Podcasts about Algorithmic

Learning analytics dashboards and metrics are an increasing presence in higher education. We talk to Hannes Hautz (University of Innsbruck) about his research on students' mixed reactions to learning analytics, and how we can ensure more equitable and reflective use of student data. Recommended reading >>> Hautz, H. & Lipp, S. (2026). Algorithmic governmentality and student subjectivities: a critical examination of learning analytics in higher education. Learning, Media and Technology, 1-17.

Bruce Winder on how widespread algorithmic or surveillance pricing actually is.

Arnd Vomberg, Associate Professor of Marketing at HEC Paris, and his colleagues have spent years studying how consumers respond when prices shift without notice. Their findings, published in the International Journal of Research in Marketing, are directly relevant to every brand competing for attention in an algorithmically priced marketplace. He joins the show to discuss price fairness theory, the habituation effect, and why a guarantee that almost no one redeems can still shift consumer behavior. If dynamic pricing is already in your category, or it's coming, this conversation is where to start.

#717: Clare Flynn Levy was a hedge fund manager in London in the summer of 2007, watching her trading screens turn red — every single day. Merger arbitrage spreads were widening. Investors were pulling out. She didn't yet realize she was watching the early tremors of a global financial crisis. Clare joins us to talk about what that experience taught her about investor behavior, emotional bias, and the hidden forces that drive financial decisions. She now runs a firm that helps professional fund managers analyze their own decision-making patterns. Her core argument: most investors aren't making rational choices. They're rationalizing them. We get into two specific biases that cloud judgment — sunk cost fallacy and the endowment effect — and how they show up whether you're picking individual stocks or rebalancing a 529 plan. Clare shares a personal example. After the 2024 election, she moved her kids' college funds from equities into bonds, recorded her reasoning in her calendar, and came back nine months later to review it honestly. She was wrong. Equities kept climbing. But having a written thesis let her make a clean new decision rather than doubling down out of ego. We also walk through five investor archetypes drawn from behavioral research on fund managers. Connoisseurs let winners run. Raiders take profits too early. Rabbits freeze — or keep buying into a losing position. Hunters wait and take calculated shots. Assassins cut losses cleanly, without emotion. Most people default to rabbit behavior when things go south. The goal is to be an assassin. Clare's practical rule: don't let any single position drag your overall portfolio down more than 1 percent before forcing yourself to reassess. Her closing advice for long-term investors: ask yourself five simple questions before every major move, write down your reasoning, and go back and check. Timestamps: Note: Timestamps will vary on individual listening devices based on dynamic advertising run times. The provided timestamps are approximate and may be several minutes off due to changing ad lengths. (00:00) 5 Ways Investors Behave When Things Go Wrong (05:20) Clare Flynn Levy — hedge fund manager turned behavioral finance analyst (06:50) 2008 crisis — watching screens turn red daily (08:25) Sunk cost fallacy and the endowment effect — why investors hold losers too long (10:25) Index funds — riskier than most people think (17:09) Tech concentration — how indexes got warped (27:52) Algorithmic trading — machines changing the game (29:37) Playing the wrong game — taking cues from short-term traders (31:22) Individual stocks — same behavioral traps apply (35:22) Hit rate vs. payoff ratio — what actually drives returns (44:57) Five investor archetypes — how you behave when winning and losing (50:17) Alpha decay — when to exit a winning position (54:22) Being an assassin — rules for cutting losses without emotion (59:42) Decision journaling — five questions to ask before every move (01:03:22) Quarterly snapshots — simple way to track your own patterns (01:05:22) Closing advice — discipline, patience, and realistic expectations Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode of the Oxford Policy Pod, Thenu and Jasmine speak with Chanel Contos about the growing influence of social media algorithms on young people, relationships, and public discourse. Known for her advocacy around consent education and sexual violence prevention, Chanel reflects on how digital platforms can both amplify social movements and expose users to harmful online ecosystems.The conversation explores the ways algorithms shape behaviour, reinforce social norms, and contribute to the spread of misogynistic and radicalising content online, particularly among young men. It also examines the tension between engagement-driven platform design and user wellbeing, alongside the challenges governments and tech companies face in creating safer and more accountable digital spaces.The episode further discusses Chanel's latest campaign on algorithmic accountability, including its goals, the barriers to reform, and what gives hope for the future of online safety and digital justice.

The agency model is facing a perfect storm: in-housing is gutting the middle, independent agencies are winning on agility, and AI is automating the ‘making' part of marketing. So how is the big six responding?On this episode of the Performance Marketing Unlocked podcast, Jessica Tamsedge, UK CEO of Dentsu Creative, joins host Joe to outline how Dentsu is blowing up traditional silos to prepare for a world where a brand's survival depends on being ‘machine-readable' and ‘human-referenceable'. This podcast was hosted by PMW's Deputy Editor, Joseph Arthur.~ Episode breakdown ~ (2:58) What does it mean to be ‘machine-readable'?(12:23) How does Dentsu keep itself agile?(19:51) Overrated or underrated?(25:00) PMW's Resell Me a Pen Challenge~ Further reading ~ ChatGPT Ads to hit the UKIPA Bellwether: ‘Where is the confidence coming from?'Top 6 adtech tools this week: Reddit, SMG, Merkle, Lifesight, Adform and Dentsu Hosted on Acast. See acast.com/privacy for more information.

Aaron Wolf sits down with Rob Garza, co-founder of Thievery Corporation and the artist behind GARZA, for a conversation about creativity, culture, and human connection in an increasingly artificial world. They discuss the D.C. roots of Thievery, global influence in music, opening for Paul McCartney, and why emotionally immersive art still matters in the age of algorithms.

Algorithms shape our modern world, determining everything from which ads we might see on Instagram to who is afforded access to credit. But what decisions go into the development of these algorithms? Professor Fanna Gamal, Assistant Professor of Law at UCLA School of Law, noticed that developers often exclude race and racial proxy variables as an input when creating machine learning algorithms. Prof. Gamal's latest article in the California Law Review, "The Algorithmic Racial Proxy," discusses the difficulty of defining what a racial proxy is, and the implications of allowing those who develop machine learning algorithms to decide. today's episode, Prof. Gamal joins Source Collect to discuss her article. This episode was recorded in April 2026. Host, Script, and Production: Davis Rich (Volume 115 Podcast Editor) Soundtrack: Composed and performed by Carter Jansen (Volume 110 Technology Editor) Introductory Quote: Judge Thelton E. Henderson

-The Information reported that Anthropic has agreed to pay a staggering $200 billion to Google over the next five years. -Irish regulators have opened two investigations into Meta over whether the company is sufficiently complying with a European law requiring platforms to offer users alternatives to targeted algorithmic feeds. -Pennsylvania is suing AI startup Character.AI for offering chatbots that pretend to be licensed doctors. Learn more about your ad choices. Visit podcastchoices.com/adchoices

