Podcasts about Algorithmic

What does it really mean for AI governance to be more than just buzzwords—and how do we build systems that are worthy of our trust? This week on the Tech Humanist Show, we get candid with responsible AI expert and Algorithmic Justice League advisor, Rebekah Tweed. Together, we explore the not-so-glamorous (but oh-so-crucial) world of AI governance—think less “theater,” more real talk on trust, transparency, and protecting our privacy. Topics covered:The evolution of responsible AI as a corporate functionBalancing safety and privacy in AI applicationsAlgorithmic harms in everyday life (hiring, healthcare, security)Why harm in AI is more than just a technical bugOrganizational trust and accountability in AI governancePractical evidence of responsible AI practicesThe importance of transparency, literacy, and public trustBuilding AI governance that is operational—not just performativeRoles for government and open source in shaping responsible AIWhat gives hope for the future of AI and public infrastructureConnect with Rebekah TweedWebsiteLinkedInAI Governance Course on LinkedIn LearningEpisode Chapters:00:04 Introduction to the Tech Humanist Show00:17 Responsible AI Becomes an Organizational Norm01:29 Rebekah Tweed's Journey from Music Industry to AI Governance03:36 AI's Impact on the Creative Arts and Early Influences04:57 The Rise of AI Governance Teams and Job Roles06:12 Building Responsible Tech Career Development07:38 What Responsible AI Means in Human Terms09:36 Algorithmic Harms in Ordinary Life and Public Response15:38 When AI Harm is a Deeper Systems Problem18:57 How to Build Genuine, Non-Theatrical AI Governance25:16 Evidence That AI Governance Is Real29:12 Cultural Weirdness, Systems Strangeness, and Literacy35:13 Speed, Trust, and What Leaders Need to Know37:42 What Gives Hope for a Responsible AI Future40:22 Outro and Credits

Artificial Intelligence is transforming how information moves across society—and that transformation is reshaping democracy itself. In this episode of Soulfood and Lemonade, we examine how A.I.-powered algorithms influence elections, public opinion, and political discourse.From deepfakes and misinformation to psychological voter targeting and surveillance capitalism, A.I. now plays a central role in shaping what we see, believe, and share. Social media platforms prioritize engagement, often amplifying outrage over accuracy. False information spreads faster than facts, and synthetic media blurs the line between reality and fabrication.Democracy depends on informed citizens. But when algorithms determine visibility and digital platforms act as gatekeepers of public conversation, who truly controls the narrative?This episode explores:• Algorithmic bias in political content• Deepfakes and synthetic video manipulation• Data harvesting and behavioral targeting• Corporate control of digital public spaces• The urgent need for media literacyArtificial Intelligence is not inherently dangerous—but unchecked systems without transparency and accountability pose serious risks to democratic participation.If truth becomes programmable, democracy becomes vulnerable.

How do our everyday digital traces—social posts, check-ins, photos—shape our identities, relationships, and the very nature of privacy in a hyper-connected world? Kate O’Neill sits down with Lee Humphreys, professor and Chair of the Department of Communication at Cornell University and author of The Qualified Self: Social Media and the Accounting of Everyday Life. The conversation explores the rich history and surprising continuity of documenting daily life, from centuries-old diaries and photo albums to today's social media and sensor-driven platforms. Topics Covered: The history and meaning of phatic communication Social media as an extension of historical practices (diaries, notebooks, albums) Privacy, data, and the networked self The context collapse of online identities Location-based sharing and identity work Algorithmic identities and platform agency The impact of digital spaces on rituals and remote work Policy, power, and responsibility in platform design Hopeful uses of technology to build community Connect with Lee HumphreysCornell WebsiteLinkedIn”The Qualified Self – Social Media and the Accounting of Everyday Life” Episode Chapters: 00:04 Introduction to the Tech Humanist Show & guest00:17 The concept of phatic communication02:27 Lee's route into communication technology04:42 From photo manipulation to tech distrust06:00 Diaries, Twitter, and the origins of media accounting12:10 Social reinforcement vs. narcissism in social media13:33 Location sharing and its role in identity16:35 Parasocial relationships and context collapse19:53 Data, experience, and mismatched realities22:33 The shifting meaning of place and time in data24:31 Networked privacy and the collective dimension27:39 Incentives, policy, and platform accountability30:01 Algorithmic identity and the “qualified self”35:26 Digital rituals, remote work, and connection40:31 Closing thoughts: technology, humanity, and hope41:04 Lee’s story of hope and innovation through tech42:58 Episode wrap-up and thanks

Host Jeremy Au sits down with two-time founder Justin Banusing, who returns to BRAVE to explain why he shut down a startup that was already working, near $1M ARR and freshly funded, and what that call taught him about building across Southeast Asia and the US. Together they unpack the value-chain trap Justin calls "sharecropping on someone else's land," why college gaming and esports could not become venture-scale businesses, and how the cultural shift from campus gaming to music festivals reshaped his entire thesis on where to build. From AcadArena, the Philippines' first Series A gaming startup, through the AI-companion era of Clout Kitchen, to Clouted, the a16z Speedrun-backed AI virality engine he runs today, Justin traces the difference between revenge founders and missionary founders, why he chose to build again instead of moving into venture capital, and how he thinks about winning what he calls "algorithmic warfare." Jeremy draws out the emotional side of pulling the plug and the discipline behind it. For founders, operators, and investors in Singapore, Indonesia, Vietnam, the Philippines, Thailand, and Malaysia, this is a candid look at product-market fit, distribution, and knowing when to reset. Watch, listen or read the full insight at https://www.bravesea.com/blog/justin-banusing-clouted-ai-virality  BRAVE is Southeast Asia's leading tech podcast, hosted by Jeremy Au. Honest conversations with the region's top founders, investors, and operators on building startups in Southeast Asia. New episodes every week. Subscribe so you never miss one. Listen & Subscribe YouTube (English), YouTube (Bahasa Indonesia), Spotify (English), Spotify (Bahasa Indonesia), Spotify (Chinese), Spotify (Vietnamese), Apple Podcasts Follow BRAVE LinkedIn, X (Twitter), Instagram, TikTok, WhatsApp Follow Jeremy Au LinkedIn, X / Twitter, Instagram, TikTok, Facebook, Threads, Twitch Resources Get transcripts, startup resources & community discussions at www.bravesea.com #StartupFounder #VentureCapital #ArtificialIntelligence #SoutheastAsiaStartups #CreatorEconomy #GoingViral #TechPodcast #Philippines 00:00 Introducing Justin & Clouted 2:31 What Makes Justin a Founder 4:14 The Rise and Fall of College Gaming 6:51 Why Esports Doesn't Scale 10:44 The Messy Exit and a Deliberate Sabbatical 13:16 Founder, Not Investor 17:54 Revenge Startup vs. Missionary Founder 19:51 Building Backseat, the AI Gaming Companion 24:53 Knowing When to Pull the Plug 27:03 Falling for Music and Finding the Real Problem 33:34 Algorithmic Warfare: Why Virality Is Now Engineered 36:57 Inside Clouted: The AI Media Buyer 39:14 The Brave Question and Takeaways

