions about authenticity, understanding, and the limits of machine-generated reasoning.

At the same time, the episode brings the conversation back to practical action. Adam encourages institutions to create safe, low-stakes environments for experimentation—starting with simple, high-impact use cases that support students and reduce administrative friction. For higher education leaders, this is a thoughtful look at how to approach AI with both philosophical depth and practical intention.

Ronan shares how AI has become a personalized learning partner—helping him translate ideas into code, accelerate research, and tackle projects that would typically require years of experience. Rather than replacing effort, he describes a continuous feedback loop between himself, AI, and his professors—where critical thinking and validation remain essential to the process.

The episode also highlights a growing disconnect between how students are using AI outside the classroom and how it’s being addressed within it. For educators and administrators, this conversation is a reminder that students are already building with these tools—and that the opportunity now is to shift from controlling usage to guiding it.

Orly shares why the arrival of generative AI felt like a milestone moment for educators who have long struggled to meet every learner where they are. Rather than replacing teachers, she sees AI as a powerful bridge—one that can transform passive experiences like lectures or museum exhibits into interactive conversations where learners actively participate and reflect on their thinking.

The conversation also tackles one of the biggest concerns educators face today: authenticity. Orly argues that when AI is used transparently as a brainstorming partner, reflection tool, or support system for complex tasks, it can actually strengthen human creativity rather than dilute it. The key is shifting the focus from final output to the learning process itself.

Looking ahead, the episode explores the potential of personalized AI tutors that understand a student’s learning history, motivations, and challenges. For educators navigating this moment of change, Orly offers a clear message: the future of AI in education is not about replacing human intelligence—it’s about designing systems that help it flourish.

The discussion highlights a growing shift across campuses: educators are no longer just debating AI—they’re asking for hands-on time to try it. Tawnya shares what she’s seeing succeed in workshops and faculty training, from building custom AI assistants to rethinking assignments to identify where human insight matters most.

The conversation also explores the psychological barriers faculty face, including fear of replacement, discomfort with unfamiliar tools, and the pressure of teaching technologies they’re still learning themselves. Through practical strategies like peer storytelling, dedicated learning time, and clearly defining what work remains uniquely human, Tawnya offers a thoughtful roadmap for institutions navigating AI implementation in higher education.

Zia Hassan—educator, professional coach, and PhD researcher at Johns Hopkins University—joins Zach for a thoughtful conversation about how generative AI is reshaping student motivation, classroom dynamics, and the very purpose of learning. Rather than focusing on tools or tactics, Zia explores how students mature in their AI use over time—learning to protect the parts of their work that make them feel “alive and human” while outsourcing the mundane.

The episode challenges control-based approaches to academic integrity and reframes AI not as a shortcut to police, but as a catalyst forcing education to move from “getting the right answer” to “asking the right questions.” Zia makes a compelling case for ungrading, personal knowledge management, and designing productive struggle—all while keeping relationships at the center.

As we mark 50 episodes, this conversation captures what the podcast has always been about: not hype, not fear—but deep thinking about how AI can help us build more humane, motivation-driven learning environments.

Kyle challenges the fixation on prompt engineering and AI detection, arguing that these conversations miss the bigger picture. If AI can easily complete an assignment, the issue isn’t the tool—it’s the design of learning itself. The discussion reframes academic integrity as a human problem, not a technical one, and invites educators to rethink how assessment can better reflect critical thinking, creativity, and growth.

The episode also highlights AI’s potential as an equalizer, particularly for students with learning differences who have long been underserved by traditional systems. By positioning AI as a thought partner rather than a shortcut, this conversation offers higher-ed leaders a thoughtful lens on how AI can support more humane, inclusive, and future-ready education.

Reilly offers a rare, engineer-first look at how large language models actually work—moving past hype and fear to explain embeddings, tokens, and probability in plain terms. By demystifying the technology, the episode helps educators and administrators better understand both the capabilities and the limits of AI, and why misunderstanding those fundamentals can lead to risky classroom use and misguided policy.

