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This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president could still fire commissioners, as the Court now permits, but if those firings broke quorum, the agency would be unable to proceed until replacements were confirmed. The guardrail would

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.There was an issue with this only going to paid subscribers, so sending it again. Apologies to those who get it twice. I appreciate being paid so feel free to upgrade if you enjoy TWTW.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president

Political theorist Yascha Mounk returns to assess whether the United States is sliding toward autocracy or demonstrating institutional resilience under pressure. He argues that while the Trump administration's actions have been more extreme than expected, courts, elections, and a decentralized system have so far acted as real constraints rather than hollow rituals, a case he first laid out in The People vs. Democracy: Why Our Freedom Is in Danger and How to Save It. Mounk also warns against exaggeration that fuels anticipatory obedience, even as he concedes the next three years remain an open test of democratic durability. Plus, Britain's Epstein reckoning, where Keir Starmer loses top aides over ties to Jeffrey Epstein, while close associations in Epstein's own country (the USA) don't matter. Produced by Corey Wara Video and Social Media by Geoff Craig Do you have questions or comments, or just want to say hello? Email us at ⁠⁠⁠⁠thegist@mikepesca.com For full Pesca content and updates, check out our website at https://www.mikepesca.com/⁠ For ad-free content or to become a Pesca Plus subscriber, check out ⁠⁠⁠⁠https://subscribe.mikepesca.com/ For Mike's daily takes on Substack, subscribe to The Gist List https://mikepesca.substack.com/ Follow us on Social Media:⁠⁠⁠⁠ YouTube https://www.youtube.com/channel/UC4_bh0wHgk2YfpKf4rg40_g⁠⁠⁠⁠ Instagram https://www.instagram.com/pescagist/ X https://x.com/pescami TikTok https://www.tiktok.com/@pescagist To advertise on the show, contact ⁠⁠⁠⁠ad-sales@libsyn.com⁠⁠⁠⁠ or visit ⁠⁠⁠⁠https://advertising.libsyn.com/TheGist

In part two of Dan's conversation with political scientist Yascha Mounk, the two discuss identity politics, its growing influence on the American left, and the danger this trend poses to pluralistic societies.They examine why identity politics is so seductive, how it reshapes government, schools, and civic  institutions, and why Mounk believes it ultimately undermines both individuality and democratic cohesion. The conversation also turns inward, exploring Jewish identity: where it strengthens pluralism, where it becomes politicized, and why Jews, in particular, should be cautious about abandoning universal principles for group-based power.In this episode...- Why liberalism today feels unrecognizable- What identity politics is and why it's so appealing- How universalism gave way to group-based politics- When inclusion turns into segregation- Jewish identity and the limits of identity-based politics- Why free speech remains essential for a pluralistic democracyFrom the episode:- Listen to Yascha's podcast The Good Fight- Subscribe to Persuasion- Purchase Yascha's book, The Identity TrapMore Ark Media:Want to join Ark Media? Check out our careers page for new openings.Subscribe to Inside Call me BackListen to For Heaven's SakeListen to What's Your Number?Watch Call me Back on YouTubeNewsletters | Ark Media | Amit Segal | Nadav EyalInstagram | Ark Media | DanX | DanDan Senor & Saul Singer's book, The Genius of IsraelGet in touchCredits: Ilan Benatar, Adaam James Levin-Areddy, Brittany Cohen, Martin Huergo, Mariangeles Burgos, and Patricio Spadavecchia, Yuval Semo 

In part two of Dan's conversation with political scientist Yascha Mounk, the two discuss identity politics, its growing influence on the American left, and the danger this trend poses to pluralistic societies. They examine why identity politics is so seductive, how it reshapes government, schools, and civic  institutions, and why Mounk believes it ultimately undermines […]

Is Antizionism the new common denominator of the left? Political scientist Yascha Mounk, founder of Persuasion and author of The Identity Trap, joins Dan to discuss whether the rise of Zohran Mamdani is indicative of a growing connection between socialist causes and hostility towards Jews. Drawing on his personal history, Mounk explains the different iterations of Antisemitism on the left and discusses with Dan whether it is categorically different from what we're increasingly seeing on the American right.The conversation went longer than normal, so stay tuned for part 2 in which Dan and Yascha discuss how identity politics consumed America and Jews should be wary of falling into the same trap.In this episode...- Yascha's political upbringing- The history of Antizionism on the left - What would Mamdani compromise on?- Is the IHRA's definition of Antisemitism dangerous to free speech? - The Western left's silence on repression in IranThis episode was sponsored by Maimonides Fund: Sign up for the SAPIR journal at sapirjournal.org/CallMeBackFrom the episode:- Listen to Yascha's podcast The Good Fight- Subscribe to Persuasion- Purchase Yascha's book, The Identity TrapMore Ark Media:Want to join Ark Media? Check out our careers page for new openings.Subscribe to Inside Call me BackListen to For Heaven's SakeListen to What's Your Number?Watch Call me Back on YouTubeNewsletters | Ark Media | Amit Segal | Nadav EyalInstagram | Ark Media | DanX | DanDan Senor & Saul Singer's book, The Genius of IsraelGet in touchCredits: Ilan Benatar, Adaam James Levin-Areddy, Brittany Cohen, Martin Huergo, Mariangeles Burgos, and Patricio Spadavecchia, Yuval Semo 

Is Anti-Zionism the new common denominator of the left? Political scientist Yascha Mounk, founder of Persuasion and author of The Identity Trap, joins Dan to discuss whether the rise of Zohran Mamdani is indicative of a growing connection between socialist causes and hostility towards Jews. Drawing on his personal history, Mounk explains the different iterations […]

https://www.youtube.com/watch?v=KZCJXTdch2E Podcast audio: In this episode of ARI Bookshelf, Sam Weaver, Ben Bayer, Nikos Sotirakopoulos and Ibis Slade critically examine America's Cultural Revolution by Christopher Rufo and The Identity Trap by Yascha Mounk. Among the topics covered: Nature of “woke” ideology; “Domino” view of ideological influence; Influence of right-wing ideas; Rufo's authoritarianism; Mounk's egalitarianism and collectivism; Books' perspectives on real injustices; Merits of Mounk's book; Weakness of Rufo's critiques; Rufo's un-American tribalism; Influence of postmodern epistemology; Why “woke” ideology isn't Marxism Recommended in this podcast are Ayn Rand's essay “The Left: Old and New”, Rand's book Introduction to Objectivist Epistemology, and Leonard Peikoff's book The DIM Hypothesis. This episode was recorded on October 3, 2025, and posted on October 10, 2025.