In this episode, Ray Cochrane digs into “algorithmic outing,” new research showing that social feeds can infer your sexual orientation before you have consciously come out. He also covers Meta’s privacy-aware AI infrastructure, Alberta’s 466-million-line code scan with Claude, NVIDIA on reinforcement learning, and the many journeys of learning Rust. Along the way, he hits Google DeepMind’s A24 deal, WhatsApp usernames, and scuba-diving cyborg cockroaches. Finally, he looks up with Webb’s puzzling early universe, NASA’s emergency telescope rescue, and a gorgeous aurora from orbit. – Want to start a podcast? Its easy to get started! Sign-up at Blubrry – Thinking of buying a Starlink? Use my link to support the show. Subscribe to the Newsletter. Email Ray if you want to get in touch! Like and Follow Geek News Central’s Facebook Page. Support my Show Sponsor: Best Godaddy Promo Codes Get 1Password Full Summary Cochrane opens with a quick personal update. He hopes listeners had a good holiday weekend, and he shares that he spent his time working his other job at Oregon’s Finest, chatting with people around Portland. Because his Blurbry workweek tends to be solitary, he refills his social meter on the weekends. He then recalls a Saturday night out with coworkers at the Hungry Tiger before turning to the lead story. Algorithmic Outing: When Your Feed Knows Before You Do Cochrane leads with new research from Australia that identifies a phenomenon called “algorithmic outing.” In short, the recommendation systems behind your social feeds can infer your sexual orientation or gender identity and start serving related content before you have worked it out yourself. Importantly, the study is small and qualitative, built on in-depth interviews with twenty LGBTQ+ adults in the Hunter region of New South Wales and published in the journal Gender, Place and Culture. The mechanism is engagement signals: what you like, who you follow, and how long you linger on a post, a metric the industry calls dwell time. Lead researcher Dr. Justin Ellis of the University of Newcastle notes that several participants said the algorithm “knew” they were queer before they did, an experience that felt validating for some but frightening for others in public settings. For Cochrane, the deeper worry is what else that hidden pattern encodes, from upbringing to mental health, and where that data ultimately gets sold. Sponsor: GoDaddy Economy hosting $6.99/month, WordPress hosting $12.99/month, domains $11.99. Website builder trial available. Use codes at geeknewscentral.com/godaddy to support the show. Meta’s Blueprint for Privacy-Aware AI Infrastructure Next, Cochrane turns to a sharp engineering piece from Meta on privacy-aware infrastructure. The core challenge is that a system must understand what a piece of data actually is before any privacy rule can protect it. A field named “age,” for example, might describe a person in one place and a cache setting in another. Meta’s answer deploys a large language model only on the genuinely ambiguous cases, then distills what it learns into fixed, human-reviewed rules. The payoff is concrete. According to Meta, those deterministic rules already handle about 85 percent of the traffic, and only the last 15 percent falls back to the model, which costs roughly 400 times more compute. Cochrane loves this edge-case approach. However, he contrasts it sharply with the AI-everywhere software he wrestles with at his weekend job, which he says the heavy AI reliance genuinely makes worse and harder to audit. Alberta Scans 466 Million Lines of Code With Claude This one comes from Anthropic, and it ties directly to Meta’s theme. A team inside Alberta’s Ministry of Technology and Innovation used Claude to scan 466 million lines of code in about twenty hours, a review Anthropic estimates would have taken humans roughly six and a half years. Notably, they ran around fifty AI agents in parallel, essentially an automated red team and blue team probing the systems at once. For Cochrane, this is the good version of AI in production: cleaning up and locking down real systems rather than running the show unsupervised. NVIDIA on Reinforcement Learning for AI Agents On the AI-building side, Cochrane walks through an NVIDIA developer piece on reinforcement learning for agents. Reinforcement learning rewards a model for good behavior rather than showing it the right answer, much like training a dog with treats. Additionally, he clears up a common mix-up. NVIDIA treats RAG, retrieval-augmented generation, as a separate tool: reinforcement learning changes how a model behaves, while RAG changes what facts it can reach. GitHub Retires Two Gemini Models Meanwhile, GitHub is retiring Gemini 2.5 Pro and Gemini 3 Flash across all of Copilot on July 31. The migration paths are Gemini 3.1 Pro and Gemini 3.5 Flash. Cochrane flags it as a sign of the times, since tools that felt brand new a couple of years ago are already getting sunset. He also wonders how quickly today’s “AI-optimized” chips will turn over as the models keep changing. The Many Journeys of Learning Rust One for the programmers, and Cochrane makes no secret of loving Rust. The Rust blog’s Vision Doc series explores how people actually learn the language, which is built around memory safety and its strict borrow checker. Honest themes surface throughout, including “clone guilt,” where beginners refuse to copy anything, and “silent attrition,” the learners who quietly bounce off. His take stands: getting your brain onto a memory-safe language rewires how you approach a problem. Google DeepMind Partners With A24 In an interesting collision of worlds, Google DeepMind is teaming up with A24, the studio behind Hereditary and Everything Everywhere All at Once. The two call it a first-of-its-kind research partnership, with DeepMind researchers and A24 building creative tools shaped by the artists who use them. Cochrane adds a detail worth noting: Google also invested in A24, so this is money on the table, not just a research handshake. For now, though, the announcement stays deliberately vague, with no named films or products. Google’s $1 Million Africa Indie Game Fund Another one from Google, and it is good news for developers. Google is launching an indie games fund for sub-Saharan Africa, a region whose gaming scene is growing about as fast as anywhere. The fund puts up $1 million across ten local studios, each receiving between $50,000 and $200,000 plus mentorship and hands-on support. Applications close at noon UTC on July 31. WhatsApp Usernames Are Here to Reserve WhatsApp is finally moving off phone numbers as your identity. With usernames, someone can start a conversation with you without ever seeing your number. Starting this week, you can reserve the name you want ahead of the full launch later this year. To claim yours, head into Settings, then Account, then Username. Intel Sets Its Q2 Earnings Date Cochrane flags a date worth watching for anyone tracking Intel. The company reports second-quarter results on July 23, right after market close, with an earnings call at 2 p.m. Pacific. Given recent US government investment and a shifting chip landscape, he is curious how the domestic chipmaker is holding up. Your Smartwatch Might Spot Illness Before You Do Shifting to health, Engadget reports that the wearables-plus-AI wave is starting to deliver. These devices excel at catching the moment your body drifts off its own baseline, often the first nudge to get checked out. A 2025 study from Texas A&M and Stanford suggests smartwatches can detect early signs of COVID or the flu within hours of infection. Additionally, Apple Watch’s irregular-rhythm alerts have flagged AFib correctly about 84 percent of the time. Working Memory and Consciousness Here is a heady one from Scientific American, written by philosopher Henry Taylor at the University of Birmingham. Working memory is the mental scratchpad holding whatever you are doing right now. Taylor opens with the doorway effect, that blank moment when you enter a room and forget why. Intriguingly, when information leaves working memory, it seems to leave conscious awareness at the same instant, a link drawing fresh attention across psychology, philosophy, and neuroscience. Scuba-Diving Cyborg Cockroaches Now for the wild one. Scientists have built tiny diving suits that let Madagascar hissing cockroaches survive underwater for up to three hours, while an unequipped roach suffocates in minutes. The 3D-printed suit feeds oxygen through tubes into the insect’s breathing holes, called spiracles, using a chemical generator with no electronics. This lab already steered the roaches with electrodes, so the diving suit is the new trick on top. Researchers pitch it for search and rescue, though Cochrane notes the reality of the spy bug has already arrived. Quantum Time Runs Backward at Los Alamos Next, a genuine brain-bender. Physicists at Los Alamos, led by Luis Pedro García-Pintos, found a way to make a quantum system look like it is running backward in time. To be clear, time is not literally reversing. Precise measurements just make the system’s evolution appear to unfold in reverse. The useful part is energy: measurement itself becomes a resource in what they call a continuous measurement engine. Cochrane admits the paper drifted further from his reality the more he read. Tall Trees Shrug Off Drought A new study in Science overturns some textbook wisdom. For years, the assumption held that taller trees suffer more in drought because they must lift water higher. However, researchers studying dipterocarps in Southeast Asia found that trees topping seventy meters slowed their growth by about the same amount as short ones during the 2023-2024 El Niño drought. The trick is plumbing: a seventy-meter tree grows base vessels roughly twice as wide as a ten-meter tree, so the real driver of drought stress is subtler than raw height. The Energy Department Purges Conservation Pages This next one frustrates Cochrane. The US Department of Energy deleted roughly 6,000 web pages about energy conservation, and the timing is brutal during a record heatwave. The move followed backlash over New York Mayor Zohran Mamdani urging residents to ease strain on the grid. Fortunately, the Internet Archive and its Wayback Machine preserved the pages before they vanished. For Cochrane, deleting that kind of public information simply does not make sense. Webb’s Puzzling New Universe Heading to space, Quanta Magazine explores how the James Webb Space Telescope keeps finding early-universe objects that should not exist. Those include black holes that grew enormous too fast and hundreds of mysterious “little red dots” around 650 million years after the Big Bang. As astrophysicist Rachel Somerville of the Flatiron Institute puts it, scientists have “almost gone from having too many early galaxies to having too many theories.” The hard part now is figuring out which theory is right. NASA’s Emergency Telescope Rescue NASA has a rescue mission underway for the Swift Observatory, a 2004 telescope that studies gamma-ray bursts. Recent solar storms puffed up Earth’s atmosphere, and the added drag has dragged Swift’s orbit down to about 224 miles, low enough to risk burning up this year. To intervene, NASA enlisted Katalyst Space Technologies of Flagstaff, Arizona, whose LINK spacecraft launched Friday. The plan is to boost Swift back up to roughly 373 miles. A Gorgeous Aurora From Orbit Finally, Cochrane closes on something beautiful. ESA shared a stunning aurora captured from orbit, a shimmering green band of light rippling over the planet. If you have a few minutes, it is well worth a look. Cochrane wraps with housekeeping and a thank-you to GoDaddy for two decades of support, then signs off, wishing listeners a wonderful evening. The post Algorithmic Outing: When Your Feed Knows Before You Do #1869 appeared first on Geek News Central.

