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In this episode, we sit down with three disinformation researchers whose new paper found something surprising about both our resistance and our susceptibility to both true news we wish was fake and fake news we wish was true.Our guests are three of the scientists exploring a newly named cognitive distortion, one that every human being is prone to exhibiting, one that is so common and so easily provoked that nefarious actors depend on it when distributing disinformation and propaganda.Samuel Woolley, Katie Joseff, and Michael Schwalbe will share their methods, findings, and takeaways. They will also explain the troublesome nature of something they are calling concordance over truth bias – a distortion that most often appears in those who have the most (undeserved) confidence in their own (not-so-objective) objectivity. - How Minds Change- Show Notes- Newsletter- David McRaney's BlueSky- David McRaney's Twitter- YANSS Twitter- Why Do We Share Our Feelings With Others?- Concordance Over Truth Bias- Samuel Wooley- Katie Joseff- Michael Schwalbe- Geoffrey Cohen Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
(Episode #319) A message for you if you've been questioning your body, your purpose, or why “doing it the normal way” never quite works.You didn't land here by accident. This conversation is an invitation to remember what your body already knows and to stop outsourcing your truth to systems that were never built for you.In this episode of The Higher Self Hotline, I'm joined by Veronica (Pleasure as Praxis) a somatic practitioner and doctoral candidate who is unafraid to name the male bias baked into Western science. Together, we explore the female nervous system, embodied wisdom, and why pleasure is not indulgent or optional, it's a biological necessity.This episode is for anyone who's felt dismissed by medicine, disconnected from their body, or quietly sensing there has to be another way.In this episode we're talking about:(00:00) How chronic illness forced her to question Western science(14:03) Why it's more expensive to study female bodies(16:23) How the male bias gaslights women about their experiences(36:15) Why pleasure is a physiological necessity, not a luxury(42:32) Menopause and matriarchy: reclaiming postmenopausal powerWe're reframing pleasure as data, not indulgence, a language the female nervous system uses to signal safety, truth, and regulation. Veronica shares why embodied awareness can't be erased by policy, politics, or outdated science, and how tracking your body, your cycle, and your internal rhythms builds an authority no external system can take from you.If you've been feeling something stirring without the words for it yet, this episode is an invitation to listen.Stay in touch with Victoria here: TikTok: https://www.tiktok.com/@pleasure_as_praxisTake my FREE quiz! What's your intuitive style? Discover your unique intuitive gifts with my free quiz:http://zoeygreco.com/quizMeet me in the studio. Watch this full episode and see all the magic unfold on YouTube: https://youtu.be/mlkyYKpz3QEDid you love this episode? The Higher Self Hotline Team lovingly asks for your support! We'd be eternally grateful if you'd rate, review, and subscribe! We want to make sure you never miss a dose of divine guidance.If this conversation resonated with you, we hope you share it with someone you think would connect with the message. Stay connected with us and your higher self! Follow Zoey on socials. Connect with Zoey here: Instagram: @thezoeygrecoTikTok: @thezoeygrecoWebsite: ZoeyGreco.comAudio Editing by:Mike Sims | echovalleyaudio.comContact: echovalleyaudio@gmail.com
Dr. Lisa Flexner — educator, leader, and founder of Flex Health Consulting. Catch her at CSM 2026 delivering three sessions on workplace culture, substance use in patients, and weight bias in PT.This episode covers:Why clinic culture is the #1 retention toolHow to stop blaming clinicians for system problemsWhat PTs must understand about patients using cannabis, opioids, and psilocybinHow weight stigma harms health outcomes — and how to have the conversation rightGuest Info:Website: FlexHealthConsulting.comLinkedIn: Lisa FlexnerCSM 2026 Sessions:OK Boomer, Meet Gen Z – Generational culture clash in PT teamsAll Your Patients Are on Drugs – TED-style session on patient substance useA Weighty Matter – How weight stigma affects outcomes and cliniciansSponsor Shoutouts:Pre-Roll: Brooks IHL — Turn good clinicians into great ones: brooksihl.orgMid-Roll: Empower EMR — AI-powered workflows to give you time back: empoweremr.comPre-Parting Shot: US Physical Therapy — Practice with purpose: usph.com
In this free-for-all-Friday Trent explores the problem of "normalcy bias" in life-threatening situations.
In this episode of Mining Stock Education, host Bill Powers and co-host Brian Leni of Junior Stock Review engage in their monthly Junior Mining Insights discussion. They cover Brian's recent attendance at the Metals Investor Forum and the Vancouver Resource Investment Conference, highlighting the positive sentiment and increased interest from investors. The conversation also explores demographics and the influence of younger investors transitioning from cryptocurrency to junior mining stocks. The duo discusses where current value can be found in a precious metals bull market. They delve into the importance of understanding an information conveyor's bias and process when evaluating information in the sector. Brian shares his experience from a recent site tour in South America and the impact of community engagement by mining companies. The episode concludes with Bill discussing potential investment opportunities in critical metals and copper, influenced by broader market sentiment and insights from industry experts. 00:00 Introduction 00:27 Conference Insights: Vancouver Events 01:40 Market Sentiment and Demographics 03:40 Crypto Investors in Mining 06:40 Viewer Feedback and Market Psychology 09:37 Investment Strategies and Market Trends 15:12 Bias and Process in Mining Investments 22:44 Community Engagement in Mining 27:55 Analyzing Brian's Hot Chili Investment 28:37 The Importance of Water in Mining 29:18 Copper Market and Investment Strategy 30:10 Understanding Brian's Investment Bias 30:35 Quantifying Market Opportunities 31:14 The Role of New Discoveries in Investment Decisions 32:06 Portfolio Composition and Strategy 33:42 Learning from Investment Successes and Failures 36:03 Investor Psychology and Decision Making 42:49 Current Investment Questions and Opportunities 48:51 Brian's New Newsletter Brian's website: https://www.juniorstockreview.com/ Brian's YT: https://www.youtube.com/@FIELD_NOTES Bill's Twitter: https://x.com/MiningStockEdu Sign up for our free newsletter and receive interview transcripts, stock profiles and investment ideas: http://eepurl.com/cHxJ39 Mining Stock Education offers informational content based on available data but it does not constitute investment, tax, or legal advice. It may not be appropriate for all situations or objectives. Readers and listeners should seek professional advice, make independent investigations and assessments before investing. MSE does not guarantee the accuracy or completeness of its content and should not be solely relied upon for investment decisions. MSE and its owner may hold financial interests in the companies discussed and can trade such securities without notice. MSE is biased towards its advertising sponsors which make this platform possible. MSE is not liable for representations, warranties, or omissions in its content. By accessing MSE content, users agree that MSE and its affiliates bear no liability related to the information provided or the investment decisions you make. Full disclaimer: https://www.miningstockeducation.com/disclaimer/
It's the first This Month in Birding panel of the new year, and Nate welcomes a crew of birders featuring Mollee Brown, Frank Izaguirre, and Jordan Rutter to discuss predation of penguins, evolving junco bills, and weird bird stuff in our houses. Plus, is pishing an ethical birding practice? Links to items discussed in this episode: Penguins Become Prey for the Pumas of Patagonia Without campus leftovers to pick through, the beaks of this bird changed shape during the pandemic Bias in density estimates from avian point-count surveys: Prospects for post-hoc corrections using calibration data Woman's viral "bird theory" about white people has everyone checking their homes Subscribe to the podcast at Apple Podcasts, Spotify, or wherever you get your podcasts and please leave a rating or a review if you are so inclined! We appreciate it! This episode brought to you by All4Birding
Watch the YouTube version of this episode HEREAre you a law firm owner who needs advice on leading a team in a crisis? In this episode of the Maximum Lawyer Podcast, attorney and law firm owner Tiffany Webber shares the profound personal and professional impact of her law partner's sudden passing. She recounts the immediate aftermath, the challenges of leading her firm through crisis, and the lessons learned about resilience, leadership, and preparation. Tiffany shares her insights on leading a firm amidst losing a loved one. One thing is having the skill to be calm under pressure. You can't control when someone close to you passes, but you can control yourself and your reaction to something. As a lawyer, people come to you with answers, so it is important to know when to remain calm and collected. Another thing to have is a bias for action. Many people will sit back and analyze. They will wait to make a decision when they have received all the answers. But, in this field, you will never always have every piece of information. Sometimes, you need to make decisions in the moment with what you have.Having a good leadership team is crucial, especially when you as the owner have a lot of things on their plate. Other leaders in the firm can not only support you by taking on the additional load, but you can lean on them for support. Also, if you don't know something about a topic, having others as subject matter experts can be such an advantage. This also helps with succession planning, so someone can take over while you focus on other things.Listen in to learn more!2:06 Survival Guide for a Crisis4:12 Bias for Action12:03 Facing Discomfort18:00 Creating a Good Leadership Team20:46 Letting the Right People InConnect with Tiffany:Website Tune in to today's episode and checkout the full show notes here.
In this episode, we discuss how the Fed kept interest rates steady in January while hinting that easing may happen at some point when supported by the economic data. The discussion and content provided within this podcast is intended for informational purposes only and may not be appropriate for all investors. Reliance upon information provided in a podcast is at the sole responsibility of the listener. The information included herein is not based on any particularized financial situation, or need, and is not intended to be, and should not be construed as, a forecast, research, investment advice or a recommendation for any specific PIMCO or other security, strategy, product or service. Past performance is not a guarantee of future results. All investments contain risk and may lose value. Investors should speak to their financial advisors regarding the investment mix that may be right for them based on their financial situation and investment objective. Podcasts may involve discussions with non-PIMCO personnel and such content contain the current opinions of the speaker but not necessarily those of PIMCO. Other podcasts may consist of audio recording of an existing PIMCO article and such material contains the current opinions of the manager. The opinions expressed in all podcasts are subject to change without notice. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. PIMCO as a general matter provides services to qualified institutions, financial intermediaries and institutional investors. This is not an offer to any person in any jurisdiction where unlawful or unauthorized. For additional important information go to www.pimco.com/gbl/en/general/legal-pages/podcast-disclosures
Modern technology doesn't run on code alone, it runs on data. Generated constantly and often invisibly, it shapes how our health is understood, and few people understand this better than Sheena Franklin.Joining Matthew Roberts in this episode, Sheena is a digital health founder, women's health advocate, and recognized voice in inclusive data and AI policy. Together, they unpack the historical biases embedded in clinical research, the challenges of unstructured and siloed healthcare data, and the growing role of wearables, AI, and regulation in shaping modern care.The conversation looks beyond innovation to stewardship, examining who owns health data, how it is governed, and why women's health has become a catalyst for broader transformation across the healthcare ecosystem.Technology is only as powerful as the care and consideration behind it—this episode is a reminder of what's at stake, and who the future of healthcare is really being built for.
Headlines: – Welcome To Mo News (02:00) – ICE in Minnesota: Mayor Frey Meets With Border Czar Tom Homan, Asks For End To ICE Surge (07:20) – Trump Faults Alex Pretti for Carrying Gun, But Says He Wants ‘Honest' Inquiry (08:15) – Congresswoman Ilhan Omar Attacked By Man, Sprayed With Substance At Event (12:45) – Social Media Giants Face Landmark Youth Addiction Trial In California (16:00) – Trump Says Iran Wants A Deal As U.S. "Armada" Arrives (23:45) – Military Casualties in Ukraine War Near 2 Million, Study Finds (29:00) – TikTok Denies Censoring Anti-ICE Content, Blames Outage (31:50) – Helping To Raise Your Grandchildren? It's Good For Your Brain (35:50) – On This Day In History (40:20) Thanks To Our Sponsors: – Industrious - Coworking office. 50% off day pass | Code: MONEWS50 – Incogni - 60% off an annual plan| Code: MONEWS – Monarch - 50% off your first year | Code: MONEWS – Factor - 50% off your first box | Code: monews50off – ShipStation - Try for free for 60 days | Code: MONEWS
Learn to counter normalcy bias with micro-drills, baseline awareness, and quick mental cues for faster, confident responses. The post Train Your Mind to Overcome Normalcy Bias appeared first on Mind4Survival.
