AI Rounds

AI Rounds
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Welcome to AI Rounds, the podcast exploring how artificial intelligence is reshaping the way medical writers and educators learn, think, teach, and write. Join your hosts, medical writers and AI experts Drs. Núria Negrão and Morgan Leafe, for practical and insightful conversations that move beyond the hype and into real-world integration. Each episode tackles pressing topics in the medical communication and education fields, from the best AI tools for research and editing to ethical guardrails and controversies surrounding AI use in the workplace.

  1. 7h ago

    Claude Is Watermarking Everything Now. What That Means for Your Work

    Anthropic is now watermarking content generated with Claude, and Morgan read the headlines the way a lot of working writers did: Is my client going to see a watermark on my work? Núria explains what is actually happening, starting with the EU AI Act transparency phase that took effect in August 2026, which requires AI-generated content shown to the public to be labeled, with a carve-out for content that has been sufficiently edited and quality-controlled by humans. The watermark itself is not a visible stamp. It is a statistical pattern in word choice, the same approach Google has used with Gemini since 2024, and neither company has released a public tool that can read it. The watermark also cannot tell anyone how much human involvement went into a document. Heavy AI editing of a fully human draft can leave a watermark behind, and light AI use may leave none, so its presence or absence says much less than people assume. OpenAI, meanwhile, tried watermarking, dropped it after user backlash, and is expected to need something like it to comply with the EU rules. From there the hosts get into the AI detector question that comes up at every conference. Most detectors are doing pattern recognition, not watermark reading, and they routinely flag formulaic writing, which includes scientific and medical writing, and prose by people writing in English as a second language. The one exception people keep naming is Pangram, which optimizes against false positives. The bigger question, they argue, is why you want to detect AI at all: catching deepfakes and unreviewed AI advice is a different problem from wanting a guarantee that a human stands behind the quality of the work. That is where client conversations, AI policies, and disclosure come in, including the medical communications companies that now hand contractors a Copilot license so the AI use stays inside their walls. In this episode What triggered the watermarking decision: the EU AI Act’s transparency requirementsThe human-editing carve-out, and who the law is actually trying to protectHow a statistical watermark works, and why nobody can read it yetGoogle’s head start: Gemini has been watermarked since 2024Why a watermark cannot measure human involvement in either directionOpenAI’s abandoned watermark and the user backlash behind itWhy AI detectors flag scientific writing and second-language EnglishPangram, false positives, and optimizing for precision over recallThe real question: what are you trying to find out when you test for AI?Client trust, AI policies, and disclosing your processMedcomms companies issuing Copilot licenses to keep confidential work containedWhat clients actually want: a guarantee of quality at the end LINKS: Hosted by Nuria Negrão (⁠⁠⁠⁠nurianegrao.com⁠⁠⁠⁠) and Morgan Leafe (⁠⁠⁠⁠morganleafemd.com⁠⁠⁠⁠). Sign up for Nuria's newsletter: ⁠⁠⁠⁠https://nurianegrao.kit.com/signup⁠

