Podcasts about Causality

In this Huberman Lab Essentials episode, I explain the biology and psychology of obsessive-compulsive disorder (OCD) and describe the neural circuitry behind repetitive "thought-action loops," including why compulsive actions actually strengthen the underlying obsessions rather than relieve them. I discuss the most effective treatments for OCD, including exposure-based cognitive behavioral therapy and SSRIs, and explain what the research shows about how these compare when used alone versus together. Finally, I describe a specific clinical protocol in which patients are guided into states of anxiety while learning to suppress compulsive responses, retraining the brain to break the OCD cycle. Read the episode show notes at hubermanlab.com. Thank you to our sponsors AG1: https://drinkag1.com/huberman Eight Sleep: https://eightsleep.com/huberman Rorra: https://rorra.com/huberman Timestamps (00:00:00) Obsessive-Compulsive Disorder (OCD) (00:00:11) OCD Prevalence & Impact, Obsessions & Compulsions (00:01:54) Categories: Checking, Repetition & Order; Contamination & Disgust (00:04:30) Anxiety, Fear (00:05:20) Sponsor: AG1 (00:06:40) Genetic Component of OCD (00:08:45) Neural Circuitry, Cortex, Striatum, Thalamus (00:10:16) Cortico-Striatal-Thalamic Loop; Imaging Studies, SSRIs (00:14:30) Sponsor: Eight Sleep (00:16:00) Diagnosis, Yale-Brown Obsessive Compulsive Scale (Y-BOCS) (00:18:00) Y-BOCS Categories, Identifying the Core Fear (00:19:30) Tool: Cognitive Behavioral Therapy (CBT) & Exposure Therapy (00:21:39) Anxiety Tolerance, Interrupting the Compulsion (00:23:23) Dr. Helen Blair Simpson, Ritual Prevention, Exposure Sessions (00:25:18) CBT vs Placebo vs SSRIs (00:26:30) Sponsor: Rorra (00:28:07) SSRIs & Serotonin System; Psychiatry & Causality (00:29:13) Cannabis, CBD & OCD; Transcranial Magnetic Stimulation (TMS) (00:31:48) Mindfulness Meditation, Holistic Treatments, NIH (00:33:40) Nutraceuticals, Inositol; Recap & Conclusion Disclaimer & Disclosures Learn more about your ad choices. Visit megaphone.fm/adchoices

As America celebrates 250 years of independence, one question rises above all the celebrations: What were we set free to become? On this episode of Like It Matters Radio, Mr. Black reflects on the meaning of freedom, responsibility, and courage in a nation founded on the ideals of liberty. Freedom was never meant to be the absence of restraint—it was meant to be the opportunity to build strong families, raise responsible children, live with purpose, and honor God. This episode explores the growing challenges facing our nation: The decline of the family Rising loneliness, anxiety, and suicide Young adults delaying responsibility and purpose The growing disconnect from faith among younger generations Through the Law of Causality, Mr. Black reminds listeners that nothing happens by accident. Every effect has a cause, and every choice produces consequences. If we want a different future, we must be willing to examine the decisions and beliefs shaping our present. Joining the program are Joe Soltis and his son Jake, who share how they are investing in the next generation, encouraging young people to live boldly for Christ and helping reverse the trend of spiritual decline. The episode also looks at historical lessons, including the often-cited cycle of republics throughout history, and asks whether America has the courage to reclaim the values that made it strong. Because freedom without responsibility eventually becomes chaos. It takes courage to lead a family.It takes courage to keep your commitments.It takes courage to stand for truth.And it takes courage to use your freedom well. This is an Hour of Power about leadership, faith, family, and the responsibility that comes with liberty. Because the land of the free has always depended on the home of the brave. Inspiration. Education. Application. When you live your life like it matters… it does.See omnystudio.com/listener for privacy information.

Looking for transcripts? ⁠⁠⁠⁠⁠Click here!⁠⁠⁠⁠⁠⁠⁠Reserve a Room on the Patreon!⁠⁠⁠Follow us on Blue Sky! @hoteldayradioCredits and Attributions:Music used and edited under a CC-BY-4.0Choro das Terras Baixas, written & performed by Bert AlinkMusic used and edited under a CC-BY-3.0 De buen humor, written and performed by Bert Alink Canção triste, EL478 written and performed by Edson Lopes (edited)Music used from the Public Domain:Ponce - Preludio in E Major written by Sylvius Leopold Weiss, performed by Jeff CarterAll sounds were sourced from the Public Domain.

Rick London...who is a first time author makes his Unexplained Inc. debut...the book he is promoting can be purchased bought and learned about at this website below:https://dancingwolfeman.com/Rick comes on to share what he believes were some harrowing paranormal experiences as a young lad and how an unexpected road trip in his home of northern California led to the inspiration of this book...here are some other conversation points:- Was this road trip a form of retro causality?- Classic werewolf flicks and songs- The power of music- The wolf man & shadow work- Some paranormal and not-so-paranormal experiences growing up- King & LovecraftPlus so much more...Watch this episode on Rumble here:https://rumble.com/user/UnexplainedincConnect with Unexplained Inc. here:https://www.unexplainedinc.com

This episode is all about keeping it raw, spontaneous, and mind-bending. First, we're setting the record straight on the current "stink" in the community regarding AI art, breaking down the massive double standards between huge corporate entities and independent creators trying to visually map out the unexplainable. Don't worry, that's only in the introduction! Then, things get deeply esoteric. Isaac shares a chilling family history update involving missing time, an alien hybrid dream, and a tip toe on a theory on when the soul actually enters a vessel. We also dive face-first into a massive temporal paradox: can a dream about a future punk band create a retrocausal time loop across a century? Isaac's future vessel might literally be listening to this episode right now.To wrap it up, Megan starts naturally tapping into a subconscious trance on air, which creates conversation about a possible future episode. ⏱️ Chapters In This EpisodeIntroductionAddressing the “Stink” in the AirThe Reality of AI for Indie CreatorsThe First Trimester Soul TheoryMissing Time, The Greys & The Hybrid DreamRetrocausality & The Future Punk Rock VesselA Century of Musical LineageCalling All The Weirdos: Halloween SubmissionsTapping Into the Subconscious TranceNext Level: Testing Abilities with Intuitional QuestionsOutroMusic CreditsIntro and Outro Music: “Swamp Witch”Additional Intro Music: “Stacy Dahl” by MaudlinFollow Maudlin on TikTok and Instagram: @maudlinListen to Hidden in The Shadows Podcast on Spotify and YouTubeShare Your Paranormal ExperiencesSend us a message on social media, fill out our contact form, or email us:

What about Fate? Control over one's destiny? The illusion of control over one's destiny? Causality? And technology? Huh? Your 35+ year Tarot and interweb-experienced guide T from Burning Tarot is uniquely positioned to take you through these fascinating questions, plus, she is the kind of person who can't write the phrase "uniquely positioned" without snickering snarkily.The nature walk and blathery woo-woo chitchat here in Central Oregon forest will cover all this and more. Oh yes. Maybe even our good (eyeroll) friend AI, artificial intelligence, LLMs, etc.T from Burning Tarot - Tiffany Lee Brown - offers astrology and Tarot readings and whatnot, at tiffanyleebrown.com.

Good morning True Believers!This episode is posting in the AM on Saturday instead of its usual Friday evening slot due to some scheduling conflicts...but trust me when I say this one is worth the wait.Monk Yun Rou resides in Tucson, AZ and is a long time practitioner of taoism in all its forms. He teaches tai-chi and is an author of both fiction and non-fiction. Like most of us Yun is fascinated with the ongoing saga of extra-terrestrial contact and how it may influence human evolution more than we even think. Below is a link and an excerpt of his latest book...plus he tells a crazy story about how it came together...if you believe in retro-causality or used a computer in the early 1990's...you will be floored:The Revelation - A Novel of Interstellar Contact...you can buy the book here...https://www.amazon.com/Revelation-Novel-Interstellar-Contact-ebook/dp/B0GS77MBVJ/ref=sr_1_1?crid=C8BSH3U7ESXM&dib=eyJ2IjoiMSJ9.rzWXah9W7krzqkb4tkXCGbt2niDJ5I4XxxDd8gPu55rGjHj071QN20LucGBJIEps.gBNKOm6As1TyzP0ZXuU0LA5-AWogUrqH9wHRZ0YRkDE&dib_tag=se&keywords=yun+rou+the+revelation&qid=1781320663&sprefix=yun+rou+the+revelation%2Caps%2C117&sr=8-1Here is what it is about: Extraordinary children begin to appear - healing theincurable, evolving beyond known biology. At the same time, governments are forced to admit the truth they had long concealed: extraterrestrial visitors are real, and they have been present for millennia. By 1992 secrecy collapsed, and the world entered what later became known as the Revelation.Some other topics of discussion:- Yun's ongoing battle with illness and how he is persevering- How this illness actually killed him twice and his miraculous revivals.- He describes what he was shown during his multiple NDE's and it's not all pretty- Disclosure info being 'leaked' through entertainment- Phil's theory of an old X-Files episode possibly predicting what will be a 'smoking gun' in terms of disclosure that nobody would be able to turn away from.- How taoism can maybe enhance E.T. contactPlus so much more...You can explore Yun's full body of work here on his website:https://www.monkyunrou.com/Watch this episode on Rumble here:https://rumble.com/user/UnexplainedincConnect with Unexplained Inc. here:https://www.unexplainedinc.com

Send us Fan Mail*How do you forecast an event that has never happened before?*How do you forecast an event that has never happened before?The recent closure and reopening of the Strait of Hormuz are unique events. For events like these, traditional risk models lose their statistical basis: repetition. Alexander Denev returns to the podcast to show how causal models (Bayesian networks) let us reason about rare events despite this limitation.In this episode, we cover:- Why value-at-risk and other correlation-based models break exactly when you need them most- How a causal structure can "hold in time"- Building scenarios with LLMs - benefits, drawbacks, and lessons learned- Historical analogy as a modeling tool: Bosphorus, Hormuz, and more- A three-way robustness test for any Bayesian network- How the model's call held up: a ceasefire, a still-closed strait, and lasting infrastructure damage keeping oil elevated"History doesn't repeat itself, but it rhymes."------------------------------------------------------------------------------------------------------Video version available on the Youtube: https://youtu.be/FzKy2ws-7qsRecorded on May 29, 2026 in London, UK.------------------------------------------------------------------------------------------------------*About The Guest*Alexander Denev works at the intersection of quantitative finance, causality, and AI. He's the CEO of Turnleaf Analytics and the author of two books on applying Bayesian networks and probabilistic graphical models to finance and scenario analysis.Connect with Alexander:- Alexander on LinkedIn: https://www.linkedin.com/in/alexander-denev-66a25824/- Alexander's web page: https://turnleafanalytics.com/*About The Host*Aleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality (https://amzn.to/3QhsRz4 ).Connect with Alex:- Alex on the Internet: https://bit.ly/aleksander-molak*Links*Web- Alexander's LinkedIn post, Bayesian-network scenario for the Strait of Hormuz / Israel-Iran-US conflict: https://www.linkedin.com/posts/alexander-denev-66a25824_when-modelling-the-impact-of-events-that-share-7442892381668048896-JDs5/- Risk.net article, "Iran confusion makes the case for causal modelling": https://www.risk.net/our-take/7963361/iran-confusion-makes-the-case-for-causal-modellingBooks- Rebonato, R. & Denev, A. - Portfolio Management under Stress: A Bayesian-Net Approach to Coherent Asset Allocation (https://amzn.to/3vE6Jc1)- López de Prado, M. - Advances in Financial Machine Learning (https://amzn.to/3PXD8kH)- Molak, A. - Causal Inference and Discovery in Python (https://amzn.to/3VVK4m3)- Denev, A. - Probabilistic Graphical Models: A New Way of Thinking in Financial Modelling (https://amzn.to/3VQeLJm)- Pearl, J. & Mackenzie, D. - The Book of Why (recommended entry point) (https://amzn.to/4e0ATrZ)- Pearl, J. - Causality: Models, Reasoning and Inference (for advanced readers) (https://amzn.to/49zBKf5)- Rebonato, R. - Coherent Stress Testing: A Bayesian Approach to the Analysis of Financial Stress (https://amzn.to/3RC411e)*Perks & resources*

Discover how the future of TV advertising is shifting toward outcome-based measurement and AI-driven optimization coming out of the 2026 upfronts . iSpot CEO Sean Muller joins the show to break down their fundamental "Creative + Audience = Outcome" equation, the integration of their new AI platform Sage, and why the industry must prioritize trusted, neutral data over ongoing currency debates. Key Highlights

Are Millennials and Gen Z falling apart…or standing at the edge of a massive awakening? On this episode of Like It Matters Radio, Mr. Black tackles one of the biggest leadership and cultural questions of our time:Is the next generation a mess—or an opportunity? The statistics are staggering: Loneliness is skyrocketing Anxiety and depression are rising sharply Emotional intelligence is declining Purpose is collapsing Hope is eroding And the effects are showing up everywhere—from relationships and mental health to the workplace itself. Surveys reveal many business leaders see Gen Z as the most difficult generation to work with, citing struggles with communication, conflict resolution, motivation, and emotional resilience. But Mr. Black makes something very clear: This didn’t happen by accident. Through the lens of the Law of Causality and the Chain of Causation, this episode examines how culture, technology, isolation, and spiritual drift have shaped an entire generation. Drawing from Jonathan Cahn’s The Return of the Gods, Mr. Black connects major cultural and legal shifts to the broader battle over identity, values, and the soul of a nation. But this episode is not about condemnation.It’s about intervention. Joining the conversation is Garrett Bryant from Prayer at the Heart, sharing why many Gen Z young adults are turning back toward prayer, faith, and spiritual community in search of what social media, achievement, and endless comparison could never provide. Because underneath the anxiety is a deeper hunger: To belong To matter To find purpose To know truth Mr. Black closes with a direct challenge to leaders, parents, mentors, and believers: The time is NOW. We can still shape the next generation.We can still interrupt the cycle.We can still change eternal destinations. Because helpless and hopeless are not the final answer. This is an Hour of Power about leadership, culture, purpose, and the fight for the hearts and minds of the next generation. “If not you, then who?If not now, then when?” Inspiration. Education. Application.When you live your life like it matters… it does.See omnystudio.com/listener for privacy information.