Les références : Nice — Le Panoptique Le Panoptique, Jeremy Bentham (1791) Loi RIPOST : le Sénat prolonge et étend la vidéosurveillance algorithmique (Public Sénat) Londres — Fahrenheit 451 Fahrenheit 451, Ray Bradbury (1953) Chat Control : vérification d'âge et fin de l'anonymat (EDRi) Lisbonne — Ravage Ravage, René Barjavel (1943) Black-out en Espagne et au Portugal du 28 avril 2025 (Connaissance des Énergies) Menlo Park — Le Meilleur des mondes Le Meilleur des mondes, Aldous Huxley (1932) Algorithmic dopamine economies (The British Journal of Psychiatry) Denver — Minority Report Minority Report (Rapport minoritaire), Philip K. Dick (1956) Inside ICE's Expanding AI Surveillance Machine, Palantir et l'outil ELITE (Parriva) Idaho — La Servante écarlate La Servante écarlate, Margaret Atwood (1985) Surveillance numérique et criminalisation de l'avortement (National Partnership for Women & Families) Kenya — La Machine à explorer le temps La Machine à explorer le temps, H. G. Wells (1895) L'IA repose sur des travailleurs invisibles exploités dans les pays pauvres (RTS) Shanghai — Nous autres Nous autres, Ievgueni Zamiatine (1924) Reconnaissance biométrique : 30 propositions pour écarter la société de surveillance (Sénat) Paris — 1984 1984, George Orwell (1949) Contrôles d'identité : défendons-nous contre la reconnaissance faciale (La Quadrature du Net) Bruxelles — La Ferme des animaux La Ferme des animaux, George Orwell (1945) Chat Control : l'UE s'apprête à contourner son propre Parlement (Cryptoast)Vous pouvez mettre un commentaire pour l'épisode. Et même mettre une note sur 5 étoiles si vous le souhaitez. Il est important pour nous d'avoir vos retours car, contrairement par exemple à une conférence, nous n'avons pas un public en face de nous qui peut réagir. Pour mettre un commentaire ou une note, rendez-vous sur la page dédiée à l'épisode.Aidez-nous à mieux vous connaître et améliorer l'émission en répondant à notre questionnaire (en cinq minutes). Vos réponses à ce questionnaire sont très précieuses pour nous. De votre côté, ce questionnaire est une occasion de nous faire des retours. Pour connaître les nouvelles concernant l'émission (annonce des podcasts, des émissions à venir, ainsi que des bonus et des annonces en avant-première) inscrivez-vous à la lettre d'actus.

