Cultivating Intelligence

Cultivating Intelligence by Intrinseco Inc
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Cultivating Intelligence is a thought-provoking podcast exploring how we create, lead, and adapt in a world shaped by art, nature, and artificial intelligence. Through the lenses of creativity, nature, and AI, each episode unpacks powerful ideas about leadership, systems thinking, innovation, and digital transformation, without the corporate jargon. This podcast challenges conventional thinking around control, growth, failure, and creativity, offering practical insights for leaders, creators, and curious minds navigating complex environments. If you’re interested in AI’s impact on creativity, leadership in uncertain systems, and how real growth happens, Cultivating Intelligence connects the dots in a way that’s both strategic and deeply human.

  1. 2d ago

    The Decoy Effect

    More employers now use AI avatars to interview job candidates, and people still smile, pause and thank them as if a person were there. This Episode of Cultivating Intelligence uses the history of decoys to ask what an artificial interviewer really replaces. Christine, host of Cultivating Intelligence from Intrinseco Inc., uses art, nature and AI as lenses for leadership. The essay moves from plastic owls, duck decoys and artificial wasp nests through Zeuxis and Parrhasius, trompe-l'oeil and Magritte's The Treachery of Images to the uncanny valley and a 2023 study of avatar-based interviews. The Episode covers why a decoy doesn't have to convince us it's real to change how we behave; why faster screening doesn't prove an organization is hiring better, and how candidates and AI systems end up optimizing for each other; and how leaders can tell which human interactions add value before replacing them, because, as Christine puts it, the mistake is not choosing an artificial plant but expecting it to grow. Connect with Cultivating Intelligence: BlueskyYouTubeLinkedIn

  2. 2d ago

    The Confidence Gap

    AI lets anyone produce expert-looking work, and that can hide the Dunning-Kruger effect inside organizations: confidence growing faster than competence. This Episode of Cultivating Intelligence asks what leaders lose when polished output is mistaken for understanding. Christine uses art, nature and AI as lenses for leadership. The essay moves from the 1999 research of psychologists David Dunning and Justin Kruger through animal play, honeybee consensus and Picasso's formal training to the pressures on organizations adopting AI today. The Episode covers why AI output can be "borrowed competence" that conceals the boundary between what a person understands and what the tool can simulate; why workforce planning must ask not only what tasks AI can perform but what knowledge disappears if a role disappears; and how leaders make correction safe, from pilots, premortems and red teams to asking the quiet expert to speak first and saying "I don't know." Connect with Cultivating Intelligence: BlueskyYouTubeLinkedIn

  3. Oct 28

    The Intelligence of Waste

    Somewhere above a highway, a turkey vulture is circling, looking for something the rest of us would rather not see. Nature has always been good at finding value in leftovers, and so have we. We compost, we recycle, and artists have spent generations turning discarded objects into extraordinary work. Now artificial intelligence has handed us a brand new kind of waste, and it already has a name: AI slop. In this episode of Cultivating Intelligence, Christine digs through the digital trash heap to ask whether all of it is really garbage, or whether some of it might be raw material. Christine makes the case that throwaway experiments have always been part of how people learn and create. The bad sketch stays in the sketchbook, and the rejected photo stays on the contact sheet. What AI has changed is how easy it is to skip from practice straight to publishing, and how invisible the cost has become. There's no pile of sawdust beside the keyboard, but every prompt still draws on electricity, water, and physical infrastructure. From the strange risks of AI models learning from their own output to the 20-slide deck that should have been five, she looks at how abundance can quietly turn into pollution, both online and inside our organizations. Drawing on artists like Louise Nevelson, El Anatsui, Vik Muniz, and Thomas Dambo, Christine shows that trash only becomes art when someone makes thoughtful choices about what to keep, what to cut, and what it all means. That same judgment may be the most important human skill in an age of near-unlimited generation. Creating and publishing are two different acts, and while AI has made the first one effortless, the second still belongs to us. This episode is an invitation to think more carefully about what's worth making, what's worth keeping, and what it really costs to create it in the first place. Connect with Cultivating Intelligence: BlueskyYouTubeLinkedIn