Why are you where you are right now? Luck? Circumstances? Other people?Or something deeper? On this episode of Like It Matters Radio, Mr. Black breaks down one of the most misunderstood truths in life and leadership: causality. Every effect has a cause. Every cause becomes part of a chain. And your life today is the result of that chain—built one decision at a time. But here’s where it gets dangerous: Humans are wired to connect dots… even when they shouldn’t be connected. This episode tackles the concept of spurious correlations—when we assume something caused an outcome simply because it happened at the same time. Like blaming the wrong source, missing the real issue, and building beliefs on faulty conclusions. Because if your beliefs are built on false connections…your decisions will be too. Mr. Black walks through: The Law of Causality and the Chain of Causation Why choices → consequences → habits → character → destiny How false cause fallacies distort thinking and behavior Why examining your life is the starting point of real leadership This episode also zooms out to a broader cultural level—exploring patterns, pressures, and narratives that have shaped how people think, especially around identity, purpose, and responsibility. Because leadership starts internally. Not with position.Not with titles.But with the ability to examine your thinking, challenge your beliefs, and take ownership of the next decision. You are not defined by the chain that brought you here.But you are responsible for the next link. So the question becomes: What are you choosing next? This is an Hour of Power for anyone ready to think clearly, lead intentionally, and stop living on autopilot. Because when you change the cause…you change the outcome. Inspiration. Education. Application.When you live your life like it matters… it does.See omnystudio.com/listener for privacy information.

SPONSORS: - Go to https://expressvpn.com/theoriesofeverythingyt to find out how you can get up to 4 extra months thanks to our sponsor, ExpressVPN - Accelerate your efficiency. Sign up for your one-dollar-per-month trial today at http://shopify.com/theories - I subscribe to The Economist for their science and tech coverage. As a TOE listener, get 35% off! No other podcast has this: https://economist.com/TOE This conversation belongs in a category I wish were larger on this channel: the experimentalist who also thinks (deeply) about foundations. Professor Aephraim Steinberg, winner of Physics World's Breakthrough of the Year in 2011, is that species! For basically 30 years, he's been measuring aspects of physics that others wouldn't touch: Bohmian trajectories, Heisenberg's disturbance bound (he showed it was wrong), even where the photon is inside the double slit (which most textbooks will tell you is impossible). His lab measured negative time — and it keeps reappearing across completely different experiments, stubbornly suggesting it means something. FOLLOW: - Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e - Substack: https://curtjaimungal.substack.com/subscribe - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs - Crypto: https://commerce.coinbase.com/checkout/de803625-87d3-4300-ab6d-85d4258834a9 - PayPal: https://www.paypal.com/donate?hosted_button_id=XUBHNMFXUX5S4 TIMESTAMPS: - 00:00:00 - Defining Negative Time - 00:06:50 - Quantum Trajectory Theory - 00:12:44 - The Holland Tunnel Analogy - 00:18:40 - Resonant Atomic Interactions - 00:26:05 - Superluminal Energy Propagation - 00:32:00 - Eight Velocities of Light - 00:38:00 - Causality and Retrocausality - 00:44:00 - Dwell Time vs. Delay - 00:50:24 - Time: Operator or Parameter? - 00:58:21 - Bell's Theorem and Realism - 01:04:55 - Heisenberg's Measurement Disturbance - 01:11:26 - Weak Measurement Formalism - 01:17:37 - Time Symmetry and Entropy - 01:27:07 - Bohmian Trajectories Observed - 01:35:56 - Spin-Statistics and Indistinguishability - 01:42:14 - Quantum Computational Advantage - 01:48:15 - Many Worlds vs. Complexity - 01:54:51 - Psi-Ontic vs. Psi-Epistemic - 02:01:37 - Collapsing Tunneling Particles - 02:08:48 - Larmor vs. Atto Clocks - 02:15:24 - Locality and Information LINKS MENTIONED: - Aephraim's Website: https://www.physics.utoronto.ca/~aephraim/ - Aephraim's Papers: https://scholar.google.com/citations?user=PzUyb6IAAAAJ - Photon Negative Time in Atom Cloud [Paper]: https://arxiv.org/pdf/2409.03680 - How Much Time Does a Photon Spend as Atomic Excitation? [Paper]: https://arxiv.org/abs/2310.00432 - Measuring Time Atoms Spend in Excited State [Paper]: https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.3.010314 - Tunneling Atom Time in Barrier [Paper]: https://arxiv.org/abs/1907.13523 - Single-Photon Tunneling Time [Paper]: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.71.708 - Traversal Time for Tunneling [Paper]: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.49.1739 - Propagation of a Gaussian Light Pulse [Paper]: https://journals.aps.org/pra/abstract/10.1103/PhysRevA.1.305 - Linear Pulse Propagation in Absorbing Medium [Paper]: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.48.738 - Eighth Velocity of Light [Paper]: https://pubs.aip.org/aapt/ajp/article-abstract/45/6/538/1045817/Eighth-velocity-of-light - Attosecond Ionization [Paper]: https://www.science.org/doi/10.1126/science.1163439 - Tunneling Optical Pulses Photonic Band Gaps [Paper]: https://attoworld.de/fileadmin/user_upload/tx_attoworld/publications/paper_PhysRevLett_Y1994_M10_D24_V73_P2308.pdf - Evidence of Negative Time [Article]: https://www.scientificamerican.com/article/evidence-of-negative-time-found-in-quantum-physics-experiment/ - Light Speed Reduction [Article]: https://www.nature.com/articles/17561 - On the Theory of Light and Colors [Paper]: https://www.jstor.org/stable/pdf/107113.pdf - Wave Propagation and Group Velocity [Book]: https://amazon.com/dp/1483253937?tag=toe08-20 - EPR Paper [Paper]: https://journals.aps.org/pr/abstract/10.1103/PhysRev.47.777 - Uncertainty Principle: https://en.wikipedia.org/wiki/Uncertainty_principle - QBism [Paper]: https://arxiv.org/abs/1003.5209 More links at https://curtjaimungal.substack.com Guests do not pay to appear. #science Learn more about your ad choices. Visit megaphone.fm/adchoices

Hindsight ep. 822 E.B. Sommer's work has appeared in The Daily Tomorrow, Moonday Mag, and The Stygian Zine.  On April 17th, 2026 one of her stories will appear in the latest Harvey Duckman anthology, the Soup of Causality, available on Amazon. She is an Associate Member of SFWA and a full list of her published stories can be found on her website, at www.ebsommer.com. She lives in Minnesota with her family and their dogs, Sam and Sally.    ---- Listen Elsewhere ---- YouTube:  https://www.youtube.com/c/TallTaleTV Website: http://www.TallTaleTV.com   ---- Story Submission ---- Got a short story you'd like to submit? Submission guidelines can be found at http://www.TallTaleTV.com   ---- About Tall Tale TV ---- Hi there! My name is Chris Herron and I'm an audiobook narrator. In 2015, I suffered from poor Type 1 diabetes control which lead me to become legally blind for almost a year. The doctors didn't give me much hope, predicting an 80% chance that I would never see again. But I refused to give up and changed my lifestyle drastically. Through sheer willpower (and an amazing eye surgeon) I beat the odds and regained my vision. During that difficult time, I couldn't read or write, which was devastating as they had always been a source of comfort for me since childhood. However, my wife took me to the local library where she read out the titles of audiobooks to me. I selected some of my favorite books, such as the Disc World series, Name of the Wind, Harry Potter, and more, and the audiobooks brought these stories to life in a way I had never experienced before. They helped me through the darkest period of my life and I fell in love with audiobooks. Once I regained my vision, I decided to pursue a career as an audiobook narrator instead of a writer. That's why I created Tall Tale TV, to support aspiring authors in the writing communities that I had grown to love before my ordeal. My goal was to help them promote their work by providing a promotional audio short story that showcases their writing skills to readers. They say the strongest form of advertising is word of mouth, so I offer a platform for readers to share these videos and help spread the word about these talented writers. Please consider sharing these stories with your friends and family to support these amazing authors. Thank you!   ---- legal ---- All stories on Tall Tale TV have been submitted in accordance with the terms of service provided on http://www.talltaletv.com or obtained with permission by the author. All images used on Tall Tale TV are either original or Royalty and Attribution free. Most stock images used are provided by http://www.pixabay.com , https://www.canstockphoto.com/ or created using AI. Image attribution will be declared only when required by the copyright owner. Common Affiliates are: Amazon, Smashwords  

Rich people live longer than poor people in every country that researchers have studied. In the United States today, the gap in life expectancy between the richest and poorest 1% of individuals exceeds ten years. The relationship between money and health is steepest at the bottom of the income distribution, where additional resources buy the most: when people are poor, there is a great deal that money can do for their health. In this week's episode, Adriana Lleras-Muney of UCLA tells Tim Phillips that the evidence on the relationship between poverty and health is less certain than policymakers tend to assume. Causality runs in both directions: poor health is one of the fastest routes into poverty, and understanding how much of the association flows in each direction is still an active debate. Giving poor people more money does not reliably translate into better health within the timescales and amounts that most experiments can test, because the details matter: how long the transfer lasts, whether it is conditional, and what receiving it signals about a person's economic future all shape what they actually do with it.The most consistent finding from the policy evidence is that public health insurance and access to cheap, proven preventive interventions tend to deliver more reliable health gains than cash transfers — but whether either works in practice depends heavily on the implementation and the trust that governments can build with the populations they are trying to help.The research behind this episode:Lleras-Muney, Adriana, Hannes Schwandt, and Laura R. Wherry. 2025. "Poverty and Health." Annual Review of Economics 17.To cite this episode:Phillips, Tim and Adriana Lleras-Muney, 2026. "Poverty and Health." VoxDev Talk (podcast).Assign this as extra listening: the citation above is formatted and ready for a reading list or VLE.About Adriana Lleras-MuneyAdriana Lleras-Muney is Professor of Economics at the University of California, Los Angeles, where her research focuses on health economics and the relationship between socioeconomic conditions and health outcomes across the life course. The paper discussed in this episode is co-authored with Hannes Schwandt (Northwestern University) and Laura R. Wherry (NYU Wagner Graduate School of Public Service).More VoxDev Talks on this topicThe history of cash transfers: Tim Phillips speaks with Ugo Gentilini about his research tracing 2,500 years of giving people money, from Ancient Rome to the COVID pandemic, and what history reveals about the recurring debates over when and why cash transfers work.Improving access to and use of clean water: Tim Phillips speaks with Pascaline Dupas about why access to clean water remains one of the most cost-effective public health interventions available, and the barriers that prevent its wider adoption in low-income settings.Related reading on VoxDevCash transfers reduce adult and child mortality rates in low- and middle-income countries: evidence that unconditional cash transfers have measurable effects on mortality in poor settings, with implications for how we think about the relationship between income and health.Effective health aid: Evidence from Gavi's vaccine programme: what a large-scale vaccination programme reveals about the conditions under which targeted public health interventions can make a lasting difference in low-income countries.