Using the metaphor of a “sensible car” versus a Ferrari, the conversation explores why educational AI needs guardrails by design. It also makes a strong case for teaching communication, critical thinking, and ethical reasoning as core AI skills—keeping humans firmly in the loop as AI becomes a normal part of teaching and learning.

What is AI doing to our intellectual character?

Christian draws a powerful distinction between moral character (how we behave) and intellectual character (how we pursue truth, knowledge, and understanding). Through personal reflection, philosophy, and cognitive science, he unpacks how generative AI introduces a uniquely tempting shortcut—one that doesn’t just risk academic integrity, but quietly reshapes how we think.

This conversation explores:

• The difference between moral wrongdoing and intellectual self-deception
• The seductive “glimmering ticket” AI offers when we’re overwhelmed
• “Knowledge laundering” and why unearned understanding erodes trust
• The long-term risk of reasoning atrophy when thinking is outsourced
• Why the real harm of AI misuse isn’t grades—but habit formation
• A Kantian ethical framework educators can use to guide AI decisions

Rather than focusing on detection or punishment, this episode reframes the conversation around who students are becoming in an AI-rich world—and what responsibility educators have to explicitly teach intellectual character, not just content.

This episode pairs especially well with conversations around post-plagiarism pedagogy and transparent AI policies, offering the philosophical and human counterweight to institutional approaches.

Peter introduces the idea of “reps” as the foundation of real expertise. Whether it’s building 100 financial models by hand or defending an investment thesis out loud, deep understanding only comes from repeated, manual engagement. AI can accelerate learning—but only if it’s used as a coach, not a crutch.

This conversation dives into:

• Why experiential learning beats textbook theory
• The difference between outsourcing thinking vs. sharpening it with AI
• Why verbal accountability is becoming the most honest form of assessment
• How AI is reshaping the workforce toward orchestration, not task execution
• Why liberal arts skills—psychology, judgment, communication—are becoming more valuable, not less
• What educators must redesign now to ensure students can explain, not just submit, their work

For educators, employers, and students alike, this episode is a wake-up call: in an AI-accelerated world, understanding beats output—and reps still matter.

Dr. Kassorla introduces a powerful reframing of Bloom’s Taxonomy for the AI era. If AI can now create first, then the real intellectual work for students begins afterward—through evaluation, analysis, application, and reflection. Rather than resisting this shift, she argues that educators should redesign learning to emphasize process over product.

Together, they discuss:

• Why AI should be treated as a starting point, not an endpoint
• How “Inverted Bloom’s Taxonomy” changes assignment design
• Why grading the journey eliminates the incentive to cheat
• The limits of AI detection and the harm of adversarial classrooms
• How shared vulnerability between faculty and students builds trust
• Practical ways to scaffold assignments and assess AI transparency

This episode offers a concrete, actionable framework for educators ready to move beyond detection and toward learning environments that reward thinking, iteration, and human judgment.

Dr. Bowen argues that while the internet changed our relationship with knowledge, AI is changing our relationship with thinking itself. As information becomes abundant—but increasingly unreliable—educators are no longer just teaching content. They’re teaching how to think, how to evaluate, and how to work alongside intelligent systems.

In this conversation, they discuss:

• Why AI should be viewed as a thinking partner, not just a tool
• What it means to teach when you’re no longer the “expert in the room”
• How AI reshapes writing, feedback, and learning processes
• Why metacognition and bias awareness are now core educational skills
• How faculty can prepare students for a world where thinking itself is augmented

This episode is essential listening for faculty, instructional designers, and academic leaders navigating what teaching looks like when AI is embedded into how humans reason, write, and decide.

Judith shares what she’s learned from more than a decade of consulting with institutions and leadership teams—and why AI leadership today has far less to do with being technical and far more to do with curiosity, courage, and comfort with ambiguity.

Together, they explore:

• Why AI leadership is not about being a “techie”
• How fear (not technology) is the biggest blocker to adoption
• Why faculty need guardrails, not bans
• What it means to lead when no one has all the answers yet
• How institutions can balance integrity, innovation, and trust

This conversation is especially relevant for presidents, provosts, deans, CIOs, and faculty leaders navigating AI strategy at the institutional level. Rather than focusing on tools, this episode focuses on mindset, governance, and human leadership in an era of rapid change.