Host Marcia Franklin talks with political scientist Yascha Mounk about identity, political divides and his outlook on America. Mounk is the author of several books, including "The People vs. Democracy," "The Great Experiment," and "Stranger in My Own Country." Don't forget to subscribe, and visit the Dialogue website for more conversations that matter. Originally Aired: 11/18/2022 The interview is part of Dialogue's series "Conversations from the Sun Valley Writers' Conference" and was taped at the 2022 conference. Since 1995, the conference has been bringing together some of the world's most well-known and illuminating authors to discuss literature and life.

durée : 00:05:16 - C'est une chanson - par : Frédéric Pommier - Du 8 au 12 octobre, il présente son nouveau spectacle, "Opération Rumba", au théâtre de l'Athénée à Paris. Au micro de Frédéric Pommier, l'auteur et metteur en scène congolais Dieudonné Niangouna témoigne de son affection pour "Amour de Nombakélé" de Pamelo Mounk'a, chanson qui a bercé son enfance. Vous aimez ce podcast ? Pour écouter tous les autres épisodes sans limite, rendez-vous sur Radio France.

Die US-Regierung benutzt die politische Macht, um Universitäten anzugreifen. Wie zeigt sich das im Alltag? Was sind die Gründe? Der Politikwissenschaftler Yascha Mounk ist Professor an der Johns-Hopkins-Universität in Baltimore. An den Universitäten gab es in den letzten Jahren echte Missstände, erklärt Mounk. Die Cancel Culture habe Studentinnen und Professoren in der Meinungsäusserung eingeschränkt. Doch was die Regierung Trump nun im Namen der Meinungsfreiheit mache, sei ein rabiater Angriff auf genau diese. Der rechte Populismus sei eine Gefahr für die Demokratie. Es sei aber wichtig, dass sich auch die Linken fragen, wie es dazu kommen konnte. Mounk ist überzeugt, dass die linke Identitätspolitik zum Aufstieg von Donald Trump beigetragen hat. Yascha Mounk ist zu Gast bei Simone Hulliger im Tagesgespräch.

Ist Identitätspolitik schuld am Aufstieg von Trump, AfD & Co.? Yascha Mounk meint, ja. Ein Podcast vom Pragmaticus. Das Thema:Im amerikanischen Original heißt das jüngste Buch von Yascha Mounk The Identity Trap, die Identitätsfalle. Dahinter steht diese These: Mitbestimmung, Teilhabe und Rechte im Namen einer Identität (als Frau, als Minderheit, als schwuler Mann oder queere Person) einzufordern, war einmal ein Akt der Befreiung, hat aber zugleich die Gesellschaft in einzelne Teile zerbrechen lassen. Jene, die sich durch die Identitätspolitik ausgegrenzt fühlen oder mit Queer nichts anfangen können, nähmen die Angebote von Trump, AfD & Co. daher gerne an.Ist der Politikwissenschaftler in Zeiten, wo Donald Trump den Krieg gegen Woke ausruft, Viktor Orban am liebesten alle NGO verbieten würde, die AfD im deutschen Bundestag eine Identitätspolitik von rechts fordert und den weißen Mann bedroht wähnt, auf dem falschen Dampfer oder geben ihm gerade diese Entwicklungen recht? Unser Gast in dieser Folge: Yascha Mounk wurde 1982 in München geboren. Er ist Politikwissenschaftler und Associate Professor für Internationale Beziehungen an der Johns Hopkins University in Baltimore. Er ist Autor zahlreicher Bücher, unter anderem Der Zerfall der Demokratie. Wie der Populismus den Rechtsstaat bedroht (2018), Das große Experiment. Wie Diversität die Demokratie bedroht und bereichert (2022) und Im Zeitalter der Identität: Der Aufstieg einer gefährlichen Idee (2024).Dies ist ein Podcast von Der Pragmaticus. Sie finden uns auch auf Instagram, Facebook, LinkedIn und X (Twitter).

Political scientist Yascha Mounk joins The Winston Marshall Show for a sharp, wide-ranging discussion on the evolution of populism, the crisis of democracy, and the future of America's political coalitions.Mounk draws a clear line between populism and fascism, warning that even democratically elected movements can veer into dangerous territory—citing Venezuela and Turkey as cautionary tales. He critiques the failures of modern media, the persistence of woke ideology post-Trump, and the inefficiencies of U.S. foreign aid programs like USAID.The conversation turns to 2024: Kamala Harris's faltering coalition, the Republican Party's pivot toward a multi-racial working-class base, and the growing tension between big donors and Main Street voters.All this—populism's promise and peril, woke culture's staying power, the death of old political norms, and the battle for America's soul... Hosted on Acast. See acast.com/privacy for more information.

  On this episode of Unsupervised Learning, Razib talks to Yasha Mounk. The founder of Persuasion, a contributor to The Atlantic and a professor at Johns Hopkins, Mounk now has his own Substack, where he hosts his weekly column and podcast. He is the author of The Great Experiment: Why Diverse Democracies Fall Apart and How They Can Endure, The People vs. Democracy: Why Our Freedom Is in Danger and How to Save It and The Identity Trap: A Story of Ideas and Power in Our Time.  Razib and Mounk first discuss Mounk's immediate reaction to the 2024 election, and how the Democrats might pick up the pieces going forward. Mounk believes that the argument in his book The Identity Trap, neatly captures many of the problems for the party. Democrats leaned in on the inevitably of racial polarization in an age of progressive depolarization. Razib also asks Mounk for his retrospective on the COVID-19 epidemic, in which he was a commentator who argued in The Atlantic for more stringent habits and then later, for an opening up. They also discuss how the Public Health establishment COVID interventions threw the whole field into disrepute, and what it tells us about the nature of expertise. Then Razib asks Mounk about European nations and their future. In particular, whether their low productivity and fertility rates combined with mass migration doom them to a future of irrelevance and national dissolution. Mounk highlights the unfortunate case of the UK in particular, though he notes that his home nation of Germany is finding itself in a precarious situation with China competing with its manufacturers and Russia cutting off its gas supply. Finally, Razib closes by asking Mounk whether he is still as worried about American democracy in the wake of the 2024 Trump win as he was in 2016.

Diversity has often been seen as the United States' defining strength – but today, some Americans see it as a threat. And this isn't new. Throughout history, differences of religion, ethnicity, and origin have driven states around the world to war, violence, and extreme division. However, German-American political scientist Yascha Mounk says this isn't the only path.  On this week's episode, we revisit our 2022 conversation with Mounk about his book, “The Great Experiment: Why Diverse Democracies Fall Apart And How They Can Endure." Two years after our original recording, we wonder whether it's still possible for diverse diverse democracies to succeed in an increasingly polarized political landscape. Guest: Yascha Mounk, associate professor at Johns Hopkins University, contributing editor at The Atlantic and author of The Great Experiment: Why Diverse Democracies Fall Apart and How They Can Endure Host: Ray Suarez If you appreciate this episode and want to support the work we do, please consider making a donation to Commonwealth Club World Affairs. We cannot do this work without your help. Thank you.

durée : 00:43:21 - Signes des temps - par : Marc Weitzmann - Le monde vient de changer radicalement mais nous ne savons pas encore comment. Nous ne le découvrirons pas avant le début de l'année prochaine et l'investiture du 47ème président des Etats-Unis. Mais une chose, une seule est sûre : l'époque a désormais le visage de Donald Trump. - réalisation : Luc-Jean Reynaud - invités : Yascha Mounk Politologue.