”Entanglement, Causality, and the Cohesion of Space-Time” by Michael A. Amaral, from the “Science” issue of the Rosicrucian Digest. In this podcast, Michael A. Amaral proposes that quantum entanglement serves as a fundamental scaffold for space-time cohesion and causality, suggesting a symmetrical relationship between events that allows for the possibility of the future influencing the past. Running Time: 22:59 Podcast Copyright © 2026 Rosicrucian Order, AMORC. All Rights Reserved. https://1b42c19cdededc568f7a-da3de02c40b8b01b9925237888827896.ssl.cf5.rackcdn.com/Entanglement_Causality_and_the_Cohesion_of_Space-Time.mp3

Send us Fan MailCausality, Experimentation, and MarketplacesMeet Lawrence de Geest (Zoox, ex-Lyft, ex-NBA), a former soccer player and an ex-NBA data scientist, who fell in love with marketplaces, despite the fact he hated math.In the episode we ponder how to deal with causality when our interventions change the dynamics of the environment we intervene upon, what to do with SUTVA violations, and how to design efficient quasi-experiments.- Why simple A/B tests fail at marketplaces- How reversing synthetic controls logic can help us design better experiments- Why Lawrence thinks that average treatment effect is just a snapshot of here and now- How Magellan used data science to prove that Portugal was harvesting spices on Spanish territory------------------------------------------------------------------------------------------------------Video version available on YouTube: https://youtu.be/acCy16L33tURecorded in 2026 in San Francisco, USA.------------------------------------------------------------------------------------------------------About The GuestLawrence De Geest is an economist and data scientist at Zoox. He was previously a data scientist at Lyft and the NBA, and before joining industry, an Assistant Professor at Suffolk University, with visiting appointments at Boston College and the University of San Francisco. His main research interests are marketplaces, collective action and experimentation. Outside of work he loves biking, surfing, and playing with his dog.Connect with Lawrence:- Lawrence on LinkedIn: https://www.linkedin.com/in/lawrence-de-geest-21a206a/- Lawrence's web page: https://lrdegeest.github.io/About The HostAleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality (https://amzn.to/3QhsRz4 ).Connect with Alex:- Alex on the Internet: https://bit.ly/aleksander-molakSupport the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn:   https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io  The Causal Book: https://amzn.to/3QhsRz4

Support the show to get full episodes, full archive, and join the Discord community. The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists. Read more about our partnership. Check out this story: Neural manifolds: Latest buzzword or pathway to understand the brain? Sign up for Brain Inspired email alerts to be notified every time a new Brain Inspired episode is released. To explore more neuroscience news and perspectives, visit thetransmitter.org. Juan Gallego runs the Neocybernetics Lab at the Champalimaud Centre for the Unknown in Lisbon, Portugal, affiliated with the neuroscience of disease and neuroscience programs, and the centre for restorative neurotechnology. Juan has worked a lot on neural manifolds - the mathematical objects neuroscience is using more and more to describe how big populations of neurons coordinate their activity to do useful things. In fact, he recently gave a short talk that he titled The Manifold Manifesto, because he was asked to be provocative. And he was provocative, suggesting that manifolds are real - as real as chairs and tables are, that they have causal power, and they might be a target of evolution. Of course he talked about his own and others work to support those claims. So today we discuss many of those themes, through the lens of his own and others work, and we talk about what keeps him up at night about the possible limits of using manifolds to connect brain activity with behavior and mental phenomena. He's not just a manifold person, though. Juan is more broadly interested in motor control and how brains do it. We also discuss his work in patients with spinal cord injuries, who don't have enough nerve connections to their muscles to actually move, but have enough nerve connections that some signal gets through. Juan and his colleagues can detect that little bit getting through, and use it to infer what behaviors the patients intend to do, and they can use that information to control actions in a computer simulation. The hope is that this will translate to controlling prosthetics to give spinal cord injury patients their mobility again. Neocybernetics Lab. @juangallego.bsky.social Related papers A neural manifold view of the brain. A neural implementation model of feedback-based motor learning. Conjoint specification of action by neocortex and striatum. Integrating across behaviors and timescales to understand the neural control of movement. Evolutionarily conserved neural dynamics across mice, monkeys, and humans. Read the transcript. 0:00 - Intro 4:37 - Manifolds 14:30 - Strengths and weaknesses 24:32 - Conserved manifolds across animals and species 34:31 - Causality and manifolds 47:29 - Constraints and causes 51:05 - What to measure 58:55 - Complexity and manifolds 1:10:29 - Juan's background 1:14:08 - Prosthetics for spinal cord injuries 1:41:06 - Integrating across behaviors and timescales 1:46:56 - Conjoint specification of action by neocortex and striatum.

Professor John Donoghue explains why quantum physics and gravity actually work perfectly together. He tackles quadratic gravity, effective field theory, and random dynamics, arguing that grand unification and naturalness aren't required for a theory of everything. As a listener of TOE you can get a special 20% off discount to The Economist and all it has to offer! Visit https://www.economist.com/toe SUPPORT: - Support me on Substack: https://curtjaimungal.substack.com/subscribe - Support me on Crypto: https://commerce.coinbase.com/checkout/de803625-87d3-4300-ab6d-85d4258834a9 - Support me on PayPal: https://www.paypal.com/donate?hosted_button_id=XUBHNMFXUX5S4 JOIN MY SUBSTACK (Personal Writings): https://curtjaimungal.substack.com LISTEN ON SPOTIFY: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e TIMESTAMPS: - 00:00:00 - Limits of Quantum Mechanics - 00:06:35 - Effective Field Theory - 00:12:24 - Gravity: Geometry or Force? - 00:18:46 - QFT and Gravity Tension - 00:24:59 - Quadratic Gravity Theory - 00:34:16 - Dueling Arrows of Causality - 00:41:57 - Random Dynamics and Anti-Unification - 00:48:13 - The Naturalness Problem - 00:53:40 - Questioning Hidden Assumptions LINKS MENTIONED: - John's lectures: https://www.youtube.com/@johndonoghue469/featured - John's papers: https://arxiv.org/a/donoghue_j_1.html - The Renormalization Group and Critical Phenomena [Paper]: https://www.nobelprize.org/uploads/2018/06/wilson-lecture-2.pdf - Anthropic Considerations in Multiple-Domain Theories [Paper]: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.80.1822 - Old "Ghost" Theory of Quantum Gravity Makes a Comeback [Article]: https://www.quantamagazine.org/old-ghost-theory-of-quantum-gravity-makes-a-comeback-20251117/ - Unitarity, Stability and Loops of Unstable Ghosts [Paper]: https://arxiv.org/pdf/1908.02416 - An Effective Field Theory of Gravity for Extended Objects [Paper]: https://arxiv.org/abs/hep-th/0409156 - Not Quite a Black Hole [Paper]: https://arxiv.org/pdf/1612.04889 - On Quadratic Gravity [Paper]: https://arxiv.org/pdf/2112.01974 - Quadratic Gravity [Paper]: https://arxiv.org/pdf/1804.09944 - Renormalization of Higher Derivative Quantum Gravity [Paper]: http://www.weylmann.com/stelle.pdf - Quantum Theory in a Nutshell [Book]: https://www.amazon.com/Quantum-Field-Theory-Nutshell-nutshell/dp/0691140340 - Field Theory: A Modern Primer [Book]: https://www.amazon.com/Field-Theory-Modern-Frontiers-Physics/dp/0201546116 - Origin of Symmetries [Book]: https://amzn.to/4qxnLzj - String Theory Iceberg [TOE]: https://youtu.be/X4PdPnQuwjY - Neil Turok [TOE]: https://youtu.be/zNZCa1pVE20 - Avshalom Elitzur [TOE]: https://youtu.be/pWRAaimQT1E - Sir Roger Penrose [TOE]: https://youtu.be/iO03t21xhdk - Ted Jacobson [TOE]: https://youtu.be/3mhctWlXyV8 - Leonard Susskind [TOE]: https://youtu.be/2p_Hlm6aCok - Jonathan Oppenheim [TOE]: https://youtu.be/NKOd8imBa2s - Peter Woit [TOE]: https://youtu.be/TTSeqsCgxj8 - Joseph Conlon & Peter Woit [TOE]: https://youtu.be/fAaXk_WoQqQ - Michael Levin [TOE]: https://youtu.be/c8iFtaltX-s Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode, we'll compare Nietzsche's view of causality, habit, and free will to Hume. Although, in substance, they make very similar arguments, we'll explore important differences. Nietzsche arrives at his critique of causality through his attack on free will, and the subsequent understanding of metaphysical beliefs as necessitated by moral beliefs - whereas for Hume, the issue of liberty versus necessity is secondary to the critique of reason's ability to derive necessary connexions. For Hume, habit cannot be further explained, because this would be to ignore our practical affirmation of habit and the insufficiency of reason; Nietzsche wishes to investigate the genealogy of habit as part of his critique of morals. Perhaps most importantly, Hume places his philosophy in "subserviency" to the easy and obvious philosophy of commonsense, whereas Nietzsche sets his philosophy against common sense - and everything "common".

In this episode of Longevity by Design, host Dr. Gil Blander sits down with Dr. David Allison, Director of the USDA Children's Nutrition Research Center at Baylor College of Medicine. Together, they examine what it takes to build public trust in nutrition and longevity science, and why clear, reproducible evidence matters more than ever. David highlights how public perception and scientific rigor can drift apart, especially in fields crowded with strong opinions and shifting trends.David shares sharp insights on weight management, challenging the idea that slow and steady always wins. He explains the “dentistry model” of weight loss, where maintenance matters more than one-time fixes, and explores why most people regain weight without ongoing support. The discussion cuts through assumptions about exercise, protein, and processed foods, showing where animal research aligns, or fails to align, with human studies.Throughout, David pushes for honest communication and transparency in science. He urges listeners to question hype, look past nutrition fads, and recognize the real limits of current evidence. The episode offers practical wisdom for anyone who wants to approach health, nutrition, and longevity with both curiosity and caution. Guest-at-a-Glance

In a rare departure from our usual diet of online weirdos, this episode features an academic who is very much not a guru. We're joined by Julia Rohrer, a psychologist at Leipzig University whose work straddles the disciplinary boundaries of open science, research transparency, and causal inference. Julia is also an editor at Psychological Science and has spent much of the last decade politely pointing out that psychologists often don't quite know what they're estimating, why, or under which assumptions.We talk about the state of psychology after the replication crisis, whether open science reforms have genuinely improved research practice (or just added new boxes to tick), and why causal thinking is unavoidable even when researchers insist they are “only describing associations.” Julia explains why the standard dance of imply causality → deny causality → add boilerplate disclaimer is unhelpful, and argues instead for being explicit about the causal questions researchers actually care about and the assumptions required to answer them.Along the way we discuss images of scientists in the public and amongst the gurus, how post-treatment bias sneaks into even well-intentioned experimental designs, why specifying the estimand matters more than running ever-fancier models, and how psychology's current norms can potentially punish honesty about uncertainty. We also touch on her work on birth-order effects and offer some possible reasons for optimism.With all the guru talk, people sometimes ask us to recommend things that we like, and Julia's work is one such example!LinksJulia Rohrer's websiteThe 100% CI blogRohrer, J. M. (2024). Causal inference for psychologists who think that causal inference is not for them. Social and Personality Psychology Compass, 18(3), e12948.Rohrer, J. M., Tierney, W., Uhlmann, E. L., DeBruine, L. M., Heyman, T., Jones, B., ... & Yarkoni, T. (2021). Putting the self in self-correction: Findings from the loss-of-confidence project. Perspectives on Psychological Science, 16(6), 1255-1269.Rohrer, J. M., Egloff, B., & Schmukle, S. C. (2015). Examining the effects of birth order on personality. Proceedings of the National Academy of Sciences, 112(46), 14224-14229.BEMC MAY 2024 - Julia Rohrer - "Causal confusions correlate with casual conclusions"Dr. Tobias Dienlin - Less casual causal inference for experiments and longitudinal data: Research talk by Julia Rohrer

Send us a textDo Heterogeneous Treatment Effects Exist?For the last 50 years, we've designed cars to be safe...For the 50th-percentile male.Well, that's actually not 100% correct.According to Stanford's report, we introduced "female" crash test dummies in the 1960s, but...They were just scaled-down versions of male dummies and...Represented the 5th percentile of females in terms of body size and mass (aka the smallest 5% of women in the general population).These dummies also did not take into account female-typical injury tolerance, biomechanics, spinal alignment, and more.But...Does it matter for actual safety?In the episode, we cover:- Do heterogeneous treatment effects (different effects in different contexts) exist?- If so, can we actually detect them?- Is it more ethical to look for heterogeneous treatment effects or rather look at global averages?Video version available on the Youtube: https://youtu.be/V801RQTBpp4Recorded on Nov 12, 2025 in Malaga, Spain.------------------------------------------------------------------------------------------------------About RichardProfessor Richard Hahn, PhD, is a professor of statistics at Arizona State University (ASU). He develops novel statistical methods for analyzing data arising from the social sciences, including psychology, economics, education, and business. His current focus revolves around causal inference using regression tree models, as well as foundational issues in Bayesian statistics.Connect with Richard:- Richard on LinkedIn: https://www.linkedin.com/in/richard-hahn-a1096050/About StephenStephen Senn, PhD, is a statistician and consultant who specializes in drug development clinical trials. He is a former Group Head at Ciba-Geigy and has taught at the University of Glasgow and University College London (UCL). He is the author of "Statistical Issues in Drug Development," "Crossover Trials in Clinical Research," and "Dicing with Death."Connect with Stephen:- Stephen on LinkedIn: Support the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

In this episode of our series about Metaphysics and modern AI, we break causality down to first principles and explain how to tell factual mechanisms from convincing correlations. From gold-standard Randomized Control Trials (RCT) to natural experiments and counterfactuals, we map the tools that build trustworthy models and safer AI.Defining causes, effects, and common causal structuresGestalt theory: Why correlation misleads and how pattern-seeking tricks usStatistical association vs causal explanationRCTs and why randomization mattersNatural experiments as ethical, scalable alternativesJudea Pearl's do-calculus, counterfactuals, and first-principles modelsLimits of causality, sample size, and inferenceBuilding resilient AI with causal grounding and governanceThis is the fourth episode in our metaphysics series. Each topic in the series is leading to the fundamental question, "Should AI try to think?"Check out previous episodes:Series IntroWhat is reality?What is space and time?If conversations like this sharpen your curiosity and help you think more clearly about complex systems, then step away from your keyboard and enjoy this journey with us.What did you think? Let us know.Do you have a question or a discussion topic for the AI Fundamentalists? Connect with them to comment on your favorite topics: LinkedIn - Episode summaries, shares of cited articles, and more. YouTube - Was it something that we said? Good. Share your favorite quotes. Visit our page - see past episodes and submit your feedback! It continues to inspire future episodes.