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This is Part 18 of *Practical Anarchy – A Guide to Self-Determination*.. Please Like, Comment, Subscribe and Watch the whole series in order. Acknowledgements Dedication Introduction by Mark Sleigh Introduction to the author ► Full playlist:    https://www.youtube.com/playlist?list=PLDT6pJU3_gViYVxWUTl8PcR29sW0GAcQK ► Join the Facebook group: https://www.facebook.com/groups/1864387554451463/permalink/1881786316044920/ ► Buy the book: https://shop.ingramspark.com/b/084?params=9dOIqr4EMtGT3x43Y9bhrmDaCPKCIzif4Y1dUjMvxgr #anarchy #history #politics #counterculture

From January 9, 2022 (Episode 310): Daphne Keller discusses her paper “Amplification and Its Discontents” with Corbin Barthold and Ari Cohn. Links: Amplification and Its Discontents: Why Regulating the Reach of Online Content Is Hard Tech Policy Podcast 389: The Rise of the Compliant Speech Platform

In this episode we sit down with Sheamus McGovern, founder of the Open Data Science Conference (ODSC AI), to unpack what AI actually looks like. Sheamus shares what's really happening behind the scenes of the AI boom and why the biggest shift isn't job loss, but a complete transformation of skills. From explaining why AI is reshaping—not replacing—jobs, to breaking down the gap between hype and real-world applications, this conversation explores how early algorithmic trading foreshadowed today's AI revolution, why open-source tools like TensorFlow and PyTorch changed everything, what the “AI Skill Flip” means for your career, and why even data scientists are questioning their future. Along the way, the biggest mistake people make when trying to learn AI, and why the smartest approach isn't to learn everything—but to start intentionally and build from there. Timestamps00:00 – The biggest misconception about AI 02:00 – Algorithmic trading and the origins of AI in finance 05:00 – The birth of ODSC AI and the data science movement 09:30 – Breakthrough moments in AI 16:30 – Democratization of AI and open-source tools 19:00 –The AI Skill Flip 24:00 – The truth about AI replacing jobs 27:00 – Real-world AI success stories 32:30 – How to actually start learning AI todayFollow Sheamus McGovern onLinkedIn (https://www.linkedin.com/in/sheamus/)ODSC Website (https://odsc.ai/) Follow Breaking Math onSubstack (https://breakingmath.substack.com/)Twitter (https://x.com/breakingmathpod)Instagram (https://www.instagram.com/breakingmathmedia/)Bluesky (https://bsky.app/profile/breakingmath.bsky.social)Website (https://www.breakingmath.io/)YouTube (https://www.youtube.com/@BreakingMathPod)Follow Noah onInstagram (https://www.instagram.com/profnoahgian/)Twitter (https://x.com/ProfNoahGian)Bluesky (https://bsky.app/profile/profnoahgian.bsky.social)Follow Autumn onTwitter (https://x.com/1autumn_leaf)Bluesky (https://bsky.app/profile/1autumnleaf.bsky.social)Instagram (https://www.instagram.com/1autumnleaf/)Substack (https://substack.com/@1autumnleaf)email: breakingmathpodcast@gmail.com

The 2026 job market is brutal. Hiring freezes. Ghost jobs. Mass layoffs. Algorithmic rejection. If you've been applying for months and hearing nothing, the problem isn't you — it's the job search playbook you've been handed. In this episode, we breaks down the 3 shifts that separate people who actually get a job they love in a bad job market from people stuck in endless application loops: clarity before search, conversations before applications, and designing your career instead of defaulting into one.    What you'll learn Why referrals produce 7x the interview rate of cold applications (69% vs. 8%) Why "apply to more jobs" is the worst career advice being given in 2026 How to get clarity before you start your job search (and why most people skip this entirely)   Our book, Happen To Your Career: An Unconventional Approach To Career Change and Meaningful Work, is now available for FREE on audiobook! Visit https://happentoyourcareer.com/audiobook/ to listen to it today! Want to chat with our team about your unique situation? Schedule a conversation   Free Resources What career fits you? Join our free 8 Day Mini Course to figure it out! Career Change Guide - Learn how high-performers discover their ideal career and find meaningful, well-paid work without starting over.   Related Episodes Figuring Out Your Perfect Career Match (Spotify / Apple Podcasts) Six Career Experiments To Help You Discover Your Ideal New Role (Spotify / Apple Podcasts) Stuck in a Career You're Unhappy With? Fear Of Taking Risks Could Be Keeping You There (Spotify / Apple Podcasts)

In Episode 5 of Psychotherapy on the Couch, the host explores a profound and unsettling premise: psychosis, paranoia, and conspiracy theories are not random malfunctions of the brain. Rather, they are the language our culture uses to express its unprocessed, collective trauma. From the animistic voices of the early 1900s to the algorithmic paranoia of the 2020s, this episode traces how the "American Unconscious" absorbs what society refuses to acknowledge—and how the psychiatric establishment has systematically failed to listen. By pathologizing systemic wounds into individual symptoms, modern psychology has left us uniquely vulnerable to cults, conspiracy theories, and an epidemic of isolation. Key Themes & Takeaways 1. The Evolution of Psychosis Psychotic delusions act as a mirror to the cultural environment, adapting their vocabulary to the dominant anxieties of the era: 1910s: Voices tied to nature, ancestry, and the land. 1930s (The Depression): Hungry, pleading voices reflecting profound economic and manufactured inadequacy. 1950s–1970s (The Cold War): Voices of surveillance and persecution, directly mirroring the existential dread of the atomic bomb and the very real operations of the covert state (e.g., MKULTRA, COINTELPRO). 2020s: Algorithmic, technologically driven voices reflecting the reality of digital surveillance and data capture. 2. The Neurology of Meaning Drawing on Paul MacLean's "Triune Brain" model and Jungian psychology, the episode highlights how Western culture aggressively privileges the analytical cortex while dismissing the older, emotional, meaning-making layers of the brain (the paleomammalian layer). When a culture numbs its trauma, it also numbs its intuition, forcing the unconscious to speak through improper channels—like physical exhaustion, hallucinations, or societal panic. 3. The Map is Wrong, but the Wound is Real Conspiracy theories—from the anti-Masonic panics of the labor era to modern QAnon—are framed not as intellectual defects, but as misdirected grief. People accurately perceive that they are being exploited, manipulated, or discarded by a system, but they lack the vocabulary to name the true structural causes. Because the "map" is wrong, their very real rage is directed at scapegoats. 4. The Tragedy of the Satanic Panic The episode examines the 1980s Satanic Panic as a prime example of a culture losing its symbolic language. Both feminists and religious conservatives accurately sensed a massive cultural crisis regarding the sexual exploitation of women and children. However, because modern psychology had abandoned symbolic, mythological language in favor of rigid cognitive-behavioral literalism, this valid cultural terror was forced to express itself as a literal hallucination of underground cults. 5. The Weaponization of Diagnosis The script addresses the dark history of psychology acting as an arm of state control, specifically highlighting how the diagnostic criteria for schizophrenia were deliberately altered in the 1960s to pathologize the justified rage of Black civil rights activists. 6. The Algorithmic Shadow Unlike past collective traumas, today's algorithmic feeds deliver highly personalized, individualized "wounds." This has created a fragmented landscape of paranoia where people feel—accurately—that their nervous systems are being manipulated by tech platforms, but incorrectly attribute the manipulation to shadowy cabals rather than engagement-optimized incentive structures. The Core Lesson for Mental Health Therapy was originally designed to listen to the symptom as a form of communication. Today, however, the clinical apparatus has been captured by 15-minute med checks, billing codes, and symptom-reduction protocols. To heal the culture, we must stop arguing with the "hallucination" of the conspiracy theorist and start addressing the legitimate, bleeding wound beneath it. History of Psychology, Carl Jung, Collective Unconscious, Conspiracy Theories, QAnon Psychology, Mental Health System, Satanic Panic, Cognitive Behavioral Therapy, Trauma, Systemic Abuse, Somatic Experiencing, Psycho-history, Taproot Therapy Collective.   Find More information and resources at our Hoover, AL therapy clinic website. 