Avoiding bad news doesn't make it go away! Want to test yourself on how well you can recognize fallacies in real life? Take the Meme Fallacy Quiz! www.filteritthroughabraincell.com/quiz Learn more about Crazy Thinkers membership where you can practice critical thinking using real-life memes, articles & headlines: www.filteritthroughabraincell.com/crazy Here's how you can purchase the Logical Fallacies ebook: https://www.filteritthroughabraincell.com/offers/z6xbAcB2 Send me any questions, comments or even the fallacies you're seeing around you! think@filteritthroughabraincell.com Or, tag me on Instagram: @filteritthroughabraincell Sign up on my email list at: www.filteritthroughabraincell.com/contact Learn more about Classical Conversations: www.classicalconversations.com/filterit Thank you to our sponsor, CTC Math! Website: https://www.ctcmath.com/?tr_id=brain Homeschool page: https://www.ctcmath.com/how-it-works/home-school?tr_id=brain Free trail: https://www.ctcmath.com/trial?tr_id=brain Special offer! Get 1/2-off discounts plus bonus 6-months free! Critical Thinking for Teens Logical Fallacies for Teens Cognitive Biases for Teens Homeschool Logic Critical thinking for Middle schoolers
Today’s first caller is doing a remodel of the family room and is wondering about bias lighting behind a big-screen, flat-panel TV. Next up, a caller was wondering how long you can keep your water heater beyond the warranty and before it leaks? Another caller needs to replace her front exterior door and is wondering if she should go for fiber glass, timber, or whatever options Dean may recommend. And what about water in natural gas? Does one need a dripline to mitigate this phenomenon?See omnystudio.com/listener for privacy information.
Bias in hiring has been a topic of discussion for decades, yet our understanding of what actually happens within recruiting processes remains surprisingly limited. Most research focuses on single types of bias in isolation, making it impossible to build a complete picture. Meanwhile, the arrival of AI tools is intensifying the scrutiny of hiring decisions, demanding a level of accountability that many organizations simply aren't prepared for. TA leaders often assume they know where bias exists in their processes. But what if those assumptions are wrong? What if the patterns are more complex and counterintuitive than anyone expected? My guest this week is Bas van de Haterd, Co-founder of the TA Audit Institute. In our conversation, he shares findings from new research that challenges conventional thinking about where bias actually occurs and reveals how much we still don't know. In the interview, we discuss: Research methodology and sample size How this research compares to previous academic research What was measured and what was not measured What do the results tell us about bias in the hiring process? Is bias universal, institutional, or personal? Are employers doing better at removing bias than they think? Using data to drive targeted change Lessons learned and advice to TA Leaders. What's the future direction of the research? Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.
The implications of Tucker's king's ransom payday, Bob Nightengale seemingly turns Carlos Beltran's HOF candidacy into an opportunity to show his bias against the Astros, and saying farewell to the end of an Astros legend's career.
AI is getting smarter, but now it needs better judgment. In this episode of the Eye on AI Podcast, we speak with Robbie Goldfarb, former Meta product leader and co-founder of Forum AI, about why treating AI as a truth engine is one of the most dangerous assumptions in modern artificial intelligence. Robbie brings first-hand experience from Meta's trust and safety and AI teams, where he worked on misinformation, elections, youth safety, and AI governance. He explains why large language models shouldn't be treated as arbiters of truth, why subjective domains like politics, health, and mental health pose serious risks, and why more data does not solve the alignment problem. The conversation breaks down how AI systems are evaluated today, how engagement incentives create sycophantic and biased models, and why trust is becoming the biggest barrier to real AI adoption. Robbie also shares how Forum AI is building expert-driven AI evaluation systems that scale human judgment instead of crowd labels, and why transparency about who trains AI matters more than ever. This episode explores AI safety, AI trust, model evaluation, expert judgment, mental health risks, misinformation, and the future of responsible AI deployment. If you are building, deploying, regulating, or relying on AI systems, this conversation will fundamentally change how you think about intelligence, truth, and responsibility. Want to know more about Forum AI? Website: https://www.byforum.com/ X: https://x.com/TheForumAI LinkedIn: https://www.linkedin.com/company/byforum/ Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Why Treating AI as a "Truth Engine" Is Dangerous (02:47) What Forum AI Does and Why Expert Judgment Matters (06:32) How Expert Thinking Is Extracted and Structured (09:40) Bias, Training Data, and the Myth of Objectivity in AI (14:04) Evaluating AI Through Consequences, Not Just Accuracy (18:48) Who Decides "Ground Truth" in Subjective Domains (24:27) How AI Models Are Actually Evaluated in Practice (28:24) Why Quality of Experts Beats Scale in AI Evaluation (36:33) Trust as the Biggest Bottleneck to AI Adoption (45:01) What "Good Judgment" Means for AI Systems (49:58) The Risks of Engagement-Driven AI Incentives (54:51) Transparency, Accountability, and the Future of AI
News flash: other people can't read your mind! Want to test yourself on how well you can recognize fallacies in real life? Take the Meme Fallacy Quiz! www.filteritthroughabraincell.com/quiz Learn more about Crazy Thinkers membership where you can practice critical thinking using real-life memes, articles & headlines: www.filteritthroughabraincell.com/crazy Here's how you can purchase the Logical Fallacies ebook: https://www.filteritthroughabraincell.com/offers/z6xbAcB2 Send me any questions, comments or even the fallacies you're seeing around you! think@filteritthroughabraincell.com Or, tag me on Instagram: @filteritthroughabraincell Sign up on my email list at: www.filteritthroughabraincell.com/contact Learn more about Classical Conversations: www.classicalconversations.com/filterit Thank you to our sponsor, CTC Math! Website: https://www.ctcmath.com/?tr_id=brain Homeschool page: https://www.ctcmath.com/how-it-works/home-school?tr_id=brain Free trail: https://www.ctcmath.com/trial?tr_id=brain Special offer! Get 1/2-off discounts plus bonus 6-months free! Critical Thinking for Teens Logical Fallacies for Teens Cognitive Biases for Teens Homeschool Logic Critical thinking for Middle schoolers
In this episode of That's So Hindu, Mat McDermott, Pawan Deshpande, and Devala Rees discuss the intersection of AI and Hinduism, exploring how AI can be integrated into devotional practices, the biases present in AI systems, and the implications of misinformation in educational contexts. They delve into the philosophical questions surrounding consciousness and AI, and the potential future of AI in relation to Hindu traditions. The discussion emphasizes the importance of accurate representation and the opportunities AI presents for spreading knowledge about Hinduism.TakeawaysAI images can be used in Hindu practices but with caution.Hinduism encompasses over 300 distinct traditions.Misinformation in educational materials about Hinduism is prevalent.Caste is often misrepresented in AI outputs.AI can mimic human-like features but lacks true consciousness.The optimization function in AI influences its responses.AI performs better when users interact positively with it.Hindus are significant users of AI technologies like ChatGPT.AI presents opportunities for accurate representation of Hinduism.The future of AI in Hinduism raises important philosophical questions.Chapters00:00Introduction to the Guests and Their Backgrounds02:54AI in Hindu Devotional Practices05:49Understanding AI: Definitions and Implications11:59Bias and Misinformation in AI17:52Educational Challenges and Misrepresentation of Hinduism23:44The Role of AI in Cultural Representation29:45Consciousness and AI: A Philosophical Exploration35:57The Future of AI and Hinduism41:45Conclusion and Final ThoughtsKeywordsAI, Hinduism, Devotional Practices, Misinformation, Bias, Education, Cultural Representation, Consciousness, Philosophy, Technology Hosted on Acast. See acast.com/privacy for more information.
Discover all of the podcasts in our network, search for specific episodes, get the Optimal Living Daily workbook, and learn more at: OLDPodcast.com. Episode 1939: Dr. Jenny Brockis shares a deeply personal experience of workplace pregnancy bias to highlight how unconscious bias can undermine fairness and decision-making. She explores the science behind our mental shortcuts, the consequences of unchecked bias, and the practical strategies that help us build a more equitable and aware workplace. Read along with the original article(s) here: https://www.drjennybrockis.com/2013/7/3/breaking-bias/ Quotes to ponder: "The reality is we are all biased and probably to a far greater extent than we either know or care to admit to." "Bias is simply a mental shortcut in our unconsciousness that allows us to perceive the world in a certain way and contributes to the decisions we make." "Because we don't realise the extent of our biases, we often don't know the difference between being right about our beliefs, and believing we are right." Episode references: K. Schulz's TED Talk on Being Wrong: https://www.ted.com/talks/kathryn_schulz_on_being_wrong
What does it take to rise after life tells you “you can't”? In this episode of The Health Disparities Podcast, we sit down with Grace Moore—Financial Empowerment Specialist, Founder, Speaker, and 2025 Movement Is Life Health Summit Speaker—whose journey is a powerful testament to resilience, faith, and the transformative force of mindset. At just 17, Grace was told she would never walk again. After waking from a nap with her left leg paralyzed, she faced a defining crossroads: accept limitation or choose possibility. She chose movement—of the body, the mind, and the spirit. Today, Grace speaks from the lens of the patient, sharing what it looks like to keep moving forward while living with daily pain. Her message is simple but profound: we can choose to be “up and able” rather than “down and defeated.” Grace also brings her expertise in financial wellness to the conversation, highlighting how financial empowerment—especially for seniors—directly connects to health equity, stability, and community well‑being. She breaks down the barriers people face, the myths that hold them back, and the power of language to either uplift or limit our lives. In this episode, Grace opens up about: • Her journey from paralysis to purpose • How mindset can shift the trajectory of your life • Why financial empowerment is a health equity issue • The importance of speaking life into yourself and others • Her upcoming journal, Graceful Movement, and how it helps readers embrace pain with compassion and courage Grace's story is a reminder that movement isn't just physical—it's emotional, mental, and deeply personal. Her voice is one of hope, empowerment, and unwavering belief in what's possible. Never miss an episode—subscribe to The Health Disparities Podcast on Apple Podcasts, YouTube, or wherever you listen.
Gretchen Stewart knows she doesn't know it all, always asks why, challenges oversimplified AI stories, champions multi-disciplinary teams and doubles down on data. Gretchen and Kimberly discuss conflating GenAI with AI, data as the underpinning for all things AI, workflow engineering, AI as a team sport, organizational and data siloes, programming as a valued skill, agentic AI and workforce reductions, the complexity inherent in an interconnected world, data volume vs. quality, backsliding on governance, not knowing it all and diversity as a force multiplier.Gretchen Stewart is a Principal Engineer at Intel. She serves as the Chief Data Scientist for the public sector and is a member of the enterprise HPC and AI architecture team. A self-professed human to geek translator, Gretchen was recently nominated as a Top 100 Data and AI Leader by OnConferences. A transcript of this episode is here.