Mike Oaten is the Founder and CEO of TIKOS, working on building AI assurance, explainability, and trustworthy AI infrastructure, helping organizations test, monitor, and govern AI models and systems to make them transparent, fair, robust, and compliant with emerging regulations.Cracking the Black Box: Real-Time Neuron Monitoring & Causality Traces // MLOps Podcast #358 with Mike Oaten, Founder and CEO of TIKOSJoin the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractAs AI models move into high-stakes environments like Defence and Financial Services, standard input/output testing, evals, and monitoring are becoming dangerously insufficient. To achieve true compliance, MLOps teams need to access and analyse the internal reasoning of their models to achieve compliance with the EU AI Act, NIST AI RMF, and other requirements.In this session, Mike introduces the company's patent-pending AI assurance technology that moves beyond statistical proxies. He will break down the architecture of the Synapses Logger, a patent-pending technology that embeds directly into the neural activation flow to capture weights, activations, and activation paths in real-time.// BioMike Oaten serves as the CEO of TIKOS, leading the company's mission to progress trustworthy AI through unique, high-performance AI model assurance technology. A seasoned technical and data entrepreneur, Mike brings experience from successfully co-founding and exiting two previous data science startups: Riskopy Inc. (acquired by Nasdaq-listed Coupa Software in 2017) and Regulation Technologies Limited (acquired by mnAi Data Solutions in 2022).Mike's expertise spans data, analytics, and ML product and governance leadership. At TIKOS, Mike leads a VC-backed team developing technology to test and monitor deep-learning models in high-stakes environments, such as defence and financial services, so they comply with the stringent new laws and regulations.// Related LinksWebsite: https://tikos.tech/LLM guardrails: https://medium.com/tikos-tech/your-llm-output-is-confidently-wrong-heres-how-to-fix-it-08194fdf92b9Model Bias: https://medium.com/tikos-tech/from-hints-to-hard-evidence-finally-how-to-find-and-fix-model-bias-in-dnns-2553b072fd83Model Robustness: https://medium.com/tikos-tech/tikos-spots-neural-network-weaknesses-before-they-fail-the-iris-dataset-b079265c04daGPU Optimisation: https://medium.com/tikos-tech/400x-performance-a-lightweight-open-source-python-cuda-utility-to-break-vram-barriers-d545e5b6492fHyperbolic GPU Cloud: app.hyperbolic.ai.Coding Agents Conference: https://luma.com/codingagents~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Mike on LinkedIn: /mike-oaten/Timestamps:[00:00] Regulations as Opportunity[00:25] Regulation Compliance Fun[02:49] AI Act Layers Explained[05:19] Observability in Systems vs ML[09:05] Risk Transfer in AI[11:26] LLMs and Model Approval[14:53] LLMs in Finance[17:17] Hyperbolic GPU Cloud Ad[18:16] Stakeholder Alignment and Tech[22:20] AI in Regulated Environments[28:55] Autonomous Boat Regulations[34:20] Data Compliance Mapping[39:11] Data Capture Strategy[41:13] EU AI Act Insights[44:52] Wrap up[45:45] Join the Coding Agents Conference!

On this Sunday Morning Live on the 11th of January 2026, Stefan Molyneux examines the causes of societal violence and personal decisions, drawing from the shooting of Renee Goode. He considers the effects of wars like World War I and II, looking at how outside forces influence choices and the gap between individual accountability and what society demands. He talks about factors that push people to favor strong beliefs over family obligations and reviews how broader problems sustain patterns of violence. He seeks to prompt people to think about their own stories and how linked decisions can help build a society.The livestream continues on just for donors! Subscribers can continue the livestream here:Premium Content Hub: https://premium.freedomain.com/4b6c61b3/the-myth-of-the-karenX: https://x.com/StefanMolyneux/status/2010515764109853049Locals: https://freedomain.locals.com/post/7593928/the-myth-of-the-karenSubscribestar: https://www.subscribestar.com/posts/2285046Freedomain Members: https://freedomain.com/the-myth-of-the-karen/Not yet a subscriber?You can subscribe on:X: https://x.com/StefanMolyneuxLocals: https://freedomain.locals.com/support/promo/UPB2025Subscribestar: https://subscribestar.com/freedomainFreedomain: https://fdrurl.com/membersSubscribers get 12 HOURS on the "Truth About the French Revolution," multiple interactive multi-lingual philosophy AIs trained on thousands of hours of my material - as well as AIs for Real-Time Relationships, Bitcoin, Peaceful Parenting, and Call-In Shows!You also receive private livestreams, HUNDREDS of exclusive premium shows, early release podcasts, the 22 Part History of Philosophers series and much more!See you soon!

Send us a text*What can we learn about causal inference from the “war” between Bayesians and frequentists?*What can we learn about causal inference from the “war” between Bayesians and frequentists?In the episode, we cover:- What can we learn from the “war” between Bayesians and frequentists?- Why do Bayesian Additive Regression Trees (BART) “just work”?- Do heterogeneous treatment effects exist?- Is RCT generalization a heterogeneity problem?In the episode, we accidentally coined a new term: “feature-level selection bias.”------------------------------------------------------------------------------------------------------Video version available on the Youtube: https://youtu.be/-hRS8eU3TowRecorded in Arizona, US.------------------------------------------------------------------------------------------------------*About The Guest*Professor Richard Hahn, PhD, is a professor of statistics at Arizona State University (ASU). He develops novel statistical methods for analyzing data arising from the social sciences, including psychology, economics, education, and business. His current focus revolves around causal inference using regression tree models, as well as foundational issues in Bayesian statistics.Connect with Richard:- Richard on LinkedIn: https://www.linkedin.com/in/richard-hahn-a1096050/- Richard's web page: https://methodologymatters.substack.com/about*About The Host*Aleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality (https://amzn.to/3QhsRz4 ).Connect with Alex:- Alex on the Internet: https://bit.ly/aleksander-molak*Links*Repo- https://stochtree.aiPapers- Hahn et al (2020) - "Bayesian Regression Tree Models for Causal Inference" (https://projecteuclid.org/journals/bayesian-analysis/volume-15/issue-3/Bayesian-Regression-Tree-Models-for-Causal-Inference--Regularization-Confounding/10.1214/19-BA1195.full)- Yeager, ..., Dweck et al (2019) - "A national experiment reveals where a growth mindset improves achievement" (https://www.nature.com/articles/s41586-019-1466-y)- Herren, Hahn, et al (20Support the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

Kinsella on Liberty Podcast: Episode 478. Related: The Universal Principles of Liberty Announcing the Universal Principles of Liberty Fusillo on the Universal Principles of Liberty and Liberland KOL473 | The Universal Principles of Liberty, with Mark Maresca of The White Pillbox Selling Does Not Imply Ownership, and Vice-Versa: A Dissection, in Legal Foundations of a Free Society A Libertarian Theory of Contract: Title Transfer, Binding Promises, and Inalienability and Inalienability and Punishment: A Reply to George Smith, in Legal Foundations of a Free Society Disentangling Legal and Economic Concepts Dualism, Monism, Scientism, Causality, Teleology: Hoppe, Mises, Rothbard Libertarian Answer Man: Mind-Body Dualism, Self-Ownership, and Property Rights God as Slaveowner; Conversations with Murphy Mises on God KOL293 | Faith and Free Will, with Steve Mendelsohn  This is my appearance on Adam Haman's podcast and Youtube channel, Haman Nature (Haman Nature substack), Kinsella's Legal Treatise On Universal Principles Of Liberty | Hn 185 (recorded Nov. 9,  2025; released Dec. 9, 2025). https://youtu.be/tc-hdB_yiS4?si=icPwq5mSS6nDU8LP Adam's show notes: On this episode of Haman Nature, libertarian poker pro Adam Haman is joined once again by libertarian legal theorist (and patent attorney who despises IP) Stephan Kinsella about his new creation: The Universal Principles of Liberty. (apologies, folks - my mic was a bit wonky on this one) 00:00 -- Intro. Welcoming author, attorney, world-traveler, and all-around great guy Stephan Kinsella! 02:54 -- What are "The Universal Principles of Liberty", and why should we be excited by it? 11:40 -- What is a "person"? What is "property"? Why are these things so important to think about clearly? 34:24 -- This simple and elegant document can handle deep and complex issues. 47:54 -- When (and why) does selling not imply ownership, and vice-versa? What does "dualism" have to do with this? What's the confusion between economics and law when dealing with this stuff? 56:53 -- Outro. Go comment on TUPoL! (linked below) Thanks for watching Haman Nature!  Shownotes, links, grok summary, and transcript below. Shownotes (Grok) Haman Nature Podcast – Show Notes Guest: Stephan Kinsella Host: Adam Haman Episode Topic: The Universal Principles of Liberty – A New Foundation for Free Societies   0:00 – Opening Banter & Liberland Passport Shenanigans Stephan shows up in casual clothes after taking a suit-and-tie selfie… for his upcoming Liberland passport photo   Only a libertarian would put on half a suit to pretend to be a government just to get a passport   Stephan is heading to Prague in December 2025 for the signing and announcement of the Liberland Constitution 1:04 – Who is Stephan Kinsella? Patent attorney turned leading anarchist legal theorist   Author of Against Intellectual Property and Legal Foundations of a Free Society   Recent Vegas trip with Adam: helicopter into the Grand Canyon, Venetian St. Mark's Square (tacky but awesome) 2:59 – Introducing “The Universal Principles of Liberty” (TUPoL) A one-page, elegant, civil-law-style statement of libertarian metanorms   Not a constitution, not a detailed legal code – a foundational layer that private legal systems can build upon   Voluntary opt-in document: you must explicitly sign on to be bound   Purpose: foster conflict-free interaction through reason, experience, and ethics – no state decree, no majority vote 5:09 – Origin Story: From Liberland → Bir Tawil → Universal Principles Stephan helped draft Liberland's early (still statist) constitution but was uneasy as an anarchist   Long history of libertarian startup-country projects (Seasteading, Atlantis, Prospera, etc.)   Max (FreeMax) approached Stephan about Bir Tawil (unclaimed land between Egypt & Sudan) and wanted principles instead of a state   Co-drafters: Hans-Hermann Hoppe, Alessandro Fusillo, David Dürr, Pat Tinsley 9:16 – Why This Document Now? Refinement of 30+ years of libertarian legal theory (Rothbard, Hoppe, Kinsella)   Earlier concise restatement now in the Libertarian Party platform (plank 2.1/2.2)   Goal: a short, uncontroversial, legally precise statement that any free society can point to 11:40 – Key Features & Definitions “Person” = any sentient being capable of moral agency (includes possible AGI/aliens, excludes animals)   Rights are exclusively property rights in scarce physical resources (no “right to life,” no IP)   Self-ownership is primary and inalienable (the Walter Block voluntary-slavery debate settled against alienability)   Body rights can only be forfeited by committing aggression (proportional punishment/restoration justified) 20:01 – Freedom is a Consequence, Not a Primary Right No need for enumerated positive rights (speech, religion, warm baths)   All legitimate freedoms flow from property rights in body and external resources 23:25 – Why Self-Ownership is Inalienable (and Walter Block is wrong) Body ownership arises from direct embodiment/control, not homesteading   You can abandon or sell homesteaded external resources; you cannot abandon “you”   Contracts are title transfers, not enforceable promises 29:12 – Punishment, Outlaws, and Estoppel Aggressors implicitly consent to proportional defensive/enforcement force   No need for prior signed contract with an outlaw – committing aggression waives the right to complain 34:26 – Weapons of Mass Destruction Clause (Article 8) Indiscriminate devices that cannot be aimed solely at aggressors are legitimately restrictable   Practical insurance/neighborhood covenants would handle most cases anyway 37:39 – Evidentiary Standards Borrowed from Tradition Severe remedies require heightened standards (e.g., beyond reasonable doubt, jury nullification rights)   Roman & common law are largely libertarian and will serve as starting points 40:41 – Select Unjust Laws & Aspirational Closing Explicitly lists taxation, IP, conscription, etc. as unjust   Beautiful final paragraph: “We bow to no state… no power on earth will stop us” (mostly written by Max) 42:47 – Why Law Must Develop Organically (Quote from Stephan's blog) Detailed armchair legal codes are premature and counterproductive   Law evolves case-by-case through real disputes, custom, and decentralized courts 47:58 – Deep Dive: “Selling Does Not Imply Ownership” & Misesian Dualism Crucial distinction between possession/control (causal/economic) and legal ownership (normative)   Robinson Crusoe has possession but no ownership   Labor/services are not ownable – employment contracts are conditional title transfers of money, not sales of “labor”   Confusing the two realms leads to the fallacious justification for intellectual property 1:06:20 – Free Will, Compatibilism, and Scientism In the causal realm there is no free will (no downward causation)   In the teleological realm of human action we unavoidably treat people as purposeful choosers   Stephan's “Misesian compatibilism” – both views are correct in their respective domains 1:16:53 – Closing & Future Plans Stephan will push to have TUPoL incorporated into the final Liberland Constitution (to the extent compatible)   Next big project: new comprehensive book on IP/copyright titled Copy This Book   Where to find everything: stephankinsella.com | Universal Principles of Liberty poster & text freely available Links   The Universal Principles of Liberty full text & poster: https://www.stephankinsella.com/principles/   Stephan's blog announcement: https://stephankinsella.com/2025/08/announcing-the-universal-principles-of-liberty/   Adam's original Substack post: https://hamannature.substack.com/p/kinsellas-legal-treatise-on-universal Enjoy the episode and go read (and sign!) the Universal Principles of Liberty! Transcript (Youtube/Grok): Haman Nature Interview: Stephan Kinsella on The Universal Principles of Liberty (Corrected transcript – spelling, punctuation, minor grammar, no paraphrasing. Long speaking blocks broken into ≤10-sentence paragraphs. Topical headers with timestamps added.) Opening Banter & Liberland Passport Story [0:00] Adam Haman: Intro. Welcoming author, attorney, world-traveler, and all-around great guy Stephan Kinsella! [0:00] Stephan Kinsella: You forgot your cue. I told you to ask me about my adventure this morning and putting on a suit and tie. [0:06] Adam: I thought that was off because you, sir, are not wearing a suit and tie anymore. [0:11] Stephan: I know. So it wasn't for you. You know how people—well, I don't want to mess my shirt up. I can reuse it now. You know how it's probably common knowledge now that ever since the Zoom era, a lot of people were telecommuting and so they would put on a shirt and tie but they were wearing shorts underneath, right? [0:37] Stephan: So I did something this morning and I was thinking only a libertarian would do this. I put on a suit and tie to take a photo of myself because I need a passport photo. But I don't need a regular passport photo. I need a photo that I can use for my Liberland passport because I'm going to Prague in December for the signing and announcement of the Liberland Constitution. Formal Introduction [1:04] Adam: Hello and welcome to Haman Nature. I am Adam Haman and that fine fellow fiddling with his pipe on a Houston morning is one Stephan Kinsella. How you doing, sir? [1:15] Stephan: I'm in fine fettle. You're fine fettle and a fine fellow. [1:22] Adam: For those of you who just woke up underneath a rock, Stephan Kinsella is a legal theorist, one of our best, and also the author of this highly influential book here,