Algorithmic and AI-driven tools are increasingly shaping how employers set employee compensation. But how can employers avoid compliance pitfalls when use of these tools raises competition and other regulatory concerns? Economist Rose Healy joins Anora Wang and Subrata Bhattacharjee to discuss the legal and economic risks, as well as practical tools such as bias audits and event studies. Listen to this episode to learn how wage-setting algorithms are being used today—and what may lie ahead as these technologies evolve. With special guest: Rose Healy, Director, Resolution Economics Hosted by: Anora Wang, Arnold & Porter and Subrata Bhattacharjee, Borden Ladner Gervais

PostbagShould I delete posts on LinkedIn?Richard G Abrahams: Should I write a newsletter?Mark Lee: Can I target my posts to certain locations?Clip from my UpLift Live 26 talk on "direct messages and algorithmic immunity".I put in around 12 hours of editing time to get the replays ready, and we have about 17.5 hours of content in total now available over the past 3 years of the conference.Get your replay ticketSocial Insider report on document post engagement ratesLook out for messages saying "Email not reachable" and "Update your email to ensure you don't lose access to your account" – they're legitimate messages but seem to be associated only with LinkedIn accounts that have Gmail email addresses. Hopefully, this is a temporary issue only.Ryan Roslansky's book: Open To Work released

Algorithmic border systems are quietly reshaping global mobility; passport rankings fail to capture the risk.View the full article here.Subscribe to the IMI Daily newsletter here. 

Today's MadTech Daily covers Meta announcing reduced reliance on third-party vendors as it expands its AI tools, Walmart securing two new patents for algorithmic pricing, and OpenAI planning a desktop superapp. 

Thank you to Cisco for sponsoring this video and sponsoring my trip to Cisco Live Amsterdam 2026. In this interview, Cisco VP Rick Miles breaks down the evolution of the firewall, the massive hardware leap of the 6100 series, and how AI agents and eBPF are completely reshaping the industry. Whether you're trying to secure AI models against prompt injection or wondering if AI will replace your networking job by 2030, this is the technical reality check every engineer needs to hear right now. Has the role of the traditional firewall changed? Rick Miles, VP of Product at Cisco, joins David Bombal at Cisco Live EMEA to reveal the massive architectural shift from static "firewalls" to dynamic "firewalling." This deep-dive interview covers the incredible specs of the new Cisco Secure Firewall 6100 series—boasting 80% less space, 60% less power, and up to 8 Terabits of clustered throughput in a 2RU form factor. We also explore how eBPF is revolutionizing deep visibility and virtual patching directly at the application layer, moving security beyond the edge. But hardware is only half the story. We also break down the new "Wild West" of AI cybersecurity. Learn how to secure the network against prompt injection, poisoned AI models, and unsecured Model Context Protocols (MCP). Finally, Rick shares his vision for 2030: "Agentic" security. Will AI agents replace network engineers, or will they become the ultimate force multiplier for your career? // Rick Miles' SOCIAL // LinkedIn: / rcmiles09 // David's SOCIAL // Discord: discord.com/invite/usKSyzb Twitter: www.twitter.com/davidbombal Instagram: www.instagram.com/davidbombal LinkedIn: www.linkedin.com/in/davidbombal Facebook: www.facebook.com/davidbombal.co TikTok: tiktok.com/@davidbombal YouTube: / @davidbombal Spotify: open.spotify.com/show/3f6k6gE... SoundCloud: / davidbombal Apple Podcast: podcasts.apple.com/us/podcast... // MY STUFF // https://www.amazon.com/shop/davidbombal // SPONSORS // Interested in sponsoring my videos? Reach out to my team here: sponsors@davidbombal.com // MENU // 0:00 - Coming Up 0:19 - Introduction 01:17 - Are Firewalls Dead? 04:18 - Cisco and Firewalls 08:30 - Hyperscalers vs Neo-Clouds vs Enterprises 10:46 - EBPF and Switches as Firewalls 14:32 - Managing your Hybrid Mesh Firewall 16:20 - Cisco's Compatibility with other Firewalls 17:40 - Identity within Systems 19:05 - More on Hybrid Mesh Firewall 19:53 - Model Context Protocol and Security 23:57 - The Future of “Firewalling” 25:15 - The Effect of Agentic AI 26:57 - Will AI take all our Jobs? 27:56 - Should you get into Cyber Security? 28:48 - Cool Story about Firewall 30:30 - Talk to your Younger Self 32:32 - Does AI give Advantage to Attackers? 33:09 - Outro Please note that links listed may be affiliate links and provide me with a small percentage/kickback should you use them to purchase any of the items listed or recommended. Thank you for supporting me and this channel! Disclaimer: This video is for educational purposes only. #firewall #cisco #cybersecurity

In Episode 129 of DC EKG, Joe Grogan sits down with returning guest Adam Thierer, Resident Senior Fellow for Technology and Innovation at the R Street Institute, to break down the surge of state by state AI laws and why a patchwork approach could slow innovation, especially in healthcare. Adam explains how more than a thousand state AI bills are flooding the zone, what types of “everything bills” are emerging, and why some states are trying to set national standards from Albany or Sacramento. Joe and Adam connect the federalism debate to real world health innovation, including mental health chatbots, algorithmic discrimination laws, and why compliance costs hit “little tech” hardest. They also discuss Adam's “AI Articles of Confederation” framing, the failed effort to create a federal moratorium on state AI rules, and what a better model could look like, such as regulatory inventories, learning labs, and sandbox style approaches that allow experimentation without shutting innovation down. Key link: https://www.rstreet.org/commentary/congress-should-lead-on-ai-policy-not-the-states/ In This Conversation Why state AI bills are accelerating and what is driving them “Mega measures” that try to regulate frontier models, child safety, jobs, and copyright in one bill New York and California style rulemaking with national spillover The Micron example and how permitting and lawsuits can stop progress Algorithmic discrimination laws and why healthcare gets hit hardest Mental health chatbot bans and the access and workforce tradeoffs Preemption and why Congress keeps punting Alternative models: inventories, learning labs, sandboxes, and targeted gap fixes Timestamps0:00 What is happening with state AI bills right now1:36 Adam's background and how he got into AI policy5:55 The shift from federal regulation to state action10:27 What these state bills try to regulate13:29 Micron, permitting delays, and stopping progress20:00 Why some red states are pushing AI Bills of Rights26:24 “AI Articles of Confederation” and why it matters31:01 The attempted moratorium in the “big, beautiful bill”38:03 Preview of “The AI Terrible Ten” and worst state models39:43 Mental health chatbot bans and the mental health crisis44:25 What governors should do instead of rushing to regulate49:05 What Adam is tracking next51:48 What AI tools Adam uses52:42 Where to find Adam's work SEO Keywordsstate AI laws, AI policy, federal preemption, healthcare innovation, algorithmic discrimination, mental health chatbots, interoperability, AI regulation About Our GuestAdam Thierer is a Resident Senior Fellow at the R Street Institute focused on technology and innovation policy. He writes and speaks widely on AI governance, federalism and preemption, and how regulatory models can either accelerate or stall innovation, including in healthcare. Podcast: DC EKG with Joe GroganEpisode: 129Guest: Adam Thierer, Resident Senior Fellow, Technology and Innovation, R Street InstituteSponsor: Survivors for Solutions – https://survivorsforsolutions.orgExecutive Producer: John “CZ” Czwartacki, DC EKG PodcastProducer: Julie Riga, Stay on Course Studios – https://www.stayoncourse.studio