If you’re responsible for guiding others through AI adoption—and feel the weight of that responsibility—this episode is for you.

Matt brings a powerful rural perspective to the AI conversation, framing artificial intelligence as a democratizing force—one that has the potential to level the playing field for rural, first-generation, and low-income students if implemented thoughtfully.

The conversation explores why many rural educators feel hesitant to adopt AI, the risks of blanket bans, and how institutions can build faculty capacity while still prioritizing critical thinking, equity, and durable skills. Matt also shares practical examples of how AI can support admissions, recruiting, faculty workflows, and student learning—without replacing human judgment.

This episode is a grounded, honest look at how AI can expand access and opportunity in higher education, especially in communities that are often left out of emerging technology conversations.

In this episode, you’ll hear:

• Why AI can be a leveling force for rural and underserved students
• The real fears educators have about “getting AI wrong”
• How AI can build faculty capacity instead of adding workload
• Why institutions need nuanced AI policies—not blanket bans
• The importance of teaching critical thinking alongside AI literacy

Grounded in the idea that “creativity is just intelligence having fun,” this conversation challenges traditional grading models and reframes AI as a guide on the side—not a replacement for educators, but a powerful creative and pedagogical partner.

Together, Zach and Pravin unpack how AI can democratize creativity, support differentiated instruction, and open new possibilities for students who have historically been underserved by traditional systems. The episode also dives into how educators can move away from “gotcha” teaching moments and instead use AI to foster curiosity, engagement, and deeper understanding.

🎨 In this episode, you’ll hear:

• Why traditional grading often fails to reflect real learning
• How AI can support creativity without replacing human judgment
• Practical classroom uses for visual, audio, and multimodal AI tools
• The role of AI in differentiated instruction and special education
• Why AI literacy is becoming essential for educators and students alike

This episode is a thoughtful reminder that when used intentionally, AI can make learning more human—not less.

Betty’s journey is incredible.

 She grew up in classrooms without even chalkboards… and now leads AI literacy and professional development initiatives at one of the top schools of education in the world. The through-line in her story is powerful:

In this episode, Betty breaks down the core tension in education right now:

• Teachers are being asked to teach in a world that looks nothing like the one they were trained for.
• Professional development is still treated as “one-and-done,” even though classrooms evolve daily.
• AI is accelerating change, but teachers often feel unprepared, undervalued, or afraid of being replaced.

And yet — she brings a refreshing, grounded optimism.

We talk about how to build ongoing professional learning communities, how to teach AI literacy through real-world examples students actually care about, and why IT departments and educators must collaborate instead of working in silos.

From dissecting a Gulf War headline to launching programs that merge design thinking, ethics, and artificial intelligence, Austin’s approach to education is all about creating “learners who wonder.”

This conversation explores how educators can maintain the human fingerprint in a world increasingly shaped by technology—and why AI literacy isn’t optional anymore.

In this episode, we cover:

• Why “Unexpected Resistance” became the foundation of Austin’s teaching philosophy
• How to teach students to analyze, not just consume, information
• The “fingerprint” method — using AI as a thought partner, not a replacement
• How to prepare students (and teachers) for an AI-enhanced world
• Why failure, questioning, and curiosity matter more than ever

Austin’s work reminds us that education isn’t about creating workers—it’s about developing thinkers who are ready to question, adapt, and create meaning in an AI-driven future.

Luca’s story is a perfect example of what happens when curiosity meets opportunity. From using AI to study, to teaching peers, to landing early consulting work, he shows how students can turn experimentation into real-world impact.

🎧 In this episode, we discuss:

• How curiosity and initiative led Luca to consulting at just 18
• Why time-saving is the biggest benefit of AI for students and professionals
• How education is failing to teach ethical and effective AI use
• What it means when the job market shifts “from a triangle to a diamond”
• How students can stand out by knowing what’s up in a changing world

Luca’s message is clear: AI isn’t about shortcuts — it’s about amplifying your curiosity and preparing for a future where those who adapt fastest thrive.

Scott shares his journey from being a disengaged student himself to spending two decades teaching special education in Milwaukee’s inner city—and now helping districts reimagine alternative education with AI as a catalyst for change.