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What is the true structure of reality? In his fourth appearance on Mind-Body Solution, cognitive scientist Donald Hoffman returns with the most significant update yet to Conscious Realism: trace logic, decorated permutations, the emergence of spacetime from networks of conscious agents, and the strongest mathematical progress so far toward deriving Minkowski space from consciousness itself. Across nearly three hours, we explore what has changed in Hoffman's thinking since our last dialogue two years ago: breakthroughs in the trace-order formalism, new clarifications on evolution and perception, deeper implications for identity and suffering, and the surprising philosophical consequences of consciousness being fundamental. This is Hoffman at his most refined - technically rigorous, personally honest, and metaphysically bold.TIMESTAMPS:(00:00) — Intro(03:12) — What has changed in Hoffman's thinking in the last two years? (07:45) — Why Spacetime Is Doomed: The 2026 Case(12:58) — Conscious Agents: What's Changed in the New Theory(18:30) — Traces of Consciousness (2026): Don's Biggest Breakthrough Yet(25:44) — Restricted Channels of Consciousness (RCCs)(32:02) — The Mathematics of Trace Order & Trace Logic(38:55) — Is Reality Built from Relations, Not Things?(45:40) — What the Spacetime Headset Really Is(52:18) — Scattering Amplitudes & the Illusion of Objects(59:50) — Why Evolution Hides the Truth (Updated Evidence)(1:07:14) — Perception as a User Interface, Not a Window on Reality(1:14:32) — Are Particles Just Icons? The Physics Implications(1:22:10) — Causality, Emergence, Time & the √n Structure of Trace Chains(1:29:48) — Can We Test Conscious Realism in the Lab?(1:37:05) — AI, Conscious Agents & Synthetic Phenomena(1:45:22) — Conscious Realism vs Idealism, Physicalism & Competing Frameworks(1:53:44) — The Meaning Question: Why Is There Something It's Like?(2:02:58) — What This Theory Says About Death & Identity(2:10:00) – Identity, the Avatar, Death, Suffering & the “Infinite Self” (2:30:00) – Meditation & Waking Up from the Headset (2:40:00) – The New Paper Timeline & Call for Collaborators (2:48:00) – Closing reflectionsEPISODE LINKS:- Donald's Website: https://www.cogsci.uci.edu/~ddhoff/- Donald's Books: https://tinyurl.com/5x7bmzbd- Donald's Publications: https://tinyurl.com/bp7btw9a- Donald's Round 1: https://youtu.be/M5Hz1giUUT8- Donald's Round 2: https://youtu.be/Toq9YLl49KM- Donald's Round 3: https://youtu.be/QRa8r5xOaAA- Donald's Lecture 1: https://youtu.be/r_UFm8GbSvU- Donald's Lecture 2: https://youtu.be/YBmzqNIlbcICONNECT:- Website: https://mindbodysolution.org - YouTube: https://youtube.com/@MindBodySolution- Podcast: https://creators.spotify.com/pod/show/mindbodysolution- Twitter: https://twitter.com/drtevinnaidu- Facebook: https://facebook.com/drtevinnaidu - Instagram: https://instagram.com/drtevinnaidu- LinkedIn: https://linkedin.com/in/drtevinnaidu- Website: https://tevinnaidu.com=============================Disclaimer: The information provided on this channel is for educational purposes only. The content is shared in the spirit of open discourse and does not constitute, nor does it substitute, professional or medical advice. We do not accept any liability for any loss or damage incurred from you acting or not acting as a result of listening/watching any of our contents. You acknowledge that you use the information provided at your own risk. Listeners/viewers are advised to conduct their own research and consult with their own experts in the respective fields.

In this episode, we dig deep into the evolving landscape of industrial AI, from billion-dollar cloud partnerships in Europe to the fierce debate over digital sovereignty. We break down what sets 'sovereign by contract' apart from 'sovereign by origin,' and why this matters for companies navigating global AI strategies. We're joined by Professor Stratis Gavves from the University of Amsterdam to unpack the world of robotics models and the critical role of physics-informed AI. Alongside the latest industry news—like SAP's move into open-source models and the rise of edge AI—we explore what it takes to stay competitive in a rapidly shifting market. Join us as we question, challenge, and celebrate the innovations set to define the next era of industrial intelligence.

And then” isn't a plot, it's a queue. In this craft-forward episode, we swap “and then” for the more muscular because / but / therefore and show how tight causality turns scenes into story. You'll get a clear, jargon-free framework for chaining choices to consequences, plus two case studies that prove the point: a mini-autopsy of Pride & Prejudice and a contemporary comparison with Knives Out.In this episode you'll learn:Why causality (not act labels) is the real backbone of structureHow to convert event beats into decision beats with costsThe Because/But/Therefore test to expose sagging “and then” sequencesA quick Coincidence Audit (allowed to enter a story, never to exit it)A repeatable Scene Ledger: Goal → Opposition → Outcome → New Problem → Forced Next Action

Send us a textThe Causal Gap: Truly Responsible AI Needs to Understand the ConsequencesWhy do LLMs systematically drive themselves to extinction, and what does it have to do with evolution, moral reasoning, and causality?In this brand-new episode of Causal Bandits, we meet Zhijing Jin (Max Planck Institute for Intelligent Systems, University of Toronto) to answer these questions and look into the future of automated causal reasoning.In this episode, we discuss:- Zhijing's new work on the "causal scientist"- What's missing in responsible AI- Why ethics matter for agentic systems- Is causality a necessary element of moral reasoning?------------------------------------------------------------------------------------------------------Video version available on Youtube: https://youtu.be/Frb6eTW2ywkRecorded on Aug 18, 2025 in Tübingen, Germany.------------------------------------------------------------------------------------------------------About The GuestZhiijing Jin is a researcher scientist at Max Planck Institute for Intelligent Systems and an incoming Assistant Professor at the University of Toronto. Her work is focused on causality, natural language, and ethics, in particular in the context of large language models and multi-agent systems. Her work received multiple awards, including NeurIPS best paper award, and has been featured in CHIP Magazine, WIRED, and MIT News. She grew up in Shanghai. Currently she prepares to open her new research lab at the University of Toronto.Support the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

We're living through one of the most dangerous eras in history — not because of war or politics alone, but because of the extraordinary convergence of economic, financial, and geopolitical risks. In this episode, we break down: How record global debt, AI-driven speculation, and geopolitical instability are colliding. Why the current market optimism masks systemic fragility. What investors can learn from past cycles — from 1929 to 2008 — to prepare for the next regime shift. The role of central banks, fiscal excess, and policy distortions that have created a fragile illusion of stability. 0:18 - EOM Approaches, Rare Earth, & the China Deal 4:28 - Markets Set New Highs 8:57 - Lance's Grandkid Solution 10:28 - The Dumbest Stock Market in History 12:53 - Why Are Markets trading at 200% Above GDP? 16:26 - Unforeseen Consequences of Passive Investing 21:54 - More ETF's than Mutual Funds 26:47 - Passive Indexing Underwrites the Markets 31:13 - The Causality of Liquidity 34:21 - Bubbles Don't Form, the Evolve 37:25 - Be Aware of the Risks You're Taking 45:14 - Cash Levels and Margin Debt

We're living through one of the most dangerous eras in history — not because of war or politics alone, but because of the extraordinary convergence of economic, financial, and geopolitical risks. In this episode, we break down: How record global debt, AI-driven speculation, and geopolitical instability are colliding. Why the current market optimism masks systemic fragility. What investors can learn from past cycles — from 1929 to 2008 — to prepare for the next regime shift. The role of central banks, fiscal excess, and policy distortions that have created a fragile illusion of stability. 0:18 - EOM Approaches, Rare Earth, & the China Deal 4:28 - Markets Set New Highs 8:57 - Lance's Grandkid Solution 10:28 - The Dumbest Stock Market in History 12:53 - Why Are Markets trading at 200% Above GDP? 16:26 - Unforeseen Consequences of Passive Investing 21:54 - More ETF's than Mutual Funds 26:47 - Passive Indexing Underwrites the Markets 31:13 - The Causality of Liquidity 34:21 - Bubbles Don't Form, the Evolve 37:25 - Be Aware of the Risks You're Taking 45:14 - Cash Levels and Margin Debt