In Episode 129 of DC EKG, Joe Grogan sits down with returning guest Adam Thierer, Resident Senior Fellow for Technology and Innovation at the R Street Institute, to break down the surge of state by state AI laws and why a patchwork approach could slow innovation, especially in healthcare. Adam explains how more than a thousand state AI bills are flooding the zone, what types of “everything bills” are emerging, and why some states are trying to set national standards from Albany or Sacramento. Joe and Adam connect the federalism debate to real world health innovation, including mental health chatbots, algorithmic discrimination laws, and why compliance costs hit “little tech” hardest. They also discuss Adam's “AI Articles of Confederation” framing, the failed effort to create a federal moratorium on state AI rules, and what a better model could look like, such as regulatory inventories, learning labs, and sandbox style approaches that allow experimentation without shutting innovation down. Key link: https://www.rstreet.org/commentary/congress-should-lead-on-ai-policy-not-the-states/ In This Conversation Why state AI bills are accelerating and what is driving them “Mega measures” that try to regulate frontier models, child safety, jobs, and copyright in one bill New York and California style rulemaking with national spillover The Micron example and how permitting and lawsuits can stop progress Algorithmic discrimination laws and why healthcare gets hit hardest Mental health chatbot bans and the access and workforce tradeoffs Preemption and why Congress keeps punting Alternative models: inventories, learning labs, sandboxes, and targeted gap fixes Timestamps0:00 What is happening with state AI bills right now1:36 Adam's background and how he got into AI policy5:55 The shift from federal regulation to state action10:27 What these state bills try to regulate13:29 Micron, permitting delays, and stopping progress20:00 Why some red states are pushing AI Bills of Rights26:24 “AI Articles of Confederation” and why it matters31:01 The attempted moratorium in the “big, beautiful bill”38:03 Preview of “The AI Terrible Ten” and worst state models39:43 Mental health chatbot bans and the mental health crisis44:25 What governors should do instead of rushing to regulate49:05 What Adam is tracking next51:48 What AI tools Adam uses52:42 Where to find Adam's work SEO Keywordsstate AI laws, AI policy, federal preemption, healthcare innovation, algorithmic discrimination, mental health chatbots, interoperability, AI regulation About Our GuestAdam Thierer is a Resident Senior Fellow at the R Street Institute focused on technology and innovation policy. He writes and speaks widely on AI governance, federalism and preemption, and how regulatory models can either accelerate or stall innovation, including in healthcare. Podcast: DC EKG with Joe GroganEpisode: 129Guest: Adam Thierer, Resident Senior Fellow, Technology and Innovation, R Street InstituteSponsor: Survivors for Solutions – https://survivorsforsolutions.orgExecutive Producer: John “CZ” Czwartacki, DC EKG PodcastProducer: Julie Riga, Stay on Course Studios – https://www.stayoncourse.studio

Zapata's back! A tough stretch including a difficult SPAC deal, a brief move into AI, and a $20 million debt forced the company to shut down in 2024. But in this episode, Sumit Kapur, CEO of Zapata Quantum, talks with host Konstantinos Karagiannis about how the company made a remarkable comeback. They discuss the intense restructuring, the strong support from the quantum computing industry, and how Zapata's seven years of intellectual property proved too valuable to give up.The conversation goes into the prospects of quantum utility, focusing on Quantum Intermediate Representation (QIR)—a universal translator that abstracts the immense complexity of hybrid computing. Sumit explains why the industry is entering a critical arms race for application intelligence and why even skeptics are now predicting that milestones like Shor's algorithm could be achieved far sooner than previously imagined. From collaborating with DARPA on quantum benchmarking to finding the company's new north star in a post-SPAC world, this episode showcases resilience plus a forward-looking roadmap for the next decade of quantum edge.For more information on Zapata Quantum, visit https://zapataquantum.com/.   Visit Protiviti at www.protiviti.com/US-en/technology-consulting/quantum-computing-services to learn more about how Protiviti is helping organizations get post-quantum ready.  Follow host Konstantinos Karagiannis on all socials: @KonstantHacker and follow Protiviti Technology on LinkedIn and X: @ProtivitiTech.             Questions and comments are welcome!  Theme song by David Schwartz, copyright 2021.  The views expressed by the participants of this program are their own and do not represent the views of, nor are they endorsed by, Protiviti Inc., The Post-Quantum World, or their respective officers, directors, employees, agents, representatives, shareholders, or subsidiaries.  None of the content should be considered investment advice, as an offer or solicitation of an offer to buy or sell, or as an endorsement of any company, security, fund, or other securities or non-securities offering. Thanks for listening to this podcast. Protiviti Inc. is an equal opportunity employer, including minorities, females, people with disabilities, and veterans.  

In this conversation, Columbia University psychiatrist Dr. Ragy Girgis joins DemystifySci to explore why psychological breakdowns appear to be rising in modern society. The discussion examines the limits of current mental health frameworks, the role of medication, and the importance of relationships and community in stabilizing people during periods of distress. The episode also looks at how social media and AI systems can unintentionally reinforce harmful patterns of thinking by mirroring users back to themselves. Together they ask whether the real crisis lies less in individual minds and more in the systemic cages enclosing them.Part 2: https://youtu.be/nBi72lYjmSEPATREON https://www.patreon.com/c/demystifysciPARADOX LOST PRE-SALE: https://buy.stripe.com/7sY7sKdoN5d29eUdYddEs0bHOMEBREW 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-herePARADIGM DRIFThttps://demystifysci.com/paradigm-drift-show00:00 Go! 05:39 Have we ever understood psychological distress well?09:38 The culture of medication in modern mental health care13:55 The role of expectation and the therapeutic relationship17:34 Measuring outcomes in psychiatric treatment21:31 Why treatment effectiveness remains controversial22:27 Spiritual frameworks and historical approaches to psychological suffering25:08 What counts as a successful outcome in mental health care27:26 Ritual, belief, and psychological influence33:37 Community, belonging, and long-term stability34:48 Biological complexity behind severe mental conditions37:04 The limits of medication alone38:25 Early support and rebuilding a shared sense of reality41:22 Creativity, emotional intensity, and personality traits43:38 AI systems and the mirroring of unstable thinking46:10 Digital platforms as social infrastructure51:45 Algorithmic incentives and public well-being57:16 Governance, responsibility, and civic health01:00:21 Online cult dynamics and social fragmentation01:02:58 Digital echo chambers versus real community01:05:14 Cultural drivers of psychological distress01:08:41 Media, culture, and rising social instability#mentalhealthawareness #PsychologyPodcast#HumanBehavior#Psychology#SocialMediaPsychology#consciousness #physicspodcast #philosophypodcast MERCH: 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

Welcome to Show Me The Money Club live show with Sergio and Chris Tuesdays 6pm est/3pm pst.

