AI x Higher Ed Podcast

David A. Rettinger, applied professor and undergraduate program director in psychology at the University of Tulsa, joins the AI x Higher Ed podcast to discuss academic integrity, learning, and assessment in the age of generative AI. As co-author of The Opposite of Cheating, David brings together insights from cognitive science, decision science, teaching and learning, and honor systems to explore why cheating happens, how AI is changing assessment, and what higher education can do next.The conversation covers why academic integrity should be understood as a teaching and learning challenge rather than simply a rule-enforcement problem; how relationships, trust, and student motivation shape ethical behavior; why traditional assessment models are under pressure from AI; and how faculty can redesign learning experiences around process, oral assessment, experimentation, and authentic demonstrations of understanding.David also previews his keynote for the Reimagining the Liberal Arts in the Age of AI conference at the University of Mary Washington: “The Opposite of Cheating: Teaching for Integrity in the Age of AI.”Chapters00:00 – Introduction to David A. Rettinger01:12 – Previewing “The Opposite of Cheating” keynote03:20 – Writing for impact beyond traditional academic publishing05:35 – Connecting cognitive science, teaching, and academic integrity09:15 – How faculty learn to teach and how students learn integrity12:25 – Honor codes, student ownership, and the role of campus culture16:45 – Why large-scale assessment struggles in the AI era19:30 – Cheating as normal human behavior22:40 – Moral disengagement, motivation, and why students break rules26:45 – Reframing integrity as learning, not just rule-following30:10 – Starting with learning objectives in AI-era course design34:35 – Cognitive offloading, AI use, and what students still need to learn39:20 – Why process matters more than the final paper44:15 – Designing assessments that reveal learning48:00 – Experimentation, failure, and rethinking grades52:25 – Scaling challenges and the future of assessment design57:10 – Oral assessment, conversation, and knowing what students understand1:02:45 – What AI can and cannot do in ethical decision-making1:08:10 – Cheating, creativity, and changing definitions of misconduct1:13:30 – Designing systems that align students’ interests with learning1:16:45 – Where to find David’s work1:18:00 – Closing thoughtsLearn more about David Rettinger, Tricia Bertram Gallant, and The Opposite of Cheating:https://theoppositeofcheating.com#AIxHigherEdPodcast #ArtificialIntelligence #HigherEducation #AcademicIntegrity #TeachingAndLearning #GenerativeAI #AIinEducation #Assessment #LiberalArts #EdTech #FacultyDevelopment

Are we getting closer to AGI—and is higher education ready for what comes next?In this AI x Higher Ed update, we unpack the latest signals from AI leaders including Demis Hassabis, Sundar Pichai, Sam Altman, and others on AGI timelines, agentic AI, scientific breakthroughs, and the idea of intelligence becoming a utility like electricity.The conversation then turns to a major new intervention from Pope Leo XIV: a sweeping encyclical on artificial intelligence, human dignity, education, leadership, communication, and the urgent need for society to prepare. We explore why this document matters far beyond religious communities and why its message may be especially important for schools, colleges, universities, parents, and policymakers.From AI agents and blockbuster IPOs to curriculum disruption and the future role of teachers, this episode asks what it would mean to stop treating AI as a classroom tool and start treating it as a civilization-shaping force.Chapters00:00 – Are We Getting Closer to AGI?02:10 – Demis Hassabis, Google I/O, and AGI Timelines04:45 – Sundar Pichai’s More Cautious View06:28 – Gemini Solves Erdős Problems: Breakthrough or AGI?09:32 – Why Advanced Math Performance Is Not AGI12:22 – Demis Hassabis on 2030, 2029, and the Next Wave of Agents16:05 – Agentic AI as a Practice Run for What Comes Next20:10 – SpaceX, OpenAI, Anthropic, and the Coming IPO Wave23:48 – How IPOs Could Shape AI Strategy and Adoption27:40 – Google, DeepMind, and Accelerating Science31:15 – Sam Altman and Intelligence as a Utility35:20 – Why AI Could Transform Society Like Electricity39:10 – Pope Leo XIV’s Encyclical on AI44:30 – Why This Document Matters Beyond Religion49:15 – Christopher Olah, Anthropic, and Moral Oversight54:00 – AI, Human Dignity, and the Question of Consciousness1:00:20 – Education as a Central Concern1:06:10 – Why Current School AI Guidance Falls Short1:12:00 – Curriculum, Assessment, and the Role of Teachers1:18:25 – Building Awareness and Preparing Institutions1:23:15 – Human Capacities Beyond Intelligence1:28:45 – Communication, Dialogue, and Shared Meaning1:33:20 – Universities and the Integration of Knowledge1:38:40 – Parents, Schools, and the Limits of Individual Responsibility1:44:30 – Why Society Needs Alliances Around AI1:50:10 – Rejecting Fatalism: Our Choices Still Matter1:56:00 – Final Reflections: Start Preparing Now#aixhigheredpodcast #AI #AGI #HigherEd #AIEducation #ArtificialIntelligence #AIxHigherEd #FutureOfWork #AIAgents #EdTech #GoogleDeepMind #OpenAI #Anthropic #Podcast

