In this semester-in-review episode, the hosts step back to reflect on what the first months of the podcast have revealed about the accelerating pace of artificial intelligence—and why higher education sits at the center of this transformation.From the rapid evolution of frontier models (ChatGPT, Gemini, Claude, Grok) to breakthroughs in multimodality, world models, robotics, and workplace automation, the conversation traces how AI capabilities are already reshaping research, teaching, knowledge work, and society at large. The episode also explores growing resistance and backlash to AI, regulatory tensions, and the profound implications for universities facing demographic, economic, and curricular pressures.The discussion closes by looking ahead: predictions for 2026 and beyond, the future of AI literacy and learning, the rise of AI-native institutions, and what educators, students, and leaders must do now to prepare for a rapidly changing world.Chapter Titles with Time Codes00:00 – Welcome & Why This Semester Mattered01:00 – AI as the Defining Force of This Era02:10 – The Model Arms Race: GPT, Gemini, Claude, Grok03:45 – Can AI Generate New Knowledge?04:55 – Multimodality, Video, and IP Battles06:40 – Rethinking Prompting, Creativity, and Visual Reasoning08:00 – World Models, Physics, and the Path Toward AGI09:20 – Vibe Coding and the Future of Software Creation10:45 – AI in the Workplace: Speed, Cost, and Disruption12:05 – Robotics at Scale: Lessons from China13:40 – Research, Writing, and Hallucination Reduction15:45 – Professional Exams and Real-World Competence17:00 – Platform Convergence: ChatGPT Meets Adobe18:10 – Translation, Speech, and Frictionless Communication19:05 – Benefits vs. Backlash21:00 – Cultural Anxiety and AI Pushback23:55 – Government, Regulation, and Power Struggles25:25 – Higher Education at a Crossroads27:20 – Teaching AI in Practice29:00 – Guests, Themes, and What We Learned33:15 – Looking Toward 2026: Agents, Energy, and AGI38:35 – The Skills That Will Matter Most42:30 – Degrees, Credentials, and Changing Signals46:20 – Rethinking Curriculum for an AI World53:20 – Predictions: Education, Society, and AI’s Next Phase1:04:00 – Closing Reflections & Looking Ahead to Spring 2026#AIinHigherEd #ArtificialIntelligence #FutureOfEducation #EdTech #AIandSociety #WorkforceTransformation #AILiteracy #AGI #HigherEducationLeadership #FutureOfWork
Higher education is confronting one of the biggest identity crises in its history — but according to Patrick Dempsey, AI didn’t create the crisis so much as expose the weaknesses that were already there. Patrick, who works at the intersection of human learning and artificial intelligence, joins us for one of the most provocative conversations we’ve had on the podcast.He argues that universities are held back by institutional antibodies, outdated notions of rigor, and governance structures designed to stall rather than support change. We explore why 5-year-olds outperform MBAs in problem-solving, why YouTubers often teach better than professors, how AI redefines expertise, and what students and leaders must do right now to adapt to a world where knowledge is abundant and attention is scarce.This episode is a candid, challenging, and ultimately hopeful look at the future of learning.⏱️ Chapters0:00 – Intro: AI didn’t cause higher ed’s crisis—it exposed it1:37 – Why higher ed protects the status quo & the meritocracy myth4:04 – Shared governance, tenure, and when “process” blocks change9:53 – AI, credentials, and the collapse of scarcity in expertise13:22 – YouTubers, mental models, and the new role of the professor17:25 – The marshmallow tower: why 5-year-olds beat MBAs at problem solving26:24 – Unschooling, entrepreneurship, and learning outside traditional pathways30:08 – Oral exams, bias, and how AI could (actually) help assess learning36:29 – Designing AI-era assignments: “If AI can do it, your bar is too low”41:01 – The 2025 student brain: attention, algorithms, and cognitive endurance48:43 – Is college still worth it? ROI, risk, and advice for students55:16 – For terrified but ready educators: the one step to take tomorrow#aixhigheredpodcast #HigherEd #AIinEducation #EdTech #FutureOfLearning #ArtificialIntelligence #Pedagogy #AcademicInnovation #GenAI #TeachingAndLearning
As Google rolls out Gemini 3 and its Nano “banana” model across Search, images, and apps, the ground is shifting again for AI in education. In this episode, we unpack what’s actually new, why many see Gemini 3 as the current front-runner, and how Google’s tight integration across Search, Workspace, and AI Studio could reshape how students and educators work.We walk through real examples—rich visual explanations of concepts like photosynthesis, automatic structuring of messy podcast transcripts, one-click image and video ads from long-form text, and rapid app prototyping with AI Studio. Then we zoom out to the bigger question: in a world where OpenAI, Google, and others are racing to “own” schools, how many ecosystems can institutions realistically support, and what does access (free vs Pro vs Ultra) mean for students and faculty?Chapters00:04 – Setting the stageIntro, late-November context, and why Gemini 3 feels like a “step change” in models (and yes, why models now apparently have a “smell”).01:01 – The burger emoji that launched a model?The Apple vs Google cheeseburger emoji saga, Sundar’s callback, and what it reveals about Gemini 3’s multimodal reasoning and visual explanation abilities.02:12 – Benchmarks and “Humanity’s Last Exam”How Gemini 3 performs on demanding benchmarks, why its no-tools scores matter, and why some analysts now see it as the clear front-runner.03:33 – Gemini inside Google SearchAI Overviews, the new AI mode for Pro users, and what it means when AI is fully embedded in the same Google Search we already tell students to use.05:00 – Teaching with rich AI explanationsUsing Gemini 3 to explain photosynthesis with bolded key ideas, structured text, and licensed images from Getty—what this kind of output could mean for student