This Day in Legal History: Boston MassacreOn March 5, 1770, a confrontation between British soldiers and American colonists in Boston turned deadly in what became known as the Boston Massacre. Tensions had been rising for months as British troops occupied the city to enforce parliamentary taxes that many colonists believed were unjust. On that evening, a crowd gathered near the Boston Custom House and began taunting a British sentry, shouting insults and throwing snowballs and debris. As the situation escalated, additional soldiers arrived to support the guard, but the crowd continued to press in. In the confusion and fear of the moment, the soldiers fired into the crowd. Five colonists were killed and several others were wounded, including Crispus Attucks, who is often remembered as the first casualty of the American Revolution.The incident quickly became a flashpoint in colonial politics, with patriot leaders using it as evidence of British tyranny. Yet the legal response that followed was notable for its commitment to due process despite intense public anger. British Captain Thomas Preston and eight soldiers were arrested and charged with murder. Future president John Adams agreed to defend the soldiers, arguing that the rule of law required even deeply unpopular defendants to receive a fair trial. During the proceedings, Adams emphasized the evidence suggesting the soldiers had been surrounded and threatened by a hostile crowd. The jury ultimately acquitted six soldiers and convicted two of the lesser charge of manslaughter.The trials demonstrated an early American commitment to the principle that legal judgments should be guided by evidence rather than public pressure, even during moments of political upheaval.The U.S. Supreme Court ruled that New Jersey cannot use sovereign immunity to protect New Jersey Transit from personal injury lawsuits filed by riders injured outside the state. The unanimous opinion, written by Sonia Sotomayor, resolved a conflict between the Pennsylvania Supreme Court and the New York Court of Appeals over whether the transit agency qualifies as an “arm of the state.” The dispute arose from two lawsuits filed by passengers injured in NJ Transit bus crashes that occurred outside New Jersey.The justices focused heavily on how the agency was structured. During oral argument, several members of the Court questioned why New Jersey created NJ Transit as a corporation with the ability to sue and be sued while also disclaiming responsibility for its debts. Some justices suggested those design choices undermined the state's argument that the agency should receive sovereign immunity protections.New Jersey's lawyers argued that the agency's independence is largely formal and that the governor maintains significant control over the system. They also warned that allowing such lawsuits could subject the state to litigation in other states' courts. However, the Court appeared unconvinced by those arguments and emphasized that the plaintiffs were private individuals seeking compensation rather than other states trying to regulate New Jersey.The ruling ultimately sided with the New York court's earlier decision and overturned the Pennsylvania ruling, allowing the personal injury lawsuits to proceed.Supreme Court Rejects NJ Immunity Defense In NY, Pa. SuitsRegulators are increasingly focusing on dynamic or algorithmic pricing, a practice that uses personal data—such as location, browsing history, and purchasing behavior—to set individualized prices for consumers. The approach has raised concerns among privacy and consumer protection regulators because it relies on large amounts of personal data and may affect price transparency. Although grocery pricing has drawn the most attention, the practice is also used in industries like travel, financial services, and online retail.The Federal Trade Commission has been studying the issue but has not clearly stated whether dynamic pricing violates any specific federal law. In 2024, the agency issued subpoenas to companies that develop pricing algorithms to learn how they collect consumer data, train their systems, and influence the prices consumers see. A preliminary research summary released in 2025 confirmed that these tools rely heavily on consumer data and can adjust prices in real time, but it did not identify specific legal violations.While the federal approach remains uncertain, state regulators are taking more direct action. The office of Rob Bonta, the California attorney general, launched an investigative sweep in January 2026 to examine how companies use consumer data to personalize prices. Investigators sent letters to retailers, grocery stores, and hotels requesting information about pricing algorithms, data sources, and disclosures to consumers.Meanwhile, the New York Attorney General's Office is investigating companies' compliance with the state's new Algorithmic Pricing Disclosure Act. The law requires businesses to clearly inform consumers when prices are generated using algorithms that rely on their personal data. Regulators have warned that disclosures hidden behind hyperlinks may not satisfy the law's requirement that notices be clear and conspicuous.Other states are considering similar legislation, including proposals targeting surveillance-based pricing or banning dynamic pricing in certain industries. As scrutiny increases, companies that use personalized pricing tools are being urged to review their data practices, pricing disclosures, and compliance with emerging state privacy laws.Amidst uncertainty from FTC, states zero in on dynamic and algorithmic pricing | ReutersThe U.S. civilian federal workforce decreased by about 12% between September 2024 and January 2026, according to newly released government data. The reductions reflect efforts by Donald Trump's administration to shrink federal agencies, a policy he promoted as a way to reduce government size and increase efficiency.Several major departments experienced significant staffing losses. The U.S. Department of the Treasury saw its workforce drop by roughly 24%, while the U.S. Department of Health and Human Services lost about 20% of its employees during the same period. These reductions represent some of the largest declines across federal agencies.One notable exception was the U.S. Department of Homeland Security, which slightly increased its workforce by less than 1%. The agency's growth reflects the administration's continued focus on immigration enforcement and deportation efforts.Overall, the data indicates that the administration's push to cut federal staffing has had a broad impact across much of the government, significantly reducing the number of civilian employees in many departments.US government workforce shrunk by 12% since September 2024 | Reuters This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.minimumcomp.com/subscribe

In this latest episode of the OIES podcast series, Bassam Fattouh (Director of the Oxford Institute for Energy Studies) discusses with Ilia Bouchouev (managing partner at Pentathlon Investments, Senior Research Fellow at OIES, and adjunct Professor at New York University) recent trends in options trading, algorithmic trading and hedge fund strategies that are shaping oil markets. Based on […] The post OIES Podcast – Algorithmic Oil Traders, Hedge Fund Strategies and Oil Markets appeared first on Oxford Institute for Energy Studies.

Margarine money grab, Crowdsourced landlords, Liquidity at the laundromat, Banana bills, Kosovo crackdowns, Expensive password recovery, Algorithmic landlord, Cash comparisons. Jennifer, Angie, Way, and Bradley discuss a variety of curated links from the archives. Please consider supporting this ad-free content on Patreon.

Corner office churn is up as demands multiply. Heidrick & Struggles' CEO explains what CVs leave out and why flexibility and organizational fit matter more as AI and global volatility undercut the predictive power of past performance. Also, AI-enhanced recruiting and lifelong learning.