KMOX Media Expert Julie Smith joins Megan Lynch and explains a handful of new digital terms that you may not be aware of. These include algorithmic burnout, AI fatigue and social search.

Pay is personal for plenty of Americans, but a new distribution model that consumes vast quantities of worker data is turning pay into something else: personalized.For an increasing number of workers in America, the money they can expect to be paid on any given day, week, or month is unknown to them. They could work the same number of hours as they did the shift before. They could help the same number of customers. They could do everything, as nearly similar as possible, and still be paid less than another worker in the exact same position, or even themselves just last week.The mechanism behind this pay disparity is called algorithmic wage discrimination and while the term may be new, it's inner workings could sound quite familiar.Algorithmic wage discrimination describes the zig-zag pay that is meted out to contract workers by big companies like Uber and Amazon. Whereas many workers in the world rely on salaries, or commissions, or self-determined contract rates, workers at Uber are different.In the same way that Uber decides what you pay for a ride to the airport, Uber also decides what a driver makes. And the calculus behind that decision is opaque. Location, traffic, the time of day, and the number of drivers on the road all play some role, but not a complete one. And in the same way that Uber incentivizes you with a flash sale or a price so high that you maybe walk a couple blocks in a different direction to get a lower price, Uber incentivizes drivers with bonuses and challenges, keeping them on the road perhaps longer than they intended.The end result, then, isn't just unpredictable pay—it's potentially an attempt to predict and control behavior.For her 2023 paper, titled “On Algorithmic Wage Discrimination,” professor of law Veena Dubal spoke with many Uber drives who compared this system to “casino culture,” in that the pay is unpredictable but the potential for a jackpot—or, just a good payment on one ride—is enough to convince drivers to stick around, night after night, hour after hour.As one driver told Dubal:“It's like gambling! The house always wins.”Today, on the Lock and Code podcast with host David Ruiz, we speak with Dubal—professor of law at the UC Irvine School of Law—about how algorithmic wage discrimination works, what data it consumes to function, and the threat it poses as it creeps from gig work into many more industries.Tune in today.You can also find us on Apple Podcasts, Spotify, and whatever preferred podcast platform you use.For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.Show notes and credits:Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)Licensed under Creative Commons: By Attribution 4.0 Licensehttp://creativecommons.org/licenses/by/4.0/Outro Music: “Good God” by Wowa (unminus.com)Listen up—Malwarebytes doesn't just talk cybersecurity, we provide it.Protect yourself from online attacks that threaten your identity, your files, your system, and your financial well-being with our exclusive offer for Malwarebytes Premium for Lock and Code listeners.

In this third installment of the ongoing segments about the Algorithm, host BT takes the audience through the influences of dystopian fiction on modern life. In this short episode the monologue shows the value and importance of looking at the world through the lenses of fiction. Discover how modern narratives, technology and ancient stories converge to reveal humanity's enduring quest for truth. This episode explores cultural symbols, AI misinformation and the philosophical questions that underpin our understanding of reality.Donate here, your continued support makes it possible to provide episodes. To those who have supported me, thank you.