learning.05:56 – Cleaning up transcripts & coaching debateHow Gemini auto-formats messy transcripts, highlights critical ideas, and helps pull evidence and quotes from podcasts and other long-form media.07:08 – From 3,000-word blog post to marketing imageGenerating a sophisticated, on-brand image for a “Human Superintelligence Center” directly from a long Substack post—and why paid vs free accounts produce noticeably different results.08:08 – Building apps with AI StudioFirst impressions of AI Studio, integrating Maps, YouTube, search, visuals, and conversation to rapidly prototype apps—even simple games like Space Invaders.09:23 – Turning images into video ads with Veo 3.1Taking a single image and asking Gemini/Veo to “make me an ad”—and getting a full video with motion and voiceover in response.10:13 – A weekend in Tokyo (plus Nano Banana)Letting Gemini plan travel: clickable links, bookings, and AI-generated preview images for a Tokyo itinerary, powered by Nano “banana” image generation.10:56 – OpenAI’s leaked memo & the AI raceSam Altman’s reported “war footing” memo, the scramble for users, and why both Google and OpenAI are targeting schools, teachers, and students aggressively.12:38 – Choosing an ecosystem in educationWhy schools probably can’t deeply support every platform, how training, materials, and assignments create platform lock-in, and what that means for AI strategy.13:38 – Free vs Pro vs Ultra: not all Gemini is equalComparing personal, Pro, Ultra, and school/enterprise Google accounts; how capabilities differ for transcripts and image generation; and why “I tried the free version” doesn’t tell the whole story.16:10 – Access, equity, and FERPA realitiesTalking with students and colleagues about privacy-compliant school systems versus personal accounts, throttled features, and the fact that most students will never need top-tier models.17:37 – What’s next & how to get involvedTeasing a future episode on AI Studio, inviting listener questions about other platforms, and wrapping with a Thanksgiving send-off.#AIxHigherEd #AIinEducation #HigherEd #EdTech #GoogleGemini #Gemini3 #GenerativeAI #TeachingWithAI #AIInTheClassroom
In this episode, we talk with Dan Gonzalez, CEO and co-founder of District C, to explore how education must evolve to meet the demands of an AI-accelerated workforce. Gonzalez argues that as automation reshapes the labor market, human value will increasingly center on collaboration, coordinated problem-solving, and team-based innovation. He shares how District C’s teamship model builds these durable skills through authentic, real-world challenges—shifting students from a completion mindset to a contribution mindset.We examine what employers say graduates are missing, why the pace of AI outstrips traditional educational models, and what tools schools can implement now to develop more resilient, reflective, and team-capable learners. From basketball metaphors to business adoption stats, Gonzalez offers a compelling case for why human teamwork—not technical knowledge alone—defines the future of work.Chapters0:00 – The new human job description in an AI economy1:03 – Introducing guest Dan Gonzalez2:03 – Why District C is “an AI company on the human side”2:27 – The basketball metaphor: preparing students for a changed game3:14 – Why 89% of employers avoid hiring recent graduates4:12 – What a “three-point economy” requires of humans5:03 – What Teamship is and why it matters7:14 – What successful workers have in common8:02 – Building District C and the origins of the model9:09 – These skills aren’t new—so why are we drifting away from them?10:19 – Why AI accelerates the urgency for change12:03 – The problem with content-dominant schooling13:18 – AI as teammate: why we need formal integration14:35 – How students are already informally using AI16:17 – Inside a Teamship challenge17:12 – The role of coaching in team-based learning19:00 – How coaching differs from traditional teaching20:25 – Students as contributors, not completers22:00 – Example: students solving a film-studio workflow problem26:33 – Tools of Teamship: solo flight, take-seven, questioning31:03 – Why replicable processes matter32:04 – Handling setbacks and mid-cycle resets34:37 – What skills students will need 3–4 years from now36:04 – The enduring value of mobilizing others37:00 – Durable skills: collaboration, leadership, judgment39:36 – Accelerating authentic learning42:01 – Extracurriculars as authentic team-based learning44:38 – Where to find District C and final advice#AIxhigheredpodcast #AI #HigherEd #FutureOfWork #EducationReform #AIinEducation #CollaborationSkills #TeamBasedLearning #DistrictC #EdTech #WorkforceDevelopment
In this week’s update, we do something different: instead of racing through a dozen new AI releases, we go deep on a single tool that is quietly becoming one of the most powerful platforms for academic work—Notebook LM.Built on Google’s Gemini models, Notebook LM acts as a virtual research assistant, teaching assistant, and study companion all in one. We walk through how it reduces hallucinations by grounding responses in your own sources, how the interface is structured (sources, chat, and studio), and why its mind maps, audio overviews, and quizzes are particularly well suited for higher education.Along the way, we show concrete use cases: building literature reviews, designing courses, supporting collaborative student projects, and improving accessibility with multimodal overviews and multiple languages. We also look ahead to deep research and how combining serious search with structured notebooks could change how faculty and students approach scholarship.If you’re an instructor, instructional designer, or student wondering how to move beyond “just chatbots” and toward more active, source-grounded work with AI, this walkthrough of Notebook LM is for you.Chapters00:00 – Welcome & why a deep diveWeekly update format change and why Notebook LM deserves a full episode.01:00 – What is Notebook LM? Hallucinations rethoughtGoogle Labs background, Gemini under the hood, and how