Have you felt the crushing weight of otherization as the only woman or person of color in the room? Or maybe you've been told you're "too intense," "not assertive enough," or some other maddening combination of subjective, conflicting feedback at work?In this episode of Risky Conversations with Jamie Lee, we dive into why these experiences are not personal failings, but symptoms of the systemic injustices we swim in every day.As a South Korean immigrant living in the U.S., I feel the tension of both: I've gained advantages by understanding how global workplaces function, yet I've also experienced the invisible barriers many marginalized people face, working harder than most, only to be undervalued.In this episode, you'll learn:The Truth About Intersectional Feminist Coaching: Why traditional "think positive" coaching fails women of color, and how to embrace the paradox of systemic reality versus personal agency.The Biology of Bias: How systemic inequities and "otherization" trigger your nervous system and create inherited belief systems that lead to over-functioning.Real-World Case Studies: How a woman in the male-dominated construction industry reframed "intensity" into leadership; how a single mother successfully challenged the assessment that she wasn't "technical enough"; and how a BIPOC woman transformed her income and impact by choosing to believe in herself when no one else at work would.The Three Votes Strategy: A practical framework to regain your agency—voting for yourself, voting with your tribe, and voting with your feet.To learn more about my coaching philosophy, process, and pricing, come on over to www.jamieleecoach.com/apply Text me your thoughts on this episode!Enjoy the show? Don't miss an episode, listen and subscribe via Apple Podcasts or Spotify. Leave me a review in Apple Podcasts. Connect with me Book a free hour-long consultation with me. You'll leave with your custom blueprint to confidence, and we'll ensure it's a slam-dunk fit for you before you commit to working with me 1:1. Connect with me on LinkedIn Email me at jamie@jamieleecoach.com
Slam The Gavel welcomes back Wren Byrd to the podcast. Wren was last on the podcast Season 5, Episode 213. Today we discussed what has changed in regards to the system and how parents are treated, especially during litigation. We also discussed why there is no enforcement of laws ALREADY in place. Wren brought up the book, "The Family Law Professional's Field Guide to HIGH CONFLICT LITIGATION; Dynamics, Not Diagnoses by Benjamin D. Garber, PhD, Dana Prescott, JD, LMSW, PhD and Chris Mulchay, PhD. The American Bar Association is endorsing it. Where can this lead while training judges to do the right thing by all families and their children?To Reach Wren Byrd: info@foundingmoms.orgSupportshow(https://www.buymeacoffee.com/maryannpetri)Maryann Petri: dismantlingfamilycourtcorruption.comhttps://www.tiktok.com/@maryannpetriFacebook: https://youtube.com/@slamthegavelpodcast?si=INW9XaTyprKsaDklhttps://substack.com/@maryannpetri?r=kd7n6&utm_medium=iosInstagram: https://www.instagram.com/guitarpeace/Pinterest: Slam The Gavel Podcast/@guitarpeaceLinkedIn: https://www.linkedin.com/in/maryann-petri-62a46b1ab/ YouTube: https://www.youtube.com/@slamthegavelpodcasthostmar5536 Twitter https://x.com/PetriMaryannEzlegalsuit.com https://ko-fi.com/maryannpetrihttps://www.zazzle.com/store/slam_the_gavel/aboout*DISCLAIMER* The use of this information is at the viewer/user's own risk. Content on this podcast does not constitute legal, financial, medical or any other professional advice. Viewer/user/guest should consult with the relevant professionals. IRS CIRCULAR 230 DISCLOSURE: To ensure compliance with requirements imposed by the Internal Revenue Service, we inform you that any U.S. federal tax advice contained in this communication (including any attachments) is not intended or written to be used, and cannot be used, for the purpose of (1) avoiding penalties under the Internal Revenue Code or (2) promoting, marketing or recommending to another party any transaction or matter addressed herein. Reproduction, distribution, performing, publicly displaying and making a derivative of the work is explicitly prohibited without permission from content creator. The content creator maintains the exclusive copyright and any unauthorized copyright usage is strictly prohibited. Podcast is protected by owner from duplication, reproduction, distribution, making a derivative of the work or by owner displaying the podcast. Owner shall be held harmless and indemnified from any and all legal liability.Support the showSupportshow(https://www.buymeacoffee.com/maryannpetri)http://www.dismantlingfamilycourtcorruption.com/
AI in medicine is best understood as a powerful tool and a conditional partner that can enhance care when tightly supervised by clinicians, but it becomes a problem when used as a replacement, deployed without oversight, or embedded in biased and opaque systems. Whether it functions more as a partner or a problem depends on how health systems design, regulate, and integrate it into real clinical workflows. Where AI Works Well Decision support and diagnosis: AI can read imaging, ECGs, and lab patterns with very high accuracy, helping detect cancers, heart disease, and other conditions earlier and reducing some diagnostic errors. Workflow and documentation: Tools that draft visit notes, summarize records, and route messages can cut administrative burden and free up clinician time for patients. Patient monitoring and triage: Algorithms can watch vital signs or wearable data to flag deterioration, triage symptoms online, and guide patients through care pathways, which is especially valuable with clinician shortages. Risks and Problems Errors, over-reliance, and "automation bias": Studies show clinicians sometimes follow incorrect AI recommendations even when the errors are detectable, which can lead to worse decisions than if AI were not used. Bias and inequity: If training data underrepresent certain groups, AI can systematically misdiagnose or undertreat them, amplifying existing health disparities. Trust, explainability, and liability: Black-box systems can undermine shared decision-making when neither doctor nor patient can understand or challenge a recommendation, and they raise hard questions about who is responsible when harm occurs. Impact on the Doctor–Patient Relationship Potential partner: By handling routine documentation and data crunching, AI can give clinicians more time for conversation, empathy, and shared decisions, supporting more person-centered care. Potential barrier: If AI outputs dominate visits or generate long lists of differential diagnoses directly to patients, it can increase anxiety, fragment communication, and weaken relational trust. How To Keep AI a Partner, Not a Problem Keep humans in the loop: Use AI as a second reader or coach, not a final decision-maker; clinicians should retain authority to accept, modify, or reject suggestions. Demand transparency and evaluation: Health systems should validate tools locally, monitor performance across different populations, and disclose AI use to patients in clear language. Align incentives with patient interests: Regulation, reimbursement, and malpractice rules should reward safe, equitable use of AI—not just speed, volume, or commercial uptake. In practice, AI in medicine becomes a true partner when it augments human judgment, enhances relationships, and improves outcomes; it becomes a problem when it is opaque, biased, or allowed to replace clinical responsibility.
Board games are supposed to bring people together—but some of them feel more like intellectual flexes than friendly competition. This week, JJ and Tucker dive deep into the board games that secretly say more about you than the game itself. From Scrabble's smug superiority complex, to Monopoly house rules that feel suspiciously like modern economics, to a surprisingly revealing game of Guess Who, the conversation spirals into stereotypes, pop culture, childhood nostalgia, and why modern board games are having a full-on renaissance. Along the way, they unpack: Why Scrabble feels like someone trying to prove they're smarter than you How Guess Who accidentally becomes a psychological profiling tool The evolution of Monopoly boards (and why Fargo might have messed one up) Carmen Sandiego, Anne Hathaway, and heist-movie logic Dead birds, Mr. McGregor, and childhood trauma The Olympics lottery, obscure events, and cheering for the flag 00:00 – Please put your clothes back on (intro) 01:08 – The board game that feels like an insult 01:49 – Monopoly trash talk and pandemic grudges 03:09 – Fargo Monopoly and questionable city design 04:33 – Monopoly house rules gone completely off the rails 05:15 – Scrabble: the "I'm better than you" game 06:14 – Scrabble boards, editions, and nostalgia 07:47 – Travel games and modern Guess Who 08:49 – Guess Who as personality profiling 10:20 – Bias, stereotypes, and reading strangers 11:25 – Why Guess Who should be a TV show 11:56 – Carmen Sandiego rights and reboots 13:20 – Anne Hathaway and heist movie logic 15:27 – The Princess Diaries (somehow gets darker) 18:50 – Board game collecting and Kickstarter culture 19:35 – Viticulture, birds, and pigeon slander 21:02 – Finding a dead turkey vulture 23:03 – Peter Rabbit and childhood fear 27:32 – Registering for the 2028 Olympics lottery 29:25 – Skateboarding, table tennis, and obscure events 32:27 – Eddie the Eagle and Olympic loopholes 34:09 – Closing and credits Support the show: For more episodes of JJ Meets World, or to find out how you can support the podcast, visit http://www.jjmeetsworld.com/ Patreon: / jjmeetsworld Merch Shop: https://shop.spreadshirt.com/jj-meets... Apple Podcasts: https://podcasts.apple.com/us/podcast... Spotify: https://open.spotify.com/show/0L9IGvJ... YouTube: / @jjmeetsworldpodcast3115
Is artificial intelligence here to help financial professionals—or replace them?In this special episode of Real Money, Real Experts, hosts Dr. Brandy Baxter and Rachael DeLeon kick off the new season with their very first video podcast recording and welcome back fan-favorite guest Dr. Jessica Limbrick, professor, researcher, AFCPE Board Member, and 2026 Treasurer.Fresh off her highly rated AFCPE Symposium session, “Will AI Take My Job?”, Dr. Limbrick joins the show to unpack what AI really means for financial counselors, coaches, planners, and educators. Together, they explore how AI can be used as a powerful assistant—from budgeting and lesson planning to brainstorming client strategies—while also discussing its limitations, risks, and ethical considerations.This episode dives into:How financial professionals can use AI without over-relying on itWhy fact-checking and asking better questions matters more than everEquity, bias, and access concerns in AI-driven financial adviceEnvironmental and ethical implications of emerging technologiesWhether AI will actually replace financial counselors—or simply reshape the professionWhether you're AI-curious, AI-cautious, or already experimenting with new tools, this conversation offers a grounded, human-centered perspective on how technology and financial counseling can—and should—coexist.Now available on YouTube and wherever you get your podcasts.Show Notes:01:30 – Introducing Dr. Jessica Limbrick03:00 – How Jessica Got Interested in AI06:00 – Using AI as an Assistant, Not an Authority09:30 – AI in Financial Counseling: Opportunities & Risks13:30 – Ethical Considerations & Bias in AI17:30 – The Future of the Financial Profession20:45 – Will AI Take My Job?22:45 – Jessica's 2 CentsShow Note Links:Connect with Jessica on Instagram!Connect with Jessica on Linkedin!Want to get involved with AFCPE®?Here are a few places to start: Become a Member, Sign up for an Essentials Course, or Get AFC Certified today! Want to support the podcast? We love partnering with organizations that share our mission and values. Download our media kit.