Kyle Chayka is a staff writer for the New Yorker and also the author of the books Filterworld: How Algorithms Flattened Culture and The Longing for Less: What's Missing from Minimalism. Greg and Kyle discuss how algorithmic feeds shift culture from the “long tail” promise of niche discovery toward homogenization, rapid fads, and blockbuster dominance. Kyle argues platforms lower barriers to publish but make reaching audiences dependent on gaming recommendation systems, pushing creators, journalists, and even restaurants and tourism toward engagement-driven, Instagrammable, simplified outputs and fast feedback loops.  Kyle discusses “algorithmic anxiety,” authenticity and taste being shaped by feeds, and incentives like Spotify's 30-second stream metric affecting music length, quality, and what artists do to respond to that system. They contrast shallow metrics with criticism and curation, discuss minimalism and performative authenticity, and note countervailing long-tail models like newsletters, Patreon, and podcasts, emphasizing the need to exit feeds for deeper engagement. *unSILOed Podcast is produced by University FM.* Episode Quotes: Why everything online starts to look the same 06:02: Algorithmic feeds and recommendations kind of encourage people to homogenize themselves. Like, they don't just stamp the content. The digital platform doesn't dictate exactly what the content looks like, but it encourages all of us, all of the writers and creators and musicians, to behave in similar ways in order to game the system and get an audience for ourselves. Do algorithmic feeds reward simplicity? 09:46: I think algorithmic feeds reward simplicity. Like, they reward the idea translated into the fewest words or the image that is the most, like, basically attractive or compelling, that lights up your brain right away. So I think people tend to present themselves and mold themselves in that direction as well. Have we lost control of what we like? 28:45: Taste is never totally organic, right? Like, a record label executive is going to pick the hot young band of the moment in the 1990s. A museum curator will choose who to put in a gallery show, and that will influence what you're actually seeing. But to me, that sense of anxiety was new. Like, that fear that you had lost control of what you liked and that you couldn't identify with it because it was somehow alien to you, that was really striking to me. Show Links: Recommended Resources: Andy Warhol Walter Benjamin Pierre Bourdieu Mark Fisher Marie Kondo Donald Judd Guest Profile: The New Yorker Profile and Work KyleChayka.com LinkedIn Profile Wikipedia Page Social Profile on X Social Profile on Instagram Guest Work: Amazon Author Page Filterworld: How Algorithms Flattened Culture The Longing for Less: What's Missing from Minimalism Kyle Chayka Industries | Substack Newsletter Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This Day in Legal History: DobbsOn June 24, 2022, the U.S. Supreme Court issued its decision in Dobbs v. Jackson Women's Health Organization, a case that fundamentally changed American constitutional law. The case centered on a Mississippi statute that prohibited most abortions after 15 weeks of pregnancy. In a 6–3 ruling, the Court held that the Constitution does not protect a right to abortion. The decision expressly overturned Roe v. Wade, decided in 1973, and Planned Parenthood v. Casey, decided in 1992. Justice Samuel Alito wrote the majority opinion, arguing that abortion was not a right deeply rooted in the nation's history and tradition. The ruling returned the authority to regulate abortion primarily to the states.Almost immediately, abortion access began to vary widely across the country, depending on state law. Some states enforced near-total bans or severe restrictions, while others expanded protections for abortion access. The decision was also significant because it narrowed the use of substantive due process, the doctrine under which courts have recognized certain unenumerated constitutional rights. Supporters of the ruling argued that the Court had corrected a constitutional error and restored democratic control over abortion policy. Critics argued that the decision removed a long-recognized liberty interest and placed major personal medical decisions under state control. Dobbs also sparked renewed debate over stare decisis, the principle that courts should generally follow precedent.For many legal observers, the case became a defining example of how changes in the Court's membership can reshape constitutional rights. June 24 therefore stands as the date the Supreme Court ended the federal constitutional right to abortion and transformed the legal landscape of reproductive freedom in the United States.New York's Court of Appeals, the state's highest court, has upheld the constitutionality of a law designed to restrict hate speech on social media platforms. The ruling represents a significant victory for free speech limitations in the digital age. Here's what happened: New York passed a law requiring social media platforms to remove or restrict content that incites hatred or violence based on protected characteristics like race, religion, ethnicity, or national origin. The law's supporters argue that online platforms have become the new town squares where public discourse happens, and that hate speech can radicalize people and lead to real-world violence. Critics worried the law was too broad and would violate the First Amendment by punishing protected speech.For generations, the government couldn't regulate speech just because it was hateful or offensive. The First Amendment protected even deeply offensive speech. But online platforms create a new kind of public space where algorithms amplify divisive content, and a single post can reach millions. The question the court had to answer was: Can states regulate hate speech on these platforms the way they might regulate incitement to violence? New York's highest court said yes, the law likely passes constitutional scrutiny.The court found that the law targets speech that genuinely incites hatred and violence, not merely offensive opinions. It's narrowly tailored to achieve the state's legitimate interest in preventing violence and discrimination. This ruling opens the door for other states to pass similar laws. It represents a potential shift in how courts balance the absolute protection of offensive speech against the harms caused by hate speech in the digital age. Tech companies will likely face increased regulation around hate speech, and the definition of what counts as unprotected incitement may narrow. The decision reflects a judicial recognition that online speech operates differently than traditional speech and may warrant different legal treatment.New York's top court says hate speech social media law likely passes muster | ReutersGoogle's YouTube has agreed to settle a lawsuit with a plaintiff rather than face a second trial over questions of social media liability and content moderation. The settlement ends litigation that challenged YouTube's responsibility for user-generated content that allegedly caused harm. Here's the broad strokes context: Section 230 of the Communications Decency Act is a federal law that shields online platforms from liability for content posted by users. In other words, if someone posts defamatory content on YouTube, the person who posted it can be sued, but YouTube itself typically cannot be held responsible.The logic is that Section 230 encourages platforms to host diverse content by protecting them from lawsuits about every post. However, plaintiffs have been arguing that Section 230 doesn't shield platforms from all liability, and that platforms have a responsibility for content they actively moderate or promote. Imagine you own an apartment building. If a tenant commits a crime in their apartment, you're not responsible for that crime. But if you knowingly rent apartments to criminals or knowingly create conditions that enable crime, that's different. The question in social media cases is: When does YouTube's moderation and recommendation algorithms cross the line from passive hosting into active promotion that removes Section 230 protection?YouTube settled rather than litigate this question again, suggesting the company wanted to avoid another trial where a jury might rule against it. The settlement amount and terms weren't disclosed. Settlement doesn't necessarily mean YouTube admitted wrongdoing, but it does avoid a precedent-setting jury verdict that could have limited Section 230 protections. This case illustrates the ongoing tension between platforms' desire to host diverse content and their responsibility to moderate harmful material. As social media litigation continues, Section 230 protections may continue to erode, forcing platforms to be more responsible for content they host or recommend.Google's YouTube settles case over social media harm to children | ReutersA federal judge has vacated (struck down) Trump administration policies that authorized immigration agents to arrest undocumented immigrants at courthouses. The ruling represents a significant limitation on immigration enforcement tactics. The Trump administration issued policies directing Immigration and Customs Enforcement (ICE) to conduct arrests of undocumented immigrants in and around courthouses, even during court proceedings.The policy's supporters argued it was an effective enforcement tool that would apprehend deportable aliens. Critics argued the policy undermined the judicial system because it chilled access to courts. If immigrants fear being arrested when they go to court, they won't report crimes, testify as witnesses, or seek legal protection from domestic violence. They'll be afraid to appear for required court appearances related to immigration proceedings. The federal judge agreed with the critics.The courthouse is supposed to be a safe space where people can seek justice. Historically, both federal and state judges have issued standing orders prohibiting ICE arrests in courthouses because such arrests interfere with the administration of justice. If people are afraid to go to court because they might be arrested, the entire justice system suffers. Witnesses won't testify, victims won't report crimes, and the judicial process breaks down.The judge found that the administration's policies violated well-established principles protecting courthouse access and were an abuse of enforcement discretion. The ICE agents conducting the arrests violated state court rules and judicial orders protecting courthouse integrity. Why this matters: This ruling reaffirms that even immigration enforcement—an area where the executive branch typically has broad authority—must respect core judicial functions. The decision protects immigrants' ability to access courts without fear of enforcement. It may encourage undocumented immigrants to report crimes, testify in cases, and pursue legal remedies. Immigration advocates see this as a significant victory. Immigration enforcement officials may argue it limits their ability to apprehend deportable aliens. The decision reflects a judicial judgment that courthouse access is so fundamental that even immigration enforcement must yield to it.US judge vacates Trump immigration courthouse arrest policies | 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