  2. Sep 3

    Only 8% of Local Health Departments Use AI. Heather Duncan Wants to Change That

    Heather Duncan started out as an English professor, went back to school for an MPH, and is now a PhD student in epidemiology working on how local health departments can actually use AI. She joins Núria and Morgan to talk about the gap between what the technology can do and what public health is currently doing with it. A 2024 survey from the National Association of County and City Health Officials found that about 8% of local health department staff were using AI at all, while roughly 70% said they were interested. Heather explains what sits in that gap: cost, cybersecurity, unclear legal exposure around sensitive health data, and enterprise tools built for profit-driven organizations being sold to agencies that are not one. She also takes on two arguments that come up in almost every AI conversation. On the environment, she makes the case that the all-or-nothing framing misses the options in between, including locally run open-weight models and retrieval-augmented generation systems that a county health department can host itself. On bias, she walks through the melanoma detection model that performed well until researchers stratified by skin tone, and why the failure was in the training data rather than the algorithm. Her line on this: AI is a mirror, and it amplifies what is already there. In this episode Heather’s route from literary studies to epidemiology, and the question that carried across both Learning SAS, R, and Python, and why coding education has not caught up to how coding actually works now The three worlds of public health: academic, applied/governmental, and private sector, and where AI adoption actually sits in each Where AI is already earning its place in epidemiology: genomics, precision medicine, pharmacoepidemiology, population monitoring, and data quality checks AI as an institutional knowledge resource in departments with heavy staff turnover Why enterprise AI tools are a poor fit for public health, and the value misalignment behind that Data centers, environmental mitigation, and the siting of infrastructure in historically redlined neighborhoods Open-weight models, local hosting, and RAG as a lower-resource alternative The melanoma model that broke down on darker skin, and the structural reasons the training data was thin Shaming people for using AI as a class and access issue Don't miss Heather's session at the AI Fluent Professional Summit on implementation and evaluation frameworks for organizations without a profit motive this November. Join the summit: ⁠⁠https://nuria-negrao.thrivecart.com/ai-fluent-professional-summit/?ref=heather-duncan LINKS: Heather's LinkedIn: https://www.linkedin.com/in/heather-duncan-mph-59686694/M&D Science Consulting: https://www.mdscienceconsulting.com/Those Nerdy Girls contributor profile: https://thosenerdygirls.org/nerdygirls/heather-duncan-mph/Hosted by Nuria Negrão (⁠⁠nurianegrao.com⁠⁠) and Morgan Leafe (⁠⁠morganleafemd.com⁠⁠). Sign up for Nuria's newsletter: ⁠⁠https://nurianegrao.kit.com/signup⁠

  3. Aug 27

    Who Does This Harm? Anne Murphy on Leading AI With Care

    Anne Murphy spent decades in nonprofit fundraising before founding She Leads AI, where she's trained thousands of women to use AI responsibly and is building a living archive of women using it to change the rules.In this episode, Anne, Nuria, and Morgan get into why women's voices are critical in this moment — not for professional development or celebration, but for impact — and why women's use of AI is almost certainly underreported. Anne makes the case for building your "discernment muscle" before the gray-area moment arrives, shares the story of a She Leads AI member who built an app to help her non-English-speaking neighbors during ICE raids, and reframes disruption as spotting the white spaces and fixing them. Along the way: what fundraising and AI have in common (all you really have is trust), why no use case is too small, and the very real change-management fallout when an AI note-taker walks into a six-person team.Don't miss Anne's session at the AI Fluent Professional Summit this November. Join the summit: ⁠https://nuria-negrao.thrivecart.com/ai-fluent-professional-summit/?ref=anne-murphy LINKS: - Anne Murphy on LinkedIn: https://www.linkedin.com/in/she-leads-ai/- She Leads AI (community + the 1000 Disruptors project): https://sheleadsai.ai/- CREATE 2026 conference: https://sheleadsai.ai/create-2026 - Hosted by Nuria Negrão (⁠nurianegrao.com⁠) and Morgan Leafe (⁠morganleafemd.com⁠). - Sign up for Nuria's newsletter: ⁠https://nurianegrao.kit.com/signup⁠

  4. Aug 20

    What Works? Rebuilding Evidence for the Age of AI

    A traditional research meta-analysis — the gold standard for knowing whether something actually works — can cost over a million dollars and take three to four years. Claire Han thinks that's far too slow for the decisions schools and policymakers have to make right now. Claire earned her PhD in education at Johns Hopkins, trained under the late Robert Slavin, and after federal research contracts collapsed she built My Education Researcher — an AI tool that runs the same rigorous analysis in minutes for a few hundred dollars instead of millions. In this episode she walks Nuria and Morgan through what a meta-analysis really is, why messy education data demands such careful screening, and — crucially — where the human expert still has to stay in the loop: framing the question, judging what generalizes to your context, and reading the heterogeneity behind the average effect. It's a hopeful counter-story to "AI is taking our jobs": when Claire lost hers, she used AI to build something new. Catch Claire live at the AI Fluent Professional Summit this November. Join the summit: https://nuria-negrao.thrivecart.com/ai-fluent-professional-summit/?ref=claire-han LINKS:- Claire Han on LinkedIn: https://www.linkedin.com/in/claire-chuter/- My Education Researcher: https://myeducationresearcher.com/ Hosted by Nuria Negrão (nurianegrao.com) and Morgan Leafe (morganleafemd.com). - Sign up for Nuria's newsletter: https://nurianegrao.kit.com/signup

