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A bi-weekly news show informing you on the latest in Bitcoin, privacy and open source tech hosted by Ungovernables, Max and Q. AOBFreedom.Tech launch reminderKeyOS v1.3 now publicly availableNEWSIndia orders GitHub to take down BitChat's source code; Internet Freedom Foundation calls it unconstitutional - TFTC: India BitChat GitHub takedown, I4C, IFF / CoinDeskFourth Circuit says border agents can hand-search your phone with zero suspicion, as a man is prosecuted for a duress-wipe - EFF: Fourth Circuit says border agents can search your phone by hand, no suspicion required / TechCrunch: US accuses American of wiping his phone with a duress password at the borderSenate Democrats kill the CLARITY Act before recess; the developer safe harbor (Section 604) stalls with it - TFTC: CLARITY Act rejected, Bitcoin ownership surpasses goldState Department launches a "Freedom Tech" program with BPI, Palantir, and Anduril as founding partners - Bitcoin Magazine: State Department tech program with BitcoinBlock open-sources Buzz: a Nostr-native, keypair-identity workspace for humans and AI agents - LINKBIP-110 approaches its mandatory signaling window with support under 1%, and enforcing nodes staring at a minority fork - TFTC: BIP-110 enters mandatory signaling window below 1% hashrateRELEASESBitcoin core / protocolbtcd v0.26.2 - 2026-07-25Security-hardening for the Go full node: stricter PSBT/input parsing, Schnorr and WIF validation, rejection of malformed bech32, tighter inbound admission.Hardware / signingKeystone 3 v3.0.0 - 2026-07-21Major firmware across all variants of the airgapped open-source signer: reworked passcode/recovery flow, stronger validation, upgraded security policies. Reproducible with published checksums.Trezor Suite v26.7.2 - 2026-07-22Firmware security updates plus a lower 0.2 sat/vB minimum fee and cancel-pending-transaction support.Nunchuk 2.7.1 - 2026-07-16Collaborative-custody multisig wallet. 2.7.0 (07-15) added self-custodial USDT on Liquid and Trezor Bluetooth support; 2.7.1 is bug fixes on top. On-lens for multisig self-custody.Bitkey App 2026.11.0 - 2026-07-14Block's consumer hardware wallet. Release highlights its Emergency Access (recovery/inheritance) path; full notes hosted off-repo at bitkey.world/releases.LightningCore Lightning v26.06.6 - 2026-07-22Patch release (26.06.3-5 pulled over broken PyPI publishing). Now rejects channels reusing an existing funding outpoint, closing a channel-security edge case.LNDg v1.11.0 - 2026-07-26Self-hosted LND dashboard: peer-offline reporting, auto re-index on data migration, historic failed-HTLC data via API. Update logging config on upgrade.Zeus v13.1.3 - 2026-07-21Point release / version bump on the 13.1 line for the self-custodial Lightning wallet.LNbits v1.5.6 - 2026-07-15Minor patch on 1.5.5 (payments extension-field refactor and fixes) for the self-hosted Lightning accounts system.Lightning Labs Wavelength - 2026-07-21A toolkit for adding self-custodial bitcoin (and stablecoin) payments to any application, designed to create the best developer experience for humans and agents.EcashCashu TS v5.0.0-rc.5 - 2026-07-23RC for the major v5 of the reference TS Cashu library: NUT-18 payment requests (PaymentRequestBuilder), mint-preference support, hardened P2PK validation, integer fee math. Foundational for ecash wallets.Nutshell 0.20.3 - 2026-07-22Reference mint/wallet: Pay-to-Blinded-Key (lock ecash to a receiver without revealing their pubkey to the mint), a Spark L2 backend, and a false-UNPAID melt-race fix. DB migration, back up first.Fedimint v0.12.0-beta.0 - 2026-07-23Beta pre-release of the federated ecash / community-custody protocol. Flagged unstable, no upgrade guarantee. "In the pipeline," not production. (Admin UI: Fedimint UI v0.7.4, adds arm64 image.)On-chain privacy / coinjoinWasabi Wallet v2.8.1 - 2026-07-22Now receives to Taproot addresses by default (a real "state of the network" adoption nudge, four-plus years post-activation), adds Linux AppImage, on top of 2.8.0's serverless P2P filter sync.Ashigaru Desktop v1.1.2 - 2026-07-25Whirlpool coinjoin QoL: live Tor/Electrum status, one-click connect, faster startup, self-clearing coordinator banner.JoinMarket-NG 0.34.2 - 2026-07-20Actively-maintained modern fork of JoinMarket: safe expired-fidelity-bond handling, correct