In this episode, I sit down with Travis Misurell, founder of Fink (Future Is Coalition), to discuss his ambitious plan to rebuild America's broken political system from the ground up. Travis explains how the real problem isn't left versus right ideology, but rather "up versus down" – politicians serving big donors versus those serving everyday voters. We dive into his vision for new civic infrastructure that gives citizens transparent access to politician report cards, campaign funding sources, voting records, and broken promises all in one digital hub. The goal is to level the playing field so grassroots candidates don't need millions of dollars to compete with establishment politicians who are bought and paid for by special interests. Travis shares how this citizen-owned platform will connect voters directly with candidates, journalists, and movements without party gatekeepers controlling the narrative. We discuss the challenges of preventing bias, the timeline for launch (aiming for some features by the 2026 midterms), and how everyday Americans can get involved as "citizen architects" to help build this new system. This is about creating real accountability and giving power back to the people – not just switching which party is in charge. Chapters: 0:00 - Introduction: America's Broken Political System1:56 - Sponsor: Fox & Sons Coffee2:26 - Meet Travis Misurell & Fink's Mission3:00 - Travis's Background & 2016 Political Awakening5:53 - The Vision: New Civic Infrastructure for the Digital Age8:33 - How It Works: Politician Report Cards & Transparency11:00 - Making Public Data User-Friendly12:36 - The "Up vs Down" Framework (Not Left vs Right)19:00 - The Real Problem: Money in Politics23:00 - Protecting the Platform from Bias & Special Interests28:51 - How Citizens Can Get Involved Right Now33:17 - Preventing Buyouts & Maintaining Grassroots Funding36:37 - Helping New Candidates Challenge Incumbents42:00 - Timeline: When Will This Be Ready?47:40 - Final Thoughts & Where to Sign Up Links:
Ever wonder why we remember certain things but not others? Want to test yourself on how well you can recognize fallacies in real life? Take the Meme Fallacy Quiz! www.filteritthroughabraincell.com/quiz Learn more about Crazy Thinkers membership where you can practice critical thinking using real-life memes, articles & headlines: www.filteritthroughabraincell.com/crazy Here's how you can purchase the Logical Fallacies ebook: https://www.filteritthroughabraincell.com/offers/z6xbAcB2 Send me any questions, comments or even the fallacies you're seeing around you! think@filteritthroughabraincell.com Or, tag me on Instagram: @filteritthroughabraincell Sign up on my email list at: www.filteritthroughabraincell.com/contact Learn more about Classical Conversations: www.classicalconversations.com/filterit Thank you to our sponsor, CTC Math! Website: https://www.ctcmath.com/?tr_id=brain Homeschool page: https://www.ctcmath.com/how-it-works/home-school?tr_id=brain Free trail: https://www.ctcmath.com/trial?tr_id=brain Special offer! Get 1/2-off discounts plus bonus 6-months free! Critical Thinking for Teens Logical Fallacies for Teens Cognitive Biases for Teens Homeschool Logic Critical thinking for Middle schoolers
In this episode, I sit down with Travis Misurell, founder of Fink (Future Is Coalition), to discuss his ambitious plan to rebuild America's broken political system from the ground up. Travis explains how the real problem isn't left versus right ideology, but rather "up versus down" – politicians serving big donors versus those serving everyday voters. We dive into his vision for new civic infrastructure that gives citizens transparent access to politician report cards, campaign funding sources, voting records, and broken promises all in one digital hub. The goal is to level the playing field so grassroots candidates don't need millions of dollars to compete with establishment politicians who are bought and paid for by special interests. Travis shares how this citizen-owned platform will connect voters directly with candidates, journalists, and movements without party gatekeepers controlling the narrative. We discuss the challenges of preventing bias, the timeline for launch (aiming for some features by the 2026 midterms), and how everyday Americans can get involved as "citizen architects" to help build this new system. This is about creating real accountability and giving power back to the people – not just switching which party is in charge. Chapters: 0:00 - Introduction: America's Broken Political System1:56 - Sponsor: Fox & Sons Coffee2:26 - Meet Travis Misurell & Fink's Mission3:00 - Travis's Background & 2016 Political Awakening5:53 - The Vision: New Civic Infrastructure for the Digital Age8:33 - How It Works: Politician Report Cards & Transparency11:00 - Making Public Data User-Friendly12:36 - The "Up vs Down" Framework (Not Left vs Right)19:00 - The Real Problem: Money in Politics23:00 - Protecting the Platform from Bias & Special Interests28:51 - How Citizens Can Get Involved Right Now33:17 - Preventing Buyouts & Maintaining Grassroots Funding36:37 - Helping New Candidates Challenge Incumbents42:00 - Timeline: When Will This Be Ready?47:40 - Final Thoughts & Where to Sign Up Links:
After a divorce, many people notice something unsettling: their mind feels more negative, more guarded, and quicker to expect the worst. If that sounds familiar, this episode is for you. In today's conversation, we explore positivity bias—the brain's natural tendency to notice and expect good outcomes—and why that bias often weakens after divorce. Drawing on brain research highlighted by psychiatrist Dr. Daniel Amen, we'll talk about how trauma and emotional loss shift the brain into survival mode, making negativity feel automatic—not because something is wrong with you, but because your brain is trying to protect you. We'll also look at how healing happens—not through forcing positivity or denying pain, but by gently retraining the brain to recognize safety, hope, and goodness again. From a faith-centered perspective, we reflect on the steady optimism of President Gordon B. Hinckley, who taught the importance of believing that tomorrow can be better than today—even when life feels heavy. If you've been wondering why hope feels harder after divorce—and how to rebuild it without guilt or pressure—this episode offers clarity, compassion, and practical encouragement. ✨ If this podcast has been helpful to you, make sure you're subscribed so you don't miss an episode. And please consider leaving a five-star rating and review—it helps others find this support when they need it most. • Join my exclusive Life Coaching and Divorce Mentoring Program, Faith Filled Divorce, HERE: httpshttps:https://www.findthejoywithjenn.com/program-details • Get your FREE Podcast Atlas at: https://www.findthejoywithjenn.com/joy-in-the-journey-podcast • Make sure you are part of the Find the Joy With Jenn Fam! Follow me on Instagram: www.instagram.com/findthejoywithjenn/ • Join my FREE Facebook Community: www.facebook.com/groups/findthejoywithjenn • Thank you so much for listening to this episode! I'm honored and excited to be on this journey to healing and personal growth with you. If you enjoyed the podcast, I'd love to ask you to take 2 minutes to leave me a 5-star review on your podcast app; that way, we can help even more men and women find joy in their divorce journeys. You can win a $100 AMAZON GIFT when you do! Just send a screenshot of your review to jenn@jennzingmark.com. Make sure you put "Podcast Review" in the subject line. XO- Jenn
What happens when medical care reduces a whole human being to a number on a scale? In this episode of Dr. Marianne-Land, I'm joined by Ivy Felicia, Body Relationship Coach and founder of Luxuriant Life, for a deeply grounding conversation about anti-fat bias in healthcare, chronic illness, and what it actually takes to build peace with your body in a system that often causes harm. Ivy shares her lived experience as a Black woman of size navigating PCOS, autoimmune illness, thyroid disease, and repeated medical dismissal. We talk openly about the moment a provider told her weight loss surgery was the only option and what it meant to be treated as disposable when she declined. That moment became a turning point that reshaped her relationship with her body and ultimately led to the creation of her Body Relationship Method, a size-inclusive, weight-neutral approach grounded in compassion, self-trust, and holistic wellness. Throughout this conversation, we explore how chronic illness, medical trauma, and anti-fat bias intersect, and why body positivity is not always accessible or supportive for people living in pain, disability, or marginalized bodies. Ivy explains why she centers body peace rather than body love, and how choosing neutrality and non-violence toward your body can be a more realistic and healing place to start. We also discuss the role of spirituality and surrender in healing a relationship with your body. Ivy describes how prayer, connection to nature, journaling, and honoring ancestors support her through periods of overwhelm, and why taking healing one breath at a time can feel far more attainable than one day at a time when you live with chronic pain or illness. This episode also dives into internalized anti-fat bias and internalized ableism. Ivy shares how listening, witnessing, and affirming someone's lived experience can be profoundly reparative, especially for people who have spent years being dismissed or erased by medical systems. We talk about visibility, self-advocacy, and how being truly heard can help people reclaim their voice and their worth. If you've ever felt disconnected from your body because of chronic illness, eating disorder recovery, medical trauma, or weight stigma, this conversation offers a gentler way forward. There is no finish line here. There is no pressure to love your body. There is space to move toward peace, at your own pace, one breath at a time. About Ivy Felicia Ivy Felicia is a Body Relationship Coach, certified holistic wellness practitioner, speaker, and founder of Luxuriant Life, LLC. She is the creator of the Body Relationship Method, a trademarked, size-inclusive, weight-neutral approach that helps people heal body image, navigate chronic illness with compassion, and rebuild self-trust. Through coaching, community, and education, Ivy supports people in marginalized bodies in cultivating peace with their bodies without dieting, scale-based wellness, or toxic positivity. Work With Ivy Felicia Ivy offers support through her Body Relationship Circle membership, group coaching programs, and one-on-one coaching. You can learn more and sign up for her newsletter at ivyfelicia.com. Follow Ivy on Instagram and Threads at @iamivyfelicia. Content Note This episode includes discussion of anti-fat bias in healthcare, chronic illness, medical dismissal, and weight loss surgery recommendations. Want More Support? If anti-fat bias, chronic illness, or medical trauma has impacted your relationship with food or your body, you're not alone. I offer eating disorder therapy and recovery support with a liberation-oriented, neurodivergent-affirming, trauma-informed approach. I work with clients in California, Texas, Washington, D.C., and globally via coaching and education. You can learn more about working with me and explore my courses and resources at drmariannemiller.com. Listen in, take a breath, and remember: peace is allowed to come before love.
We are all back in attendance for another water cooler talk episode where debate text etiquette, JB speed reads thru tea time, a discussion about supporting actors and more. Come thru and chill!
Chris "Bear" Fallica joins the show and puts on his Miami Hurricanes homer cap to tell us why he like the Canes to upset Indiana. Are the Hoosiers cheating? Bear's not saying that while saying it. Plus, the crew talks it out on Divisional round games and can't really come to any agreements.See omnystudio.com/listener for privacy information.
Chris "Bear" Fallica joins the show and puts on his Miami Hurricanes homer cap to tell us why he like the Canes to upset Indiana. Are the Hoosiers cheating? Bear's not saying that while saying it. Plus, the crew talks it out on Divisional round games and can't really come to any agreements.See omnystudio.com/listener for privacy information.
Expect to learn the psychological bias holding you back from making true lasting change in your life.My IG: https://www.instagram.com/jamesbrackiniv/Want to work with me? https://docs.google.com/forms/d/e/1FAIpQLScx1-ILH2euEUchlEmSSj3ccMc0qR464ZpLlN4W74f5_gq_iw/viewformLearn about your health: https://bit.ly/45L3fmyGet the best flavored toothpicks: bit.ly/4sBCKtO
Every leader has blind spots. Not because they're careless or incompetent — but because they're human.In this episode, Dex shares a formative leadership mistake from early in his career and uses it to unpack how beliefs, biases, and unexamined assumptions quietly shape leadership decisions. Often at a cost.You'll explore why blind spots exist, how they show up under pressure, and the practical signals that tell you when one is running the show. Dex also explains why self-awareness alone isn't enough — and how coaching (human and AI) can help you see what you literally cannot see on your own.This is about leadership maturity, not self-criticism.In this episode:A real leadership succession mistake — and the lesson it taughtWhy beliefs quietly limit leadership optionsHow bias forms early and becomes invisibleCommon leadership blind spots (imposter syndrome, people problems, indecision, perfectionism)Why emotional reactivity is often the clueHow coaching helps rewire outdated beliefsWhere AI coaching helps — and where it doesn'tPractical AI prompts to surface blind spots fastPractical prompts mentioned:“What am I not seeing in this situation?”“How can I identify my leadership blind spots?”“What's an effective next step with this team member?”“How can I resolve this conflict without sacrificing my deadlines?”Resources:Dex AI Coach: https://dexrandall.comLeadership coaching with Dex: https://go.dexrandall.com/leadershipIf leadership feels heavier than it should right now, this episode will help you loosen the grip — without losing authority.Send us a text----------------------------------- Resources:Start 1-on-1 coaching at https:/mini.dexrandall.comLead Better with Dex AI Coach https://app.coachvox.ai/share/dexrandallConfidential. Expert. Free. Solve problems fast.For even more TIPS see FACEBOOK: @coachdexrandallINSTAGRAM: @coachdexrandallLINKEDIN: @coachdexrandallYOUTUBE: @dexburnoutcoachSee https://linktr.ee/coachdexrandall for all links
Episode: 3244 Bias and Diversity in Photography and Face Recognition Software. Today, bodies, in beautiful black and white.