The integration of Artificial Intelligence (AI) into post-injury rehabilitation is transforming recovery paradigms by enabling personalized, adaptive, and efficient rehabilitation pathways tailored to individual patient needs. This podcast reviews the current advances in AI applications that facilitate assessment, monitoring, and optimization of rehabilitation programs following injuries. Through machine learning algorithms, wearable sensors, and predictive analytics, AI enhances the precision of therapy plans, tracks patient progress in real-time, and predicts recovery trajectories. The discussion includes the benefits of AI-driven rehabilitation, including improved functional outcomes, reduced recovery times, and increased patient engagement. It also addresses challenges such as data privacy, algorithmic bias, and integration with clinical workflows.  1. Transforming recovery paradigms Traditional post‑injury rehab relies on periodic in‑person assessments, therapist intuition, and standardized protocols that only partially account for individual variability. AI is shifting this model toward: Continuous, data‑driven care: Instead of snapshots in clinic, rehab can be informed by near real‑time streams of kinematic, physiological, and behavioral data from wearables, smart devices, and robot interfaces. Dynamic adaptation: Therapy intensity, task difficulty, and exercise selection can be automatically adjusted based on ongoing performance, fatigue, and recovery trends, rather than fixed schedules. Precision rehabilitation: Algorithms can identify which patients are likely to respond to specific interventions (e.g., constraint‑induced movement therapy vs robotics) and tailor plans accordingly. This moves rehabilitation from a "one‑size‑fits‑many" paradigm toward precision, context‑aware therapy, analogous to precision oncology but focused on function and participation. 2. Assessment, monitoring, and optimization AI for assessment Sensor‑based movement analysis: Machine learning models process accelerometer, IMU, EMG, and pressure data to quantify gait symmetry, joint kinematics, balance, and fine motor control with higher resolution than visual observation alone. Automated scoring: AI can approximate or support standardized scales (e.g., Fugl‑Meyer, Berg Balance Scale) by mapping sensor features or video-derived pose estimates to clinical scores, reducing inter‑rater variability and saving clinician time. Continuous monitoring Home and community tracking: Wearable and ambient sensors enable monitoring of daily steps, walking speed, arm use, posture, and adherence to exercises outside the clinic, feeding rich longitudinal datasets into AI models. Real‑time alerts: Algorithms can detect abnormal patterns—such as increased fall risk, reduced limb use, or signs of over‑exertion—and flag the clinician or adjust digital therapy content automatically. Optimization and decision support Predictive models: Using historical data, AI can forecast functional gains, plateau points, or risk of complications (e.g., falls, readmission), supporting individualized goal‑setting and resource allocation. Reinforcement learning and "digital twins": Emerging work in neurorehabilitation treats rehab as a sequential decision problem, using model‑based reinforcement learning and patient "digital twins" to recommend optimal timing, dosing, and progression of interventions over weeks to months.​ 3. Technologies: ML, wearables, analytics Machine learning algorithms: Supervised ML classifies movement quality (normal vs compensatory), detects exercise type from sensor streams, and estimates clinical scores. Unsupervised learning clusters patients into phenotypes (e.g., gait patterns after stroke), revealing subgroups that respond differently to certain therapies. Reinforcement learning and contextual bandits explore which therapy adjustments yield the best long‑term functional outcomes for a given individual.​ Wearable sensors and robotics: Inertial sensors, EMG, pressure insoles, and exoskeleton sensors capture high‑frequency movement and muscle activity data during training. Robotic devices (upper‑limb exoskeletons, gait trainers) coupled with AI can modulate assistance, resistance, or task difficulty in real time based on performance and predicted fatigue. Predictive and prescriptive analytics: Predictive analytics estimate trajectories (e.g., time to independent walking, expected upper‑limb function) to inform shared decisions with patients and families. Prescriptive analytics recommend therapy intensity, modality mix, and scheduling to maximize functional gains under resource constraints. 4. Benefits: outcomes, efficiency, engagement Improved functional outcomes: Studies report better motor recovery, gait quality, and ADL performance when AI‑assisted training is used—especially when robotics and intelligent feedback are involved. Reduced recovery time and resource use: More precise dosing and earlier identification of non‑responders can reduce ineffective sessions, shorten time to key milestones, and support safe earlier discharge with robust remote follow‑up. Increased adherence and engagement: AI‑driven digital rehab platforms use gamification, adaptive difficulty, and personalized feedback to keep patients engaged in home programs, improving adherence compared to static paper instructions. Support for clinicians: Instead of replacing therapists, AI can offload repetitive measurement tasks, highlight concerning trends, and offer data‑driven suggestions, allowing clinicians to focus on relational, motivational, and complex decision‑making aspects of care. 5. Challenges and ethical considerations Data privacy and security: Rehab AI often relies on continuous collection of sensitive motion, physiological, and sometimes audio/video data, raising questions about consent, storage, secondary use, and breach risk. Approaches like federated learning and on‑device processing are being explored to reduce centralization of identifiable data while still enabling model training. Algorithmic bias and fairness: If training data under‑represent older adults, women, certain racial/ethnic groups, or people with severe disability, AI models may misestimate performance or risk for those groups, potentially widening disparities in rehab access and outcomes. Ongoing auditing, diverse datasets, and participatory design with patients and clinicians are needed to ensure equitable performance. Integration with clinical workflows: Many AI tools are developed in research settings and are not yet seamlessly integrated into EHRs, scheduling systems, or therapist documentation workflows. Poorly integrated tools risk adding documentation burden or "alert fatigue," reducing adoption. Successful implementations co‑design interfaces with frontline therapists and physicians. Regulation, liability, and trust: It remains unclear in many jurisdictions how to regulate adaptive rehab algorithms (as medical devices, clinical decision support, or wellness tools) and who is liable when AI‑informed plans cause harm.​ Transparent, explainable models and clear communication to patients about the role of AI are critical for maintaining trust. 6. Case studies and emerging trends Remote and hybrid digital rehabilitation: AI‑driven platforms providing home‑based stroke, orthopedic, or Parkinson's rehab with clinician dashboards are improving adherence and extending care beyond brick‑and‑mortar clinics. Collaborative AI for precision neurorehabilitation: Frameworks combining patient‑clinician goal setting, digital twins, and reinforcement learning exemplify "collaborative AI" that augments rather than replaces therapists.​ Multimodal personalization: Integration of movement data, EMG, heart rate, sleep, and self‑reported pain/fatigue is enabling more nuanced adaptation to daily fluctuations in capacity. Conversational AI for education and coaching: Early work is assessing tools like ChatGPT as low‑risk supports for exercise education and motivation, though they are not yet precise enough to replace professional plan design AI is moving rehab toward patient‑centered, continuously adapting, and data‑rich care, but realizing this promise depends on addressing privacy, bias, workflow, and regulatory challenges in partnership with clinicians and patients.