Marine veteran, entrepreneur, and nonprofit leader Rich Brown joins the AI x Higher Ed Podcast for a wide-ranging conversation on Agentic AI, leadership, education, and what it means to prepare students for a rapidly changing future.Rich shares how he has been using AI agents across business, nonprofit work, curriculum design, executive protection, and even personal communication. Rather than treating AI as a shortcut, Rich describes it as a force multiplier: a tool that can help people move faster, think more deeply, refine their ideas, and solve meaningful problems.The conversation explores why education must move beyond simply banning or permitting AI and instead focus on process, judgment, iteration, and student agency. Rich also discusses the Service Leadership Academy, a program designed to help high school students develop self-awareness, team leadership, conflict navigation, and community problem-solving skills. The result is a conversation about AI that is ultimately about people: how we lead, how we learn, and how we prepare for a world where the ability to solve problems may matter more than any single career path.

In this thoughtful and wide-ranging conversation, Dr. Theresa Burriss joins the AI x Higher Ed Podcast to explore what authenticity means in the age of artificial intelligence. Drawing from philosophy, Appalachian studies, environmental justice, and decades of teaching experience, Dr. Burriss reflects on how AI challenges our assumptions about voice, creativity, learning, and human connection.The discussion moves from existentialism and storytelling to AI literacy, environmental impacts of data centers, representation of marginalized communities in generative models, and the enduring importance of the liberal arts. Throughout the episode, Dr. Burus argues for embracing tension rather than eliminating it — recognizing AI as both a powerful tool and a profound disruptor that requires ethics, critical thinking, and deeply human conversations.

n this week’s AI x Higher Ed update, we unpack the accelerating pace of artificial intelligence development and what it means for higher education, industry, and society at large. From AI systems collaborating with one another and coding autonomously for hours at a time, to major infrastructure battles over compute power, the conversation explores how rapidly the AI landscape is evolving.The episode covers new breakthroughs from Thinking Machines, Anthropic, OpenAI, Google, and Neuralink, along with emerging applications in law, cybersecurity, robotics, scientific research, and mathematics. The hosts also examine the growing societal tensions around AI, including student backlash, workforce disruption, ethical concerns, and debates over universal basic income.As AI capabilities continue to scale, the discussion highlights a central challenge for higher education: preparing students and institutions for a future where AI is not just a tool, but an active collaborator shaping nearly every field.#aixhigheredpodcast #ArtificialIntelligence #HigherEducation #AIinEducation #GenerativeAI #Anthropic #OpenAI #Robotics #FutureOfWork #AIResearch #EdTech #AILeadership #HigherEd

In this episode, we sit down with Tim Mousel (Lone Star College), kinesiology professor turned AI innovator, to explore how curiosity, necessity, and relentless perseverance led him to become one of the most influential voices in AI and higher education.From building early software tools before ChatGPT existed to advising national AI initiatives, Tim shares a powerful perspective on why AI isn’t just a tool—but a fundamental shift in how we teach, learn, and prepare students for the future.We dive into:- The importance of purpose-driven learning- Why most assignments are broken (and how to fix them)- How faculty can overcome resistance to AI- The growing gap between education and workforce expectations- Why AI will expose mediocrity—and what to do about itIf you care about the future of education, this is a must-listen.⏱️ Chapters00:00 – Intro & Meeting Tim at Lone Star College02:10 – From Kinesiology to Coding: An Unlikely Journey06:30 – Building AI Tools Before ChatGPT10:45 – The Power of Purpose-Driven Learning15:20 – Martial Arts, Resilience, and the “Never Quit” Mindset20:10 – Why Students (and Faculty) Lack Motivation24:30 – Faculty Resistance to AI: What’s Changing29:00 – Why We Overestimated AI Adoption Speed33:15 – The Future of Higher Ed (and Who Gets Left Behind)38:40 – AI-Responsive Assignment Design (A-RAD Framework)45:10 – A Better Assignment: From Paper to Chatbot Creation52:30 – The AI Literacy Gap (97% vs. 20%)58:00 – Why One AI Course Isn’t Enough1:02:20 – Building System-Wide AI Transformation (Task Force Strategy)1:10:15 – Agentic AI & Multi-Model Workflows Explained1:18:40 – Building a Business in 6 Hours with AI1:24:30 – The White House AI Meeting: Missing Educators1:30:10 – The Dangerous Gap Between College and Workforce Expectations1:36:00 – “AI Will Expose Mediocrity”1:41:20 – Final Thoughts & Where to Find Tim#AIinHigherEd #EdTech #GenerativeAI #FutureOfWork #HigherEducation #AIEducation #DigitalTransformation #FacultyInnovation #AILeadership