Host Marcia Franklin talks with political scientist Yascha Mounk about identity, political divides and his outlook on America. Mounk is the author of several books, including “The People vs. Democracy,” “The Great Experiment,” and “Stranger in My Own Country.” Don't forget to subscribe, and visit the Dialogue website for more conversations that matter. Originally Aired: 11/18/2022 The interview is part of Dialogue's series “Conversations from the Sun Valley Writers' Conference” and was taped at the 2022 conference. Since 1995, the conference has been bringing together some of the world's most well-known and illuminating authors to discuss literature and life.

In Yascha Mounk's new book, he “traces the origin of a set of ideas about identity and social justice that is rapidly transforming America — and explains why it will fail to accomplish its noble goals.” This hour, Mounk joins us to talk about the future of democracy and The Identity Trap: A Story of Ideas and Power in Our Time. GUEST: Yascha Mounk: Professor of the practice of international affairs at Johns Hopkins University; founder of Persuasion; host of The Good Fight; and the author, most recently, of The Identity Trap: A Story of Ideas and Power in Our Time The Colin McEnroe Show is available as a podcast on Apple Podcasts, Spotify, Amazon Music, TuneIn, Listen Notes, or wherever you get your podcasts. Subscribe and never miss an episode! Subscribe to The Noseletter, an email compendium of merriment, secrets, and ancient wisdom brought to you by The Colin McEnroe Show. Join the conversation on Facebook and Twitter. Colin McEnroe, Jonathan McNicol, and Cat Pastor contributed to this show, which originally aired October 4, 2023. Our programming is made possible thanks to listeners like you. Please consider supporting this show and Connecticut Public with a donation today.Support the show: http://www.wnpr.org/donateSee omnystudio.com/listener for privacy information.

Is “identity synthesis” the remedy for racial injustice? This political scientist says no. Yascha Mounk, a professor at Johns Hopkins University and host of “The Good Fight” podcast, explains how identity synthesis - an ideology based on treating people differently depending on their race, gender, or sexual orientation - can be quite harmful to society. He uses the example of racially segregated classrooms, claiming that it is human tendency to inherently side with someone in your “group” before you side with someone from another. Mounk argues that identity synthesis will only further divide us, as it goes directly against the ideologies of Black American thinkers like Fredrick Douglas and Martin Luther King Jr, who fought avidly for equality in the United States. By following this identity-first ideology, we may be reversing the work done by these social rights activists. Instead, we should lean further into their legacy of advocating for universal principles, where individuals are judged not by the categories they belong to but by their character and actions. -------------------------------- Go Deeper with Big Think:- ►Become a Big Think Member Get exclusive access to full interviews, early access to new releases, Big Think merch and more ►Get Big Think+ for Business Guide, inspire and accelerate leaders at all levels of your company with the biggest minds in business ---------------------------------------------------------------------------------- About Yascha Mounk: Yascha Mounk is a writer and academic known for his work on the crisis of democracy and the defense of philosophically liberal values. Born in Germany to Polish parents, Yascha received his BA in History from Trinity College Cambridge and his PhD in Government from Harvard University. He is a Professor of the Practice of International Affairs at Johns Hopkins University, where he holds appointments in both the School of Advanced International Studies and the SNF Agora Institute. Yascha is also a Contributing Editor at The Atlantic, a Senior Fellow at the Council on Foreign Relations, a Moynihan Public Fellow at City College. He is the Founder of Persuasion, the host of The Good Fight podcast, and serves as a publisher (Herausgeber) at Die Zeit. Yascha has written five books: Stranger in My Own Country - A Jewish Family in Modern Germany, a memoir about Germany's fraught attempts to deal with its past; The Age of Responsibility – Luck, Choice and the Welfare State, which argues that a growing obsession with the concept of individual responsibility has transformed western welfare states; The People versus Democracy – Why Our Freedom Is in Danger and How to Save It, which explains the causes of the populist rise and investigates how to renew liberal democracy; and The Great Experiment - Why Diverse Democracies Fall Apart and How They Can Endure, which argues that anybody who seeks to help ethnically and religiously diverse democracies thrive has reason to embrace a more ambitious vision for their future than is now fashionable; and his latest, The Identity Trap - A Story of Ideas and Power in Our Time, which tells the story of how a new set of ideas about race, gender and sexual orientation came to be extremely influential in mainstream institutions, and why it would be a mistake to give up on a more universalist humanism. Next to his work for The Atlantic, Yascha also occasionally writes for newspapers and magazines including The New York Times, the Wall Street Journal, and Foreign Affairs. He is also a regular contributor to major international publications including Die Zeit, La Repubblica, El País, l'Express and Folha de São Paolo, among others. Learn more about your ad choices. Visit megaphone.fm/adchoices

On today's episode I'm speaking with Yascha Mounk, who is a senior fellow at the Council on Foreign Relations and an international affairs professor at Johns Hopkins University. He also hosts his own podcast called The Good Fight (check out his Substack at ) , where I first found out about him. He's written a bunch of books, and his latest – The identity trap: a story of ideas and power in our time (Penguin press) – just came out. It's about diversity, equity and inclusion abbreviated as DEI, the woke ideology and identity politics. All of these terms are often used interchangeably. But instead of using these politically contested concepts Mounk opts to use the term “the identity synthesis” instead. He traces the ideas back to the works of scholars like Derrick Bell, Michel Foucault, and Kimberlé Crenshaw, highlighting how their ideas have been simplified, misinterpreted, twisted and/or radicalized in popular discourse and institutional policies. Mounk argues that while these theories have provided valuable insights into the complexities of identity and oppression, their current application often undermines social cohesion, free speech, and the pursuit of equality by promoting division, silencing dissent, and prioritizing identity over shared humanity. He also argues that the left's long march through institutions, that's often referred to, actually was much shorter than believed. The takeover was swift, he claims, and therefore we should perhaps not focus so much on the counterculture of the 1960s. He's also concerned with the backlash from the right, and recently had an interesting debate with Chris Rufo on Bari Weiss' podcast Honestly. While they agree on a lot of the issues, they differ a lot on the strategy of how to counter “the identity synthesis”. Rufo, Mounk says, if fighting fire with fire, and that will, well, backfire. Laws and regulations won't increase freedom, Mounk argues, and it won't stop ideas from spreading. So how should one do it? Listen and find out.Rak höger expanderarI takt med att fler blir betalande prenumeranter har Rak höger kunnat expandera med fler skribenter och mer innehåll. Vi får inget presstöd, vi tar inte emot pengar från någon intresseorganisation eller lobbygrupp. Det är endast tack vare er prenumeranter vi kan fortsätta vara självständiga röster i en konform samtid. Så stort tack för att ni är med, utan er hade det inget av detta varit möjligt.Den som vill stötta oss på andra sätt än genom en prenumeration får gärna göra det med Swish, Plusgiro, Bankgiro, Paypal eller Donorbox.Swishnummer: 123-027 60 89Plusgiro: 198 08 62-5Bankgiro: 5808-1837Utgivaren ansvarar inte för kommentarsfältet. (Myndigheten för press, radio och tv (MPRT) vill att jag skriver ovanstående för att visa att det inte är jag, utan den som kommenterar, som ansvarar för innehållet i det som skrivs i kommentarsfältet.) This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.enrakhoger.se/subscribe