The conversation dives deep into what truly drives engagement: relevance, experimentation, and permission to fail forward. Rather than chasing the next tool, Scott challenges educators to focus on connecting learning to life, freeing up time for meaningful interactions, and building a culture of innovation where educators feel empowered to experiment.

In this episode, you’ll hear about:

• How Scott’s early struggles in school shaped his entire career
• Why disengagement—not technology—is the real crisis in education
• How AI can amplify what great educators already do
• Practical ways to give teachers permission to tinker and learn together
• A roadmap for small, iterative innovation that makes learning relevant again

Scott’s story is both grounding and inspiring—a reminder that technology alone won’t transform education, but the people using it can.

From limited clinical access to overworked faculty, Galen paints a clear picture of the challenges today’s nursing programs face—and how thoughtfully implemented AI tools can bridge those gaps.

This conversation goes far beyond theory. Galen shares the four-step AI module she built for her students and unpacks how tools like Google Bard, Google Lens, and Boodle Blocks are helping nurses think more critically, access better information, and prepare for a workforce shaped by technology.

If you’ve ever wondered what AI in a high-stakes, human-centered field like nursing really looks like… this one’s a must-listen.

Mike’s story is one that every educator should hear: he went from actively avoiding AI to building an entire company around helping teachers not just adopt AI—but thrive with it.

This isn’t just a conversation about tools—it’s a deep, personal, and empowering discussion about mindset, transformation, and what it means to be an educator in an AI-powered world.

In this episode, you'll hear:

• How Mike spent 8–10 months ignoring ChatGPT—and why
• The book that changed everything (hint: 🧀)
• Why standardized testing might be the biggest obstacle to real innovation
• What teachers can do today to start learning AI, without pressure
• How AI can actually create jobs for teachers—not replace them
• What a future classroom looks like when AI and educators work together

Whether you’re a teacher, administrator, or education leader, this episode offers a roadmap to AI literacy grounded in honesty, humility, and hope.

Michael’s path is anything but ordinary — moving between the worlds of video game development and academia, he’s built a rare perspective on how to bridge creativity, technology, and education.

Together, Zach and Michael explore how the skills that make great game designers — experimentation, iteration, and imagination — are exactly what higher education needs to navigate the AI era.

In this episode, you’ll hear about:

• How Michael’s work in video games naturally led him to AI innovation
• Why universities need “translators” who can bridge technical and non-technical communities
• The expectation problem — why people think AI should act like every other program
• What makes ChatGPT 3.5 a turning point for higher education
• How AI can serve as a “thought partner” for rapid ideation and creative exploration
• The importance of managing hype while embracing potential

Michael’s story shows that the future of education isn’t just about adopting new tools — it’s about rethinking how we connect creativity, communication, and technology across disciplines.

In this special episode of the Smarter Campus Podcast, host Zach Kinzler sits down with Dawson Brown, a 7th-grade student from Sacajawea Middle School in Bozeman, Montana. Dawson shares his unique perspective on AI in education—and trust us, he’s got a lot to teach us.

Topics covered:

• ✅ Why Dawson prefers BoodleBox over other AI platforms (and what he thinks about Snapchat AI 👎)
• 🎓 How he uses AI to get ahead in math class
• 🧠 His bold claim: “AI has made me smarter”
• 🤝 Why teachers aren’t talking about AI—and why they should
• ⚖️ Dawson’s call for moderation and using AI as a learning tool, not a cheat code

This is the kind of conversation that will make you rethink how early AI literacy should start—and who should be leading it.

Whether you're an educator, a parent, or just someone interested in how the next generation is learning, this episode is a must-listen.

From decathlete to venture capitalist, Matt’s unorthodox journey shapes a unique perspective on AI, education, and the future of work. Together, Zach and Matt explore:

• How Matt uses ChatGPT as a thought partner—not a crutch
• Why today's education systems aren't preparing students for AI-integrated careers
• What soft skills will matter most in the AI age
• The paradox of democratized knowledge vs. shallow understanding
• Real talk on AI’s impact on job applications, productivity, and creativity

Matt’s advice? Use AI to sharpen your thinking, not skip it. And double down on the human skills machines can’t replace.