Notebook LM changes the type of hallucinations you see.03:10 – Free vs. paid, source limits, and supported content50 vs. 300 sources, YouTube transcripts, PDFs, web links, Google Drive, and what “non-multimodal” means in practice.05:20 – Inside a featured notebook (The Economist example)Exploring featured notebooks from outlets like The Atlantic, Our World in Data, and The Economist’s “World Ahead 2025.”09:10 – The Studio: mind maps, chat, and grounded citationsUsing mind maps for topic exploration, hovering over citations, and teaching students to verify sources directly.13:40 – Audio & video overviews as tutorsHow automatically generated “AI podcasters” summarize your sources and the new interactive audio mode for asking follow-up questions.16:45 – Flashcards, quizzes, and real student study workflowsGenerating flashcards and quizzes, explanation features, and how students are actually using these for exam prep.18:45 – Building a notebook from scratchCreating a new notebook with web pages, YouTube transcripts, Google Drive docs, and Discover for additional web/Drive sources.24:50 – Reports, study guides, and writing supportUsing built-in templates for study guides, briefing documents, research proposals, and blog posts.26:30 – Teaching, research, and accessibility use casesCourse design, collaborative research notebooks, lecture transcripts, and accessibility gains through audio, visuals, and languages.32:00 – Sharing, collaboration, and analyticsNotebook-level sharing, object-level sharing (just an audio overview or notebook), permissions, and usage analytics.35:10 – Are we still thinking? Rethinking learning with AIMind maps, interactive audio, and group notebooks as ways to deepen—not replace—student thinking.37:25 – Deep research and the future of Notebook LMHow deep research could supercharge notebooks with high-quality academic sources and what that means for the free tier.39:50 – Final thoughts & call for use casesWhy Notebook LM stands out today and an invitation for listeners to share their own experiments.#aixhigheredpodcast #notebooklm #GoogleGemini#AIinEducation#HigherEdAI#GenerativeAI#EdTech#TeachingAndLearning#AIforTeachers#AIinHigherEd
A fast-paced roundup on the AI x Higher Ed Podcast covering the global AI infrastructure race, emerging creator tools students can use today, shifting labor signals, and what all of this means for classrooms, campuses, and careers. We also touch on model advances, robots, privacy, and the hard realities of jobs in transition—ending with a call for human skills and community to anchor AI literacy.Chapters00:04 – Opening & What’s New This WeekQuick setup for the November 6, 2025 update.00:19 – AI Infrastructure Arms RaceBig cloud and compute moves (multi-year deals, international builds) and what they signal for capacity and access.00:51 – Europe’s Slow Buildout?Germany’s GPU scale-up vs. U.S. megaprojects; reading the capacity tea leaves.01:23 – Data Centers Meet CommunitiesLocal opposition near universities (south of Ann Arbor) and the town–gown tensions educators will feel.01:46 – “Talent Development,” Not Just ResearchNew initiatives (e.g., in Saudi Arabia) framed around growing talent, not merely funding labs.02:11 – Tools, Students & the Creator EconomyWhy immediately useful tools may matter more than frontier model bragging rights.02:28 – Google Labs’ “Pamelly” for Instant Brand CreativeHow ingesting a website yields themes, images, and slogans—classroom and small-business use cases.04:49 – From Social Posts to StorytellingBetter assets, faster: what this implies for students’ marketing literacy and expectations online.05:50 – DIY Video Ads with “Pippet”Sora/Gemini-based commercial generation on a budget; early strengths, critiques, and where it fits.07:13 – Universities: From Curiosity to CapabilityHow students can monetize new skills quickly—and why “signals” like essays matter less.07:51 – When Writing Stops Signaling“Making Talk Cheap” and the fading value of cover letters and admissions essays as ability proxies.09:01 – Workforce Prep ≠ Just Tech SkillsDurable human skills (communication, collaboration, empathy, problem-solving) as the center of AI-enabled work.10:32 – Human Skills in Action: A Campaign CaseGround game, simple messaging, and community—lessons for classrooms seeking connection at scale.13:30 – Are We Teaching the Right Things?“Deskkilling,” shifting skill profiles, and rebalancing writing with other competencies.14:25 – AI-Written Media & Academic LagMore AI in newsrooms; research and publishing cycles trailing fast-moving models.16:38 – School Partnerships & AccessClassroom pilots and teacher tools expanding access to stronger models—plus non-Western language support.18:45 – Values, Judgment & EvaluationTeaching students how to decide what good looks like (and how to assess AI outputs against it).19:45 – Teen Brains, Fast Thinking & Shallow ProcessingOxford study takeaways and what it means for assignment design.21:11 – Model Advances You’ll Feel in ClassFrom concepts over tokens to swarm inference—accuracy trends without waiting for “the next big model.”23:12 – Robots Come Home (Sort Of)Early household robots, subscription models, autonomy limits, and privacy questions.24:31 – Jobs: Layoffs, Freezes & New OpeningsWhere AI is slowing hiring, where new roles may emerge, and what educators can do now.26:00 – Preparing Students for the Next EconomyDurable skills + AI literacy + creator mindsets as a practical roadmap.27:58 – Closing & What’s NextTeaser for next week’s update.#AIxHigherEd #AIinEducation #GenAI #CreatorEconomy #AIEconomy #AIInfrastructure #StudentSkills #SoftSkills #LLMs #Robotics #AIJobs #DigitalLiteracy #HigherEd