Gesellschaftliche Debatten drehen sich zunehmend um Identität. Es geht um Hautfarbe, Geschlecht, Herkunft und sexuelle Orientierung. Was ist von dieser Identitätspolitik zu halten? Und woher kommen ihre Grundideen? Darüber spricht Yves Bossart mit dem Politikwissenschaftler Yascha Mounk. Rechtspopulismus und Identitätspolitik hängen eng zusammen. Das meint der in den USA lehrende Politikwissenschaftler Yascha Mounk. In seinem neuen Buch «Im Zeitalter der Identität. Der Aufstieg einer gefährlichen Idee» analysiert er die Ursprünge und Auswirkungen dessen, was gerne als «woke» bezeichnet wird. Strömungen wie die Postmoderne, der Postkolonialismus und die «Critical Race Theory» hätten massgeblich dazu beigetragen, dass Kategorien wie Identität und Gruppenzugehörigkeit politisch wichtiger geworden sind, Wahrheit und Universalismus dagegen an Glaubwürdigkeit verloren haben. Mounk zufolge bedroht diese Entwicklung die liberale Demokratie, befeuert die gesellschaftliche Spaltung und schränkt die Redefreiheit ein. Aber stimmt das? Yves Bossart spricht mit dem in Deutschland aufgewachsenen Politikwissenschaftler über die Ursprünge und Folgen der Identitätspolitik.

Gesellschaftliche Debatten drehen sich zunehmend um Identität. Es geht um Hautfarbe, Geschlecht, Herkunft und sexuelle Orientierung. Was ist von dieser Identitätspolitik zu halten? Und woher kommen ihre Grundideen? Darüber spricht Yves Bossart mit dem Politikwissenschaftler Yascha Mounk. Rechtspopulismus und Identitätspolitik hängen eng zusammen. Das meint der in den USA lehrende Politikwissenschaftler Yascha Mounk. In seinem neuen Buch «Im Zeitalter der Identität. Der Aufstieg einer gefährlichen Idee» analysiert er die Ursprünge und Auswirkungen dessen, was gerne als «woke» bezeichnet wird. Strömungen wie die Postmoderne, der Postkolonialismus und die «Critical Race Theory» hätten massgeblich dazu beigetragen, dass Kategorien wie Identität und Gruppenzugehörigkeit politisch wichtiger geworden sind, Wahrheit und Universalismus dagegen an Glaubwürdigkeit verloren haben. Mounk zufolge bedroht diese Entwicklung die liberale Demokratie, befeuert die gesellschaftliche Spaltung und schränkt die Redefreiheit ein. Aber stimmt das? Yves Bossart spricht mit dem in Deutschland aufgewachsenen Politikwissenschaftler über die Ursprünge und Folgen der Identitätspolitik.

This is a free preview of a paid episode. To hear more, visit smokeempodcast.substack.comOn Jan 2, a writer named Celeste Marcus published an essay entitled, “After Rape: A Guide for the Tormented” in the free-speech literary journal Liberties, where Celeste is managing editor. She wrote about an incident in 2021 with a close male friend as they slept beside each other in bed. She called it rape; he did not. The man remained unnamed until February 4, when Celeste posted an email exchange to Twitter with Atlantic editor-in-chief Jeffrey Goldberg. In one email, Marcus had written, “The rapist was Yascha Mounk. You have a rapist on the staff of your illustrious publication.”Mounk is an Atlantic contributor who specializes in free-speech issues. He's the founder of the journal Persuasion and host of The Good Fight podcast. On Sunday, the Atlantic announced they'd cut ties with Mounk, who has mostly stayed silent.We brought on criminal defense attorney Scott Greenfield to discuss this thorny situation. Greenfield is a straight-shooter who wrote about the case in a recent blog post called “The Atlantic Caves to #MeToo.” To question a victim's story has become taboo, but to interrogate every story has been a necessary tradition of justice, journalism, and rational discourse. Greenfield is not a fan of what he calls “the sex police.”Can we ever be sure what happens in other people's bedrooms? And why has it become so popular, even noble, to try? Gird your loins for a conversation about #MeToo and its aftermath that is frank, illuminating, and challenging — possibly to listeners, definitely to the narrative. Notable talking points:* “Am I allowed to say, ‘I call bullshit' on this pod?”* When did people go from being the heroes of their own stories to the victims of their own stories?* Why drinking matters in sexual assault cases* “A lot of the campus policies under Title IX are unlawful.”* The clear bright line of “no means no”* Plot twist! Leon Wieseltier, #MeToo casualty, is the editor of Liberties journal* How feminist activists bypassed the dead-lock of “he said/she said”* “You can't call a woman crazy. But what if they are crazy?”* Felicia Sonmez, remembered* How do Atlantic writers feel about Goldberg kicking a contributor to the curb?* What should Yascha Mounk do now?* Let's built tolerance for ambiguity!* The bravery of journalist Emily Yoffe* The sadness of “compare and despair”* Can we ever walk this back?* Advice to parents!* “Hot box???”

We anticipate our upcoming series on Aristotle's Metaphysics by talking through some preliminary issues about the text including what translations we're reading. Is this book really "timeless," or is it like old, outdated science? Also, what kind of person becomes an ancient philosophy student? Plus (in the full discussion), we talk more about Mounk, Presidential disqualification, and more. If you're not hearing the full version of this discussion, sign up via one of the options described at partiallyexaminedlife.com/support.

Political scientist and author Yascha Mounk joins Ian Bremmer on the GZERO World Podcast to discuss his latest book, “The Identity Trap: A Story of Ideas and Power in Our Time.” Mounk delves into the complicated dynamics of identity politics and challenges the conventional wisdom from the progressive left that focusing on identity and what makes us different from each other leads to a more equitable society. By highlighting our differences rather than shared values, Mounk argues, well-meaning liberals are exacerbating societal division and hindering progress toward greater equality. While acknowledging that our society is deeply imperfect and genuine injustices remain, Mounk unpacks the implications of identity politics and questions whether the current focus on identity truly serves the cause of inclusivity or social harmony.

Political scientist and author Yascha Mounk joins Ian Bremmer on the GZERO World Podcast to discuss his latest book, “The Identity Trap: A Story of Ideas and Power in Our Time.” Mounk delves into the complicated dynamics of identity politics and challenges the conventional wisdom from the progressive left that focusing on identity and what makes us different from each other leads to a more equitable society. By highlighting our differences rather than shared values, Mounk argues, well-meaning liberals are exacerbating societal division and hindering progress toward greater equality. While acknowledging that our society is deeply imperfect and genuine injustices remain, Mounk unpacks the implications of identity politics and questions whether the current focus on identity truly serves the cause of inclusivity or social harmony. Subscribe to the GZERO World with Ian Bremmer Podcast on Apple Podcasts, Spotify, or your preferred podcast platform, to receive new episodes as soon as they're published.