In this episode, I'm joined by Virginie Raphael — investor, entrepreneur, and philosopher of work — for a wide-ranging conversation about incentives, technology, and how we build systems that scale without losing their humanity. We talk about her background growing up around her family's flower business, and how those early experiences shaped the way she thinks about labor, value, and operating in the real economy. That foundation carries through to her work as an investor, where she brings an operator's lens to evaluating businesses and ideas. We explore how incentives quietly shape outcomes across industries, especially in healthcare. Virginie shares why telehealth was a meaningful shift and what needs to change to move beyond one-to-one, supply-constrained models of care. We also dig into AI, venture capital, and the mistakes founders commonly make today — from hiring sales teams too early to raising too much money too fast. Virginie offers candid advice on pitching investors, why thoughtful cold outreach still works, and how doing real research signals respect and fit. The conversation closes with a contrarian take on selling: why it's not a numbers game, how focus and pre-qualification drive better outcomes, and why knowing who not to target is just as valuable as finding the right people. If you're thinking about the future of work, building with intention, or navigating entrepreneurship in an AI-accelerated world, this episode is for you. And for more conversations like this, join us at Snafu Conference 2026 on March 5th, where we'll keep exploring incentives, human skills, and what it really takes to build things that last. Start (0:00) Reflections on Work, Geography, and AI Adoption Virginie shares what she's noticing as trends in work and tech adoption: Geographic focus: she's excited to explore AI adoption outside traditional tech hubs. Examples: Atlanta, Nashville, Durham, Utah, Colorado, Georgia, North Carolina, parts of the Midwest. Rationale: businesses in these regions may adopt AI faster due to budgets, urgency, and impatience for tech that doesn't perform. "There are big corporates, there are middle and small businesses in those geos that have budget that will need the tech… and/or have less patience, I should say, for over-hub technologies that don't work." She notes that transitions to transformational technology never happen overnight, which creates opportunities: "We always underestimate how much time a transition to making anything that's so transformational… truly ubiquitous… just tends to think that it will happen overnight and it never does." Robin adds context from her own experience with Robin's Cafe and San Francisco's Mission District: Observed cultural and business momentum tied to geography Mentions Hollywood decline and rise of alternative media hubs (Atlanta, Morocco, New Jersey) Virginie reflects on COVID's impact on workforce behaviors: Opened a "window" to new modes of work and accelerated change: "There were many preexisting trends… but I do think that COVID gave a bit of a window into what was possible." Emphasis on structural change: workforce shifts require multi-year perspective and infrastructure, not just trends. Investor, Mission, and Capital Philosophy Virginie clarifies she is an investor, not a venture capitalist, resisting labels and prestige metrics. "I don't call myself a venture capitalist… I just say investor." Focuses on outcomes over categories, investing in solutions that advance the world she wants to see rather than chasing trendy tech sectors. "The outcome we want to see is everyone having the mode of work that suits them best throughout their lives." Portfolio themes: Access: helping people discover jobs they wouldn't otherwise know about. Retention / support: preventing workforce dropouts, providing appropriate healthcare, childcare, and caregiving support. "Anyone anywhere building towards that vision is investible by us." Critiques traditional venture capital practices: Raising VC money is not inherently a sign of success. "Raising from a VC is just not a sign of success. It's a milestone, not the goal." Concerned about concentration of capital into a few funds, leaving many founders unsupported. "There's a sense… that the work we do commands a lot less power in the world, a lot less effectiveness than holding the capital to hire that labor." Emphasizes structural, mission-driven investing over chasing categories: Invests in companies that prevent workforce dropouts, expand opportunity, and create equitable access to meaningful work. Portfolio strategy is diversified, focusing on infrastructure and long-term impact rather than quick wins. "We've tracked over time what type of founders and what type of solutions we attract and it's exactly the type of deal that we want to see." Reflects on COVID and societal trends as a lens for her investment thesis: "COVID gave a bit of a window into what was possible," highlighting alternative modes of work and talent distribution that are often overlooked. Labor, Ownership, and Durable Skills Virginie reframes the concept of labor, wages, and ownership: "The word labor in and of itself… is something we need to change." Interested in agency and ownership as investment opportunities, especially for small businesses transitioning to employee ownership. "For a very long time… there's been a shift towards knowledge work and how those people are compensated. If you go on the blue-collar side… it's about wages still and labor." Emphasizes proper capitalization and alignment of funds to support meaningful exits for smaller businesses, rather than chasing massive exits that drive the VC zeitgeist. AI fits into this discussion as part of broader investment considerations. Childhood experience in family flower business shaped her entrepreneurial and labor perspective: Selling flowers, handling cash, and interacting with customers taught "durable skills" that persisted into adulthood. "When I think of labor, I think of literally planting pumpkin plants… pulling espresso shots… bringing a customer behind the counter." Observing her father start a business from scratch instilled risk-taking and entrepreneurial spirit. "Seeing my dad do this when I was seven… definitely part of that." Skills like sales acumen, handling money, and talking to adults were early lessons that translated into professional confidence. Non-linear career paths and expanding exposure to opportunity: Concerned that students often see only a narrow range of job options: "Kids go out of high school, they can think of three jobs, two of which are their parents' jobs… Surely because we do a poor job exposing them to other things." Advocates for creating more flexible and exploratory career pathways for young people and adults alike. Durable skills and language shaping work: Introduction of the term "durable skills" reframes how competencies are understood: "I use it all the time now… as a proof point for why we need to change language." Highlights the stigma and limitations of words like "soft skills" or "fractional work": Fractional roles are high-impact and intentional, not temporary or inferior. "Brilliant people who wanna work on a fractional basis… they truly wanna work differently… on a portfolio of things they're particularly good at solving." Work in Progress uses language intentionally to shift perceptions and empower people around work. Cultural significance of language in understanding work and people: Virginie notes that language carries stigma and meaning that shapes opportunities and perception. References Louis Thomas's essays as inspiration for attention to the nuance and power of words: He'll take the word discipline and distill it into its root, tie it back into the natural world." Robin shares a personal anecdote about language and culture: "You can always use Google Translate… but also it's somebody learning DIA or trying to learn dharia, which is Moroccan Arabic… because my fiance is Moroccan." Human-Positive AI, Process, and Apprenticeship Virginie emphasizes the value of process over pure efficiency, especially in investing and work: "It's not about the outcome often, it's about the process… there is truly an apprenticeship quality to venture and investing." Using AI to accelerate tasks like investment memos is possible, but the human learning and iterative discussion is critical: "There's some beauty in that inefficiency, that I think we ought not to lose." AI should augment human work rather than replace the nuanced judgment, particularly in roles requiring creativity, judgment, and relationship-building: "No individual should be in a job that's either unsafe or totally boring or a hundred percent automatable." Introduces the term "human-positive AI" to highlight tools that enhance human potential rather than simply automate tasks: "How do we use it to truly augment the work that we do and augment the people?" Project selection and learning as a metric of value: Virginie evaluates opportunities not just on outcome, but what she will learn and who she becomes by doing the work: "If this project were to fail, what would I still learn? What would I still get out of it?" Cites examples like running a one-day SNAFU conference to engage people in human-centered selling principles: "Who do I become as a result of doing that is always been much more important to me than the concrete outcomes of this thing going well." AI Bubble, Transition, and Opportunity Discusses the current AI landscape and the comparison to past tech bubbles: "I think we're in an AI bubble… 1999 was a tech bubble and Amazon grew out of it." Differentiates between speculative hype and foundational technological transformation: "It is fundamental. It is foundational. It is transformative. There's no question about that." Highlights the lag between technological introduction and widespread adoption: "There's always a pendulum swing… it takes time for massively transformative technology to fully integrate." AI as an enabler, not a replacement: Transition periods create opportunity for investment and human-positive augmentation. Examples from healthcare illustrate AI's potential when applied correctly: "We need other people to care for other people. Should we leverage AI so the doctor doesn't have to face away from the patient taking notes? Yes, ambient scribing is wonderful." Emphasizes building AI around real human use cases and avoiding over-automation: "What are the true use cases for it that make a ton of sense versus the ones we need to stay away from?" History and parallels with autonomous vehicles illustrate the delay between hype and full implementation: Lyft/Uber example: companies predicted autonomous vehicles as cost drivers; the transition opened up gig work: "I was a gig worker long before that was a term… the conversation around benefits and portability is still ongoing." AI will similarly require time to stabilize and integrate into workflows while creating new jobs. Bias, Structural Challenges, and Real-World AI Experiments Discusses the importance of addressing systemic bias in AI and tech: Shares the LinkedIn "#WearThePants" experiment: women altered gender identifiers to measure algorithmic reach: "They changed their picture, in some cases changed their names… and got much more massive reach." Demonstrates that AI can perpetuate structural biases baked into systems and historical behavior: "It's not just about building AI that's unbiased; it's about understanding what the algorithm might learn from centuries of entrenched behavior." Highlights the ongoing challenge of designing AI to avoid reinforcing existing inequities: "Now you understand the deeply structural ingrained issues we need to solve to not continue to compound what is already massively problematic." Parenting, Durable Skills, and Resilience Focus on instilling adaptability and problem-solving in children: "I refuse to problem solve for them. If they forget their homework, they figure it out, they email the teacher, they apologize the next day. I don't care. I don't help them." Emphasizes allowing children to navigate consequences themselves to build independence: "If he forgets his flute, he forgets his flute. I am not making the extra trip to school to bring him his flute." Everyday activities are opportunities to cultivate soft skills and confidence: "I let them order themselves at the restaurant… they need to look the waiter in the eye and order themselves… you need to speak more clearly or speak loudly." Cultural context and exposure shape learning: Practices like family meals without devices help children appreciate attention, respect, and communication: "No iPad or iPhone on our table… we sit properly, enjoy a meal together, and talk about things." Travel and cultural exposure are part of teaching adaptability and perspective: "We spent some time in France over the summer… the mindset they get from that is that meals matter, and people operate differently." Respecting individuality while fostering independence: "They are their own people and you need to respect that and step away… give them the ability to figure out who they are and what they like to do." Parenting as a balance of guidance and autonomy: "Feel like that was a handbook that you just offered for parenting or for management? Either one. Nobody prepares you for that… part of figuring out." Future of Work and Technology Horizons Timeframes for predicting trends: Focus on a 5-year horizon as a middle ground between short-term unpredictability and long-term uncertainty: "Five years feels like this middle zone that I'm kind of guessing in the haze, but I can kind of see some odd shapes." Short-term (6–18 months) is more precise; long-term (10–15 years) is harder to anticipate: "I'm a breezy investor. Six months at a time max… deal making between two people still matters in 18 months." Identifying emerging technologies with latent potential: Invests in technologies that are ready for massive impact but haven't yet had a "moment": "I like to look at technologies that have yet to have a moment… the combo of VR and AI is prime." Example: Skill Maker, a VR+AI training platform for auto technicians, addressing both a labor shortage and outdated certification processes: "We are short 650,000 auto technicians… if you can train a technician closer to a month or two versus two years, I promise you the auto shops are all over you." Focuses on alignment of incentives, business model innovation, and meaningful outcomes: "You train people faster, even expert technicians can benefit… earn more money… right, not as meaningful to them and not as profitable otherwise." Principles guiding technology and investment choices: Solving enduring problems rather than temporary fads: "What is a problem that is still not going to go away within the next 10–15 years?" Ensuring impact at scale while creating economic and personal value for participants: "Can make a huge difference in the lives of 650,000 people who would then have good paying jobs." Scaling, Incentives, and Opportunity Re-examining traditional practices and identifying opportunities for change: "If you've done a very specific thing the exact same way, at some point, that's prime to change." Telehealth is an example: while helpful for remote access, it hasn't fundamentally created capacity: "You're still in that one-to-one patient's relationship and an hour of your time with a provider is still an hour at a time." Next version of telehealth should aim to scale care beyond individual constraints: "Where do we take telehealth next… what is the next version of that that enables you to truly scale and change?" Incentives shape outcomes: "Thinking through that and all the incentives… if I were to change the incentives, then people would behave differently? The answer very often is yes, indeed." Paraphrasing Charlie Munger: "Look for the incentives and I can tell you the outcome." Founders, Pitching, and Common Mistakes Pet peeves in founder pitches: Lack of research and generic outreach is a major turn-off: "I can really quickly tell if you have indeed spent a fraction of a minute on my site… dear sir, automatic junk. I won't even read the thing." Well-crafted, thoughtful cold inbound pitches get attention: "Take some time. A well crafted cold inbound will get my attention… you don't need to figure out an intro." Big mistakes entrepreneurs make: Hiring too early, especially in sales: "Until you have a playbook, like don't hire a sales team… if you don't have about a million in revenue, you're probably not ready." Raising too much capital too quickly: "You get into that, you're just gonna spend a lot more time fundraising than you are building a company." Comparing oneself to others: "You don't know if it's true… there's always a backstory… that overnight success was 15 years in the making." Sales Strategy and Non-Sales Selling Approach is contrarian: focus on conversion, not volume: "It is not a numbers game. I think it's a conversion game… I would much rather spend more time with a narrower set of targets and drive better conversion." Understanding fit is key: "You gotta find your people… and just finding who is not or should not be on your list is equally valuable." Recognizes that each fund and business is unique, so a tailored approach is essential: "The pitch is better when I'm talking to the quote unquote right people in the right place about the right things." Where to Find Virginie and Her Work Resources for listeners: Full Circle Fund: fullcirclefund.io Work in Progress: workinprogress.io LinkedIn: Virginie Raphael Where to Access Snafu Go to joinsnafu.com and sign up for free.
