Podcast
AI Rounds by the Cumming School of Medicine
Hosted by Office of Faculty Development, Cumming School of Medicine, University of Calgary · EN
AI Rounds is an educational podcast designed for university faculty in medicine and health sciences navigating the evolving landscape of artificial intelligence in healthcare and education. Each episode breaks down complex AI concepts into digestible insights, exploring practical applications and discussing how these technologies are reshaping medical research and education. Join us as we examine AI through a beginner's lens, creating a space where faculty can grow their understanding of these powerful tools that are transforming healthcare delivery, research, and education.
18episodes
Episodes
Newest firstAll episodes
What You Gain and What You Lose: A Risk/Benefit Framework for AI Use
Mar 2500:16:53Tap to summarizeAI agents are everywhere now — tools that can manage your email, execute research tasks, book appointments. But before we explore what AI agents can do for you, we need to understand what you're actually trading every time you use AI.In this Season 2 opener, I walk through the major trade-offs faculty face when using AI in research, education, and clinical work: efficiency versus depth, breadth versus expertise, automation versus agency, and convenience versus privacy. Using the same risk/benefit framework you apply to clinical decisions, I'll help you evaluate when AI use makes sense and when the trade-off isn't worth it.Understanding these fundamentals — especially around agency and privacy — becomes critical as AI takes on more autonomous roles. You're already skilled at risk/benefit analysis. You just need to apply it to a new domain.https://www.media.mit.edu/publications/your-brain-on-chatgpt/
Transcribe →That’s a Wrap on Season 1 of AI Rounds
Dec 1000:05:17Tap to summarizeThis brief episode wraps up Season 1 of AI Rounds. Thank you, listeners, for tuning in, we've covered a lot of ground together — from how AI models learn to practical applications in teaching, research, and clinical work. Season 2 will launch in Spring 2026, and I'd love your help shaping upcoming content. If you have topic suggestions, please send them to ofd@ucalgary.ca.
Transcribe →When to Choose the Harder Path: Navigating Thoughtful Use of AI as a Graduate Student
Nov 500:29:59Tap to summarizeIn an era where AI tools promise to accelerate every aspect of academic work, graduate students face a paradox: having access to powerful technology while needing to develop fundamental research skills.In this episode, Inara Lalani, a current graduate student shares insights about the critical importance of discernment in AI use. The conversation explores prioritizing process over product in the learning environment, developing frameworks for deciding when AI helps versus hinders their learning, cultivating critical thinking skills that will serve them throughout their research careers, and unexpected ways GenAI is impacting graduate research.Join us for a nuanced and thought provoking conversation that touches on several themes we've seen throughout this season.
Transcribe →From Tools to Teammates: Building Your First AI Agent
Oct 2200:15:48Tap to summarizeWhat if your AI could work independently toward your goals instead of just answering individual questions? In this episode, we explore AI agents—autonomous systems that can monitor information, make decisions, and take actions without constant oversight.Unlike traditional AI tools that respond to single requests, agents operate continuously to achieve specific objectives. For medical faculty, this means AI that can monitor research literature, track administrative deadlines, support educational workflows, and enhance clinical decision-making.In this episode we break down what AI agents actually are, explores types most relevant to clinical practice and medical education, and provides a practical framework for building your first agent using no-code platforms. The episode covers essential considerations for medical environments, including privacy, security, and integration with existing systems.Links from this episode:zapier.comifttt.commicrosoft.com/en-us/power-platform/products/power-automate
Transcribe →Teaching Through Change: Navigating AI and Educational Technology Disruption
Oct 800:24:59Tap to summarizeFeeling overwhelmed by AI in education? You've been here before.In this conversation, Dr. D'Arcy Norman draws on three decades of educational technology experience to reveal a striking pattern: roughly every ten years, a "revolutionary" technology emerges that promises to transform education forever. Computers. The Internet. MOOCs. And now, AI.Each time, the same fears surface. Each time, vendors promise disruption and personalization. And each time, education evolves—not by replacing human connection, but by thoughtfully integrating new tools into teaching practice.D'Arcy shares insights from his work leading learning technology initiatives at the University of Calgary, offering medical educators a practical perspective for evaluating AI tools while preserving what matters most: the relationships, mentorship, and clinical judgment that form the core of medical training.If you're a medical faculty member navigating AI fears, wondering how to maintain academic integrity, or simply trying to understand where AI fits in your teaching, this episode provides both historical perspective and actionable guidance. The message is clear: teachers won't be replaced by AI, and student learning won't be diminished—provided we embrace intentional course design and authentic assessment.The wave will pass. The question is how we ride it.
Transcribe →Teaching Machines to Say "I Don't Know"—The AI Hallucination Problem
Sep 2400:15:08Tap to summarizeWhy do GenAI systems confidently state incorrect medical facts instead of saying "I don't know?" Groundbreaking research from OpenAI and Georgia Tech reveals that AI hallucinations aren't bugs to be fixed—they're inevitable consequences of how these systems are trained. This episode explores the "singleton problem" that makes AI systematically unreliable on rare facts, connects to our previous discussion of AI benchmark saturation (Episode 9), and explains why the same evaluation methods that create impressive test scores actually reward confident guessing over appropriate uncertainty. For medical faculty evaluating AI tools, understanding these statistical realities is crucial for teaching students, conducting research, and developing institutional policies that account for AI's fundamental limitations.Links from this episode:https://openai.com/index/why-language-models-hallucinate
Transcribe →Rewriting the PhD Playbook: How GenAI is Transforming Graduate Science Education
Sep 1000:31:22Tap to summarizeWhat happens when artificial intelligence collides with centuries-old academic traditions? In this thought-provoking episode, Dr. Heather Jamniczky, Associate Dean of Graduate Science Education and 3M National Teaching Fellow, tackles the seismic shifts reshaping how we train the next generation of medical researchers.From late-night worries about academic integrity to bold visions of AI-ready graduates, Heather shares candid insights on navigating uncharted territory. We explore the faculty hesitations to embracing AI, reimagine what authentic assessment looks like when AI can write and analyze, and dive deep into the ethical minefields emerging in AI-assisted research.But here's the kicker – in a mic-drop moment that will make you question everything, Heather poses the ultimate challenge: "Should we even examine a written thesis anymore?" This isn't just about adapting to new tools; it's about fundamentally rethinking what graduate education means in an AI-ubiquitous world.Whether you're supervising students, designing curricula, or simply trying to keep pace with the AI revolution in academia, this episode will challenge your assumptions and equip you with practical thoughts for the road ahead. The future of graduate education isn't coming – it's here.Join us for a conversation that's equal parts challenging and inspiring, as we explore how to prepare medical graduates not just to use AI, but to lead its ethical implementation in research and clinical practice.
Transcribe →An Overview of Scite for Academics
Aug 2700:19:17Tap to summarizeOur institution now has campus-wide access to scite.ai, an AI-powered research tool that's fundamentally different from traditional databases. In this episode, we explore how medical faculty can leverage this powerful platform to transform their research workflows, enhance teaching, and support evidence-based clinical decisions. Whether you're writing your next grant, preparing tomorrow's lecture, or answering a resident's question during rounds, this episode provides concrete strategies to work smarter, not harder with scite!Links from this episode:scite can be accessed at https://scite.aiFor UCalgary users if you are on the UCalgary network you will automatically have full access to all features, no log in required. From outside of the network you an log in via the UCalgary library ezproxy. No account is required but if you make one you will have the advantage of being able to save your work.
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