We continue our discussion with Yascha Mounk, one of the leading public intellectuals of our time. The subject is a hugely influential ideology that attempts to put racial, sexual and gender identity at the center of our social, cultural and political life. The "identity synthesis", Mounk argues, denies that members of different groups can truly understand one another and this stifles public discourse.In this podcast episode, we learn why an obsession with identity undermines social justice, fuels culture wars, and boosts hateful hardliners on the right and left— from Donald Trump to protesters who support Hamas and its murderous attacks on Israeli civilians. We also hear how to politely but firmly push back against those who have become ensnared in "The Identity Trap," the name of Yascha Mounk's new book."Categories like race and gender and sexual orientation help to explain what's going on in the world, but they're not the only categories that help to explain it," Mounk tells us. "There's also social class, religion and patriotism as well as individual actions, attributes and aspirations.""The Identity Trap" has been called "the most ambitious and comprehensive account to date of the origins, consequences and limitations" of "wokeness". In our last episode, Yascha Mounk explained how postmodernism, postcolonialism and critical race theory gained currency on many college campuses by 2020. Today, a simplified version of these ideas exerts a strong influence in business, government and media. In this episode, Mounk urges listeners to claim the moral high ground. "Don't apologize about arguing against a worldview that emphasizes identity to the exclusion of other factors". Recognize we have genuine disagreements but argue for convictions that you believe will result in a better world. People are open to persuasion, he says.Mounk mentions two of the most effective critics of the identity ideology were once very drawn to it: Maurice Mitchell of the Working Families Party and interfaith organizer, Eboo Patel.Recommendation: Richard has just read "The Speech", by Gary Younge, who writes for the Guardian and The Nation. His book is the story behind Martin Luther King Jr.'s powerful "I have a Dream" speech delivered to a vast audience in 1963. Hosted on Acast. See acast.com/privacy for more information.

durée : 02:59:22 - Le 7/10 - Les invités de la Matinale de France Inter ce lundi 18 décembre 2023 sont : Annie Genevard / Yascha Mounk / B. Teinturier x J. Sainte-Marie / Judith Godrèche / Martin Bourboulon

Having skewered right-wing populism and its demagogues in his two previous best-selling books, politics professor, writer, and podcaster Yasha Mounk turns now to the threat posed to liberalism from those progressives who champion "woke" identity politics. We discuss his latest, "The Identity Trap: A Story of Ideas and Power In Our Time."This episode— the first of two with Yasha Mounk — looks at the complex roots of a highly influential ideology based on personal identity— specifically race, gender and sexual orientation. These are said to determine a person's power, role in society, and how they see themselves. Mounk explains how the identity synthesis, which has become widely accepted in many universities, nonprofits and large corporations, had its origins in several intellectual traditions, including post-colonialism, postmodernism and critical race theory.Our interview mentions ideas and concepts raised by Michel Foucault, Derrick Bell, Kimberlé Krenshaw, Edward Said, Gayatri Chakravorty Spivak, and others. We learn how these thinkers sharply criticized modern liberalism and the civil rights movement of the Sixties and beyond.Yascha Mounk is a German-born American who teaches international affairs at Johns Hopkins University. His writing appears in The Atlantic and other publications. He is also founder and editor-in-chief of the Substack publication "Persuasion", and hosts the podcast, "The Good Fight".Mounk's new book has won widespread critical praise. The Washington Post said that "Mounk has told the story of the Great Awokening better than any other writer who has attempted to make sense of it."Recommendation: Jim is reading "UFO: The Inside Story of the US Government's Search for Alien Life Here— and Out There: by Garrett Graff. Hosted on Acast. See acast.com/privacy for more information.

In his new book, The Identity Trap: A Story of Ideas and Power in Our Time, political scientist Yascha Mounk has written the most comprehensive and detailed account yet of how a new form of progressive thinking has taken over the politics of the left. Mounk chronicles the rise of a set of ideas which are “centrally concerned with the role that identity categories like race, gender, and sexual orientation play in the world.” This fixation on identity, rejecting “universal values and neutral rules like free speech and equal opportunity as mere distractions,” draws its strength, Mounk argues, from the way it took over cultural institutions, although it has not convinced more than a small number of people. These ideas are not just frequently wrong but inimical to a functioning society, he tells Hugh Linhan in today's Inside Politics podcast.Produced by Declan Conlon. JJ Vernon on sound. Hosted on Acast. See acast.com/privacy for more information.

durée : 00:44:57 - Signes des temps - par : Marc Weitzmann - Qu'est-ce que l'essentialisme stratégique ? Le politologue Yascha Mounk, qui publie "Le piège de l'identité" aux éditions de l'Observatoire revient sur la genèse du mouvement woke et ses conséquences à l'université et plus largement dans la société américaine. - invités : Yascha Mounk Politologue

For this episode, Yascha Mounk, the writer and political scientist discusses his recent book The Identity Trap, which explores what Mounk refers to as the modern world's counterproductive obsession with group identity in all its forms. Joining Mounk in conversation is writer Tomiwa Owolade, author of the book This is Not America.  Want the hear the full extended conversation right now? Become a supporter of Intelligence Squared to get access to all of our longer form interviews and members-only content. Just visit intelligencesquared.com/membership to find out more.  For £4.99 per month you'll receive: - Full-length and ad-free Intelligence Squared episodes, wherever you get your podcasts - Bonus Intelligence Squared podcasts, curated feeds and members exclusive series, wherever you get your podcasts - 15% discount on livestreams and in-person tickets for all Intelligence Squared events - Our member-only newsletter The Monthly Read, sent straight to your inbox Or Subscribe on Apple for £4.99: - Full-length and ad-free Intelligence Squared podcasts - Bonus Intelligence Squared podcasts, curated feeds and members exclusive series ... Already a subscriber? Thank you for supporting our mission to foster honest debate and compelling conversations! Visit intelligencesquared.com to explore all your benefits including ad-free podcasts, exclusive bonus content, early access and much more The Full Length Video is here: https://www.intelligencesquaredplus.com/videos/yascha-mounk-on-the-identity-trap-with-tomiwa-owolade ... Subscribe to our newsletter here to hear about our latest events, discounts and much more. https://www.intelligencesquared.com/newsletter-signup/ ... Get in touch with any feedback and guest or debate ideas by emailing us at podcasts@intelligencesquared.com or Tweet us @intelligence2.  Learn more about your ad choices. Visit podcastchoices.com/adchoices