  5. Aug 13

    Tarot, Fan Fiction, and Work Buddies: How People Really Use AI in 2026

    Every so often we check in on how people are really using AI — and Harvard Business Review just dropped its 2026 report, so we do a full top-10 countdown. Some entries are no surprise (therapy and companionship holds at #1, work buddy, troubleshooting), and some genuinely shocked us: astrology and tarot at #9, fan fiction and storytelling at #4, autonomous agentic operations debuting at #6. We dig into what's new, what fell off the list (learning and education didn't crack the top 10), the "think slop" phenomenon, and how the two of us actually use AI — from editing and needs assessments to finding a gym, planning a trip to Europe, and troubleshooting a broken A/C unit. LINKS - Hosted by Nuria Negrão (nurianegrao.com) and Morgan Leafe (morganleafemd.com). - Sign up for Nuria's newsletter: https://nurianegrao.kit.com/signup - Missed the robot episode? Listen in here!

  6. Aug 6

    The Tables Turn: When Clients Are the Ones Misusing AI

    We spend a lot of time talking about how writers can use AI responsibly — but the conversation goes both ways. This week we get into two recent run-ins where clients and companies were the ones using AI badly: RFPs landing in our inboxes with made-up citations and references that are half wrong, and a prospective client who fed a copyrighted writing sample into ChatGPT, then questioned the work based on what the bot said. We talk about why hallucinated references are inexcusable this far into the game, the etiquette of putting someone else's work into an AI tool, the still-unsettled copyright questions, and why "my AI says your work isn't good enough" is a conversation no writer should have to have. If you've run into this too, we want to hear from you. Hosted by Nuria Negrão (⁠nurianegrao.com⁠) and Morgan Leafe (⁠morganleafemd.com⁠).

  7. Jul 16

    AI Is Already in Your Hospital: Breaking Down the HIMSS Healthcare AI Report

    Nuria and Morgan dig into the HIMSS State of Healthcare AI and Digital Transformation report, which found that 71% of US healthcare organizations have already adopted AI in some capacity. From ambient documentation that halves the time physicians spend on notes, to AI-powered call centers cutting wait times, to the crucial distinction between closed clinical AI systems and general chatbots, they offer practical context for medical writers and healthcare communicators. Hosted by Nuria Negrão (nurianegrao.com) and Morgan Leafe (morganleafemd.com). Sign up for Nuria's newsletter: https://nurianegrao.kit.com/signup LINKS: - The State of Healthcare AI & Digital Transformation: Adoption, Risk, and Readiness (HIMSS) https://info.himss.org/NDIwLVlOQS0yOTIAAAGiN91XBLakuE4CrHlxS6FIy6AaU7HxxklPqKsVr7Qo7gppBiK2L5YeqUlQcmfQPJ0eDhYaVRY=

  8. Jul 9

    The Robot That Told Dolly Parton Jokes: AI Companionship for Isolated Seniors

    Nuria and Morgan share the heartwarming story of Jan Worrell, an 85-year-old living alone in remote Washington State, whose relationship with an AI companion robot called ElliQ improved her cognitive test scores and offered comfort after a family tragedy. They explore the broader implications for elder care and the loneliness epidemic, and what it means that a robot that learns your taste in music and tells Dolly Parton jokes might be one of the most promising healthcare AI tools of 2026. Hosted by Nuria Negrão (nurianegrao.com) and Morgan Leafe (morganleafemd.com). Sign up for Nuria's newsletter: https://nurianegrao.kit.com/signup LINKS - AI robot and elderly loneliness (NYT Daily podcast) https://www.nytimes.com/2026/05/28/podcasts/the-daily/ai-robot-elderly-loneliness.html  - ElliQ AI robot senior companion (NYT article) https://www.nytimes.com/2026/02/12/us/elliq-ai-robot-senior-companion.html

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Welcome to AI Rounds, the podcast exploring how artificial intelligence is reshaping the way medical writers and educators learn, think, teach, and write. Join your hosts, medical writers and AI experts Drs. Núria Negrão and Morgan Leafe, for practical and insightful conversations that move beyond the hype and into real-world integration. Each episode tackles pressing topics in the medical communication and education fields, from the best AI tools for research and editing to ethical guardrails and controversies surrounding AI use in the workplace.

Information

  • Creator
    AI Rounds
  • Years Active
    2025 - 2026
  • Episodes
    39
  • Rating
    Clean
  • Copyright
    © AI Rounds
  • Show Website
    AI Rounds

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