The pace of AI development is accelerating faster than most institutions, and most people, are prepared for. In this May 5, 2026, AI Update, the AI x Higher Ed team explores the growing momentum toward AGI, recursive self-improvement, humanoid robotics, AI-driven job displacement, and the emerging moral dilemmas shaping the future of society.The conversation examines why leaders like Sam Altman and Mark Cuban believe AI literacy is becoming essential for students and workers alike, while also unpacking growing concerns around employment disruption, AI consciousness, military integration, government oversight, and AI alignment.The episode also dives deeply into AI pluralism — the argument that society cannot rely on a single dominant AI worldview — and why higher education institutions may play a critical role in helping students navigate the ethical, political, and social consequences of increasingly powerful AI systems.#ArtificialIntelligence #HigherEducation #AGI #AIAlignment #AIPluralism #EdTech #FutureOfWork #Automation #GenerativeAI #HigherEd #AIethics #HumanoidRobots

What happens when artificial intelligence forces higher education to confront long-standing assumptions about teaching, learning, and assessment?In this episode of AI x Higher Ed, Stefan and Anand sit down with Lance Eaton, Senior Associate Director of AI in Teaching and Learning at Northeastern University, to explore why AI is not simply another educational technology disruption — and why liberal arts institutions may be uniquely positioned to respond.Lance discusses the tension between resisting AI and critically engaging with it, the “militant apathy” emerging among students after the pandemic, the limits of traditional lectures and assessments, and why higher education must rethink learning design for an AI-enabled world.The conversation also dives into faculty development, communities of practice, agentic AI workflows, and what successful institutional transformation could look like over the next several years.Whether you’re skeptical, curious, or already experimenting with AI in the classroom, this episode offers a thoughtful and deeply practical discussion about the future of teaching and learning.Chapter Markers00:00 – Introduction to Lance Eaton and upcoming keynote on liberal arts and AI03:10 – Why AI exposes long-standing problems in higher education08:15 – Convenience models, lectures, and the structure of education14:20 – “Militant apathy” and the post-pandemic student experience20:45 – Why AI feels different from previous technological disruptions28:10 – Small design shifts faculty can make right now35:30 – Meeting students where they are with AI-assisted research42:40 – Resistance, privilege, and the ethics of AI avoidance53:20 – The highest-leverage moves faculty can make this fall59:50 – Faculty cohorts and communities of practice around AI1:06:40 – Liberal arts, transfer skills, and teaching for adaptability1:15:10 – Agentic AI and the next phase of educational transformation1:25:30 – What successful AI transition could look like in 3–5 years1:33:00 – Final reflections and where to follow Lance Eaton#AI #HigherEducation #GenerativeAI #LiberalArts #TeachingAndLearning #FacultyDevelopment #EdTech #AgenticAI #NortheasternUniversity #AIinEducation