In this riveting interview from the AI x Higher Ed Podcast, co-founder of DebaterHub, John Hines, delves into the transformative power of AI in education and the surprising findings from their NSF-funded research. Discover how their autonomous debating system achieves superhuman performance in policy debate, far surpassing even the most advanced consumer AI models. But beyond the technological marvel, Hines reveals a deeper truth: AI isn't just a tool for learning; it's a mirror reflecting the fundamental flaws in our current educational assessment methods and posing an existential crisis for higher education. Learn why skills like active listening, critical thinking, and empathy—once deemed "soft skills"—are the true power skills of the future, and how debate-centered learning with ethical AI integration is paving the way for a more equitable and impactful educational landscape.Chapter Markers:[00:00] Introduction to DebaterHub and the power of debate[01:56] The initial impetus for DebaterHub and the state of democracy[03:59] How debate became an exclusive activity and the US Constitution's vision[06:05] The impact of ChatGPT and AI on DebaterHub's mission[08:00] IBM Project Debater and the challenge of AI in debate[10:10] The scientific questions addressed by DebaterHub's NSF grant[12:12] The purpose of I-Corps interviews and customer discovery[14:15] The surprising truth about AI cheating in higher education[17:04] The existential crisis facing higher education revealed by AI[18:49] The battle between job-focused and holistic education[20:30] The importance of "soft skills" (durable skills) in the future workforce[22:00] How computational argumentation can track human communication skills[24:59] The experiment: pitting human and AI-generated debate cases against each other[29:05] The problem of hallucination and evidence verification[33:04] DebaterHub's performance compared to human and other AI systems[36:06] The critical difference: AI's honesty vs. human manipulation in evidence[37:09] The future: AI as an ethical communication tool in education and beyond#aixhigheredpodcast #AIVsHuman #Debate #EdTech #HigherEd #AIinEducation #FutureofWork #Rhetoric #Argumentation #CriticalThinking #Education #DebaterHub #NSFgrant
Educators keep asking the wrong question—which tool should my students use?MIT Lincoln Lab veteran Dr. Tim Dasey (https://www.linkedin.com/in/timdasey/) argues we should first teach how thinking and learning work (for humans and machines), then use AI intentionally. In this candid conversation, he lays out a practical roadmap for schools: measure what matters, move from waterfall to agile change, and shift student work from low-level tasks to architecture, systems thinking, and judgment.Why watch- A research-to-practice perspective from 30 years at MIT Lincoln Lab (national security, health, disaster response).- Concrete playbook for departments, deans, and teachers who want progress next semester—not in five years.- Nuanced takes on ethics, energy, and bias that move beyond slogans to incentives and action.Highlights- “You don’t have to use AI to teach about AI.”- Replace slow strategic plans with agile experiments.- Stop saying “durable skills” unless you measure them.- Coding is shifting: less syntax, more architecture & abstraction.- Treat the model like a transfer student—teach it your class norms.- Ethics = trade-offs; fix incentives (e.g., metered API usage) instead of preaching.- Prepare sociologists to manage AI agent cultures.- Goal: reduce anxiety, increase agency—students who love learning will be okay.Chapters00:34 — Guest intro: MIT’s Dr. Tim Dasey04:03 — Interdisciplinary mindset; “learning signals” for teams06:36 — Seek variety; prompt the unusual08:27 — Build learning orgs; measure what matters11:10 — “You don’t have to use AI to teach AI”13:07 — Meta-lessons; supervised learning in class15:39 — Make every class improve itself16:39 — Classes of problems; values and ethics18:50 — Energy, bias, and incentives (metered APIs)24:54 — Should kids learn coding? Shift to architecture27:10 — Computational + pattern-based thinking for youth28:41 — Rebalance CS: beyond “95% coding”29:33 — Supervising AI agents; need sociologists33:57 — Tech revolutions favor new grads; empower youth36:00 — Wright Brothers analogy; AI ≠ brain copy38:52 — Treat AI like a transfer student40:05 — Case studies at scale; practice edge cases41:55 — Virtual classes for classroom management42:33 — Wisdom vs. judgment; educate intuition45:12 — K–college pathway: complexity, open-ended problems50:18 — Don’t repeat social media mistake51:27 — Reduce anxiety; nurture love of learningWho it’s forFaculty, instructional designers, department chairs, deans, school leaders, and anyone building AI-ready curricula across the arts, humanities, and STEM.Hashtags#AIinEducation #HigherEd #TeachingWithAI #AIPedagogy #EdLeadership #CurriculumDesign #AgileEducation
AI isn’t just another classroom tool—it’s a general-purpose technology that’s reshaping the world our students are entering. In this candid conversation, Prof. Mairéad Pratschke (internationally recognized authority in digital education and AI) argues that higher ed doesn’t need to defend its existence—it needs to redefine its purpose, its pace, and its practices.What we cover:- Why “AI ≠ edtech” and why that framing is holding campuses back- The real existential question: What is the purpose of higher education—formation, employability, or both?- Maker spaces, communities of practice, and “experiment first, permission later”- Leadership failures (and fixes): supporting faculty on the front lines- Global context: recolonization risks, language, regulation, and cost realities- Social pain vs. “radical abundance”: preparing students for the messy middle- A five-year outlook: agents, robotics, world models—and why we can’t still be talking about chatbotsChapters:00:28 – Guest intro: Professor Mairéad Pratschke's background02:36 – Does AI challenge the role of the university—or clarify it?05:03 – The speed gap: AI vs. higher ed processes07:11 – Big reframing: “Stop thinking about AI as edtech.”10:03 – Will higher ed split? New models and the educator’s evolving role13:41 – If you were provost: makerspaces, incentives, and communities of practice16:49 – First steps for busy faculty: trusted voices, free learning, shared time18:54 – What students should do now: policies, guidance, and using the university’s breadth23:06 – Languages, culture, and where AI helps vs. where humans matter24:34 – “Every student should start a company” (project-based learning in practice)27:05 – Surprises from global leaders: recolonization, cost, and context30:00 – Beyond techno-utopias: social pain and policy37:04 – Five-year outlook: from chatbots to agentic systems39:46 – Closing + where to find the guestIf you’re a provost, faculty member, or student wondering how to navigate what’s next, this episode gives you the language, the mindset, and the first steps.👋 Guest: Dr. Mairéad Pratschke — AI Strategist and Advisor, Mairead Pratschke Ltd🔗 Connect: Website (https://maireadpratschke.com/)+ LinkedIn (https://www.linkedin.com/in/maireadpratschke/)#HigherEd #AIinEducation #AIPolicy #TeachingInnovation #DigitalPedagogy #GenAI #Universities #FutureOfWork