  4. Oct 27

    When Fear Sets the Pace

    It can feel like everyone else already has AI figured out. A competitor has rolled it out, a coworker is finishing work in half the time, and another company just announced its AI strategy. In this episode of Cultivating Intelligence, Christine looks at a feeling researchers have started to study directly: AI FOMO, the fear of being left behind. It isn't limited to people who are new to technology. In a 2026 Nature survey of more than 1,900 researchers, many said they felt pressure to adopt AI even though they had real doubts about it. And one of the best defenses against that anxiety may not be enthusiasm at all, but understanding. To make sense of why we follow the crowd, Christine turns to the natural world. Birds flock, fish school, and ants build trails that let thousands of individuals move as one, because following others is often a smart way to survive. But nature also depends on variation, and a population where everyone responds the same way has nothing in reserve when conditions change. That difference between adapting and simply imitating shows up in schools, where new studies link heavy AI reliance to weaker critical thinking and poorer long-term memory. The point isn't that students should avoid AI. It's that some kinds of struggle are how learning actually happens, and education will need to decide which ones are worth keeping. The same question reaches into leadership and the arts. Leaders are being encouraged to let AI summarize, analyze, and draft, yet much of their most important thinking happens before any output exists. Artists have survived photography, recorded sound, and synthesizers, but generative AI can reduce the need to know how to make something at all. Drawing on the idea of cultivation, Christine makes the case for a path between resisting change and racing ahead without thinking. The real question may not be whether AI will leave us behind, but what we are willing to leave behind to keep up, and what we might later realize we needed. Connect with Cultivating Intelligence: BlueskyYouTubeLinkedInCitation list Yu, C-L. (2025). “Fear of missing out on AI: A psychological cost of technological revolution.” Telematics and Informatics Reports, 20, 100277. The U.S. study of 557 adults found elevated FOMO-AI among more than one in nine participants and identified AI literacy as a potential buffer. https://www.sciencedirect.com/science/article/pii/S277250302500091XFengyi, D., et al. (2025). “When everyone is talking about AI: The development of fear of missing out on AI scale.” Telematics and Informatics, 100, 102283. Introduces the FoMO-AI construct and dimensions including backwardness anxiety, access concerns and concern about missing AI-related benefits. https://www.sciencedirect.com/science/article/abs/pii/S0736585325000450Basu, M. (2026). “Scientists have a bad case of AI FOMO, Nature poll reveals.” Nature, June 9, 2026. Reports results from more than 1,900 researchers and the tension between negative attitudes toward AI and pressure to adopt it. https://www.nature.com/articles/d41586-026-01690-7Tian, J. & Zhang, R. (2025). “Learners' AI dependence and critical thinking: The psychological mechanism of fatigue and the social buffering role of AI literacy.” Acta Psychologica, 260, 105725. Study of 580 university students examining AI dependence, cognitive fatigue, information literacy and critical thinking. https://pubmed.ncbi.nlm.nih.gov/41076923/“ChatGPT as a cognitive crutch: Evidence from a randomized controlled trial on knowledge retention.” (2025). Social Sciences & Humanities Open, 12, 102287. Randomized study of 120 undergraduates found lower performance on a surprise retention test 45 days later among the ChatGPT-assisted group. https://www.sciencedirect.com/science/article/pii/S2590291125010186Gallup (2026). “Global Indicator: Artificial Intelligence.” Gallup's workplace research reports that manager support is a major driver of frequent workplace AI adoption. https://www.gallup.com/699797/indicator-artificial-intelligence.aspxQueen Mary University of London (2025). CREAATIF research into generative AI and creative-industry workers. Research involving 335 creative workers examined concerns about job security, value, working conditions and AI's potential benefits. https://www.qmul.ac.uk/news/latest-news/2025/queen-mary-news/pr/creative-industry-workers-feel-job-worth-and-security-under-threat-from-ai-.html“AI FoMO in SME Decision-Makers' Reflections on AI Adoption: A Mixed-Method Approach.” (2026). Proceedings of Mensch und Computer 2026. Explores competitive pressure, social comparison, limited evaluative capability and fear of falling behind in organizational AI adoption. https://dl.acm.org/doi/10.1145/3820253.3820263