What if students didn’t just learn about complex global issues—but lived inside them?In this episode of the AI x Higher Ed Podcast, we explore how simulation-based learning—powered by AI—is redefining engagement, retention, and critical thinking in education. From a struggling classroom at Georgetown to immersive geopolitical simulations used by universities, the military, and even high schools, this conversation reveals how games are becoming one of the most powerful learning tools of our time.We dive into the creation of the Providence platform, how large language models are enabling scalable simulation design, and why the future of education may lie at the intersection of storytelling, strategy, and unpredictability. We are joined by CEO Daveed Gartenstein-Ross and Product Owner Jesse Nimons from ExpertTheory. You can find out more at: https://www.experttheory.com/ ⏱️ Chapter Markers00:00 – The classroom moment that changed everything02:14 – The “click” moment: when learning becomes immersive04:50 – Why traditional game design was too slow (and expensive)06:47 – The ChatGPT breakthrough and the birth of Providence08:34 – What simulation learning actually looks like in practice10:19 – Inside a live simulation: what engagement really means12:22 – From classrooms to global strategy games15:02 – How students apply knowledge in real time17:11 – Why simulations improve memory and understanding18:26 – Learning through storytelling and perspective-taking19:45 – When real-world professionals learn from games23:10 – The “secret sauce” of immersive simulations25:09 – Beyond security studies: applying games to any field27:24 – Case study: reimagining the lottery industry through gameplay30:18 – Why traditional war games fall short31:19 – Embracing unpredictability in learning33:35 – Designing for chaos, creativity, and competition35:01 – When “off-the-rails” behavior becomes strategy37:53 – Hiring through gameplay: a new signal of talent38:26 – AI anxiety vs. deeper thinking through simulations39:40 – Bringing simulation learning to high schools40:52 – Arctic Awakenings: climate, geopolitics, and complexity43:22 – Middle school simulations and “six touches” learning46:27 – Can games replace traditional education?49:30 – Why gamification fails—and what works instead50:23 – The hybrid model: lecture + simulation52:00 – Scaling access with AI and affordability54:02 – The future: AI adjudication and democratized learning#AIinEducation #HigherEd #EdTech #ActiveLearning #SimulationLearning #FutureOfEducation #AI #LearningInnovation

In this week’s AI x Higher Ed podcast update, we explore a provocative question increasingly raised by AI leaders and researchers: are we entering AI’s equivalent of “January 2020” — the moment just before exponential change becomes impossible to ignore?Drawing on comments from Sam Altman, Demis Hassabis, Emad Mostaque, and Nick Bostrom, we unpack growing signs that AI capabilities may be accelerating faster than expected. From self-improving coding systems and AI solving long-standing math problems to autonomous buses, AI-run stores, humanoid robotics, and the transformation of legal work, this episode examines how rapidly expanding AI capabilities could reshape education, labor markets, geopolitics, and society itself.We also discuss the constraints that may slow widespread adoption — including energy, compute, data center capacity, and organizational readiness — while asking whether capability growth is already entering escape velocity even if implementation lags behind.The conversation closes with a deeper examination of AGI, national security concerns, AI regulation, and the increasingly uneasy balance between commercial incentives, safety, and global competition.Chapter Markers00:00 — Introduction: The “January 2020” AI AnalogyThe hosts introduce the growing comparison between today’s AI moment and the early days of COVID-19 before exponential spread became obvious.02:17 — Are We Already at Human-Level AI?Nick Bostrom, Demis Hassabis, and the debate over whether current models are already approaching AGI-level capabilities.04:37 — AI Solves a 60-Year-Old Math ProblemDiscussion of how generative AI systems are beginning to exceed expectations in specialized reasoning tasks.06:09 — AI Traders, Robotics, and Ping Pong ChampionsPrediction market bots, autonomous systems, and AI defeating professional human players.08:24 — AI Companions and the Social ConsequencesThe rise of AI girlfriends, loneliness, and concerns about long-term social and workplace impacts.10:11 — Programming Jobs, AI Hiring, and Economic DisruptionThe changing labor market for software engineers and the uncertain future of technical careers.12:10 — Meta Layoffs, Employee Surveillance, and Training AI ReplacementsHow companies are using workplace monitoring data to train future AI systems.14:13 — Data Centers, Energy Constraints, and Space-Based Solar PowerThe infrastructure bottlenecks limiting AI growth and the race to power future compute demand.15:05 — AI in Law Firms and the Transformation of Legal WorkHarvey AI, Anthropic partnerships, and how legal services may radically change.18:39 — The AI-Run Convenience Store ExperimentAutonomous business management, algorithmic bias, and the future of AI-operated organizations.20:44 — Governments, Public Services, and Autonomous TransportationThe UAE’s plan to automate government services and new autonomous bus deployments in Norway.22:25 — Humanoid Robots and Automation in Physical LaborAI-powered robotics entering airports and other real-world operational environments.23:07 — Escape Velocity: Self-Improving AI SystemsThe accelerating pace of AI model releases and what happens when systems begin improving themselves.26:00 — Will AI Spread Exponentially Through Society?A nuanced discussion about whether capability growth and societal adoption will happen at the same speed.32:08 — AGI, National Security, and Geopolitical RiskThe implications of advanced AI systems for governments, cyberwarfare, and global power dynamics.37:58 — Final ReflectionsClosing thoughts on why AI is rapidly becoming far more consequential than simply helping students write papers.#aixhigheredpodcast #ArtificialIntelligence #HigherEducation #AGI #AI #EdTech #GenerativeAI #FutureOfWork #AIResearch #Technology #Education #Automation #AIinEducation #DigitalTransformation #Podcast