PennWest’s Dr. Camille Dempsey (Director, PennWest Center for Artificial Intelligence & Emerging Technologies) joins us to talk about launching an AI center at speed, empowering rural and urban communities, and keeping human judgment at the core of AI-enabled learning. We dig into her upcoming book Once Upon a Chatbot: Fairy Tales about Artificial Intelligence, the student ambassador model, certificate/badging plans, and how to move past “plagiarism panic” toward responsible use, critical thinking, and real-world readiness.You’ll learn:- How a grassroots vision became a university AI hub serving faculty, students, and local partner- A practical playbook for universities starting with limited resources- Ways to scaffold “human-first, AI-assisted” coursework without outsourcing thinking- Why communities of practice + student ambassadors accelerate culture changeGuest: Dr. Camille Dempsey, Director, PennWest Center for AI & Emerging Technologies00:34 — Intro — Erie and the Pennwest Center2:29 — Once Upon a Chatbot4:54 — How AI is different6:49 — Story of the launch of PennWest10:17 — Serving the broader community11:29 — People reach out to established centers14:09 — AI is here, we need to prepare our students17:09 — Student ambassadors23:03 — Badging and professional development25:19 — AI as a copilot and writing35:49 — Changing mindstes40:29 — Learn as much as you can#AIinHigherEd #AIEthics #AIandTeaching #PennWest #AIEd
AI’s Tipping Point in Higher Education: Agency, Equity, and Urgent Change“Avoidance—both at individual and institutional levels—is no longer possible.”Is your campus ready for the AI revolution—or waiting for someone else to figure it out? Dr. Adam Pacton, inaugural Dean Fellow for AI Literacy and Integration at Arizona State University, lays out why 2025–26 is a make-or-break moment for higher education.In this candid and forward-thinking conversation, Dr. Pacton reveals:- Why AI literacy is no longer optional for students or faculty- How ASU is launching faculty AI upskilling and cross-campus integration efforts- The growing “AI digital canyon” and what it means for equity and access- How writing, assessment, and knowledge production are being fundamentally redefined- Practical ways to spark intrinsic motivation and protect student agency with AI tools- Why play may be the most powerful on-ramp for educators overwhelmed by changeWhether you’re a faculty member, administrator, or education leader, this episode delivers crucial insights for navigating the most disruptive technological shift higher ed has ever faced. The decisions you make now will determine whether your institution thrives—or gets left behind.#AIxHigherEdPodcast #AIinEducation #HigherEducation #EdTech #AcademicInnovation #FutureOfWorkTimestamps:1:02 – Introduction and CISA’s AI Literacy Mission2:01 – Faculty Upskilling and Institutional Communication4:20 - Maintaining Relevance and Agency7:29 – Why Waiting Is No Longer an Option8:52 - AI in Changing Fields and Writing Instruction12:03 – The Existential Questions Facing Universities22:05 – Writing, Assessment, and the AI Paradigm Shift29:00 – Intrinsic Motivation, Agency, and Student Buy-In36:15 - Rhetoric, AI, and Agency40:41 - Prompting47:46 – Agentic AI, Security, and Institutional Risks54:43 - Intrinsic Motivation56:35 – Practical Advice: Start Small, Start PlayingAbout Dr. Adam Pacton:Dr. Pacton is the inaugural Dean's Fellow for AI Literacy & Integration at Arizona State University’s College of Integrative Sciences and Arts. He leads efforts to build faculty AI literacy, integrate AI across disciplines, and foster equitable access to emerging technologies.Follow Adam on LinkedIn: https://www.linkedin.com/in/adampacton/Subscribe for more episodes: https://www.youtube.com/@AIxHigherEdPodcast 🎙️Catch more episodes: https://aixhighered.com/
AI's Existential Threat to Higher Education: A Wake-Up Call for Educators“The gulf between where we’re still at and how it keeps moving further and further away from the awareness and abilities of academics, the more it becomes an existential threat.”Is your institution ready for the AI revolution, or is it stuck in academic inertia? Dr. James Hudson from Lindenwood University delivers hard truths about how AI is fundamentally reshaping higher education—and why most universities are dangerously unprepared.In this eye-opening conversation, Dr. Hudson reveals:- Why the traditional 4-year degree model is becoming obsolete- How AI tools are outpacing academic research and best practices- The psychology behind faculty resistance to AI adoption- Practical strategies for integrating AI in classrooms despite institutional barriers- What the "Class of 2030" needs to succeed in an AI-driven workforceWhether you're a faculty member, administrator, or education leader, this episode offers crucial insights into navigating the most significant technological disruption higher education has ever faced. Don't get left behind—the future of education is being written now.