Cover 2 with Blaine and Zach - Hour 2 - Mike McDaniel Interviews with Titans + How can Recency Bias play into HC HireSee omnystudio.com/listener for privacy information.
In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss analyzing survey data using generative artificial intelligence tools. You will discover how to use new AI functions embedded in spreadsheets to code hundreds of open-ended survey responses instantly. You’ll learn the exact prompts needed to perform complex topic clustering and sentiment analysis without writing any custom software. You will understand why establishing a calibrated, known good dataset is essential before trusting any automated qualitative data analysis. You’ll find out the overwhelming trend in digital marketing content that will shape future strategies for growing your business. Watch now to revolutionize how you transform raw feedback into powerful strategy! Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-processing-survey-data-with-generative-ai.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s In Ear Insights, let’s talk about surveys and processing survey data. Now, this is something that we’ve talked about. Gosh, I think since the founding of the company, we’ve been doing surveys of some kind. And Katie, you and I have been running surveys of some form since we started working together 11 years ago because something that the old PR agency used to do a ton of—not necessarily well, but they used to do it well. Katie Robbert: When they asked us to participate, it would go well. Christopher S. Penn: Yes, exactly. Christopher S. Penn: And this week we’re talking about how do you approach survey analysis in the age of generative AI where it is everywhere now. And so this morning you discovered something completely new and different. Katie Robbert: Well, I mean, I discovered it via you, so credit where credit is due. But for those who don’t know, we have been a little delinquent in getting it out. But we typically run a one-question survey every quarter that just, it helps us get a good understanding of where our audience is, where people’s heads are at. Because the worst thing you can possibly do as business owners, as marketers, as professionals, is make assumptions about what people want. And that’s something that Chris and I work very hard to make sure we’re not doing. And so one of the best ways to do that is just to ask people. We’re a small company, so we don’t have the resources unfortunately to hold a lot of one-on-one meetings. But what we can do is ask questions virtually. And that’s what we did. So we put out a one-question survey. And in the survey, the question was around if you could pick a topic to deep dive on in 2026 to learn about, what would it be. Now keep in mind, I didn’t say about AI or about marketing because that’s where—and Chris was sort of alluding to—surveys go wrong. When we worked at the old shop, the problem was that people would present us with, “and this is the headline that my client wants to promote.” So how do we run a survey around it? Without going too far in the weeds, that’s called bias, and that’s bad. Bias equals bad. You don’t want to lead with what you want people to respond with. All of that being said, we’ve gotten almost 400 responses over the weekend, which is a fantastic number of responses. That gives us a lot of data to work with. But now we have to do something with it. What Chris discovered and then shared with me, which I’m very excited about, is you don’t have to code anything to do this. There were and there still are a lot of data analysis platforms for market research data, which is essentially what this is for: unstructured, qualitative, sentence structured data, which is really hard to work with if you don’t know what you’re looking for. And the more you have of it, the harder it is to figure out where the trends are. But now people are probably thinking, “oh, I just bring it into generative AI and say, summarize this for me.” Well, that’s not good enough. First of all, let’s just don’t do that. But there are ways to do it, no code, that you can really work with the data. So without further ado, Chris, do you want to talk about what you’ve been working on this morning? And we’re going to do a deep dive on our livestream on Thursday, which you can join us every Thursday at 1:00 PM Eastern. Go to Trust Insights AI TI podcast. Nope, that’s us today. Wait a second. TrustInsights AI YouTube, and you can follow live or catch the replay. And we’ll do a deep dive into how this works, both low code and high tech. But I think it’s worth at least acknowledging, Chris, what you have discovered this morning, and then we can sort of talk about some of the findings that we’re getting. Christopher S. Penn: So one of the most useful things that AI companies have done in the last 6 months is put generative AI into the tools that we already use. So Google has done this. They’ve put Gemini in Google Sheets, Google Docs, in your Gmail. Finally, by the way—slight tangent. They finally put it in Google Analytics. Three years later. Microsoft has put Copilot into all these different places as well. In Excel, in Word, in PowerPoint, and so on and so forth. And so what you can do inside of these tools is they now have formulas that essentially invoke an AI agent. So inside of Google Sheets you can type equals Gemini, then give it a prompt and then give it a cell to work on and have it do its thing. Christopher S. Penn: So what I did naturally was to say, “Okay, let’s write a prompt to do topic analysis.” “Okay, here’s 7 different topics you can choose from.” Gemini, tell me for this cell, this one survey response, which of the 7 topics does it fit in? And then it returns just the topic name and puts it in that cell. And so what used to be a very laborious hand coding—”okay, this is about this”—now you can just drag and fill the column and you’ve got all 400 responses classified. You can do sentiment analysis, you can do all sorts of stuff. Katie Robbert: I remember a quick anecdote, and I think I’ve told this story before. When I was doing clinical trial research, we were trying to develop an automated system to categorize sentiment for online posts about the use and abuse of opiates and stimulants. So, is it a positive sentiment? Is it a negative sentiment? With the goal of trying to understand the trends of, “oh, this is a pharmaceutical that just hit the market. People love it. The sentiment is super positive in the wrong places.” Therefore, it’s something that we should keep an eye on. All to say, I remember sitting there with stacks and stacks of printed out online conversation hand coding. One positive, two negative. And it’s completely subjective because we had to have 4 or 5 different hand coders doing the sentiment analysis over and over again until we came to agreement, and then we could start to build the computer program. So to see that you did this all in the span of maybe 20 minutes this morning is just—it’s mind blowing to me. Christopher S. Penn: Yeah. And the best part is you just have to be able to write good prompts. Katie Robbert: Well, therein lies the caveat. And I think that this is worth repeating. Critical thinking is something that AI is not going to do for you. You still have to think about what it is you want. Giving a spreadsheet to AI and saying, “summarize this,” you’re going to get crappy results. Christopher S. Penn: Exactly. So, and we’ll show this on the live stream. We’re going to walk through the steps on how do you build this? Very simple, no tech way of doing it, but at the very least, one of the things you’ll want to do. And we’ve done this. In fact, we did this not too long ago for an enterprise client building a sentiment analysis system: you have to have a known, good starting data set of stuff that has been coded that you agree with. And it can be 3 or 4 or 5 things, but ideally you start with that. So you can say, this is examples of what good and bad sentiment is, or positive and negative, or what the topic is. Write a prompt to essentially get these same results. It’s what the tech folks would call back testing, just calibration, saying, “This is a note, it still says, ‘I hate Justin Zeitzac, man, all this and stuff.’ Okay, that’s a minus 5.” What do they hate us as a company? Oh, okay. “That annoying Korean guy,” minus 5. So you’d want to do that stuff too. So that’s the mechanics of getting into this. Now, one of the things that I think we wanted to chat about was kind of at a very high level, what we saw. Katie Robbert: Yeah. Christopher S. Penn: So when we put all the big stuff into the big version of Gemini to try and get a sense of what are the big topics, really, 6 different topics popped out: Generative AI, broadly, of course; people wanting to learn about agentic AI; content marketing; attribution and analytics; use cases in general; and best practices in general. Although, of course, a lot of those had overlap with the AI portion. And when we look at the numbers, the number one topic by a very large margin is agentic AI. People want to know, what do we do with this thing, these things? How do we get them going? What is it even? And one of the things I think is worth pointing out is having Gemini in your spreadsheet, by definition, is kind of an agent in the sense that you don’t have to go back to an AI system and say, “I’ll do this.” Then copy-paste results back and forth. It’s right there as a utility. Katie Robbert: And I think that I’m not surprised by the results that we’re seeing. I assumed that there would be a lot of questions around agentic AI, generative AI in general. What I am happy to see is that it’s not all AI, that there is still a place for non-AI. So, one of the questions was what to measure and why, which to be fair, is very broad. But you can make assumptions that since they’re asking us, it’s around digital marketing or business operations. I think that there’s one of the things that we try to ask in our free Slack group, Analytics for Marketers, which you can join for free at trustinsights.ai/analyticsformarketers. We chatting in there every day is to make sure that we have a good blend of AI-related questions, but also non-AI-related questions because there is still a lot of work being done without AI, or AI is part of the platform, but it’s not the reason you’re doing it. We know that most of these tools at this day and age include AI, but people still need to know the fundamentals of how do I build KPIs, what do I need to measure, how do I manage my team, how do I put together a content calendar based on what people want. You can use AI as a supporting role, but it’s not AI forward. Christopher S. Penn: And I think the breakout, it’s about, if you just do back of the envelope, it’s about 70/30. 