Get tickets for our event: https://skeptic.com/event For much of history, societies have violently oppressed ethnic, religious, and sexual minorities. It is no surprise that many who passionately believe in social justice came to believe that members of marginalized groups need to take pride in their identity to resist injustice. But over the past decades, a healthy appreciation for the culture and heritage of minority groups has transformed into a counterproductive obsession with group identity in all its forms. A new ideology aiming to place each person's matrix of identities at the center of social, cultural, and political life has quickly become highly influential. It stifles discourse, vilifies mutual influence as cultural appropriation, denies that members of different groups can truly understand one another, and insists that the way governments treat their citizens should depend on the color of their skin. This, Yascha Mounk argues, is the identity trap. Though those who battle for these ideas are full of good intentions, they will ultimately make it harder to achieve progress toward the genuine equality we desperately need. Shermer and Mounk discuss: the identity synthesis/trap • Israel, Hamas, Palestine • why students & student groups are pro-Palestinian and anti-Israel • the rise of anti-Semitism in recent years • proximate/ultimate causes of anti-Semitism • the rejection of the civil rights movement and the rise of critical race theory • overt racism vs. systemic racism • the problem of woke ideology • Trump and the 2024 election • the possibility of another Civil War • What should we do personally and politically about the Identity Trap? Yascha Mounk is a writer and academic known for his work on the rise of populism and the crisis of liberal democracy. Born in Germany to Polish parents, Mounk received his BA in history from Trinity College Cambridge, and his PhD in government from Harvard University. He is a professor of the practice of international affairs at Johns Hopkins University, the founder of the digital magazine Persuasion, a contributing editor at The Atlantic, and a senior fellow at the Council on Foreign Relations. He is the author of numerous books, incl. The Great Experiment: Why Diverse Democracies Fall Apart and How They Can Endure (featured on President Barack Obama's summer reading list).

Mark, Wes, Dylan, and now Seth too discuss further Mounk's project in The Identity Trap and what philosophically we can glean from it. If you're not hearing the full version of this part of the discussion, sign up via one of the options described at partiallyexaminedlife.com/support.

Joe Selvaggi hosts a conversation with Johns Hopkins University Professor Yasha Mounk regarding "The Identity Trap," Mounk's latest book that delves into the origins of woke identity politics, its potential impact on classical liberal values, and strategies for its informed opponents to effectively counter its influence.

The phrases "woke" and "anti-woke" have entered the general lexicon in recent years, providing combative fodder to both sides of the debate, and fueling division in American discourse. But what are the origins and consequences of so-called "wokeness?"rnrnIn Yascha Mounk's previous visit to the City Club, he discussed shifts in the global thoughts about democracy, how we got here, and how it can be saved. Mounk has built his acclaimed scholarly career on being one of the first to warn of the risks right-wing populists pose to American democracy. Now, Mounk joins us once again to discuss his latest book that tackles the appeal and limitations of identity-based politics--which has rapidly transformed America and college campuses across the country. He calls it the "identity trap," and argues those on the left and center who are stuck in the identity trap will ultimately make it harder to achieve progress toward genuine equality.rnrnYascha Mounk, Ph.D. is a political scientist known for his work on the rise of populism and the crisis of liberal democracy. He is a professor of the practice of international affairs at Johns Hopkins University, the founder of the digital magazine Persuasion, a contributing editor at The Atlantic, and a senior fellow at the Council on Foreign Relations. The Identity Trap is his fifth book.

Political scientist Yascha Mounk joins Margaret Hoover to discuss his latest book, “The Identity Trap,” and rising threats to democracy on the right and left. Mounk–a professor at Johns Hopkins University and contributing writer for The Atlantic–explains how the identity-focused politics of the left have become a “trap” that he fears is likely to produce more prejudice and division, and he traces the evolution of these ideas as they increasingly take hold in mainstream institutions. He offers examples of the harm this “identity synthesis” has caused in education and health care, details strategies for fighting back against it, and makes the case for a more universalist political philosophy. Mounk, who has previously written about the dangers of populism, also takes on the identity politics of the right and warns that progressives' embrace of unpopular ideas about race and gender could send Donald Trump back to the White House.  Support for “Firing Line for Margaret Hoover” is provided by Robert Granieri, Stephens Inc., Vanessa and Henry Cornell, The Fairweather Foundation, The Tepper Foundation, The Asness Family Foundation, Kathleen and Andrew McKenna through The McKenna Family Foundation, Charles R. Schwab, The Rosalind P. Walter Foundation, and Damon Button.

Former LA Dodgers pitcher Trevor Bauer was essentially run out of baseball after an accusation of sexual assault was lodged against him. Bauer always maintained his innocence, and this week, with the settlement of a legal suit, he posted information on social media that, while incomplete, seems at least somewhat, if not wholly, exculpatory. Mike examines the media's paralysis in covering this matter and ideological media's willingness to lead the way. Plus, Yascha Mounk is out with a new book, The Identity Trap: A Story of Ideas and Power in Our Time. It's an excellent intellectual and practical examination of what some call identity politics and what Mounk rebrands as "identity synthesis." The Washington Post says, "Mounk has told the story of the Great Awokening better than any other writer who has attempted to make sense of it." Produced by Joel Patterson and Corey Wara Email us at thegist@mikepesca.com To advertise on the show, visit: https://advertisecast.com/TheGist Subscribe to The Gist Subscribe: https://subscribe.mikepesca.com/ Follow Mikes Substack at: Pesca Profundities | Mike Pesca | Substack Learn more about your ad choices. Visit podcastchoices.com/adchoices

Sixty years ago, outlawing racial segregation was a dominant civil rights priority of liberals. Today, in the name of racial equality, many progressive thinkers and activists champion policies and actions that promote segregation. The story of how that moral transformation took place is one of the central preoccupations of the professor Yascha Mounk, the author of The Identity Trap: A Story of Ideas and Power in Our Time. In that book, released last month, Mounk plots the relevant intellectual history, from the postmodern philosophy of Michel Foucault to the post-colonial writing of Edward Said to early expressions of critical race theory in the work of Derrick Bell and to the articulation of the governing idea of intersectionality in the work of Kimberlé Crenshaw. Mounk explores how the architects of what he calls “the identity synthesis”—his term for what alternatively goes by identity politics or wokeness, terms that he avoids because he believes they are overly polemical—are not accidentally but conscientiously opposed to the race-blind aspirations of their liberal predecessors. All this he discusses this week with Mosaic editor Jonathan Silver. The two also turn to the question of what this revolutionary moral transformation has to do with the Jews. Does the very notion that Americans should be categorized and evaluated in political, civic, and educational settings on the basis of race—and that, moreover, Jews are often fit into the racially white, oppressor category—mean that logic of the identity synthesis tends toward anti-Semitism? Does the legitimating of racial categorization give ammunition to white supremacists to reject the whiteness of Jews, and indulge their own Jew-hatred? And what does all this mean for the central goal of Jewish education—to teach children to assume responsibility for and pride in the Jewish tradition? Musical selections in this podcast are drawn from the Quintet for Clarinet and Strings, op. 31a, composed by Paul Ben-Haim and performed by the ARC Ensemble.