#AIxHigherEdPodcast #AIinEducation #HigherEducation #EdTech #AcademicInnovation #futureofwork 0:57 - Introduction and Moving Beyond Specialization7:07 - Rate of Change & Struggling with a Response13:42 - Faculty Awareness, Assessment Challenges, and Dated information20:20 - AI as One Higher Education Challenge22:20 - Waiting to Address AI Creates Existential Challenges25:00 - AI Collapsing Learning Trajectories26:20 -Leadership, Redirecting the Higher Education Ship, and Resistance29:15 - Disruption: AI, Modeling, and Financial Planning32:30 - AI Rapidly Accelerates Research35:24 - Rapid Change, Higher Education Decision-Making Procedures, and Requiring Faculty AI Usage41:20 - Institutional Resistance and Lack of Training43:10 - Identity, Occupational Change45:30 - New Emerging Models of Higher Ed46:00 - Automation and the Decline of Majors47:45 - Practical Steps Professors Can Take50:00 - Student Resistance to AI and the Job Market52:55 - Policies and Empower Educators55:45 - Preparing Students for the AGI World: New Curriculum and Generalization1:02:00 - Metacognition, Growth Mindset, Meta Cognition1:04:00 - Transitional Measures1:05:00 - Advice for Students and Durable SkillsDr. James Hudson is the lead XR disruptor and department head of art, history, AI, and visual culture at Lindenwood University, with a PhD in AI (2023) and extensive experience developing online education programs. He has authored over 200 publications on AI and education, serves as editor-in-chief of the International Journal of Emerging and Disruptive Innovation and Education, and is a leading expert on AI's transformative impact on higher education.James Hutson LinkedIn profile James Hutson - Lindenwood University Directory - Subscribe for more episodes of https://www.youtube.com/@AIxHigherEdPodcast 🎙️Catch more episodes here:Website URL: https://aixhighered.com/
ACT’s lead research scientist Jeff Schiel joins the AI x Higher Ed Podcast to unpack a new report on how U.S. high school students view AI—and how those views relate to AI training in school, intended college major, and gender. We talk about what “moderate” training really means (as students see it), why attitudes differ across majors (hello, business/CS vs. arts), the gender optimism gap and the power of role models, limitations of cross-sectional surveys, and where the research goes next (including AI in admissions).Chapters00:00 Key findings at a glance: training, majors, gender00:32 Welcome & study overview: why ACT asked students about AI01:44 What motivated the research + core questions (trust, impact, preparedness)04:01 Who was surveyed and why ACT test-takers matter05:37 What counts as “moderate” AI training? (self-reported)07:20 Only ~8% reported moderate/extensive training—should higher ed worry?10:02 Arts majors’ concerns vs. optimism in business/CS/math12:16 AI, CS jobs, and what the study did—and didn’t—measure14:57 Gender optimism gap & promoting female AI role models19:05 Methods: ~4.7% response rate and survey caveats23:02 Cross-sectional limits; ideas for longitudinal follow-up24:21 Do AI tools build skills? (critical thinking, problem-solving, creativity)26:29 “Lukewarm” on college prep—until training enters the picture31:14 Takeaways for campus leaders (correlation ≠ causation)36:18 Sneak peek: new ACT study on AI in admissions38:20 Wrap-up & what’s nextDr. Jeff Schiel is a lead research scientist on ACT’s applied research team, specializes in the design and methodology of surveys and survey sampling. You can read the full ACT report at https://leadershipblog.act.org/2025/08/ACT-research-gen-z-students-and-AI.html #AIinEducation #HigherEd #StudentVoice #EdTech #ACT #GenAI #STEM #ArtsEducation #EquityInAI #ComputerScience
In this August 2025 update, Stefan and Anand offer a high-level update on developments in AI and their implications for education. There is a lot of ground to cover from the summer. Be sure to check back through the school year for their weekly updates.August 2025 Update Topics:0:14 - Introduction0:50 - Major Themes 1:38 - AI Model Updates11:26 - Agentic Abilities17:38 - Photo & Video Generation19:09 - Robotics22:08 - AI & Companionship24:44 - Building AI Infrastructure29:47 - AI Applications35:40 - Labor & Economic Trends37:18 - Universities Respond Subscribe for more episodes of https://www.youtube.com/@AIxHigherEdPodcast 🎙️Catch more episodes here:Website URL: https://aixhighered.com/
This week’s AI Update dives into major breakthroughs, classroom adoption, and urgent ethical debates:- Google’s Nano Banana model and astonishing continuity in AI image editing- New Google Vids workflows with Gemini V3 for video production- Live translation tools reshaping communication and education- Apple’s on-device AI model for captioning and visual description- New research showing 85%+ of students and faculty already using AI in education- Professor Mairéad Pratschke's call to build pedagogical systems beyond chatbots- How educators are teaching AI, including new approaches to defining it- A heartbreaking case of a teen suicide after chatbot interactions, and OpenAI’s responseJoin us as we explore the promise and perils of AI in classrooms, workplaces, and society.🔔 Don’t forget to like, share, and subscribe for weekly AI insights!⏱️ Chapters0:00 – Intro & Overview0:51 – Claude adds browser agents1:42 – Google’s Nano Banana image editing breakthroughs3:33 – Google Vids with Gemini V3 for video workflows4:57 – Live translation and global communication impact6:56 – Apple’s on-device AI: local captioning & privacy focus8:42 – Research: 85% of students/faculty now use AI11:43 – Paper highlight: From AI Tools to Pedagogical Systems15:04 – Teaching AI: defining intelligence in classrooms17:38 – Controversies: teen suicide and chatbot safeguards21:09 – OpenAI’s response & Harvard study on emotional manipulation23:58 – Comparing AI risks with social media & addictive platforms26:25 – Parental controls, student safeguards & education’s role29:41 – Final reflections & looking aheadContent Warning: This episode includes discussion of suicide in the context of AI and mental health. Please take care while listening. If you are struggling, we encourage you to reach out to a trusted friend, family member, or professional for support. In the U.S., you can dial 988 for the Suicide & Crisis Lifeline.