today we outline the transformative role and ethical boundaries of generative AI across journalism, academic publishing, and digital media. In newsrooms, AI is framed as an efficiency tool for data-to-text generation and verification rather than a replacement for human editorial judgment. Academic and legal perspectives emphasize that while AI can assist in manuscript preparation and research, it cannot be credited as an author due to a lack of legal accountability. Guidelines from major publishers like Elsevier and Amazon KDP mandate strict transparency and disclosure requirements for AI-generated text and imagery to maintain public trust. Furthermore, the texts explore economic shifts, such as data licensing and the legal tensions surrounding copyright infringement in AI training. Ultimately, the consensus across these industries is that human oversight remains essential to safeguard accuracy, originality, and professional ethics.

In this episode, Lex chats with Cactus Raazi — CEO Americas at B2C2, one of the original and largest institutional market makers in digital assets, serving roughly 1,500 institutions and pricing across more than 40 exchanges globally. They discuss what a market maker actually does, how balance sheet and signal generation underpin roughly $1 billion a day of stablecoin flow at B2C2, and why the two extremes of crypto market making - riskless principal aggregation versus proprietary alpha - produce very different client outcomes that buyers rarely understand. Cactus explains B2C2's 18-month bet that the Circle-versus-Tether debate would give way to a multi-issuer world, the launch of its PENNY product for instant zero-cost cross-stablecoin swaps, and they explore why programmability is the next frontier for digital dollars, why US capital markets have almost no structure for funding genuine risk-taking businesses, and whether the current combination of scale, speed, and complexity makes this the hardest investing environment Wall Street has ever faced. NOTABLE DISCUSSION POINTS: Market makers aren't a homogeneous category, and clients pay for the difference. At one extreme, a market maker is essentially a riskless agent - aggregating prices across 40+ exchanges and quoting on top with no real view. At the other extreme, a market maker is a proprietary quant shop running alpha signals on horizons from seconds to days, and the price you get is heavily conditioned by where the signal says the asset is going. B2C2 sits in the middle, partly because its public-company parent (SBI) constrains risk appetite. The implication for institutional buyers: who you trade with structurally determines the quality of execution, not just the spread. Algorithmic fixed income market making didn't fail on technology, it failed on capital structure. US capital markets are excellent at funding venture, growth equity, private equity, and buyouts, but there is almost no domestic pool of “risk equity” - capital comfortable with the possibility that the machines (or the humans) lose money on a given day. Market makers need exactly that kind of balance sheet, and the mismatch between what the business requires and what the US capital base offers is a structural reason firms like Elefant struggled, regardless of execution quality. The Circle-vs-Tether framing is already obsolete; the next product wedge is interoperability. B2C2 made an 18-month-old contrarian bet that the duopoly narrative was wrong and that Stripe (via Bridge), Western Union, Revolut, and many other consumer and platform companies would issue their own stablecoins. PENNY - instant, zero-cost, zero-counterparty-risk stablecoin-to-stablecoin swaps - is the product expression of that view. The deeper claim is that stablecoins are software, and the SaaS analogy (a base layer plus an app store of programmable financial logic) is the real reason institutional adoption accelerates from here, not the transfer-of-value benefit on its own. TOPICS B2C2, Goldman Sachs, SBI Group, Binance, Coinbase, Circle, Tether, Stripe, Kraken, Credit Suisse, Market making, institutional liquidity, stablecoins, fixed income, risk management, algorithmic trading, crypto exchange infrastructure   ABOUT THE FINTECH BLUEPRINT

Adeline Atlas 11 X Published AUTHOR Digital Twin: Create Your AI Clone: ⁠⁠⁠⁠https://www.soulreno.com/digital-twin⁠⁠⁠⁠SOS: School of Soul Vault: Full Access ALL SERIES⁠⁠⁠⁠⁠https://www.soulreno.com/joinus-202f0461-ba1e-4ff8-8111-9dee8c726340⁠⁠⁠⁠Instagram: ⁠⁠⁠⁠⁠https://www.instagram.com/soulrenovation/⁠⁠⁠⁠Soul Renovation - BooksSoul Game - ⁠⁠⁠⁠https://tinyurl.com/vay2xdcp⁠⁠⁠⁠Why Play: ⁠⁠⁠⁠⁠https://tinyurl.com/2eh584jf⁠⁠⁠⁠How To Play: ⁠⁠⁠⁠⁠https://tinyurl.com/2ad4msf3⁠⁠⁠⁠Digital Soul: ⁠⁠⁠⁠https://tinyurl.com/3hk29s9x⁠⁠⁠⁠Every Word: ⁠⁠⁠⁠⁠⁠http://tiny.cc/ihrs001⁠⁠⁠⁠Drain Me: ⁠⁠⁠⁠⁠https://tinyurl.com/bde5fnf4⁠⁠⁠⁠The Rabbit Hole: ⁠⁠⁠⁠https://tinyurl.com/3swnmxfj⁠⁠⁠⁠Destiny Swapping: ⁠⁠⁠⁠https://tinyurl.com/35dzpvss⁠⁠⁠⁠Spanish Editions: Every Word: ⁠⁠⁠⁠https://tinyurl.com/ytec7cvc⁠⁠⁠⁠Drain Me: ⁠⁠⁠⁠https://tinyurl.com/3jv4fc5n⁠⁠⁠⁠