As AI technologies proliferate, a growing number of people are asking what it means to live in a world dominated by algorithms and automated systems—and what gets lost when those systems optimize human behavior at scale. These questions sit at the intersection of political theory, technology policy, and everyday life, and they are drawing scholars from fields well outside computer science into the conversation.José Marichal is a political scientist at California Lutheran University who has been writing and teaching about technology and politics for more than two decades. Marichal's new book, You Must Become an Algorithmic Problem: Renegotiating the Socio-Technical Contract, considers the age of recommendation systems and large language models. Drawing on political philosophy, he argues that individuals have entered into an implicit bargain with technology companies, trading unpredictability and novelty for the convenience of algorithmically curated experience. The consequences of that bargain, he contends, reach beyond personal preference and into the foundations of liberal democratic citizenship.

Kartik Hosanagar has been tracking AI long before “ChatGPT” became a household word, and in this conversation with Ginny Yurich, he helps parents see what's already shaping their homes (and possibly children). AI can affect what we watch, what we buy, what we believe, who we date, and our career paths. Drawing from his book A Human's Guide to Machine Intelligence, Kartik explains how machines stopped simply following “recipe-like” instructions and began learning like children do—surprising us, improvising, and sometimes operating as black boxes we can't fully interpret. You'll hear the jaw-dropping story of the early chatbots that felt like real friends, why recommendation engines narrow our options without us noticing, and what it looks like to reclaim agency by adding “friction” back into family life. This episode is both a wake-up call and a steadying roadmap for staying human in an algorithmic world. Get a copy of the Book: A Human's Guide to Machine Intelligence Check out Kartik's Substack Creative Intelligence: https://hosanagar.substack.com Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode, Ted Striphas, Jeffrey Herlihy-Mera and Alex Rivera Cartagena discuss Algorithmic Culture Before the Internet (Columbia University Press 2023), considering how some pre-digital human systems functioned through repetitive structures and automated processes that have similarities to electronic algorithms. They discuss how cognition has become digitized, dispersed across algorithmic and biological systems, and how digital tools attempt to overtake lived experiences and knowledges. Their conversation traces the history of computation while engaging culture and language as analytical tools. Their dialogue connects analog media, cultural practices, and symbolic systems to reflect on the importance of words in the human experience. Long before digital code, verbal narratives shaped (or attempted to shape) our relationship with knowledge and power; building on that insight, an important analytical point to critique algorithms begins with culture, and that culture begins in language. This episode and the Instituto Nuevos Horizontes are sponsored in part by the Teagle Foundation.Our conversation in Spanish about Algorithmic Culture Before the Internet is available here. Topics and scholars mentioned in this episode: Héctor José Huyke, Elogio a las cercanías: crítica a la cultura tecnológica actual (Editora Educación Emergente, 2024). The Late Age of Print: Everyday Book Culture from Consumerism to Control (Columbia University Press, 2011). Erik Hoel's notion of a “consciousness winter.” Lawrence Grossberg Medium theory Joshua Myerwicz Janice Radway Scriptocentrism “Things that different forms of media do to us.” -Ted Striphas Scott Kushner, University of Rhode Island, “A turnstile is more persuasive than a person saying 'go this way.'" Alan Touring The Late Age of Print: Blog and book "The locus of cultural decision making [has been] shifting in the direction of computer systems and algorithms." -Ted Striphas “Build different meanings of words so we can build different worlds,” -Ted Striphas. “What is culture when human beings are not the only one producing it?” -Ted Striphas Pluriverse, A Post-Development Dictionary (Columbia University Press, 2019), edited by Ashish Kothari, Ariel Salleh, Arturo Escobar, Federico Demaria, and Alberto Acosta. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Gus Wenner, chairman of Rolling Stone and son of the magazine's legendary founder, has spent years balancing the brand's print heritage with its digital transformation. On this week's Mixed Signals, Ben and Max talk with Wenner about his new holding company, Wenner Media Ventures, and why he thinks algorithms  disrespect audiences. They also discuss the venture's investment in the hit video series Track Star, his defense of Rolling Stone's most provocative journalism, and his potential future media investments.

En este episodio, Jeffrey Herlihy-Mera, Catedrático de Humanidades de la Universidad de Puerto Rico-Mayagüez, y Alex Rivera Cartagena de la Universidad de Puerto Rico-Mayagüez, conversan sobre Algorithmic Culture Before the Internet (Columbia U. Press, 2023) por Ted Striphas, considerando cómo un mundo predigital funcionaba por estructuras repetitivas y procesos automáticos. Ponemos especial atención en la lengua como tecnología fundamental: un sistema de reglas compartidas que hace posible el pensamiento, la memoria y la comunicación. Si las palabras no sólo describen la realidad, también la ordenan, la limitan y la expanden. A través del lenguaje, las culturas transmiten patrones, valores y formas de interpretar lo humano, funcionando como algoritmos vivos que se reescriben con el tiempo. Este episodio conecta medios analógicos, prácticas culturales y sistemas simbólicos para reflexionar sobre la importancia de las palabras en la experiencia humana y en la memoria colectiva. Considera las instrucciones, gramáticas y narrativas que moldean (o intentan moldear) nuestra relación con el conocimiento y el poder. Un espacio para entender que los algoritmos comienzan en la cultura, y como tanto, la cultura comienza en el lenguaje, y el lenguaje comienza en la palabra. Este podcast y el Instituto Nuevos Horizontes son patrocinados por el Departamento de Humanidades. Temas dialogados: Un momento cuando “The solution is now the problem.” Facebook, las emociones y la capacidad social Criticando el género, la raza, la etnicidad, el grupo lingüístico y otras categorías aprobadas por el imperio. Imperialismo Cultural “Scriptocentrism” La improvisación y el pensamiento La improvisación y la docencia “indoor lives” Cómo la infraestructura impacta al pensamiento. Cuando una escasez de tecnología es saludable en Cuba. Carlos Alberto Peón Casas, Universidad de Camagüey y “la naturaleza profunda de su relación con las palabras.” Steve Jobs Martin Luther King Scott Kushner Héctor Huyke y las tertulias de la UPR-M David Lorenzo Milena Pi Reyes “La mejor versión de sí mismo” como lema de los 1990. Cultura tecnológica El lenguaje de la imagen (imagen-centrismo) Vídeo-centrismo La universidad y la tecnología de la educación Estados Unidos como mito recientemente desarrollado. La conducta que los algoritmos desean establecer en nosotros. Learn more about your ad choices. Visit megaphone.fm/adchoices