In this episode of the AI x Higher Ed Podcast, we unpack the latest AI developments shaking up higher education and beyond:-Major AI Model Advances: Memory features in ChatGPT & Claude, and what Sam Altman’s hints about GPT-6 mean for the future.-AI in Research: Proof-of-concept experiments where AI ran the entire scientific process.-Mathematical Breakthroughs: AI solving a decades-old unsolved math problem in minutes.-Grammarly’s AI Overhaul: Citation finders, predictive grading, and why faculty and students are buzzing about it.-Meta Smart Glasses & Ambient AI: How wearable AI could transform classrooms.-Controversies & Ethics: The MIT “AI failure” report, concerns about chatbot relationships, and disturbing proposals for student “personality profiling.”-New Emerging Tools: From Marlin 2’s creative world-building to Elon Musk’s “Macrohard” and Google’s rumored “Nana Banana” video breakthrough.If you teach, work, or study in higher ed, these changes are coming to your campus—sooner than you think.0:04 – Welcome & episode overview0:47 – AI model advances: Memory in ChatGPT & Claude; GPT-6 hints2:22 – AI-driven scientific research experiment proof-of-concept3:40 – AI solves an unsolved math problem (Sebastian Bubeck)4:31 – Grammarly’s AI overhaul & predictive grading controversy8:12 – Meta smart glasses & ambient AI in classrooms11:44 – MIT AI adoption study & AI bubble fears15:01 – Chatbot “consciousness,” addiction & SpiralBench test18:30 – Study linking AI cheating to “dark traits” & ethical concerns21:00 – Emerging capabilities: Marlin 2, Musk’s “Macrohard,” Google’s “Nana Banana”24:06 – Closing thoughts & what’s nextSubscribe for weekly updates on how AI is reshaping learning, research, and the future of education.#AI #HigherEd #AIxHigherEdPodcast #EdTech #AIUpdate
This week’s AIX Higher Ed podcast dives into the fast-moving edge of AI for teaching, learning, and campus strategy. We cover Apple’s live-translation AirPods, big Google updates (NotebookLM + V3 video + AI Search), Anthropic’s in-chat doc editing, ChatGPT’s expanding Voice Mode, fresh research (agentic papers; AI building expert scientific software), UC Berkeley’s ping-pong robot, and how OpenAI’s new employer-linked certificates could challenge traditional credentials. We close with culture/ethics: jobs, AI-made movies/podcasts, and the rise of chatbot relationships—and what that means for students.Highlights:- Apple AirPods Pro 3: live translation + health features- Google NotebookLM’s multilingual audio/video overviews, study tools, and custom reports- Google V3 video: higher resolution, new aspect ratio, cheaper- AI results by default in Google Search (the “open web” shift)- Anthropic editing Word/PDFs directly in chat- Research: AI producing novel scientific models and “agentic” papers- OpenAI certificates tied to employers—implications for higher ed- Jobs, media, and student wellbeing in an AI-saturated worldIf this helps your course, please like/subscribe and share with your faculty development group. ✨Chapters00:00 – Intro & what’s new this week00:51 – Apple: AirPods Pro 3 live translation (+ heart-rate), AirPods 401:34 – Google NotebookLM: languages, audio/video overviews, flashcards, custom reports03:03 – Google V3 video: 1080p, 9:6 ratio, price drop, creative uses03:52 – AI results default in Google Search: the Perplexity-style shift04:36 – The open web in decline & pedagogy implications05:16 – Anthropic: edit Word/PDFs directly inside chat06:07 – ChatGPT: Voice Mode expands access and duration06:49 – New research: AI builds expert scientific software & novel models09:10 – From papers to agents: MCP and agentic research objects09:57 – Why LLMs hallucinate: OpenAI/Georgia Tech paper takeaways10:30 – Robotics: UC Berkeley humanoid plays table tennis10:49 – AI in schools: GSV’s “Forecast for Learning & Earning”12:27 – UNESCO’s “AI & the Future of Education”: what still holds, what’s dated14:27 – Turning static reports into living, updating agents15:12 – OpenAI’s employer-linked certificates: AI challenging schools18:22 – Labor disruption: Salesforce touts 4k fewer roles via AI19:18 – Generative film: OpenAI-backed “Critters” & creative work19:51 – A million AI podcasts? Flooded media futures21:15 – Relationships with chatbots: mental health & classroom stakes23:02 – Teaching human connection in an AI world24:06 – Wrap-up & what to watch next week#HigherEd #EdTech #AIinEducation #GenerativeAI #AIxHigherEd
What does it really mean to be intelligent in the age of artificial intelligence?Dr. Alan Coverstone joins the AI x Higher Ed Podcast to preview his upcoming University of Mary Washington talk, “Reclaiming Human Intelligence in the Age of AI: Plural Futures for Education and Society.”In this conversation, Coverstone challenges how we define intelligence — arguing that schools and universities have privileged computation, logic, and linguistic skills at the expense of the richer, plural ways humans actually know and create. He explores how AI disruption offers a once-in-a-generation opportunity to reimagine education around agency, collaboration, and authentic problem solving.🎓 Topics include:- Why education must move beyond “who can compute best”- How students can develop agency in an AI-saturated world- Why the liberal arts may hold the key to AI-era learning- The danger of schools prioritizing what’s measurable over what’s meaningfulChapters:- 0:00 — Rediscovering What Makes Us Human- 0:48 — Introducing Dr. Alan Coverstone- 2:00 — What Is Intelligence, Really?