frozen-UTXO reporting, multi-wallet RPC routing.Bitcoin Safe 2.1.1 - 2026-07-20Multisig/single-sig desktop wallet: UI fixes and improved Debian build reproducibility.P2P / no-KYCBisq 1.10.4 - 2026-07-24Mandatory security update for the decentralized no-KYC exchange (audit findings): signed DAO block providers, stricter blind-vote/dispute validation, re-enabled BSQ swaps. Required to keep trading.Bull Bitcoin 6.12.4 - 2026-07-24Bug-fix for the no-account self-custodial app (iOS startup-lockup fix). The feature release was 6.12.2 (UTXO/coin-control, Coldcard NFC, BitBox02 Nova BLE, sub-1 sat/vB).Vexl v1.45.1 - 2026-07-21Point release of the contacts-based no-KYC P2P trading app (small fixes).Peach Bitcoin 0.69.0 (381) - 2026-07-23Latest build of the no-KYC P2P Bitcoin marketplace (rolling 0.69.0 build increments 379/380/381 across the fortnight). Verify the build-tag slug before publishing (parentheses in the tag).Self-hosting / infraBTCPay Server v2.4.1 - 2026-07-23Self-hosted no-KYC payment processor: BIP-329 label import, editable invoice comments, refund-email triggers, RTL UI, restored Boltcard payments.Start9 StartOS v0.4.0 - 2026-07-24Major: a complete ground-up rewrite of StartOS, out of public beta after six years, billed as the "correct architecture for sovereign computing." Note: the only upgrade path is a fresh install (no in-place migration). One of the biggest self-hosting stories of the fortnight.Liquid GDK release_0.77.7 - 2026-07-20Blockstream's wallet SDK: libwally + Tor bumps, macOS/iOS cross-compile, single-sig gap-limit fee fix.Privacy stack / PayjoinPayjoin Dev Kit payjoin-cli 1.0.0-rc.1 - 2026-07-23RC for the reference Payjoin CLI, synced to payjoin 1.0.0-rc.6. Signals the v1.0 Payjoin stack nearing release (breaks common-input-ownership heuristics on-chain).NostrAmber v6.3.0 - 2026-07-20Android Nostr remote signer (keeps your nsec off client apps): grouped/collapsible multi-request approvals, a log-disabling privacy mode, built-in Tor, NIP-65 relay prefetch.Wallets (self-custody)BlueWallet 8.0.1 - 2026-07-21Major v8 line: iOS 26 UI refresh, BC-UR v2 airgap scanning (OneKey/Keystone), Unchained multisig cosigner import, 19 new languages, crypto-js replaced with @noble. Broad user base. Confirm the exact tag slug before publishing.Cake Wallet 6.3.2 - 2026-07-24Non-custodial BTC/Monero wallet: home-screen recent history, better OpenAlias/ENS/Unstoppable alias resolution, faster Zcash sync.EDUCATIONWhat Is a UTXO, and Why Does It Matter for Bitcoin Privacy? - 2026-07-25Community explainer thread on Stacker News. The useful part is the top response, which walks through how receive-and-spend patterns fingerprint you and where coinjoin actually helps. Good raw material for a plain-English UTXO segment, which pairs with the Wasabi and Ashigaru releases and gives newer listeners the vocabulary before the coinjoin talk.Bitcoin Optech Newsletter #415 - 2026-07-24Two items worth surfacing. Fabian Jahr's draft BIP459 proposes full aggregation of BIP340 schnorr signatures using DahLIAS, combining multiple signatures into a single 64-byte aggregate, with cross-input signature aggregation as a downstream possibility. And libsecp256k1 #1765 adds an optional BIP352 silent-payments module supporting receiver scanning from only the scan secret and spend pubkey, so the spend private key stays offline. Silent payments quietly becoming infrastructure is a good recurring beat.TO DONATE TO ROMAN'S DEFENSE FUND: https://freeromanstorm.com/donateHELP GET SAMOURAI A PARDONSIGN THE PETITION ----> https://www.change.org/p/stand-up-for-freedom-pardon-the-innocent-coders-jailed-for-building-privacy-tools DONATE TO THE FAMILIES ----> https://www.givesendgo.com/billandkeonneSUPPORT ON SOCIAL MEDIA ---> https://billandkeonne.org/VALUE FOR VALUEThanks for listening you Ungovernable Misfits, we appreciate your continued support and hope you enjoy the shows.You can support this episode using your time, talent or treasure.TIME:- create fountain clips for the show- create a meetup- help boost the signal on social mediaTALENT:- create ungovernable misfit inspired art, animation or music- design or implement some software that can make the podcast better- use whatever talents you have to make a contribution to the show!TREASURE:- BOOST IT OR STREAM SATS on the Podcasting 2.0 apps @ https://podcastapps.com- DONATE via Monero @