Whether you're a student, educator, or professional navigating this AI-driven shift, this episode will leave you inspired to think deeper, learn smarter, and stay human.

In this crossover episode, Sean Amaso—student creative, AI skeptic, and host of the brand-new podcast The Other Side—takes the interviewer seat for his show’s very first episode... and his first guest is none other than Smarter Campus host, Zach Kinzler.

Together, Sean and Zach dive deep into:

• Why balance—not blind adoption—matters when using AI
• The true role of human agency in the age of generative tech
• What we can learn from the past (like the story of ELIZA)
• Whether there’s such a thing as “ethical” or “responsible” AI
• Why Zach believes AI is a skill—not a shortcut
• And how both shows aim to reshape how we talk about technology in education

This isn’t your usual tech hype. It’s honest. It’s critical. It’s thoughtful. And it’s the start of a new kind of AI conversation.

Welcome to The Other Side.

Austin brings a fresh and relatable perspective to AI integration—not as an expert, but as a “casual user” who had to master AI tools out of necessity. Drawing from his background in outdoor recreation and workforce development, he offers an actionable blueprint for educators and professionals looking to harness AI without feeling overwhelmed.

Key Highlights:

• AI for Efficiency: How Austin used AI to streamline his multiple roles, demonstrating that you don’t have to be an expert to get results.
• Outdoor Meets AI: Why integrating technology into outdoor education matters and how it can increase access and affordability.
• The 3 C’s Framework: Austin’s roadmap for success—be curious, become competent, and be confident.
• Career Growth Mindset: Why staying “at the top of the mountain” requires continual learning and adaptation.
• Student Readiness: How AI can prepare students for the professional world without replacing critical thinking or curiosity.

This episode is perfect for educators, workforce leaders, and anyone interested in starting their AI journey with practical, low-barrier steps that create big results.

Chris shares his unconventional journey into AI, from wilderness expeditions and lab schools to leading Teton Science Schools and working in venture-backed edtech during the release of ChatGPT. His background informs a vision for AI in education that is less industrial and more experiential, personalized, and student-centered.

We dive into:

• The mission of Stanford’s Generative AI for Education Hub — to be a trusted, research-driven resource for school leaders
• Why privacy, security, and pedagogy matter more than hype in AI adoption
• How research partnerships with districts are uncovering what effective AI use looks like in practice
• Chris’s vision for transforming education away from factory models and toward more human-centered, hands-on learning

This episode captures a pivotal moment in AI adoption: one where the right balance between innovation and responsibility could redefine education for the next generation.

🔥 In this episode, we explore:

• Samantha’s journey from a freshman seminar on digital truth to becoming an active voice in AI ethics
• Why students are eager for formal guidance on AI usage—but aren’t getting it yet
• How faculty responses to AI vary widely, with some using it for coding instruction while others still avoid it entirely
• Princeton’s growing focus on ethical AI and the tension between innovation and integrity
• What it means to prepare students for an AI-driven world without sacrificing critical thinking

🎧 Whether you're a student, faculty member, or educational leader, this conversation offers a raw and thoughtful look at how one of the world’s top universities is navigating AI's impact on academic life.

With a background that blends physics, improvisational theatre, radio hosting, and educational leadership, Dr. Khaliq shares powerful insights into what teaching should look like in the age of AI.

What We Discuss:

• Why earning a doctorate doesn’t mean you know how to teach
• How AI can rebuild learning models—not just upgrade them
• Practical ways to use AI for onboarding, assessments, and collaborative faculty dialogue
• What it means to shift from delivering information to fostering curiosity
• The importance of community, improvisation, and embracing discomfort in teaching

Dr. Khaliq’s message is clear: education must evolve faster than it is—and AI is the catalyst to rethink not just how we teach, but why.

In this episode:

• Tina shares her journey from biomedical AI research to teaching humanities
• How she created the “Unblooom Method” to reimagine Bloom’s Taxonomy for AI-integrated learning
• Strategies for helping hesitant faculty ease into AI adoption
• Her belief that curiosity—not control—is key to preparing students for the future
• Practical advice on designing AI-augmented curriculum that students love

Tina’s thoughtful, nuanced approach to AI in education is a must-listen for anyone shaping the classroom of tomorrow.