Artificial intelligence is rapidly transforming retail, but are retailers giving away too much decision-making power to algorithms? On this episode of The Voice of Retail, host Michael LeBlanc welcomes back retail strategist, educator, speaker and author Carl Boutet to the podcast to discuss his latest book, The Flip. Drawing on more than three decades of retail experience and his work advising organizations around the world, Carl offers a thought-provoking perspective on how AI is reshaping retail strategy, customer engagement and business leadership. The conversation begins with Carl's unique vantage point as a global retail observer. Fresh off another teaching engagement at the Asian Institute of Technology in Bangkok, Carl shares insights from Southeast Asia's rapidly evolving retail landscape. From super apps and mobile commerce to experiential shopping destinations and high-energy retail environments, he explains why emerging markets are often leapfrogging traditional retail models and creating new opportunities for customer engagement. Michael and Carl then explore one of the most important topics facing retailers today: the growing influence of artificial intelligence on decision-making. Carl argues that while AI can dramatically improve efficiency, it also poses the risk that businesses become increasingly dependent on algorithmic recommendations, potentially sacrificing the creativity, differentiation, and strategic judgment that make brands unique. At the center of the discussion is Carl's new framework outlined in The Flip. He introduces the four forces that he believes are fundamentally reshaping commerce: automation, optimization, contextualization and immersion. Together, these forces are changing how retailers attract customers, personalize experiences, manage operations and compete in increasingly digital environments. The discussion extends beyond technology into the future of retail itself. Carl shares observations from his travels across Asia, highlighting how retailers are creating energy-rich destinations that blend shopping, entertainment, food and community. These experiences offer important lessons for North American retailers seeking to remain relevant in a world where consumers increasingly have unlimited digital choices at their fingertips. Michael and Carl also examine the rise of AI-powered customer discovery, the future of search and marketing, the growing importance of trust, and why retailers must think carefully about where human value creation fits inside increasingly automated organizations. Carl explains why curiosity, organizational adaptability and a relentless focus on core business fundamentals remain essential leadership capabilities despite the rapid pace of technological change. Michael LeBlanc is the president and founder of M.E. LeBlanc & Company Inc, a senior retail advisor, keynote speaker and now, media entrepreneur. He has been on the front lines of retail industry change for his entire career. Michael has delivered keynotes, hosted fire-side discussions and participated worldwide in thought leadership panels. He brings 25+ years of brand/retail/marketing & eCommerce leadership experience with Levi's, Black & Decker, Hudson's Bay, CanWest Media, Pandora Jewellery, The Shopping Channel and Retail Council of Canada to his advisory, speaking and media practice.Michael produces and hosts a network of leading retail trade podcasts, including the award-winning No.1 independent retail industry podcast in America, Remarkable Retail with his partner, Dallas-based best-selling author Steve Dennis; Canada's top retail industry podcast The Voice of Retail and Canada's top food industry and one of the top Canadian-produced management independent podcasts in the country, The Food Professor with Dr. Sylvain Charlebois from Dalhousie University in Halifax.Rethink Retail has recognized Michael as one of the top global retail experts for the fifth year in a row, the National Retail Federation has designated Michael as on their Top Retail Voices for 2025 and 2026. Thinkers 360 has named him on of the Top 50 global thought leaders in retail. If you are a BBQ fan, you can tune into Michael's cooking show, Last Request BBQ, on YouTube, Instagram, X and yes, TikTok.Michael is available for keynote presentations helping retailers, brands and retail industry insiders explaining the current state and future of the retail industry in North America and around the world.

The modern performance marketing framework is broken, driven down by rising customer acquisition costs and the steady decay of organic reach on traditional networks.In this episode, Nicole Collins, co-founder of 213Deli and former founding team member at Ipsy, outlines the structural adjustments brands must make to thrive within algorithmic social media marketplaces.Deconstructing early-stage subscription e-commerce architectures and evaluating their viability in today's fragmented digital ecosystems.Analyzing operational frameworks from mature Chinese live commerce networks and their domestic application gaps.Mitigating systemic startup risk through rigorous, transparent audits of co-founder operational alignment.Scaling enterprise distribution pathways in a post-follower economy dominated by algorithmic platform rules.Nicole Collins is an enterprise retail tech executive with over twenty years of experience designing high-intent discovery platforms and cross-border commercial channels.Connect with Nicole Collins on LinkedIn: https://www.linkedin.com/in/collinsinla/Explore 213Deli's Infrastructure: https://www.213deli.com/Optimize your enterprise paid media deployment via Strike Social: https://strikesocial.com/guaranteed-paid-social-media-ads-outcomes/Follow Host Dylan Conroy: https://www.linkedin.com/in/dylanconroy/

Ep 266 “The Algorithmic Recommendation Engine” – National Gun Violence Awareness Month (Bullet Poof Bulletins) Celebrating the launch of eco-fiction anti-gun novella Bullet Poof and National Gun Violence Awareness Month, Avis Kalfsbeek brings back beloved Kitty O'Compost with the Bullet Poof Bulletins. Tonight on the Spoke-Easy stage, Kitty O'Compost tears apart a leaked Silicon Valley presentation deck that exposes the predatory automation of consumer identity crises. This bulletin satirizes the "cross-selling metrics" of modern data funnels, exposing how tech stacks explicitly connect the social isolation of remote work with military-grade tactical gear for corporate profit. Inspired by the connective and protective themes of Bullet Poof, this episode exposes the mechanical exploitation of human vulnerability and points us back to the real, grounding fulfillment found in cooperative community spaces. Resources: Bullet Poof is a hopeful eco-fiction novella about what happens when ordinary people refuse to accept the gun status quo. Get the book: https://www.aviskalfsbeek.com/bullet-poof National Gun Violence Awareness Month: www.wearorange.org Theme Music: "Turn the Steel" and punk intros produced by Avis Kalfsbeek (via ElevenLabs). Music Credits & Support: Buy LPs and music downloads directly from the bands' websites, or from platforms like Bandcamp where artists retain the majority of your purchase. This project is inspired by decades of punk ethos, raw energy, and the brilliant musicians who shaped the movement. The sonic landscape of this series was informed and inspired by: The Sex Pistols, Black Flag, Rites of Spring, The Buzzcocks, Minor Threat, The Clash, Social Distortion, Bad Religion, The Dead Kennedys, The Ramones, Jawbreaker, Fugazi, Rise Against, The Damned, The Stooges, Bad Brains, Bikini Kill, The Lawrence Arms, Husker Du, Pennywise, The Adicts, The Exploited, Descendents, Stiff Little Fingers, Crass, The Germs, Dropkick Murphys, Operation Ivy, Against Me!, Green Day, Blink-182, The Hives, Sleater-Kinney, The Violent Femmes, The Network, The Jam, The Gaslight Anthem, No Use For A Name, and The Interrupters.