“Part of the beauty of America is that we all have roots in all kinds of parts of the world, and we bring that cultural richness—and the aspect of cultural diversity—with us to this country.”  So says Yascha Mounk on this episode of The Russell Moore Show. And yet, of course, differences can also bring about conflict that has a significant negative impact on individuals and society alike. Mounk, an expert on issues in liberal democracy, and Moore discuss these parallel truths through the lens of Mounk's new book, The Identity Trap: A Story of Ideas and Power in Our Time. Mounk and Moore talk about the “spiral of radicalization” the United States finds itself in today. They consider the role of political parties, institutions, and perspectives on race in shaping our cultural moment. Their conversation dives into sexual orientation, gender identity, and marriage as well as pedagogy, theology, and social psychology.  Tune in for a thoughtful dialogue that spans issues of discrimination, justice, and the power of influence in our daily lives.  Resources mentioned in this episode include: Yascha Mounk at The Atlantic Council on Foreign Relations Persuasion Journal The Good Fight podcast The Identity Trap: A Story of Ideas and Power in Our Time by Yascha Mounk Ruby Bridges Goes to School: My True Story by Ruby Bridges Chloé Valdary Do you have a question for Russell Moore? Send it to questions@russellmoore.com. Click here for a trial membership at Christianity Today. “The Russell Moore Show” is a production of Christianity Today Executive Producers: Erik Petrik, Russell Moore, and Mike Cosper Host: Russell Moore Producer: Ashley Hales Associate Producers: Abby Perry and Azurae Phelps Director of Operations for CT Media: Matt Stevens Audio engineering by Dan Phelps Video producer: Abby Egan Theme Song: “Dusty Delta Day” by Lennon Hutton Learn more about your ad choices. Visit podcastchoices.com/adchoices

In Yascha Mounk's new book, he “traces the origin of a set of ideas about identity and social justice that is rapidly transforming America — and explains why it will fail to accomplish its noble goals.” This hour, Mounk joins us to talk about the future of democracy and The Identity Trap: A Story of Ideas and Power in Our Time. GUEST:  Yascha Mounk: Professor of the Practice of International Affairs at Johns Hopkins University, the founder of the digital magazine Persuasion, and host of the podcast The Good Fight. His new book is The Identity Trap: A Story of Ideas and Power in Our Time Join the conversation on Facebook and Twitter. Subscribe to The Noseletter, an email compendium of merriment, secrets, and ancient wisdom brought to you by The Colin McEnroe Show. The Colin McEnroe Show is available as a podcast on Apple Podcasts, Spotify, Google Podcasts, Amazon Music, TuneIn, Listen Notes, or wherever you get your podcasts. Subscribe and never miss an episode.  Colin McEnroe and Cat Pastor contributed to this show.Support the show: http://www.wnpr.org/donateSee omnystudio.com/listener for privacy information.

The main purpose of this micro-episode is to give you the details on the much ballyhooed Philadelphia area meet-up of fans of the podcast.  The date is this Friday, October 6, 2023.  The place will be Neshaminy Creek Brewing Company, 909 Ray Avenue, Croydon, Pennsylvania.  The official start-time is 5:00 pm, but if you can't get there so early rest assured that I'll be around until at least 7:30, and certainly as late as the conversation remains fun and interesting. I'll aim to get there at 4:30 or so to check out the room I reserved, which I believe they call “the nook.”  I trust many of you will recognize me from my photo on the website or on Twitter or Facebook, but in case not I'll be wearing a red “History Nerd” cap.  I also read a short excerpt from Yascha Mounk's new book The Identity Trap: A Story of Ideas and Power in Our Time, which I highly recommend. Mounk explores the philosophical roots of critical theory and the full range of ideas clumsily lumped together as "wokeism," or "the successor ideology." The book is extremely useful for understanding how we arrived at our current identity politics, and is relevant to understanding the "history wars" that have played out over the last four or five years. You can buy it through the link above.

I've interviewed Yascha Mounk about his book The Identity Trap: A Story of Ideas and Power in Our Time, which was released this week."Mounk has told the story of the Great Awokening better than any other writer who has attempted to make sense of it," The Washington Post wrote in a review.Yascha's book says that we can reach across our differences and understand one another, and that we need to make the effort to do so, through conversation, debate, and relationship. I was not aware of the degree to which some progressive writers and intellectuals have argued that such mutual understanding is not even possible, and so they have discouraged the pursuit.It's hard for me to imagine a world in which we do not at least try to understand and appreciate one another, even those with whom we have profound differences. That effort is at the heart of a free and prosperous society, in my mind.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Writer and academic Yascha Mounk argues that a new set of ideas about race, gender, and sexual orientation have overtaken society, giving rise to a rigid focus on identity in our national debate. In his new book, “The Identity Trap: A Story of Ideas and Power in Our Time,” Yascha seeks to take these ideas seriously, understand their origin, dissect their merits and failings, and offer a path forward to avoid what he calls “the identity trap.” On today's show, Mounk previews his book and explains how the identity trap harms freedom of speech. Mounk is known for his work on the rise of populism and the crisis of liberal democracy. He is a professor of the practice of international affairs at Johns Hopkins University and the author of five books. He is also the founder of the digital magazine Persuasion, a contributing editor at The Atlantic, and a senior fellow at the Council on Foreign Relations. Timestamps: 0:00 - Introduction 1:35 - Origins of “the identity trap” 8:48 - What is “identity synthesis?” 12:26 - Is “cultural Marxism” a thing? / The intellectual history of identity synthesis 27:47 - Critical race theory 32:30 - Free speech culture 40:22 - Speech and violence 47:58 - The Law of Group Polarization  52:27 - How to escape the identity trap Discussed intellectuals:  Derrick Bell  Kimberlé Crenshaw  Jacques Derrida  Michel Foucault Christopher Rufo (Rufo's book, “America's Cultural Revolution,” and Nico's review, “Christopher Rufo Became the Thing He Claims to Hate”) Edward Said Jean-Paul Sartre Gayatri Spivak  Cass Sunstein (article: “The Law of Group Polarization”) www.sotospeakpodcast.com YouTube: https://www.youtube.com/@freespeechtalk Twitter: https://www.twitter.com/freespeechtalk Facebook: https://www.facebook.com/sotospeakpodcast Instagram: https://www.instagram.com/freespeechtalk/ Email us: sotospeak@thefire.org

Jim talks with Yascha Mounk about the ideas in his new book The Identity Trap: A Story of Ideas and Power. They discuss tribalism among progressives, universalism, the story of Kila Posey, how over-emphasizing ethnic identity fosters zero-sum racial conflicts, how identitarianism led to excess Covid deaths, Foucault's rejection of grand narratives, Edward Said's post-colonialism, Gayatri Spivak's strategic essentialism, being blind to race vs being blind to racism, critical race theory, Derrick Bell's idea of the permanence of racism, how the rejection of universalism escaped college campuses, why progressive organizations are tearing themselves apart, the logic of collective action, how progressive activists have passed off their ideas as those of all non-white people, statistics on police violence, Frederick Douglass's 4th of July speech, cultural appropriation, retaining trust in persuasion, fighting for liberalism, personal & political aspects of the identity trap, and much more. Episode Transcript The Identity Trap: A Story of Ideas and Power, by Yascha Mounk "Why the Latest Campus Cancellation Is Different," by Yascha Mounk JRS EP197 - Susan Neiman on Why Left Is Not Woke "A Political Analysis of Racial Differences in Police Use of Force," by Roland Fryer, Jr. Yascha Mounk is a writer and academic known for his work on the rise of populism and the crisis of liberal democracy. Born in Germany to Polish parents, Mounk received his BA in history from Trinity College Cambridge, and his PhD in government from Harvard University. He is a professor of the practice of international affairs at Johns Hopkins University, the founder of the digital magazine Persuasion, a contributing editor at The Atlantic, host of the podcast “The Good Fight,” a senior fellow at the Council on Foreign Relations, and the author of The Great Experiment and The Identity Trap.