Dr. Emily Adlam is a philosopher of quantum physics who has just finished a book about the strangest feature of fundamental physics - the perennial confusion over what it means to make a measurement. We all know that quantum physics tells us that there's this strange thing, called wavefunction collapse, which transitions a system from being in a quantum state into being in a classical state. But what does it mean to make a measurement? And what does it mean to turn a system from a quantum one into a classical one? It turns out that no one really knows, and we spend this conversation trying to figure out how that could be possible, after more than a century of theorizing about the foundations of reality. PATREON https://www.patreon.com/c/demystifysciPARADIGM DRIFThttps://demystifysci.com/paradigm-drift-showHOMEBREW MUSIC - Check out our new album!Hard Copies (Vinyl): FREE SHIPPING https://demystifysci-shop.fourthwall.com/products/vinyl-lp-secretary-of-nature-everything-is-so-good-hereStreaming:https://secretaryofnature.bandcamp.com/album/everything-is-so-good-here00:00 Go! 00:04:30 Understanding the Measurement Problem 00:08:00 The Nature of Quantum Formalisms 00:11:30 Critiques of Many-Worlds Interpretation 00:17:00 The Many-Worlds Perspective and Its Popularity 00:20:41 Discussion on the Many Worlds Interpretation of Quantum Mechanics 00:21:39 Criticism of the Many Worlds Interpretation 00:23:41 Observer Dependent Interpretations in Quantum Mechanics 00:28:14 Implications of Quantum Interpretations 00:31:45 Primitive Ontology Interpretations 00:36:07 Challenges of Quantum Field Theory 00:41:27 Discussion on Quantum Measurement 00:44:12 Transactional Interpretation of Quantum Mechanics 00:48:58 Observational Limits in Quantum Physics 00:56:09 Challenges of Understanding Quantum Reality 01:02:20 Philosophical Implications of Quantum Mechanics 01:03:16 Discussion on Causality and Probability 01:09:05 Probabilistic Features of Nature 01:12:54 Mathematical vs. Visual Intuition in Quantum Mechanics 01:17:49 Relationship Between Quantum Phenomena and Macroscopic Effects 01:19:20 Proposed Revision to Quantum Epistemology 01:25:03 Exploration of Quantum Concepts 01:27:34 The Nature of Reality in Quantum Mechanics 01:30:12 Experimental vs. Theoretical Physics 01:34:22 Challenges in Testing Quantum Mechanics 01:36:19 Evolution of Epistemology in Quantum Physics 01:40:42 Implications for Broader Inquiry 01:44:37 Fundamental Questions on Mass and Gravity 01:47:03 The Interface of Relativity and Quantum Mechanics 01:48:27 Emergence and Relational Descriptions in Physics 01:49:55 Theoretical Physics Versus Experimental Collaboration 01:50:52 Resilience in Quantum Physics Understanding#quantumphysics, #philosophy, #metaphysics, #quantummechanics, #causality, #epistemology, #relativity, #cosmos, #consciousness, #paradigmshift , #rationality, #intellectual #philosophypodcast , #longformpodcastMERCH: Rock some DemystifySci gear : https://demystifysci-shop.fourthwall.com/AMAZON: Do your shopping through this link: https://amzn.to/3YyoT98DONATE: https://bit.ly/3wkPqaDSUBSTACK: https://substack.com/@UCqV4_7i9h1_V7hY48eZZSLw@demystifysci RSS: https://anchor.fm/s/2be66934/podcast/rssMAILING LIST: https://bit.ly/3v3kz2S SOCIAL: - Discord: https://discord.gg/MJzKT8CQub- Facebook: https://www.facebook.com/groups/DemystifySci- Instagram: https://www.instagram.com/DemystifySci/- Twitter: https://twitter.com/DemystifySciMUSIC: -Shilo Delay: https://g.co/kgs/oty671

$37 billion. That's how much gets wasted annually on marketing budgets because of poor attribution and misunderstanding of what actually drives results. Companies' credit campaigns that didn't work. They kill initiatives that were actually succeeding. They double down on coincidences while ignoring what's actually driving outcomes.   Three executives lost their jobs this month for making the same mistake. They presented data showing success after their initiatives were launched. Boards approved promotions. Then someone asked the one question nobody thought to ask: "Could something else explain this?" The sales spike coincided with a competitor going bankrupt. The satisfaction increase happened when a toxic manager quit. The correlation was real. The causation was fiction. This mistake derailed their careers.   But here's the good news: once you see how this works, you'll never unsee it. And you'll become the person in the room who spots these errors before they cost millions.   But first, you need to understand what makes this mistake so common—and why even smart people fall for it every single day. What is Causal Thinking? At its core, causal thinking is the practice of identifying genuine cause-and-effect relationships rather than settling for surface-level associations. It's asking not just "do these things happen together?" but "does one actually cause the other?"   This skill means you look beyond patterns and correlations to understand what's actually producing the outcomes you're seeing. When you think causally, you can spot the difference between coincidence, correlation, and true causation—a distinction that separates effective decision-makers from those who waste millions on solutions that were never going to work. Loss of Causal Thinking Skills Across every domain of professional life, this confusion costs fortunes and derails careers.   A SaaS company sees customer churn decrease after implementing new onboarding emails—and immediately scales it company-wide. What they missed: they launched the emails the same week their biggest competitor raised prices by 40%. The competitor's pricing reduced churn. But they'll never know, because they never asked the question. Six months later, when they face real churn issues, they keep doubling down on emails that never actually worked.   This happens outside of work too. You start taking a new vitamin, and two weeks later your energy improves. But you started taking it in early March—right when days got longer and you began going outside more. Was it the vitamin or the sunlight and exercise? Most people credit the vitamin without asking the question.   But here's the good news: once you understand how to think causally, these mistakes become obvious. And one of these five strategies can be used in your very next meeting—literally 30 seconds from now. Let me show you how. How To Master Causal Thinking Mastering causal thinking isn't about becoming a statistician or learning complex formulas. It's about developing five practical strategies that work together to reveal what's really driving results. These build on each other—starting with basic tests you can apply right now, and progressing to a complete system you can use for any decision. Strategy 1: The Three Tests of True Causation Think of these as your checklist for evaluating any causal claim.   The Three Tests:   Test #1 - Timing: Confirm the supposed cause actually happened before the effect. If traffic spiked Monday but you launched the campaign Tuesday, that campaign didn't cause it. The cause must always come before the effect.   Test #2 - Consistent Movement: When the supposed cause is present, does the effect reliably occur? When the cause is absent, does the effect disappear? Document instances where they occur together. Then examine situations where the cause is absent. If the effect happens just as often without the cause, you're looking at correlation, not causation.   Test #3 - Rule Out Alternatives: Think carefully about what else could explain what you're seeing. Actively try to disprove your idea rather than only looking for supporting evidence. If you can't eliminate other explanations, you don't have causation. Strategy 2: Ask "Could Something Else Explain This?" Here's a technique you can implement in the next 30 seconds that will immediately improve your causal thinking: whenever someone presents a causal claim, ask out loud: "Could something else explain this?"   This single question is remarkably powerful. It forces the speaker to consider hidden factors they ignored. It reveals whether they've actually done causal analysis or just noticed a correlation and declared victory. It shifts the conversation from assumption to examination.   Try it in your next meeting when someone says "We did X and Y improved." Watch how often they haven't considered alternatives. Watch how often their confident causal claim becomes less certain when forced to address this simple question.   Most people present correlations as causations without even realizing it. Your question makes that leap visible. Suddenly they have to justify it with evidence or back down. It's not confrontational—it's curious. And curiosity is the foundation of good causal thinking.   Use it today. Use it every time someone attributes an outcome to a cause without ruling out alternatives.   That question leads us naturally to our next strategy—learning to identify what those "something elses" actually are. Strategy 3: Hunt for Hidden Causes A confounding variable is a third factor that influences both your suspected cause and your observed effect. It creates the illusion of a direct relationship where none exists.   Here's a simple example: ice cream sales and drowning deaths both increase during summer months. Does ice cream cause drowning? Obviously not. The confounding variable is warm weather, which causes both more ice cream purchases and more swimming.   Now here's the business version: A retail company sees both customer satisfaction and sales increase after renovating their stores. Does the renovation cause higher satisfaction? Maybe—but both also increased because they renovated during the holiday shopping season when people are generally happier and spending more anyway. Same logical structure. Same expensive mistake if they conclude renovations always boost satisfaction.   Map the Relationship: When you observe a correlation, write down your suspected cause and your observed effect. This visualization helps you spot gaps in your logic immediately.   Ask "What Else Changed?": Think carefully about what other factors were present or changed during the same period. Make a written list so your brain doesn't skip over these hidden causes.   Search for Common Causes: Identify factors that could influence both variables at the same time. For instance, if both employee satisfaction and productivity increased, could several toxic managers have left the company?   Consider Time-Based and Environmental Factors: Examine seasons, business cycles, economic trends, reorganizations, leadership changes, and industry shifts that could affect multiple outcomes at once.   Test by Controlling Variables: If possible, create scenarios where you can control or account for potential hidden causes. Try analyzing subgroups where the hidden cause is absent, or run controlled A/B tests.   Once you can spot these hidden causes, you're ready to understand why your brain makes these mistakes in the first place. And this next one? It's probably happening in your head right now without you realizing it. Strategy 4: Outsmart Your Brain's Shortcuts Your brain is wired to see causal connections everywhere, even where none exist. This isn't a design flaw—it's a survival mechanism that kept your ancestors alive. But in the modern business world, this pattern-seeking instinct can mislead you.   Your brain wants simple causal stories. Reality is usually more complex. Once you know what to watch for, you can catch yourself before making these errors.   Catch Your Instant Explanations: When you observe a pattern, pause before declaring causation. Ask yourself: "Am I seeing causation because it's really there, or because my brain desperately needs an explanation?"   Fight Confirmation Bias: Actively search for information that challenges your causal idea, not just data that supports it. If you can't find contradicting evidence, you haven't looked hard enough.   Here's how this plays out: A manager believes remote work hurts productivity. She notices every time someone's late to a Zoom call. But she doesn't notice the three on-time people. She remembers the one missed deadline but forgets the five delivered early. Her brain is filtering reality to confirm what she already believes.   Question Your Compelling Stories: Be wary of explanations that sound too neat. If your causal explanation reads like a perfect success story, double-check it.   Don't See Patterns in Randomness: Three successful quarters in a row doesn't mean you've discovered a winning formula. It might just be a lucky streak. Always ask "Could this pattern occur by chance?"   Watch the 'After Therefore Because' Trap: Every time you catch yourself thinking "we did X and then Y happened," force yourself to consider alternative explanations. Ask yourself "What would I need to see to know this isn't causal?"   Now that you understand how your brain works, let's put this all together into a practical system you can use every time you need to make a high-stakes decision. Strategy 5: The Five-Question Causation Check Mastering causal thinking requires more than understanding principles—it demands a clear approach you can apply when the stakes are high and the pressure is on.   The Five-Question Causation Check:   Define the Relationship Clearly: Write out the specific causal claim you're evaluating with precision. "Social media advertising increases qualified leads by X%" is better than "marketing works."   Verify the Basics: Does the cause come before the effect in time? Are they consistently related across different contexts? Are there possible alternative explanations?   Look for or Create Tests: Find situations where the supposed cause varies while other factors stay constant. The goal is isolation—can you isolate the variable you're testing from everything else that's changing?   Check if More Causes More: Does more of the cause lead to more of the effect? If doubling your ad spend doubles your conversions, that's stronger evidence than if the relationship is erratic.   Test Reversibility: If you remove the cause, does the effect disappear? If you reinstate the cause, does the effect return? This is why pilot programs and controlled rollbacks are so valuable. Put It Into Practice You now have the complete framework for causal thinking—five strategies that work together to reveal what's really causing what.   But here's what separates people who learn this from people who actually use it—one simple practice you can do this week that makes this framework automatic. Practice Exercise: The Causation Audit A practical and effective way to internalize these strategies is through practice with real-world scenarios from your actual work.   Here's how to conduct your own causal analysis:   Identify a Correlation from Your Work: Choose a recent pattern or causal claim that affects budgets or strategy.   State Your Causal Hypothesis: Write out your causal claim explicitly. Be specific about the supposed cause and the supposed effect.   Brainstorm Alternative Explanations: List at least five alternatives. Force yourself beyond the obvious first three.   Apply Your Three Tests: Evaluate whether your idea meets all three tests for causation. Did the cause come first? Do they consistently move together? Have you actually ruled out alternatives?   Design a Simple Test: If possible, design a test to isolate the variable you're testing. For example, have some account managers follow one approach while others don't, with otherwise similar conditions.   Share Your Analysis: Explain your reasoning to a colleague or manager. Teaching forces clarity and demonstrates analytical rigor.   With practice, you'll become skilled at spotting false causation and identifying true cause-and-effect relationships. This skill compounds over time, making you more valuable with every analysis you conduct.   So what does this actually get you? Let me paint the picture of what changes when you master this skill. The Rewards The rewards of mastering causal thinking are well worth the effort and will compound throughout your career.   You become immune to the most expensive mistakes in business—the ones where you solve the wrong problem perfectly. When everyone else is celebrating a correlation as success, you'll be asking the questions that reveal what's really driving outcomes. Imagine being in a meeting where leadership is about to allocate $2 million to scale an initiative, and you're the one who asks the question that reveals a competitor's bankruptcy actually caused the results. That's career-defining value.   Your strategic recommendations carry weight because they're based on actual causation rather than hopeful patterns. Leaders who can distinguish between correlation and causation make decisions that actually work. When your predictions prove accurate while others' fail, your credibility compounds—you become the person everyone turns to when stakes are high.   You develop the intellectual humility that marks exceptional leaders. Causal thinking teaches you to question your initial judgments, seek alternative explanations, and change your mind when evidence demands it. These qualities don't just make you a better thinker—they make you someone others trust with important decisions.   So take these strategies and practice them. Apply them in your daily work. Question causal claims, hunt for hidden causes, check your biases, and use the systematic process. This makes you a more effective decision-maker, a more credible advisor, and someone who spots opportunities and avoids disasters that others miss entirely.   And you'll become the person in the room everyone listens to when the stakes are high. Your Thinking 101 Journey In Episode 1, "Why Thinking Skills Matter Now More Than Ever," we exposed the crisis: your thinking ability is collapsing, AI dependency is creating cognitive debt, and those who can't think independently will be left behind.   In Episode 2, "How To Improve Your Logical Reasoning Skills," you learned to distinguish deductive certainty from inductive probability, calibrate your confidence to match your evidence, and stop treating patterns as proven facts.   Today, you learned how to distinguish true causation from mere correlation—saving yourself from expensive mistakes where you solve the wrong problem perfectly.   Up next—Episode 4: "Analogical Thinking—The Power of Comparison." Your brain doesn't learn through pure logic—it learns by comparison. Every breakthrough idea came from someone who made an unexpected connection. You'll learn how to generate insights through analogy, recognize when comparisons break down, and spot when others use false analogies to manipulate you.   Hit that subscribe button so you don't miss future episodes. Also—hit the like and notification bell. It helps with the algorithm so others see our content. Why not share this video with a colleague who you think would benefit from it?   Because right now, while you've been watching this, someone just approved a million-dollar budget based on a correlation they mistook for causation. The only question is: will you be the one who catches it?       SOURCES CITED IN THIS EPISODE Pathmetrics – Marketing Attribution Waste 5 Common Marketing Attribution Mistakes to Avoid. (2025). Pathmetrics. (Citing Proxima research on global marketing waste) https://www.pathmetrics.io/attribution/5-common-marketing-attribution-mistakes-to-avoid/   Harvard Business Review – Correlation vs Causation in Leadership Luca, M. (2021). Leaders: Stop Confusing Correlation with Causation. Harvard Business Review. https://hbr.org/2021/11/leaders-stop-confusing-correlation-with-causation   The CEO Project – Correlation vs Causation in Business Correlation vs Causation in Business. (2024). The CEO Project. https://theceoproject.com/correlation-vs-causation-in-business/   Nature Communications – Causality in Digital Medicine Glocker, B., Musolesi, M., Richens, J., & Uhler, C. (2021). Causality in digital medicine. Nature Communications, 12, 4993. https://www.nature.com/articles/s41467-021-25743-9   Stanford Social Innovation Review – The Case for Causal AI Sgaier, S. K., Huang, V., & Charles, G. (2020). The Case for Causal AI. Stanford Social Innovation Review. https://ssir.org/articles/entry/the_case_for_causal_ai       ADDITIONAL READING On Causation and Decision-Making Pearl, J., & Mackenzie, D. (2018). The Book of Why: The New Science of Cause and Effect. Basic Books.   On Thinking Clearly Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.   On Statistical Reasoning Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press.         Note: All sources cited in this episode have been accessed and verified as of October 2025.  