HOUR 1: Dynamic pricing, algorithmic pricing, whatever you call it, is it legal?! It's certainly wrong. full 2302 Wed, 17 Jun 2026 19:00:00 +0000 1mdHjaZnDtH0Fg3PNBWiaIqom8hMKAPo news The Dana & Parks Podcast news HOUR 1: Dynamic pricing, algorithmic pricing, whatever you call it, is it legal?! It's certainly wrong. You wanted it... Now here it is! Listen to each hour of the Dana & Parks Show whenever and wherever you want! © 2025 Audacy, Inc. News

Through PIN–UP, the German-born, New York–based editor, curator, and founder Felix Burrichter continues to expand the possibilities of what an architecture magazine can be. He constructs intuitive bridges between creative sectors—whether art, design, and music, or fashion, film, and food—and shows how the built environment shapes and responds to larger societal and cultural forces. Amid endlessly scrollable, algorithmically controlled digital feeds, PIN–UP remains committed as ever to a print-forward, human-led approach. 2026 marks the 20th anniversary of this self-described “magazine for architectural entertainment” and the launch of its 40th issue, a special edition devoted to the notion of “Independence”—a north star for Burrichter, who has long championed slower, more intentional forms of media rooted in curiosity, discovery, and pleasure. On the episode, Burrichter reflects on why he sees magazines as intimate dinner parties; how slowness and experimentation have become his publication's defining strengths; and why, despite our precarious present, he continues to strive toward utopia. Special thanks to our Season 13 presenting partner, L'ÉCOLE, School of Jewelry Arts. Show notes: Felix Burrichter [00:50 ] PIN–UP Magazine [08:48] India Mahdavi [11:40] Alexandra Cunningham Cameron [14:35] Moriyama House by Ryue Nishizawa [20:34] PIN–UP Home [30:21] Jay Osgerby [34:12] Theaster Gates [34:12] Solange Knowles and Saint Heron [34:30] Solange's “Losing You” (2012) [35:21] Luther Vandross's “A House Is Not a Home” (1981) [47:18] KPF [50:55] Jop Van Bennekom and Gert Jonkers [50:55] Stephen Todd [51:44] Dylan Fracareta [51:44] Geoffrey Han [52:36] “Taking It Slow With Spencer Bailey” [52:56] Paulo Mendes da Rocha [55:30] Bijoy Jain [1:03:09] The Barbie Dreamhouse [1:03:27] “Isamu Noguchi: ‘I Am Not a Designer'” [1:06:03] Dozie Kanu [1:10:21] Ben Ganz [1:12:51] Travis Scott [1:17:18] Rana Toofanian

It’s Pride Month. . . some cities are reversing the course on flying the flag. . . and others are flat refusing // Algorithmic wage discrimination // SCENARIOS!

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.

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.

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

Adeline Atlas 11 X Published AUTHOR Digital Twin: Create Your AI Clone: ⁠⁠⁠⁠https://www.soulreno.com/digital-twin⁠⁠⁠⁠SOS: School of Soul Vault: Full Access ALL SERIES⁠⁠⁠⁠⁠https://www.soulreno.com/joinus-202f0461-ba1e-4ff8-8111-9dee8c726340⁠⁠⁠⁠Instagram: ⁠⁠⁠⁠⁠https://www.instagram.com/soulrenovation/⁠⁠⁠⁠Soul Renovation - BooksSoul Game - ⁠⁠⁠⁠https://tinyurl.com/vay2xdcp⁠⁠⁠⁠Why Play: ⁠⁠⁠⁠⁠https://tinyurl.com/2eh584jf⁠⁠⁠⁠How To Play: ⁠⁠⁠⁠⁠https://tinyurl.com/2ad4msf3⁠⁠⁠⁠Digital Soul: ⁠⁠⁠⁠https://tinyurl.com/3hk29s9x⁠⁠⁠⁠Every Word: ⁠⁠⁠⁠⁠⁠http://tiny.cc/ihrs001⁠⁠⁠⁠Drain Me: ⁠⁠⁠⁠⁠https://tinyurl.com/bde5fnf4⁠⁠⁠⁠The Rabbit Hole: ⁠⁠⁠⁠https://tinyurl.com/3swnmxfj⁠⁠⁠⁠Destiny Swapping: ⁠⁠⁠⁠https://tinyurl.com/35dzpvss⁠⁠⁠⁠Spanish Editions: Every Word: ⁠⁠⁠⁠https://tinyurl.com/ytec7cvc⁠⁠⁠⁠Drain Me: ⁠⁠⁠⁠https://tinyurl.com/3jv4fc5n⁠⁠⁠⁠

Adeline Atlas 11 X Published AUTHOR Digital Twin: Create Your AI Clone: ⁠⁠https://www.soulreno.com/digital-twin⁠⁠SOS: School of Soul Vault: Full Access ALL SERIES⁠⁠⁠https://www.soulreno.com/joinus-202f0461-ba1e-4ff8-8111-9dee8c726340⁠⁠Instagram: ⁠⁠⁠https://www.instagram.com/soulrenovation/⁠⁠Soul Renovation - BooksSoul Game - ⁠⁠https://tinyurl.com/vay2xdcp⁠⁠Why Play: ⁠⁠⁠https://tinyurl.com/2eh584jf⁠⁠How To Play: ⁠⁠⁠https://tinyurl.com/2ad4msf3⁠⁠Digital Soul: ⁠⁠https://tinyurl.com/3hk29s9x⁠⁠Every Word: ⁠⁠⁠⁠http://tiny.cc/ihrs001⁠⁠Drain Me: ⁠⁠⁠https://tinyurl.com/bde5fnf4⁠⁠The Rabbit Hole: ⁠⁠https://tinyurl.com/3swnmxfj⁠⁠Destiny Swapping: ⁠⁠https://tinyurl.com/35dzpvss⁠⁠Spanish Editions: Every Word: ⁠⁠https://tinyurl.com/ytec7cvc⁠⁠Drain Me: ⁠⁠https://tinyurl.com/3jv4fc5n⁠

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. 

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.

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.

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

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.

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

WarRoom Battleground EP 893: AI The Algorithmic Parasite