Questa puntata di Globo parte dalla morte di Silvio Berlusconi: non per inoltrarci nella politica italiana, ma perché molti analisti e studiosi negli ultimi giorni hanno ricordato Berlusconi come il padre di un certo populismo che poi è diventato prevalente in tutto l'Occidente. Partendo da Berlusconi raccontiamo l'ascesa del populismo in Europa, e i pericoli che pone per la democrazia. Lo facciamo con uno dei massimi esperti al mondo: Yascha Mounk, autore di studi tradotti un po' in tutto il mondo, professore all'Università Johns Hopkins e membro del centro studi Council on Foreign Relations. – L'ultimo libro di Yascha Mounk, “Il grande esperimento” – Il podcast di Mounk, “The Good Fight” I CONSIGLI DI YASCHA MOUNK – “Sulla libertà” di John Stuart Mill – “Il Gattopardo” di Giuseppe Tomasi di Lampedusa – La libertà degli antichi, paragonata a quella dei moderni” di Benjamin Constant CONTINUA SUL POST – Cos'è il populismo – Il populismo ha fatto anche cose buone? – Lo stile poco ortodosso di Berlusconi in politica estera Globo è un podcast del Post condotto da Eugenio Cau. Learn more about your ad choices. Visit megaphone.fm/adchoices

Diversity has often been seen as the United States' defining strength, but today some Americans see it as a threat. And this isn't new. Throughout history, differences of religion, ethnicity, and origin have driven states around the world to war, violence, and extreme division. However, German-American political scientist Yascha Mounk says this isn't the only path.  On this week's episode, Mounk joins Ray to discuss his new book, “The Great Experiment: Why Diverse Democracies Fall Apart And How They Can Endure,” which challenges the assumptions of a modern pluralist society and imagines how diverse democracies might succeed in an increasingly polarized political landscape.   Guest:   Yascha Mounk, associate professor at Johns Hopkins University, contributing editor at The Atlantic and author of The Great Experiment: Why Diverse Democracies Fall Apart and How They Can Endure   Host:   Ray Suarez

As expat moms, we are in a unique position to live all over the world in the midst of other cultures.  This comes with some amazing benefits of exposure and significant relationships with people of many cultures and colors—this is one of the research-supported ways to promote anti-racism.  If we have close personal relationships with people who are different from us we can lose our inaccurate bias'.  However, being an expat and living in another culture also introduces new bias'.  Expat children have difficult experiences abroad that can cause bias' in a very real and personal way.   Without deliberate mothering, these experiences can cause our children to associate an entire culture with a bad experience they had.  We need mothers who are actively training the minds of their children to be anti-racist so we can build a more fair society and we can all enjoy and learn from the diversity of each other.  I hope this podcast will give you some helpful tools to raise Anti-racist kids as I discuss this topic with Rosemay Webster. Things You'll Learn on the Podcast:Why avoiding talking about skin color promotes racismHow to talk about race with your childWhat creates implicit biasHow to minimize implicit bias in our childrenUnique ways expat kids develop bias' they might not in their home countryHow to help kids avoid turning negative experiences with your host culture into broader biasResources Mentioned in the ShowPodcast:  Real Talk/Almost Docshttps://www.instagram.com/realtalkalmostdocs/Implicit Bias Testhttps://implicit.harvard.edu/implicit/takeatest.htmlDiAngelo, R. (2011). White Fragility. International Journal of Critical Pedagogy, 3(3), 54-70.Mounk, Yascha.  (2022) “Yascha Mounk on the Future of Diverse Democracies”. The Lawfare Podcast. https://podcasts.apple.com/us/podcast/yascha-mounk-on-the-future-of-diverse-democracies/id498897343?i=1000558014962 Kendi, Ibram X. How to Be an Antiracist. New York, NY: One World, 2019Munger, K. Tweetment Effects on the Tweeted: Experimentally Reducing Racist Harassment. Polit Behav 39, 629–649 (2017). The First Name Basis Podcast with Jasmine Bradshawhttps://firstnamebasis.libsyn.com/anti-racism-where-do-i-start Free Coaching SessionSign-up for a free coaching session.ScheduleOne-Minute WisdomEach week I carefully craft a short perspective shift or tool that you can read in about a  minute.  You can sign up here.Follow me on Instagram: @theexpatmomcoach or on Facebook:  @theexpatmomcoach

Is good old American flag waving patriotism dead, only to be replaced with chauvinistic nationalism, or worse, anti-Americanism? Perhaps thinking of national pride as something rooted in the Constitution, the Bill of Rights and the U.S.' proud history is too 20thcentury; maybe it is no longer working? Indeed, in a country in which history and civics get short shrift in education, it should come as no surprise that many under 50 feel no pride, no patriotic sense as Americans. But there may be another way – a new cultural patriotism, in which people have pride in the country they know rather than in the traditions that have spawned national holidays and parades. Will that work? Yascha Mounk joined Dany and Marc to discuss the findings of his new book The Great Experiment: Why Diverse Democracies Fall Apart and How They Can Endure (Penguin Press). He discusses the concept of cultural patriotism, the problem of multiculturalism and assimilation. They also debate the metaphor of America's melting pot, American exceptionalism, and the ideals that make America the best country on earth.  Mounk is one of the world's leading experts on the crisis of liberal democracy and the rise of populism. He is a contributing writer at The Atlantic, an associate professor at Johns Hopkins University, a senior fellow at the Council on Foreign Relations, and the founder of Persuasion. https://www.aei.org/wp-content/uploads/2022/04/WTH-Mounk-Transcript.pdf (Download the transcript here.)

Confidence in democracy is declining in the West at the same time authoritarian leaders like Putin and Xi Jinping have become more transparent about their demands and lack of respect for democracy, says Johns Hopkins University professor Yascha Mounk, author of a new book, "The Great Experiment: Why Diverse Democracies Fall Apart and How They Can Endure."   On the GZERO World podcast, Mounk tells Ian Bremmer we're in a new era of naked power politics, illustrated by the way Putin is transforming Russia into a repressive regime. Putin believes the West is decadent while he views himself as a strong leader with traditional values. Meanwhile, the biggest challenges ahead for democracies like the US are racial disparities in wealth, tribalism, and extreme partisanship.