Key highlights from the episode:

• Gary’s journey from assistant principal to three-time EdTech founder
• How early AI tools were used to predict and prevent student dropouts
• What the launch of ChatGPT means for access, creativity, and teaching
• Why schools aren’t changing fast enough—and how educators can lead the way
• Hard-won lessons from startup life: team building, financial literacy, and just getting started

This is a powerful conversation for anyone passionate about building real solutions for real problems in education.

Professor Lior shares her journey from researching cyberbullying to becoming a leading voice on AI policy and liability. Together, they explore topics like:

• The evolution of AI regulation and the challenges of governing emerging technologies
• Algorithmic bias in the justice system and the ethical concerns it raises
• How the insurance industry is adapting to AI-specific risks
• The complexities of assigning liability when AI systems cause harm
• Strategies for staying informed and teaching ethical AI use in classrooms

This episode is a powerful primer for educators, legal professionals, and anyone navigating the future of AI governance. Lior’s perspective offers both caution and optimism—encouraging proactive thinking as we build an AI-powered world.

Marie shares her early interest in AI sparked in late 2022 and how she’s since helped faculty reimagine classroom workflows using AI to foster efficiency, engagement, and goal-setting. She discusses post-pandemic teaching realities, barriers to adoption, and how analogies—like treating your classroom like a clean, well-designed home—help educators see the value of AI. This episode explores the deeper layers of what it takes to build trust in technology and design meaningful, student-centered learning experiences.

The episode explores Hoshino’s journey through Japan’s rigorous educational system and how that shaped his passion for student success. He recounts how milestones in AI—like Deep Blue’s victory in Go—sparked his curiosity, eventually leading him to experiment with generative AI tools in both personal and educational contexts.

Zach and Daiju delve into the tension many educators feel about integrating AI into classrooms. Hoshino acknowledges student skepticism around AI’s limitations but emphasizes the importance of developing critical thinking skills through guided, ethical use of these tools. He calls for robust support structures to help faculty and students navigate the evolving AI landscape, especially in fields like English and history where adoption may be more cautious.

From cultural comparisons to practical advice, this episode offers thoughtful reflections on how AI can serve as a partner in education—when introduced with intention, curiosity, and care.

What starts as a story about wind tunnels and biologically-inspired propulsion systems quickly evolves into a conversation about something just as dynamic: the transformation of teaching through AI. Bobby shares:

• His early work on underwater and aerial vehicles to measure hurricanes
• How experiential labs at CU Boulder help students bridge theory and practice
• Why AI made him completely rethink how technical writing is taught
• His vision for automated tutoring and AI tools that assess and support student understanding in real-time

Whether you’re in STEM education or just curious how AI is reshaping how we understand understanding, this episode is a must-listen.

Dr. Alby shares her inspiring vision to “re-enchant learning”—making education more engaging, human, and transformative. With decades of experience and research spanning pedagogy, psychology, neuroscience, and behavioral economics, she brings a refreshingly holistic lens to the conversation on AI in education.

Together, Zach and Cynthia explore:

• Her journey into AI advocacy and how she keeps up with educational trends
• The promise and peril of AI—why a balanced, thoughtful approach matters
• Use cases for AI in and out of the classroom, from public speaking support to roleplaying with parents
• How we can harness AI to amplify—not replace—what makes teaching and learning meaningful

If you're an educator, administrator, or just someone wondering how to use AI without losing the human side of education, this episode is for you.

• Prompting as musicianship: translating musical practice into crafting effective AI prompts
• The value of pedagogical friction: why struggle and resistance fuel deeper learning with AI
• Democratizing AI governance: ensuring adjuncts, staff, and students lead as much as administrators
• AI literacy as critical literacy 2.0: applying source-evaluation skills to AI-generated content
• Resources and funding: why meaningful AI integration demands time, budget, and institutional support

Join us for a deep dive into using AI to extend, not replace, human creativity—one conversation at a time.