About this episode: Does acetaminophen use during pregnancy cause autism in children? In this episode: Brian Lee, who led the largest study on acetaminophen use and neurodevelopmental outcomes, walks through the study's findings—as well as the challenges of researching the causal effects of medication use during pregnancy. Then, biostatistician Elizabeth Stuart discusses how she thinks about assessing potential cause-and-effect relationships when studies have different strengths and weaknesses. Guest: Brian Lee, PhD, MHS, is a professor of epidemiology and biostatistics at the Dornsife School of Public Health at Drexel University.   Elizabeth Stuart, PhD, is Chair in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health, where she focuses on designing and interpreting studies exploring causal effects. Host: Dr. Josh Sharfstein is distinguished professor of the practice in Health Policy and Management, a pediatrician, and former secretary of Maryland's Health Department. Show links and related content: Acetaminophen Use During Pregnancy and Children's Risk of Autism, ADHD, and Intellectual Disability—JAMA What the evidence tells us about Tylenol, leucovorin, and autism—STAT Discovering How Environment Affects Autism—Hopkins Bloomberg Public Health Magazine Does A Really Cause B? How a Biostatistician Thinks About Causality—Public Health On Call (August 2024) Transcript information: Looking for episode transcripts? Open our podcast on the Apple Podcasts app (desktop or mobile) or the Spotify mobile app to access an auto-generated transcript of any episode. Closed captioning is also available for every episode on our YouTube channel. Contact us: Have a question about something you heard? Looking for a transcript? Want to suggest a topic or guest? Contact us via email or visit our website. Follow us: @‌PublicHealthPod on Bluesky @‌JohnsHopkinsSPH on Instagram @‌JohnsHopkinsSPH on Facebook @‌PublicHealthOnCall on YouTube Here's our RSS feed Note: These podcasts are a conversation between the participants, and do not represent the position of Johns Hopkins University.

Get early access to Alex's next live-cohort courses!Today's clip is from episode 141 of the podcast, with Sam Witty.Alex and Sam discuss the ChiRho project, delving into the intricacies of causal inference, particularly focusing on Do-Calculus, regression discontinuity designs, and Bayesian structural causal inference. They explain ChiRho's design philosophy, emphasizing its modular and extensible nature, and highlights the importance of efficient estimation in causal inference, making complex statistical methods accessible to users without extensive expertise.Get the full discussion here.Intro to Bayes Course (first 2 lessons free)Advanced Regression Course (first 2 lessons free)Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!Visit our Patreon page to unlock exclusive Bayesian swag ;)TranscriptThis is an automatic transcript and may therefore contain errors. Please get in touch if you're willing to correct them.

Send us a textCreate Your Causal Inference Roadmap. Causal Inference, TMLE & SensitivityIf you're into causal inference and machine learning you probably heard about double machine learning (DML).DML is one of the most popular frameworks leveraging machine learning algorithms for causal inference, while offering good statistical properties.Yet...There's another framework that also leverages machine learning for causal inference that was created years earlier.Welcome to the world of targeted maximum likelihood estimation (TMLE).Our today's guest, Prof. Mark van der Laan (UC Berkeley) is the godfather of TMLE.In the episode, we discuss:- Similarities and differences between DML and TMLE- How to build a causal roadmap for your project- How Mark uses math to solve real-world problems- Why uncertainty quantification is so important------------------------------------------------------------------------------------------------------Video version available on the Youtube: https://youtu.be/qr5JolEAuJURecorded on Sep 16, 2025 in Berkeley, California, US.------------------------------------------------------------------------------------------------------*About The Guest*Mark van der Laan is a Professor in Biostatistics and Statistics at UC Berkeley. He's the godfather of Targeted Maximum Likelihood Estimation (TMLE), a semiparametric framework that uses machine learning to estimate causal effects or other statistical parameters from observational data, and its new incarnation Targeted Machine Learning.*About The Host*Aleksander (Alex) Molak is an independent machine learning researcher, educator, entrepreneur and a best-selling author in the area of causality (https://amzn.to/3QhsRz4 ).Connect with Alex:- Alex on the Internet: https://bit.ly/aleksander-molak*Links*Libraries- Deep LTMLE (Python): https://github.com/shirakawatoru/dltmlePapers- Dang, ..., van der Laan et al. (2023) - "A Causal Roadmap for Generating High-Quality Real-World Evidence" (https://arxiv.org/abs/2305.06850)- Gruber, ..., van der Laan (2021) - "Developing a Targeted Learning-Based Statistical AnalysisSupport the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

In this special episode, I sit down with renowned Jungian analyst Professor Murray Stein for a deep and wide-ranging conversation about Jung's core concepts: individuation, synchronicity, and kairos. We explore the mysteries of time, the nature of archetypes, the crisis of meaning in our era, and the role of consciousness in the cosmos. Along the way, we weave in personal stories, philosophical insights, and references to some of the most important works in depth psychology.Whether you're new to Jung or a longtime explorer of the psyche, I hope this episode inspires you to reflect on your own kairos moments and the deeper patterns shaping your life.Referenced Books, Ideas, and People:C.G. Jung (“Memories, Dreams, Reflections”)I Ching (Book of Changes)Hippocrates (Kairos & Kronos)Michel Serres (temporality as a folded handkerchief)Wolfgang Pauli (“Adam and Archetype: The Letters of C.G. Jung and Wolfgang Pauli”)Nathan Schwartz-Salant (“The Paradox of Negentropy”)William Blake (“To see a world in a grain of sand…”)Teilhard de Chardin (Omega Point)AstrologyMandalaThe Age of Pisces and Age of AquariusGnosticismThe Black Madonna pilgrimage site in SwitzerlandChapters & Timestamps00:00 Welcome & Introduction00:14 Key Jungian Terms: Individuation, Synchronicity, Kairos03:51 Archetypes & Synchronicity in Life14:51 Causality, Acausality, and the Nature of Time26:51 Evolution, Final Causation, and the Omega Point31:46 Consciousness, God, and the Human Role34:34 Dreams, the Unconscious, and Timelessness38:25 Synchronicity, Entropy, and Centropy44:07 Kairos, Kronos, and the Meaning of Time49:57 Collective Consciousness & Cultural Transformation54:43 Closing Reflectionswww.arabellathais.com

David Abel is a Senior Research Scientist at DeepMind on the Agency team, and an Honorary Fellow at the University of Edinburgh. His research blends computer science and philosophy, exploring foundational questions about reinforcement learning, definitions, and the nature of agency.  Featured References  Plasticity as the Mirror of Empowerment   David Abel, Michael Bowling, André Barreto, Will Dabney, Shi Dong, Steven Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, Satinder Singh  A Definition of Continual RL   David Abel, André Barreto, Benjamin Van Roy, Doina Precup, Hado van Hasselt, Satinder Singh  Agency is Frame-Dependent   David Abel, André Barreto, Michael Bowling, Will Dabney, Shi Dong, Steven Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, Satinder Singh  On the Expressivity of Markov Reward   David Abel, Will Dabney, Anna Harutyunyan, Mark Ho, Michael Littman, Doina Precup, Satinder Singh — Outstanding Paper Award, NeurIPS 2021  Additional References  Bidirectional Communication Theory — Marko 1973  Causality, Feedback and Directed Information — Massey 1990  The Big World Hypothesis — Javed et al. 2024  Loss of plasticity in deep continual learning — Dohare et al. 2024  Three Dogmas of Reinforcement Learning — Abel 2024  Explaining dopamine through prediction errors and beyond — Gershman et al. 2024  David Abel Google Scholar  David Abel personal website  

Dr. Michael Timothy Bennett is a computer scientist who's deeply interested in understanding artificial intelligence, consciousness, and what it means to be alive. He's known for his provocative paper "What the F*** is Artificial Intelligence" which challenges conventional thinking about AI and intelligence.**SPONSOR MESSAGES***Prolific: Quality data. From real people. For faster breakthroughs.https://prolific.com/mlst?utm_campaign=98404559-MLST&utm_source=youtube&utm_medium=podcast&utm_content=mb***Michael takes us on a journey through some of the biggest questions in AI and consciousness. He starts by exploring what intelligence actually is - settling on the idea that it's about "adaptation with limited resources" (a definition from researcher Pei Wang that he particularly likes).The discussion ranges from technical AI concepts to philosophical questions about consciousness, with Michael offering fresh perspectives that challenge Silicon Valley's "just scale it up" approach to AI. He argues that true intelligence isn't just about having more parameters or data - it's about being able to adapt efficiently, like biological systems do.TOC:1. Introduction & Paper Overview [00:01:34]2. Definitions of Intelligence [00:02:54]3. Formal Models (AIXI, Active Inference) [00:07:06]4. Causality, Abstraction & Embodiment [00:10:45]5. Computational Dualism & Mortal Computation [00:25:51]6. Modern AI, AGI Progress & Benchmarks [00:31:30]7. Hybrid AI Approaches [00:35:00]8. Consciousness & The Hard Problem [00:39:35]9. The Diverse Intelligences Summer Institute (DISI) [00:53:20]10. Living Systems & Self-Organization [00:54:17]11. Closing Thoughts [01:04:24]Michaels socials:https://michaeltimothybennett.com/https://x.com/MiTiBennettTranscript:https://app.rescript.info/public/share/4jSKbcM77Sf6Zn-Ms4hda7C4krRrMcQt0qwYqiqPTPIReferences:Bennett, M.T. "What the F*** is Artificial Intelligence"https://arxiv.org/abs/2503.23923Bennett, M.T. "Are Biological Systems More Intelligent Than Artificial Intelligence?" https://arxiv.org/abs/2405.02325Bennett, M.T. PhD Thesis "How To Build Conscious Machines"https://osf.io/preprints/thesiscommons/wehmg_v1Legg, S. & Hutter, M. (2007). "Universal Intelligence: A Definition of Machine Intelligence"Wang, P. "Defining Artificial Intelligence" - on non-axiomatic reasoning systems (NARS)Chollet, F. (2019). "On the Measure of Intelligence" - introduces the ARC benchmark and developer-aware generalizationHutter, M. (2005). "Universal Artificial Intelligence: Sequential Decisions Based on Algorithmic Probability"Chalmers, D. "The Hard Problem of Consciousness"Descartes, R. - Cartesian dualism and the pineal gland theory (historical context)Friston, K. - Free Energy Principle and Active Inference frameworkLevin, M. - Work on collective intelligence, cancer as information isolation, and "mind blindness"Hinton, G. (2022). "The Forward-Forward Algorithm" - introduces mortal computation conceptAlexander Ororbia & Friston - Formal treatment of mortal computationSutton, R. "The Bitter Lesson" - on search and learning in AIPearl, J. "The Book of Why" - causal inference and reasoningAlternative AGI ApproachesWang, P. - NARS (Non-Axiomatic Reasoning System)Goertzel, B. - Hyperon system and modular AGI architecturesBenchmarks & EvaluationHendrycks, D. - Humanities Last Exam benchmark (mentioned re: saturation)Filmed at:Diverse Intelligences Summer Institute (DISI) https://disi.org/