Jordan Harbinger Show: Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- Remember when Facebook was fun and Google actually worked? Cory Doctorow coined a term for what went wrong, and he's here to explain how we fight back.Full show notes and resources can be found here: jordanharbinger.com/1280What We Discuss with Cory Doctorow:"Enshittification" is Cory Doctorow's term for how platforms decay. First they're good to users, then they abuse users to serve business customers, then they abuse everyone to claw back value for themselves. Facebook, Amazon, and Google all followed this playbook — and policy makers let it happen."Switching costs" are a deliberate policy choice, not an inevitability. Companies jack up the friction of leaving their platforms through design and lobbying, but regulations like phone number portability prove we can legislate friction down when we choose to.The Digital Millennium Copyright Act criminalizes fixing things you own. Security researchers who expose corporate sabotage — like the Polish train company bricking locomotives to extort customers — face harsher legal consequences than actual pirates."Algorithmic wage discrimination" is surveillance capitalism's newest trick. Apps like Uber track how desperate workers are and pay them less accordingly — the more rides you accept, the lower your future offers, turning desperation into a permanent wage ceiling.You can fight back by supporting interoperability and making strategic choices. Use alternative services (like Kagi for search), follow advocates like the Electronic Frontier Foundation (eff.org), and remember: every time you demand the right to own what you buy, you're pushing back against enshittification.And much more...And if you're still game to support us, please leave a review here — even one sentence helps! Sign up for Six-Minute Networking — our free networking and relationship development mini course — at jordanharbinger.com/course!Subscribe to our once-a-week Wee Bit Wiser newsletter today and start filling your Wednesdays with wisdom!Do you even Reddit, bro? Join us at r/JordanHarbinger!This Episode Is Brought To You By Our Fine Sponsors: Article: Visit article.com/jordan for $50 off your first purchase of $100 or moreBetterHelp: 10% off first month: betterhelp.com/jordanBombas: Go to bombas.com/jordan to get 20% off your first orderButcherBox: Free protein for a year + $20 off first box: butcherbox.com/jordanHomes.com: Find your home: homes.comSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

We know that companies are gathering data on us as we go about our lives online, but that information might also be used to create a personalized price for something you're looking at buying. We hear from Jim Balsellie, the co-founder of the Council of Canadian Innovators and the Digital Governance Council, on how algorithmic pricing works and what guardrails need to be put in place.

Remember when Facebook was fun and Google actually worked? Cory Doctorow coined a term for what went wrong, and he's here to explain how we fight back.Full show notes and resources can be found here: jordanharbinger.com/1280What We Discuss with Cory Doctorow:"Enshittification" is Cory Doctorow's term for how platforms decay. First they're good to users, then they abuse users to serve business customers, then they abuse everyone to claw back value for themselves. Facebook, Amazon, and Google all followed this playbook — and policy makers let it happen."Switching costs" are a deliberate policy choice, not an inevitability. Companies jack up the friction of leaving their platforms through design and lobbying, but regulations like phone number portability prove we can legislate friction down when we choose to.The Digital Millennium Copyright Act criminalizes fixing things you own. Security researchers who expose corporate sabotage — like the Polish train company bricking locomotives to extort customers — face harsher legal consequences than actual pirates."Algorithmic wage discrimination" is surveillance capitalism's newest trick. Apps like Uber track how desperate workers are and pay them less accordingly — the more rides you accept, the lower your future offers, turning desperation into a permanent wage ceiling.You can fight back by supporting interoperability and making strategic choices. Use alternative services (like Kagi for search), follow advocates like the Electronic Frontier Foundation (eff.org), and remember: every time you demand the right to own what you buy, you're pushing back against enshittification.And much more...And if you're still game to support us, please leave a review here — even one sentence helps! Sign up for Six-Minute Networking — our free networking and relationship development mini course — at jordanharbinger.com/course!Subscribe to our once-a-week Wee Bit Wiser newsletter today and start filling your Wednesdays with wisdom!Do you even Reddit, bro? Join us at r/JordanHarbinger!This Episode Is Brought To You By Our Fine Sponsors: Article: Visit article.com/jordan for $50 off your first purchase of $100 or moreBetterHelp: 10% off first month: betterhelp.com/jordanBombas: Go to bombas.com/jordan to get 20% off your first orderButcherBox: Free protein for a year + $20 off first box: butcherbox.com/jordanHomes.com: Find your home: homes.comSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Dr. Kelly Cohen is a Professor of Aerospace Engineering at the University of Cincinnati and a leading authority in explainable, certifiable AI systems. With more than 31 years of experience in artificial intelligence, his research focuses on fuzzy logic, safety-critical systems, and responsible AI deployment in aerospace and autonomous environments. His lab's work has received international recognition, with students earning top global research awards and building real-world AI products used in industry.In this episode 190 of the Disruption Now Podcast,

Andrew Parish is the co-founder of Arch Public. In this conversation, we discuss tokenization, the New York Stock Exchange's latest announcement, and the growing role of algorithmic trading in crypto markets. We also break down bitcoin's recent price action, regulation and the Clarity Act in Washington, and how new AI tools are changing the way companies like Arch Public are built.======================BitcoinIRA: Buy, sell, and swap 80+ cryptocurrencies in your retirement account. Take 3 minutes to open your account & get connected to a team of IRA specialists that will guide you through every step of the process. Go to https://bitcoinira.com/pomp/ to earn up to $1,000 in rewards.======================Simple Mining makes Bitcoin mining simple and accessible for everyone. We offer a premium white glove hosting service, helping you maximize the profitability of Bitcoin mining. For more information on Simple Mining or to get started mining Bitcoin, visit https://www.simplemining.io/======================TIMESTAMPS:0:00 – Intro2:01 – NYSE tokenization announcement & impact of 24/7 markets4:56 – Coinbase & Robinhood vs Wall Street9:30 – Algorithmic trading: stocks vs crypto16:22 – AI agents vs trading algorithms19:52 – Speed, infrastructure & high-frequency trading23:01 – Crypto regulation & the Clarity Act26:19 – U.S. politics, regulation, and bitcoin30:59 – Sovereignty, taxes & asset seizure concerns34:06 – Building Arch Public with new AI dev tools

Former Cracked.com editor Jason Pargin explores the subject of how social media makes us insane and warps the universe we're in, in his new book "I'm Starting to Worry About This Black Box of Doom." He joins to discuss.

Ignite your week with Joe Oltmann Untamed, where Joe drops a bombshell: he's seriously considering a full-throttle run for office, deciding December 26—because neither side has honored the people. With Trump vowing "truckloads" of 2020 election evidence proving it was rigged, Tulsi Gabbard confirming DNI probes into election integrity, and Rasmussen highlighting historic Supreme Court rulings on federal oversight of stolen races, Joe demands justice: prison or death penalty for the thieves who stole our voice. From Colorado's betrayal to threats against patriots like Rep. Brandi Bradley, Untamed exposes the cartel still defying the will of the people—no more half-measures, no more silence.Algorithmic trading powerhouse Nick Pitruzzello—the "Algo Cowboy" and co-founder of Algo Factory—storms in with his 2026 economic and crypto forecast. As debt explodes past $36 trillion and fiat crumbles, Nick's geopolitics-infused algorithms reveal what's coming: dollar devaluation, BRICS rebellion, and whether Bitcoin surges as digital gold or regulators crush the escape hatch. From hyperinflation hedges to altcoin plays in crisis, Nick arms you with high-performance strategies to survive—and thrive—in the chaos ahead. No coding needed, just raw truth for real-market warriors.The world burns while the fight intensifies: Trump's FBI foils an Islamist New Year's Eve bombing in LA, Australia reels from a father-son massacre at Bondi Beach, and Colorado's own radicals threaten families. Joe closes with fire—this is war on evil, from rigged elections to economic slavery.

WarRoom Battleground EP 893: AI The Algorithmic Parasite