• Maurie’s tech roots, from building a Heathkit computer to co-creating Agnes, the K–12 AI toolbox
• Strategies for piloting low-cost AI ($6.97/month!) in districts to prove impact
• A grade-by-grade roadmap: digital literacy in K, ChatGPT for onboarding in 2nd–3rd, prompting in 4th–5th, and safe AI practices in middle school
• How AI can enhance everything from menu planning to tech troubleshooting
• The mindset shift AI demands: continuous learning, creativity, and adaptability

Whether you’re an educator, administrator, or policymaker, this episode is packed with actionable insights to make AI accessible and empowering for your school community.

• Anna’s journey into AI and pivotal moments that shaped her vision
• How personalized, long-term planning with AI can revolutionize teaching and learning
• The importance of philosophical and pedagogical foundations before technology adoption
• Ethical considerations and responsible use of AI tools in classrooms
• Strategies to foster creativity, critical thinking, and collaboration with AI

This deep dive offers educators, administrators, and learners actionable insights on harnessing AI for a more inclusive, innovative educational environment. Tune in and join the conversation on the future of learning!

• Stefan’s journey from computer science teacher and debate champion to AI policy expert
• His eye-opening “aha” moment discovering ChatGPT’s potential to outpace Google
• Why the real conversation should shift from cheating concerns to AI’s transformative possibilities
• Practical strategies for teachers: embrace AI tools ethically and help students navigate bias
• The looming labor market disruption ahead—and how both educators and learners can prepare

Tune in for a candid discussion on responsibly harnessing AI to unlock positive change—because adapting is everyone’s responsibility.

• Joe’s path from political science undergrad to co-directing campus AI communities of practice
• How early web experiments evolved into today’s AI-driven tools
• Strategies for intentional AI adoption in higher ed, balancing innovation with human-centered values
• Practical tips for educators: build community, model humility, and engage with AI hands-on

Tune in for a grounded conversation on leveraging AI for campus-wide impact—no portraits needed, just big ideas and bold possibilities!

• How AI’s progression “goes viral” once it hits a tipping point (thanks to insights from Peter Diamandis’s The Future Is Faster Than You Think)
• The critical role of educators in unpacking AI’s ethics and debunking bias for students
• Practical examples of incorporating AI tools into media literacy courses
• Why understanding technology’s moral and ethical dimensions is as important as mastering the tools themselves

Get ready for a lively conversation that blends real-world teaching, cutting-edge tech, and a “cool cat’s” perspective on why AI shouldn’t be feared—it should be thoughtfully embraced. Tune in and discover how to prepare the next generation of learners for a world where change accelerates at lightning speed.

• Ruth’s journey from personal tech solutions for her learning difference to leading campus-wide assessment initiatives
• The influx of new assessment practitioners from diverse fields, and what it means for higher ed
• The moment AI became impossible to ignore—and how influencers like Donald Clark and Ethan Mollick shaped Ruth’s perspective
• Strategies for embracing AI in assessment without fear, transforming accreditation and learning experiences
• Why presence and engagement are crucial to navigating AI’s rapid evolution

Discover how AI can revolutionize assessment practices and empower educators to create data-driven, future-ready learning environments.

They dig into the early wins and growing pains of launching an “Emerging Technologies Committee” (think VR, AR, and AI), building a tech‑literacy framework, and shifting a traditionally slow‑moving library world into high gear. Laura’s top advice? Don’t fear the future—“jump in and join the party.” Whether you’re an educator, administrator, or simply AI‑curious, you’ll come away with concrete strategies for overcoming resistance, empowering students, and unleashing creativity far beyond the classroom. Tune in to see how AI can transform your campus—one chatbot at a time.

• Her journey from designing K-12 and higher-ed learning systems to leading large-scale online innovation programs
• Why the “AI-proof assignment” mindset is a dead end—and how embracing AI can unlock richer, more personalized learning experiences
• Practical strategies for supporting faculty as they adopt and integrate the latest AI tools
• Real-world examples of generative AI in action, and how it can elevate both student engagement and instructional design

Tune in for a forward-looking conversation that moves beyond fear of cheating to a vision of AI as a powerful partner in education’s next chapter.