Prof. David Krakauer, President of the Santa Fe Institute argues that we are fundamentally confusing knowledge with intelligence, especially when it comes to AI.He defines true intelligence as the ability to do more with less—to solve novel problems with limited information. This is contrasted with current AI models, which he describes as doing less with more; they require astounding amounts of data to perform tasks that don't necessarily demonstrate true understanding or adaptation. He humorously calls this "really shit programming".David challenges the popular notion of "emergence" in Large Language Models (LLMs). He explains that the tech community's definition—seeing a sudden jump in a model's ability to perform a task like three-digit math—is superficial. True emergence, from a complex systems perspective, involves a fundamental change in the system's internal organization, allowing for a new, simpler, and more powerful level of description. He gives the example of moving from tracking individual water molecules to using the elegant laws of fluid dynamics. For LLMs to be truly emergent, we'd need to see them develop new, efficient internal representations, not just get better at memorizing patterns as they scale.Drawing on his background in evolutionary theory, David explains that systems like brains, and later, culture, evolved to process information that changes too quickly for genetic evolution to keep up. He calls culture "evolution at light speed" because it allows us to store our accumulated knowledge externally (in books, tools, etc.) and build upon it without corrupting the original.This leads to his concept of "exbodiment," where we outsource our cognitive load to the world through things like maps, abacuses, or even language itself. We create these external tools, internalize the skills they teach us, improve them, and create a feedback loop that enhances our collective intelligence.However, he ends with a warning. While technology has historically complemented our deficient abilities, modern AI presents a new danger. Because we have an evolutionary drive to conserve energy, we will inevitably outsource our thinking to AI if we can. He fears this is already leading to a "diminution and dilution" of human thought and creativity. Just as our muscles atrophy without use, he argues our brains will too, and we risk becoming mentally dependent on these systems.TOC:[00:00:00] Intelligence: Doing more with less[00:02:10] Why brains evolved: The limits of evolution[00:05:18] Culture as evolution at light speed[00:08:11] True meaning of emergence: "More is Different"[00:10:41] Why LLM capabilities are not true emergence[00:15:10] What real emergence would look like in AI[00:19:24] Symmetry breaking: Physics vs. Life[00:23:30] Two types of emergence: Knowledge In vs. Out[00:26:46] Causality, agency, and coarse-graining[00:32:24] "Exbodiment": Outsourcing thought to objects[00:35:05] Collective intelligence & the boundary of the mind[00:39:45] Mortal vs. Immortal forms of computation[00:42:13] The risk of AI: Atrophy of human thoughtDavid KrakauerPresident and William H. Miller Professor of Complex Systemshttps://www.santafe.edu/people/profile/david-krakauerREFS:Large Language Models and Emergence: A Complex Systems PerspectiveDavid C. Krakauer, John W. Krakauer, Melanie Mitchellhttps://arxiv.org/abs/2506.11135Filmed at the Diverse Intelligences Summer Institute:https://disi.org/

The extremely effective skill of recognizing and following the patterns that move us. And the detrimental, interfering behavior of attempting to explain those patterns.Support the showBecome a Membernontrivialpodcast.com Check out the Video Versionhttps://www.youtube.com/@nontrivialpodcast

In the present, the military and intelligence agencies are losing a war they have not yet fought. In the future, an unseen enemy has discovered a way to reverse time, albeit in a highly localized manner. Using something called “inverse radiation,” they can reverse the entropy of both objects and people so that they move through time in the opposite direction, at least from our fourth-dimensional point of view. It is a paradox in the timeline where the solution lies in how to fight a war through a backward causality loop. Additionally, the battlefield now includes narratives, alliances, and public opinion. It is about world control, domination, and the promise of a Golden Age. Listen tonight from 7-10 pm, pacific time, with Clyde Lewis and military analyst, Sean Patrick Hazlett on groundzeroplus.com. Call in to the LIVE show at 503-225-0860. #groundzeroplus #ClydeLewis #war #reversecausality #military

Support the show to get full episodes, full archive, and join the Discord community. The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists. Read more about our partnership. Sign up for Brain Inspired email alerts to be notified every time a new Brain Inspired episode is released. To explore more neuroscience news and perspectives, visit thetransmitter.org. You may have heard of the critical brain hypothesis. It goes something like this: brain activity operates near a dynamical regime called criticality, poised at the sweet spot between too much order and too much chaos, and this is a good thing because systems at criticality are optimized for computing, they maximize information transfer, they maximize the time range over which they operate, and a handful of other good properties. John Beggs has been studying criticality in brains for over 20 years now. His 2003 paper with Deitmar Plenz is one of of the first if not the first to show networks of neurons operating near criticality, and it gets cited in almost every criticality paper I read. John runs the Beggs Lab at Indiana University Bloomington, and a few years ago he literally wrote the book on criticality, called The Cortex and the Critical Point: Understanding the Power of Emergence, which I highly recommend as an excellent introduction to the topic, and he continues to work on criticality these days. On this episode we discuss what criticality is, why and how brains might strive for it, the past and present of how to measure it and why there isn't a consensus on how to measure it, what it means that criticality appears in so many natural systems outside of brains yet we want to say it's a special property of brains. These days John spends plenty of effort defending the criticality hypothesis from critics, so we discuss that, and much more. Beggs Lab. Book: The Cortex and the Critical Point: Understanding the Power of Emergence Related papers Addressing skepticism of the critical brain hypothesis Papers John mentioned: Tetzlaff et al 2010: Self-organized criticality in developing neuronal networks. Haldeman and Beggs 2005: Critical Branching Captures Activity in Living Neural Networks and Maximizes the Number of Metastable States. Bertschinger et al 2004: At the edge of chaos: Real-time computations and self-organized criticality in recurrent neural networks. Legenstein and Maass 2007: Edge of chaos and prediction of computational performance for neural circuit models. Kinouchi and Copelli 2006: Optimal dynamical range of excitable networks at criticality. Chialvo 2010: Emergent complex neural dynamics.. Mora and Bialek 2011: Are Biological Systems Poised at Criticality? Read the transcript. 0:00 - Intro 4:28 - What is criticality? 10:19 - Why is criticality special in brains? 15:34 - Measuring criticality 24:28 - Dynamic range and criticality 28:28 - Criticisms of criticality 31:43 - Current state of critical brain hypothesis 33:34 - Causality and criticality 36:39 - Criticality as a homeostatic set point 38:49 - Is criticality necessary for life? 50:15 - Shooting for criticality far from thermodynamic equilibrium 52:45 - Quasi- and near-criticality 55:03 - Cortex vs. whole brain 58:50 - Structural criticality through development 1:01:09 - Criticality in AI 1:03:56 - Most pressing criticisms of criticality 1:10:08 - Gradients of criticality 1:22:30 - Homeostasis vs. criticality 1:29:57 - Minds and criticality

Summary In this episode, Andy talks with Dr. Joe Sutherland, co-author of the new book Analytics the Right Way: A Business Leader's Guide to Putting Data to Productive Use. Joe is a leader in AI policy and practice, serving as the founding director of the Emory Center for AI Learning and lead principal investigator for the U.S. AI Safety Institute Consortium. Andy and Joe explore what it really takes to make better decisions in a world drowning in data and exploding with AI hype. They discuss the myths of data collection, how randomized controlled trials and causal inference impact decision quality, and Joe's “two magic questions” that help project managers stay focused on outcomes. They also dive into recent AI breakthroughs like DeepSeek, and why executives may be paralyzed when it comes to implementing AI strategy. If you're looking for insights on how to use data and AI more effectively to support leadership and project decision-making, this episode is for you! Sound Bites “What are we trying to achieve? And how would we know if we achieved it?” “Sometimes we're measuring success by handing out coupons to people who already had the product in their cart.” “AI doesn't replace decision-making—it demands better decisions from us.” “Causality is important for really big decisions because you want to know with a level of certainty that if I make this choice, this outcome is going to happen.” “Too often, we make decisions based on bad causal inference and wonder why the outcomes don't match our expectations.” “The ladder of evidence helps you decide how much certainty you need before making a decision—and how much it'll cost to climb higher.” “The truth is, we're not ready for human-out-of-the-loop AI—we're barely asking the right questions yet.” “Leadership isn't about replacing people with AI. It's about using AI to make your people more productive and happier.” “We're starting to see some evidence that when you use large language models in education, test scores go up in excess of 60%.” “This may be the first time the kids feel more behind than the parents when it comes to a new technology.” Chapters 00:00 Introduction 02:00 Start of Interview 02:09 What Are Some Myths About Data? 03:49 What Is the Potential Outcomes Framework? 08:50 What Are Counterfactuals? 13:00 How Do You Personally Evaluate Causality? 18:22 What Are the Two Magic Questions for Projects? 20:45 What's Getting Traction From the Book? 24:26 What Can We Learn From DeepSeek's Disruption? 27:30 Human In or Out of the AI Loop? 30:41 How Joe Uses AI Personally and Professionally 33:33 What Is the Future of Agentic AI? 35:37 Will AI Replace Jobs? 37:18 How Can Parents Prepare Kids for the AI Future? 41:19 End of Interview 41:46 Andy Comments After the Interview 45:07 Outtakes Learn More You can learn more about Joe and his book at AnalyticsTRW.com. For more learning on this topic, check out: Episode 381 with Jim Loehr about how to make wiser decisions. Episode 372 with Annie Duke on knowing when to quit. Episode 437 with Nada Sanders about future-prepping your career in the age of AI. Thank you for joining me for this episode of The People and Projects Podcast! Talent Triangle: Power Skills Topics: Leadership, Decision Making, Data Analytics, Artificial Intelligence, Project Management, Strategic Thinking, Causal Inference, Agile, AI Ethics, AI in Education, Machine Learning, Career Development, Future of Work The following music was used for this episode: Music: Ignotus by Agnese Valmaggia License (CC BY 4.0): https://filmmusic.io/standard-license Music: Synthiemania by Frank Schroeter License (CC BY 4.0): https://filmmusic.io/standard-license

Patrick answers challenging questions about faith, shares tips for talking to young adults about belief in God, and recommends useful books on Catholic apologetics. He also explores the curious practice of proxy baptisms in the Mormon church, especially regarding well-known Catholic figures like popes. Patrick addresses listener questions about confession, cremation, and ways to support friends interested in joining the Catholic Church. For insightful advice and real-life wisdom on living your faith, Patrick delivers content you won’t want to miss. Ellie (email) - I need to be first proven that the Christian God exists to believe in Heaven and then be comforted, but I’m unsure about his existence and therefore I’m unsure about any afterlife. (00:51) Craig - What do you do if your friend is dating someone who says that Jesus failed because he didn't get married? (13:22) Lee - How can I help someone else convert? (15:18) Audio: Will Mormons baptize the Pope after his death? (18:21) Was Jesus really nailed to the Cross? (37:27) Mary Joe - Thank you for explaining something I learned in my Theology class when I was young. You explained Causality perfectly! (39:14) Ellen (email) – Can cremation ashes be held in reserve? (41:57) Joan (email) – Patrick said you can’t commit a mortal son unless you know it’s a mortal sin when you commit it, which I assume goes for venial sin as well. Why then, at their first confession, do RCIA candidates confess their sins from the past if they weren’t aware that they were sins until going through RCIA? (47:12)

Is it valid or even permissible to attend a Mass led by an excommunicated priest or bishop? We explore this complex issue and also dive into questions on Mary's perpetual virginity, altar calls at Pentecostal services, and the meaning behind “baptism for the dead.” Join The CA Live Club Newsletter: Click Here Questions Covered: 04:55 – My wife is Pentecostal and I attend early morning Mass and then Pentecostal service with wife and children I want to know if it is ok  to go up to altar call with my wife and children?  14:53 – How to refute quantum mechanics disproving the Aristotelian proof of God and Causality  18:22 – Perpetual Vigirnity of Mary. Is it reasonable to think that St. Joseph did not know that Mary had taken a vow of Virginity?  24:30 – St. Paul, scripture, baptism for the dead, he has a theory of what it means, wants to get Joe's take…He thinks baptism for those who are dead in their sin  32:50 – Why does St. Paul go against the Council of Jerusalem when he says some Christians can eat meat sacrificed to idols?  36:25 – Can I attend a Mass that is being celebrated by an excommunicated priest or bishop?  42:41 – Mary's role as intercessor in light of Lukes passages on sword piercing her soul, and the Magnificat.  47:04 – Girlfriend died 3 years ago, he led her to Christ, wants to know if he can still pray to her, even though she may be in Purgatory, and can he ask her to pray for him  52:04 – Calling back with follow-up question, his wife does not want the kids baptized in the Catholic Church. Should he still passively participate?