- 3:15 — Reclaiming Human Intelligence- 7:00 — Why Schools Prioritize Measurable Intelligence- 9:30 — Beyond the Measurable: Rediscovering Human Potential- 13:00 — AI as an Opportunity for Redefining Learning- 15:00 — Building Student Agency and Authentic Learning- 19:00 — Rethinking Common Knowledge and Cultural Canon- 22:00 — From “Soft Skills” to Core Human Capacities- 24:00 — Student Agency, Motivation, and AI Misuse- 30:00 — Learning Beyond the Classroom- 32:00 — The Phone Debate: A Mirror for the AI Debate- 38:00 — Reimagining Education from the Ground Up- 40:00 — Higher Education’s Crossroads- 44:00 — Rediscovering the Purpose of the Liberal Arts- 48:00 — Practical Advice for Faculty- 52:00 — Closing Reflections📍 Dr. Coverstone will expand on these themes in his upcoming talk at UMW on October 29th.👉 Subscribe for more conversations at the intersection of AI and higher education.#AI #Education #HigherEd #HumanIntelligence #EdTech #AlanCoverstone #ArtificialIntelligence
This fast-paced update unpacks the latest AI usage reports from OpenAI and Anthropic, what they reveal about real-world adoption (and automation), and fresh K–12/teacher data summarized by the Allen Turing Institute. We dig into OpenAI’s upcoming age-gating changes, then shift to Google’s just-announced Learn Your Way—a research pilot that turns static PDFs into adaptive, quiz-ready, audio-narrated lessons tailored by grade level and interest.We also scan the horizon: Meta’s newest smart glasses, bold 2030 capability projections, and the accelerating robotics curve—from Stanford’s BEHAVIOR-1K household benchmark to delivery bots on city streets. On the dev side, agentic coding is surging: Replit’s Agent 3 now runs ~200 minutes autonomously, and we share a striking “six-hour flight → production-ready stack” case. Plus: simulated “AI societies,” an AI anti-corruption role in government, liberal-arts-reimagining in higher ed (with career design front and center), and a candid look at job disruption, three-day workweek talk, and AI-generated YouTube Shorts.If you’re an educator or campus leader, you’ll come away with concrete signals on where AI is moving—right now—and the implications for teaching, learning, and institutional strategy.Chapter Markers00:04 — Welcome & today’s roadmap01:04 — Usage snapshot: OpenAI’s categories & how people actually use ChatGPT02:16 — Anthropic/Claude: fewer individuals, more enterprise—and visible automation03:26 — Teacher surveys: adoption, productivity gains, and critical-thinking concerns05:23 — Kids 8–12 using AI: what they do with it (and why it matters)06:26 — Guardrails: OpenAI’s planned age-gating and parental permissions08:07 — Google Learn Your Way: AI-augmented textbooks (mind maps, quizzes, audio)11:48 — Meta’s smart glasses: where on-device AI could be headed12:22 — 2030 projections: timelines for SWE benchmarks, bio/wet-lab guidance, more14:13 — Robotics rebound: OpenAI’s interest, Figure, China, and BEHAVIOR-1K17:23 — Autonomy in the wild: delivery robots roll through Miami17:45 — Agentic coding surge: Replit Agent 3 and longer autonomous runs19:36 — Case study: a six-hour, multi-agent build → near-production stack21:58 — Toward AI societies: 22,000-agent sims & Albania’s AI anti-corruption role23:27 — Higher ed shifts: AI in the classroom; liberal arts reimagined; CC innovation26:01 — Jobs & policy: three-day workweek talk, layoffs, and political rifts30:24 — AI video gen comes to YouTube Shorts: opportunity vs. “AI slop”31:05 — Wrap-up & takeaways for educators#aixhigheredpodcast #AI #HigherEd #EdTech #AIinEducation #GenerativeAI #AgenticAI #Robotics #PersonalizedLearning #GoogleAI #Anthropic #OpenAI #Replit #K12 #Policy #AcademicInnovation #TeachingAndLearning #AIethics
Join Stefan Bauschard and Anand Rao in the latest AI Office Hours podcast as they discuss the most recent advancements in artificial intelligence. This week's topics include:- Gemini in Chrome: A look at how Google is expanding access to its AI assistant by integrating it directly into the Chrome browser [00:01].- Data Center Expansion: The podcast highlights the significant investments from companies like Nvidia, OpenAI, and Microsoft in building new data centers to meet the growing demand for AI [01:13].- Safety Concerns & Red Lines: The hosts discuss a letter from prominent figures calling for "international red lines" to prevent unacceptable AI risks, highlighting the ethical and societal implications of advanced AI models [02:19].- Model Advances: A summary of new developments in AI, including Fei-Fei Li's work on "world models" and new open-source models from Grok and China that offer high performance at a lower cost [05:58].- Universities & Education: The episode covers how universities are adapting to the rise of AI, including new AI skills courses at the University of Mary Washington and funding for research projects at other institutions [13:20].- The Future of Jobs: A discussion on papers from economists that model a future with AGI (Artificial General Intelligence), debating the possibility of full human replacement in many jobs and the ethical considerations that raises [17:40].