70% of the responses we got really were about AI in some fashion, either regular or agentic. And the 30% was in the other category. And that kind of fits nicely to the two themes that we’ve had. Last year’s theme was rooted, and this year’s theme is growth. So the rooted is that 30% of how do we just get basic stuff done? And the 70% is the growth. To say, this is where things are and are likely going. How do we grow to meet those challenges? That’s what our audience is asking of us. That’s what you folks listening are saying is, we recognize this is the growth opportunity. How do we take advantage of it? Katie Robbert: And so if we just look at all of these questions, it feels daunting to me, anyway. I don’t know about you, Chris—you don’t really get phased by much—but I feel a little overwhelmed: “Wow, do you really know the answers to all of these questions?” And the answer is yes, which is also a little overwhelming. Oh wait, when did that happen? But yeah, if you’re going to take the time to ask people what they’re thinking, you then have to take the time to respond and acknowledge what they’ve asked. And so our—basically our mandate—is to now do something with all of this information, which we’re going to figure out. It’s going to be a combination of a few things. But Chris, if you had your druthers, which you don’t, but if you did. Where would you start with answering some of these questions? Christopher S. Penn: What if I had my druthers? I would put. Take the entire data set one piece at a time and take the conclusion, the analysis that we’ve done, and put it into Claude Code with 4 different agents, which is actually something I did with my own newsletter this past weekend. I’d have a revenue agent saying, “How can we make some money?” I’d have a voice of the customer agent based on our ICP saying, “Hey, you gotta listen to the customer. This is what we’re saying. This is literally what we said. You gotta listen to us.” “Hey, your revenue agent, you can’t monetize everything. I’m not gonna pay for everything.” You would have a finance and operations agent to say, “Hey, let’s. What can we do?” “Here’s the limitations.” “We’re only this many people. We only have this much time in the day. We can’t do everything.” “We gotta pick the things that make sense.” And then I would have the Co-CEO agent (by virtual Katie) as the overseer and the orchestrator to say, “Okay, Revenue Agent, Customer Agent, Operations Agent, you guys tell me, and I’m going to make some executive decisions as to what makes the most sense for the company based on the imperatives.” I would essentially let them duke it out for about 20 minutes in Claude Code, sort of arguing with each other, and eventually come back with a strategy, tactics, execution, and measurement plan—which are the 4 pieces that the Co-CEO agent would generate—to say, “Okay, out of these hundreds of survey responses, we know agentic AI is the thing.” “We know these are the kinds of questions people are asking.” “We know what capabilities we have, we know limitations we have.” “Here’s the plan,” or perhaps, because it’s programmed after you, “Here’s 3 plans: the lowest possible, highest possible, middle ground.” And then we as the humans can look at it and go, “All right, let’s take some of what’s in this plan and most of what’s in this plan, merge that together, and now we have our plan for this content.” Because I did that this weekend with my newsletter, and all 4 of the agents were like, “Dude, you are completely missing all the opportunities. You could be making this a million-dollar business, and you are just ignoring it completely.” Yeah, Co-CEO was really harsh. She was like, “Dude, you are missing the boat here.” Katie Robbert: I need to get my avatar for the Co-CEO with my one eyebrow. Thanks, Dad. That’s a genetic thing. I mean, that’s what I do. Well, so first of all, I read your newsletter, and I thought that was a very interesting thing, which I’m very interested to see. I would like you to take this data and follow that same process. I’m guessing maybe you already have or are in the process of it in the background. But I think that when we talk about low tech and high tech, I think that this is really sort of what we’re after. So the lower tech version—for those who don’t want to build code, for those who don’t want to have to open up Python or even learn what it is—you can get really far without having to do that. And again, we’ll show you exactly the steps on the live stream on Thursday at 1:00 PM Eastern to do that. But then you actually have to do something with it, and that’s building a plan. And Chris, to your point, you’ve created synthetic versions of basically my brain and your brain and John’s brain and said, “Let’s put a plan together.” Or if you don’t have access to do that, believe it or not, humans still exist. And you can just say, “Hey Katie, we have all this stuff. People want to get answers to these questions based on what we know about our growth plans and the business models and all of those things. Where should we start?” And then we would have a real conversation about it and put together a plan. Because there’s so much data on me, so much data on you and John, etc., I feel confident—because I’ve helped build the Co-CEO—I feel confident that whatever we get back is going to be pretty close to what we as the humans would say. But we still want that human intervention. We would never just go, “Okay, that’s the plan, execute it.” We would still go, “Well, what the machines don’t know is what’s happening in parallel over here.” “So it’s missing that context.” “So let’s factor that in.” And so I’m really excited about all of it. I think that this is such a good use of the technology because it’s not replacing the human critical thinking—it’s just pattern matching for us so that we can do the critical thinking. Christopher S. Penn: Exactly. And the key really is for that advanced use case of using multiple agents for that scenario, the agents themselves really do have to be rock solid. So you built the ideal customer profile for the almost all the time in the newsletter. You built… Yeah, the Co-CEO. We’ve enhanced it over time, but it is rooted in who you are. So when it makes those recommendations and says those things, there was one point where it was saying, “Stop with heroics. Just develop a system and follow the system.” Huh, that sounds an awful lot. Katie Robbert: I mean, yeah, I can totally see. I can picture a few instances where that phrase would actually come out of my mouth. Christopher S. Penn: Yep, exactly. Christopher S. Penn: So that’s what we would probably do with this is take that data, put it through the smartest models we have access to with good prompts, with good data. And then, as you said, build some plans and start doing the thing. Because if you don’t do it, then you just made decorations for your office, which is not good. Katie Robbert: I think all too often that’s what a lot of companies find themselves in that position because analyzing qualitative data is not easy. There’s a reason: it’s a whole profession, it’s a whole skill set. You can’t just collect a bunch of feedback and go, “Okay, so we know what.” You need to actually figure out a process for pulling out the real insights. It’s voice of customer data. It’s literally, you’re asking your customers, “What do you want?” But then you need to do it. The number one mistake that companies make by collecting voice of customer data is not doing anything with it. Number 2 is then not going back to the customer and acknowledging it and saying, “We heard you.” “Here’s now what we’re going to do.” Because people take the time to respond to these things, and I would say 99% of the responses are thoughtful and useful and valuable. You’re always going to get a couple of trolls, and that’s normal. But then you want to actually get back to people, “I heard you.” Your voice is valuable because you’re building that trust, which is something machines can’t do. You’re building that human trust in those relationships so that when you go back to that person who gave you that feedback and said, “I heard you, I’m doing something with it.” “Here’s an acknowledgment.” “Here’s the answer.” “Here’s whatever it is.” Guess what? Think about your customer buyer’s journey. You’re building those loyalists and then eventually those evangelists. I’m sort of going on a tangent. I’m very tangential today. A lot of companies stop at the transactional purchase, but you need to continue. If you want that cycle to keep going and have people come back or to advocate on your behalf, you need to actually give them a reason to do that. And this is a great opportunity to build those loyalists and those evangelists of your brand, of your services, of your company, of whatever it is you’re doing by just showing up and acknowledging, “Hey, I heard you, I see you.” “Thank you for the feedback.” “We’re going to do something with it.” “Hey, here’s a little token of appreciation,” or “Here’s answer to your question.” It doesn’t take a lot. Our good friend Brook Sellis talks about this when she’s talking about the number one mistake brands make in online social conversations is not responding to comments. Yeah, doesn’t take a lot. Christopher S. Penn: Yeah. Doesn’t cost anything either. Katie Robbert: No. I am very tangential today. That’s all right. I’m trying not to lose the plot. Christopher S. Penn: Well, the plot is: We’ve got the survey data. We now need to do something about it. And the people have spoken, to the extent that you can make that claim, that Agentic AI and AI agents is the thing that they want to learn the most about. And if you have some thoughts about this, if you agree or disagree and you want to let us know, pop on by our free Slack, come on over to Trust Insights AI/analytics for marketers. I think we’re probably gonna have some questions about the specifics of agentic AI—what kinds of agents? I think it’s worth pointing out that, and we’ve covered this in the past on the podcast, there are multiple different kinds of AI agents. There’s everything from what are essentially GPTs, because Microsoft Copilot calls Copilot GPTs Copilot agents, which is annoying. There are chatbots and virtual customer service agents. And then there’s the agentic AI of, “this machine is just going to go off and do this thing without you.” Do you want it to do that? And so we’ll want to probably dig into the survey responses more and figure out which of those broad categories of agents do people want the most of, and then from there start making stuff. So you’ll see things in our, probably, our learning management system. You’ll definitely see things at the events that folks bring us in to speak at. And yeah, and hopefully there’ll be some things that as we build, we’ll be like, “Oh, we should probably do this ourselves.” Katie Robbert: But it’s why we ask. It’s too easy to get stuck in your own bubble and not look outside of what you’re doing. If you are making decisions on behalf of your customers of what you think they want, you’re doing it wrong. Do something else. Christopher S. Penn: Yeah, exactly. So pop on by to our free Slack. Go to TrustInsights.ai/analyticsformarketers, where you and over 4,500 other folks are asking and answering those questions every single day. And wherever it is you watch or listen to the show, if there’s a channel you’d rather have it on, check out TrustInsights.ai/tipodcast. You can find us in all the places fine podcasts are served. Thanks for tuning in. We’ll talk to you on the next one. Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Trust Insight services span the gamut from developing comprehensive data strategies and conducting deep dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology and MarTech selection and implementation, and high-level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, DALL-E, Midjourney, Stable Diffusion, and Meta Llama. Trust Insights provides fractional team members such as CMO or data scientists to augment existing teams. Beyond client work, Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the *In Ear Insights* podcast, the *Inbox Insights* newsletter, the *So What* Livestream, webinars, and keynote speaking. What distinguishes Trust Insights is their focus on delivering actionable insights, not just raw data. Trust Insights are adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet they excel at explaining complex concepts clearly through compelling narratives and visualizations, data storytelling. This commitment to clarity and accessibility extends to Trust Insights’ educational resources, which empower marketers to become more data-driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.
KI ist eine Blackbox, aber Sandra Wachter bringt Licht in den Algorithmen-Dschungel. Sie ist Professorin am Oxford Internet Institute und Humboldt-Professorin am Hasso-Plattner-Institut und forscht zu Datenethik, Regulierung und den gesellschaftlichen Auswirkungen von generativer KI. Generative KI, damit ist KI gemeint, die neue Inhalte erzeugt. Zum Beispiel Texte, Bilder, Audio oder Videos. In dieser Folge erklärt Sandra Wachter, warum der Begriff ‚Künstliche Intelligenz‘ ihrer Meinung nach irreführend ist, wo sie die größten Chancen und Risiken sieht und weshalb sie sich deutlich für mehr Regulierung ausspricht. Dabei erläutert die Juristin, was hinter Bias und Halluzinationen steckt, erklärt wie der von ihr entwickelte Fairness-Test zu mehr Klarheit für menschliche Entscheidungen führt und warum sie KI in ihren Lehrveranstaltungen verbietet. Außerdem führt sie aus, warum sie ChatGPT und andere Modelle für Blender hält und was man im alltäglichen Umgang mit ihnen beachten soll. Links: Sandra Wachter auf LinkedIn: https://www.linkedin.com/in/prof-sandra-wachter-12008bb5/ X: @SandraWachter5 Profil an der University of Oxford: https://www.oii.ox.ac.uk/people/profiles/sandra-wachter/ Profil auf der Website vom Hasso Plattner Institut: https://hpi.de/forschung/fachgebiete/technology-and-regulation/
We don’t know what happened over the weekend, but it’s cold in the studio. Nobody tell 50. Mal shows accountability, and admits he was wrong about an exclusive music drop, but he did call Teyana Taylor winning a Golden Globe. Rory told y’all Hot 97 was about to hire Mero, but nobody wanted to listen. Plus, Rory and Mal respond to 9th Wonder’s rant on X, Drake shames Rory on his IG story, and Bruno’s new single leaves Rory and Mal disappointed. #volume All lines provided by hardrock.betSee omnystudio.com/listener for privacy information.