  5. Oct 21

    The Art of Taking

    When someone steals a bicycle, everyone knows what happened. But when the thing taken is an idea, a melody, a voice, or a lifetime of expertise, the original owner still has it, and yet something is gone: credit, income, opportunity, control. In this episode of Cultivating Intelligence, Christine asks a harder question than whether AI is stealing from us. She asks whether it's making it easier for us to steal from one another. Artists have always borrowed, and culture grows by passing ideas along. What AI changes is the scale and the friction. A few typed words can now produce something that sounds like a specific artist, and neither the person asking nor the person whose work made it possible may ever know the other exists. To make sense of this, Christine turns to the natural world, where frigate birds steal food, cuckoos trick other birds into raising their young, and the dodder plant drains its neighbors. Nature can show us what works, she argues, but it can't tell us what's right. It does offer one warning, though: a parasite that exhausts its host hasn't found a winning strategy. From there, the conversation moves closer to home. Christine looks at the pressure to adopt AI before we've thought it through, the old habit of taking credit for a colleague's idea in its new AI-assisted forms, and a quieter kind of theft, where we use AI to skip the effort that would have built our own skills and judgment. The real danger, she suggests, isn't that AI gets good at taking from us. It's that taking becomes so easy we stop noticing when we're doing it. Connect with Cultivating Intelligence: BlueskyYouTubeLinkedIn

  6. Oct 20

    Endangered Intelligence

    At the John C. Campbell Folk School in Brasstown, North Carolina, people spend a week learning to forge metal, weave cloth, throw clay, or carve a spoon. There are no grades and no competition, just the experience of learning to do something you couldn't do before. In a world where AI can generate a photo, a strategy, or a financial forecast in seconds, that kind of slow, hands-on learning is starting to feel almost radical. In this episode of Cultivating Intelligence, Christine explores what craft can teach us about the moment we're living through. Drawing on the folk school's hundred-year history, recent research from Microsoft on AI and critical thinking, and new OECD reports on skills in the AI age, she makes the case that output is not expertise. AI can make us capable of producing something without making us capable of understanding it. And as AI gets better at producing work that looks competent, we may need more human expertise to spot when it isn't, even as we quietly remove the experiences that build that expertise in the first place. This isn't an argument against AI. It's an argument for being deliberate about which human capabilities we keep developing. Christine looks at why some friction is actually learning, why organizations need their own "imperfect bowls," and why leaders may soon need to track capability risk alongside financial and operational risk. If you've ever wondered what gets lost when the answer arrives before the effort, this episode is for you. Connect with Cultivating Intelligence: BlueskyYouTubeLinkedIn Resources: OECD's June 2026 AI and Skills: What We Know So Far  https://www.oecd.org/en/publications/ai-and-skills_f843b352-en/full-report.html OECD's July 2026 Skills in the AI Age  https://www.oecd.org/en/publications/skills-in-the-ai-age_972bd15e-en/full-report.html Microsoft Research critical thinking study  https://www.microsoft.com/en-us/research/publication/the-impact-of-generative-ai-on-critical-thinking-self-reported-reductions-in-cognitive-effort-and-confidence-effects-from-a-survey-of-knowledge-workers/ John C. Campbell Folk School history  https://www.folkschool.org/folk-school-experience/our-history/

  7. Oct 14

    The Pebble and the Proof

    When an octopus sleeps, its skin flashes with color, its eyes move, and its body twitches. It looks like dreaming. Science can't confirm that, but what researchers have found is remarkable in its own right. In this episode, Christine uses the sleeping octopus and a series of viral animal stories to explore one of the most important spaces we move through as humans: the small gap between what we observe and what we conclude. Otters that keep a favorite rock for life. Cows with best friends. Cats that purr to heal their bones. Crows that warn their children about you. Goats with accents. Penguins proposing with pebbles. Some of these stories are exaggerated and some are surprisingly close to the truth, but each one shows how quickly the human mind turns fragments into a finished story. That same instinct gives us art, scientific hypotheses, and innovation. It also gives us misinformation, organizational myths, and bad decisions made from half a dashboard. AI is now working in that same space between fragments, and it can fill the gaps faster and more fluently than we ever could. Christine looks at what that means for leaders: why coherence is not evidence, why repetition is not verification, and why disruption only reveals what was already there. The answer isn't to stop imagining. It's to know when we're doing it, and to practice a disciplined kind of belief that sits somewhere between gullibility and cynicism. Connect with Cultivating Intelligence: BlueskyYouTubeLinkedIn Resources: Pophale, A., Shimizu, K., Mano, T. et al. Wake-like skin patterning and neural activity during octopus sleep. Nature 619, 129–134 (2023). https://doi.org/10.1038/s41586-023-06203-4   Cornell HN, Marzluff JM, Pecoraro S. Social learning spreads knowledge about dangerous humans among American crows. Proc Biol Sci. 2012 Feb 7;279(1728):499-508. doi: 10.1098/rspb.2011.0957. Epub 2011 Jun 29. PMID: 21715408; PMCID: PMC3234554.  From      Elodie F. Briefer, Alan G. McElligott, Social effects on vocal ontogeny in an ungulate, the goat, Capra hircus, Animal Behaviour, Volume 83, Issue 4, 2012, Pages 991-1000, ISSN 0003-3472, https://doi.org/10.1016/j.anbehav.2012.01.020. (https://www.sciencedirect.com/science/article/pii/S0003347212000401)  https://www.nps.gov/places/000/fire-followers.htm  https://www.ablesci.com/scholar/paper?id=3JxmmgqK8&utm