"Kultivuj si takový prožitek, který tě v budoucnu bude podporovat."Dnes to bude trochu něco jiného, celá přednáška z Melting potu Colours of Ostrava! Díky za pozvání!Registruj se na naší Půlroční BWA Akademii 2026! Do 18.1. SLEVA! Víc Informací ZDE.V tomhle díle se noříme do jednoho z nejzásadnějších, ale nejméně viditelných procesů v naší mysli: jak se tvoří naše „mapa významnosti“ - tedy to, čemu věnujeme pozornost, co považujeme za důležité a podle čeho se rozhodujeme.Bavíme se o tom, jak dopamin funguje jako architekt této mapy, jak ji moderní svět postupně deformuje a proč levné zdroje stimulu – sociální sítě, porno, notifikace, nekonečný feed - zužují naši perspektivu, místo aby ji rozšiřovaly.Dotýkáme se fenoménu informační obezity, kdy konzumujeme obsah bez filtru, zatímco algoritmy fungují jako „knihovníci“, kteří nám hází knihy přímo do obličeje. A ptáme se:Jak se v tomhle prostředí nestát pasivním konzumentem, ale aktivním tvůrcem vlastní informační diety?Velká část epizody je i o tom, jak si znovu budovat dlouhé cykly smysluplné radosti – skrze náročné, ale obohacující aktivity, které podporují stav flow, trpělivost a skutečné učení. Třeba i tak obyčejnou věcí, jako je… keramika.Mluvíme také o:proč pozitivní emoce reálně rozšiřují naše myšlení (a máme na to data)jak vděčnost pomáhá stabilizovat dopaminový systémproč je důležité kultivovat vztah k budoucímu jájak se učit být s nepříjemnými emocemi místo okamžité únikové reakcea proč by měl být reálný svět hlavním zdrojem naší zkušenosti, ne digitální prostorTenhle díl není o tom, že by technologie byly zlo.Je o tom, že bez vědomého řízení pozornosti přenecháváme volant někomu jinému.Minutáž:00:00 Úvod: Subjektivní zkušenost06:30 Evoluce a původ našeho chování09:05 Evoluční nesoulady: Shinkansen vs. motoráček12:44 Co je to dopamin a jak funguje15:43 Očekávání a klamání organismu18:03 Levný dopamin: Proč nás moderní svět "znásilňuje"21:08 Mapa významnosti: Filtr naší reality23:01 Naivní realismus a efekt červeného auta27:46 Dlouhodobé cykly: Náhrada levného dopaminu29:42 Příklad keramiky: Drahý dopamin a trpělivost33:37 Broaden & Build: Jak pozitivní emoce rozšiřují obzory37:20 Umění být s negativním afektem40:39 Informační obezita a dieta44:02 Historie lajkovacího tlačítka46:10 Bias prestiže: Jakou hru hrají tvé vzory48:39 Ne je celá věta: Trénink odmítáníPřechod do VIP- Ne je celá věta: Trénink odmítání- Hédonická adaptace a neuspokojitelnost mysli- Krize smyslu a vědomé cíle- Být dobrými předky pro budoucí generace- Vděčnost jako protijed
Send us a textSome workplaces weren't built with women in mind — but that doesn't mean you can't lead, be heard, and thrive.In this episode of Starter Girlz, Jennifer Loehding sits down with Kae Kronthaler Williams, global software marketing executive and author of Not Made For You. Kae shares her journey from starting as a telemarketer to becoming a CMO, and what she has learned about leadership, navigating bias, and thriving in male-dominated environments.This conversation explores the realities of workplace bias, the value of diverse teams, and leadership insights Kae has gained throughout her career. You'll hear discussion-based insights on how curiosity, awareness, and collaboration shape inclusive, high-performing teams, and how women and marginalized voices can navigate systems that weren't built for them.⭐ What You'll Learn in This EpisodeHow bias shows up in everyday workplace interactions — and why noticing it mattersThe role of leadership in creating inclusive, high-performing teamsWhy diverse perspectives make teams stronger and decisions sharperHow women and marginalized voices can navigate systems that weren't built for themThe importance of connection, awareness, and reflection in leadershipSupporting others and fostering collaboration as part of effective leadershipHow curiosity and open-mindedness can shift workplace cultureKey insights from Kae's career on staying resilient and continuing to grow
Check out host Bidemi Ologunde's new show: The Work Ethic Podcast, available on Spotify and Apple Podcasts.In this episode, host Bidemi Ologunde unpacks OpenAI's newly released ChatGPT Health and what it signals about the future of consumer-facing healthcare AI. What exactly is "ChatGPT Health," and why is OpenAI moving from general chat to a dedicated health experience? When an AI gives the wrong answer in a high-stakes setting—medical advice, airline refunds, legal citations—who owns the liability: the user, the company deploying the chatbot, or the model-maker? How are regulators in the U.S., Europe, and beyond approaching AI in healthcare—and what counts as "wellness" versus "medical" software? Bidemi also explores the realities of AI error, hallucinations, and bias, and asks what these tools could mean for underserved and minority populations worldwide— including Native Americans, Pacific Islanders, and communities in low-resource health systems.Email: bidemiologunde@gmail.comSupport for The Bid Picture Podcast comes from Intuit QuickBooks. If you're running a business, a side hustle, or just trying to stay on top of your money, QuickBooks helps you track income and expenses, send invoices, and see where things stand—without living in spreadsheets. It's tech that's meant to give you time back, so you can spend more of your attention on your life, not your tabs. If you're asked how you heard about QuickBooks, please mention The Bid Picture Podcast. Learn more at quickbooks.intuit.com.Support for The Bid Picture Podcast comes from VIZZ. If age-related blurry near vision—also called presbyopia—has you holding your phone farther away or avoiding the small print, ask your eye doctor about VIZZ, a once-daily prescription eye drop for adults that treats blurry near vision. Do not use VIZZ if you are allergic to any of its ingredients. The most common side effects are eye irritation, temporary dim or dark vision, headache, and eye redness. Be careful driving at night or doing activities that require clear vision until your vision returns to normal. If you're asked how you heard about VIZZ, please mention The Bid Picture Podcast. Learn more at vizz.com.Support for The Bid Picture Podcast comes from Rula. If you're trying to build a healthier relationship with tech—setting boundaries, breaking burnout patterns, or feeling more present—therapy can help, and Rula makes it easier to find licensed mental health providers and meet by video on a schedule that fits your life. If you're asked how you heard about Rula, please mention The Bid Picture Podcast. Learn more at rula.com.Support the show
Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM This episode explores how AI is transforming hiring, reducing bias, and helping businesses reliably identify A players. Fletcher Wimbush shares practical steps for using AI to streamline job analysis, screening, assessments, and onboarding, giving small and mid sized businesses access to talent strategies once reserved for large enterprises.
- AI Coding Revolution and Its Implications (0:10) - AI Coding vs. Human Coding (2:54) - AI's Role in Business and Job Transformations (4:35) - BrighteLearn.ai and AI's Continuous Improvement (5:51) - AI's Capabilities and Future Projections (7:37) - Health and Technology Integration (15:09) - The Role of Censorship and Depopulation (30:16) - The Financial Reset and Its Implications (56:36) - Preparation for Financial Chaos (1:18:10) - The Role of AI in Future Preparedness (1:21:47) - AI Integration and Initial Setup (1:25:28) - AI Tools and Recent Developments (1:29:46) - Differences Between AI Models (1:33:59) - AI's Role in Technological Advancements (1:43:06) - AI in Content Creation and Planning (1:48:56) - AI in Video and Music Production (1:56:34) - AI's Impact on Society and the Future (2:32:50) - AI's Role in Decentralization and Freedom (2:33:03) - AI's Potential for Creating AI Avatars (2:34:15) - AI's Role in Technological Competition (2:35:10) - Challenges with Current AI Models and Bias (2:38:42) - China's Leadership in AI and Censorship (2:41:41) - Customizing Chatbots and Medical Tourism (2:43:00) - Jailbreak Techniques and Health Solutions (2:45:18) - Technocracy Atlas and Epstein Data (2:47:32) - Commitment to Open Source and Decentralized Knowledge (2:49:27) - Health Ranger Store New Year's Sale (2:51:49) For more updates, visit: http://www.brighteon.com/channel/hrreport NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we're helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️ Sign Up For Our Newsletter: https://www.naturalnews.com/Readerregistration.html ▶️ Brighteon: https://www.brighteon.com/channels/hrreport ▶️ Join Our Social Network: https://brighteon.social/@HealthRanger ▶️ Check In Stock Products at: https://PrepWithMike.com
In this hour, we peel back the curtain on why fans have soured on Mike McCarthy, with Gio arguing that it's his "twice-burned" reputation combined with a subconscious bias toward more physically fit coaches like John Harbaugh. A caller suggests NFL "interview quotas" for larger coaches to get a shot. C-Lo drops in with more on the Harbaugh brothers and the insider feud between Adam Schefter and Ian Rapoport over the Ravens' locker room. Plus, we break down the trade sending Trae Young to the Wizards, preview the Fiesta Bowl between Ole Miss and Miami, and wrap things up with a nostalgic trip through MTV's history as they shutter their music video channels for good.
Why do we tend to assume other people feel the same way about things that we do? Want to test yourself on how well you can recognize fallacies in real life? Take the Meme Fallacy Quiz! www.filteritthroughabraincell.com/quiz Learn more about Crazy Thinkers membership where you can practice critical thinking using real-life memes, articles & headlines: www.filteritthroughabraincell.com/crazy Here's how you can purchase the Logical Fallacies ebook: https://www.filteritthroughabraincell.com/offers/z6xbAcB2 Send me any questions, comments or even the fallacies you're seeing around you! think@filteritthroughabraincell.com Or, tag me on Instagram: @filteritthroughabraincell Sign up on my email list at: www.filteritthroughabraincell.com/contact Learn more about Classical Conversations: www.classicalconversations.com/filterit Thank you to our sponsor, CTC Math! Website: https://www.ctcmath.com/?tr_id=brain Homeschool page: https://www.ctcmath.com/how-it-works/home-school?tr_id=brain Free trail: https://www.ctcmath.com/trial?tr_id=brain Special offer! Get 1/2-off discounts plus bonus 6-months free! Critical Thinking for Teens Logical Fallacies for Teens Cognitive Biases for Teens Homeschool Logic Critical thinking for Middle schoolers
In episode #1705 of Good Morning Liberty, Nate Thurston sits down with Larry Sanger, the co-founder of Wikipedia and President of the Knowledge Standards Foundation. They delve into the origins of Wikipedia, discussing its transformation from a promising start to its current challenges with bias and neutrality. Sanger provides a deep dive into the philosophical and operational shifts that have affected the platform, scrutinizing how left-wing ideologies and conflict have influenced its direction. They also explore the potential role of AI and platforms like Grokipedia in shaping the future of knowledge management. Join us for an in-depth conversation about the importance of neutrality, the evolution of online encyclopedias, and what's next in the quest for unbiased information. https://larrysanger.org/nine-theses/ https://x.com/lsanger 00:00 Intro 01:13 Founding of #wikipedia 04:36 Wikipedia's Early Challenges 06:50 Shift in Wikipedia's Ideology 08:00 Bias in Encyclopedias 11:14 #LeftWing Influence in Academia 15:24 Nonprofit vs. For-Profit Wikipedia 20:34 Achieving Unbiased Content 32:16 AI and #grokipedia 34:41 Initial Impressions of Grokipedia 35:16 Comparing Grokipedia and Wikipedia 36:31 Challenges with LLMs in Grokipedia 42:09 Public Rating and Feedback for Wikipedia 44:50 Future Projects and Ideas 55:39 The Importance of Trustworthy Knowledge 01:03:52 Final Thoughts and Upcoming Plans
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