  8. Oct 13

    Precisely Wrong

    Most of us use "accuracy" and "precision" as if they mean the same thing. They don't. Accuracy is about getting close to the right answer, while precision is about getting the same answer again and again. In this episode of Cultivating Intelligence, Christine starts with a classic Lean Six Sigma diagram of four archery targets. She uses it to ask an urgent question for a world built on increasingly precise machines: what happens when we get very good at hitting the same spot without checking whether it's the right one? The answers come from some unexpected places. Migrating animals show how a group of imperfect individuals can find the right direction together, and a study of songbirds suggests that remembering yesterday's right answer can make it harder to adapt. Musicians, dancers, and photographers show that technical perfection and truth are not always the same thing. Then the conversation turns to AI: why fluent, confident answers can still be wrong, why models are sometimes rewarded for guessing instead of admitting uncertainty, and how an AI connected to outdated information can spread the wrong answer with remarkable consistency. From there, Christine looks at what this means for organizations, education, and leadership. She covers headline testing that optimizes for clicks over truth, the risk of chasing metrics that quietly replace the real goal, and why Finland teaches students to question their sources. She also makes the case for the expert intuition that is hard to measure but often right. As precision becomes cheap and widely available, the real advantage will belong to the people and organizations who know where to aim. Connect with Cultivating Intelligence: BlueskyYouTubeLinkedIn Formal citations: https://asq.org/quality-resources/gage-repeatability? https://pmc.ncbi.nlm.nih.gov/articles/PMC5882979/ Hermer, E., Murphy, B., Chaine, A.S. et al. Great t**s who remember more accurately have difficulty forgetting, but variation is not driven by environmental harshness. Sci Rep 11, 10083 (2021). https://doi.org/10.1038/s41598-021-89125-3 https://openai.com/index/why-language-models-hallucinate/ https://www.nist.gov/itl/ai-risk-management-framework/ai-risk-management-framework-faqs https://eur-lex.europa.eu/legal-content/en/TXT/?qid=1767721066212&uri=CELEX%3A32024R1689&utm https://www.unesco.org/en/articles/ai-competency-framework-students?hub=66903&utm https://apnews.com/article/fake-news-classrooms-finland-russia-194b32d8829838bfe47469d6ff357689 https://cloud.google.com/blog/products/ai-machine-learning/rag-and-grounding-on-vertex-ai/ https://www.anthropic.com/engineering/demystifying-evals-for-ai-agents Nickl, P., Moussaïd, M. & Lorenz-Spreen, P. The evolution of online news headlines. Humanit Soc Sci Commun 12, 364 (2025). https://doi.org/10.1057/s41599-025-04514-7 Pennycook, G., Epstein, Z., Mosleh, M. et al. Shifting attention to accuracy can reduce misinformation online. Nature 592, 590–595 (2021). https://doi.org/10.1038/s41586-021-03344-2

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Cultivating Intelligence is a thought-provoking podcast exploring how we create, lead, and adapt in a world shaped by art, nature, and artificial intelligence. Through the lenses of creativity, nature, and AI, each episode unpacks powerful ideas about leadership, systems thinking, innovation, and digital transformation, without the corporate jargon. This podcast challenges conventional thinking around control, growth, failure, and creativity, offering practical insights for leaders, creators, and curious minds navigating complex environments. If you’re interested in AI’s impact on creativity, leadership in uncertain systems, and how real growth happens, Cultivating Intelligence connects the dots in a way that’s both strategic and deeply human.

Information

  • Creator
    Cultivating Intelligence by Intrinseco Inc
  • Years Active
    2026
  • Episodes
    39
  • Rating
    Clean
  • Copyright
    © 2026
  • Show Website
    Cultivating Intelligence