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

The Indian government has issued a notice to Meta over WhatsApp’s planned username feature, warning that it could fuel impersonation and online fraud. Meta maintains usernames are a privacy feature designed to let users connect without sharing phone numbers. But the dispute runs much deeper. In this episode, host Anirban Chowdhury talks to Apar Gupta, co-founder, Internet Freedom Foundation about the government’s concerns, Meta’s response, the first-originator rule, end-to-end encryption, the limits of India’s IT Rules and DPDP Act, and why the bigger question is whether governments will ever lead—rather than merely react to—the future of digital identity.You can follow Anirban Chowdhury on his social media: X and LinkedinCheck out other interesting episodes like:ET Deep Dive: Swipe Left on Reality,India wants manufacturing at 25% of GDP — will AI in factories help?, Tanay Kothari Wants To Kill The Keyboard, From Doer to Director: The LinkedIn Playbook for the AI Agea, Semaglutide Goes Generic: Big Pharma’s Moat Breaks and much more. Catch the latest episode of ‘The Morning Brief’ on The Economic Times Online, Spotify, Apple Podcasts, JioSaavn, Amazon Music and Youtube.See omnystudio.com/listener for privacy information.

Earlier this week, the Department of Telecommunications ordered smartphone manufacturers to pre-install the Sanchar Saathi app on all new devices. It also told them to ensure that the app's functionalities are not disabled. It said this would protect users from cyber-fraud and phone theft. But within two days, the government revoked this order. It justified the withdrawal by citing a surge in acceptance of the app. But the revocation was preceded by a tremendous pushback against the original order – from digital rights activists as well as the Opposition. They said it was an attempt to vastly expand the scope of state surveillance. How do we contextualise this entire episode? Tune in! Guest: Apar Gupta, founder director of Internet Freedom Foundation. Host: G Sampath Produced and edited by Jude Weston Learn more about your ad choices. Visit megaphone.fm/adchoices

On Wednesday, the government withdrew a mandate requiring smartphone makers to preload the Sanchar Saathi on all new devices. Several privacy advocates had raised concerns over how the app may impact users' rights. But is the app the answer to the increasing cyber crime in the country? And how does the app impact citizens' privacy? Founder-Director of Internet Freedom Foundation, Apar Gupta explains, in conversation with Senior Assistant Editor, Apoorva Mandhani.

In this week's roundup of the latest news in online speech, content moderation and internet regulation, Ben is joined by guest host Prateek Waghre, former executive director at the Internet Freedom Foundation and currently a fellow at Tech Policy Press. Together, they cover:BookMyShow Restores Kunal Kamra's Profile After Controversy (Medianama)Kunal Kamra show audience members served notices (The Times of India)Cops force banker to cut short vacation to join Kamra probe (The Times of India)Unblock Vikatan Website – Madras High Court Orders Central Government (Vikatan)A Lack of Sense, and Censor-ability in India (Tech Policy Press)India befriends Big Tech as Trump tariffs knock on door, aided by a string of biz-friendly moves (Livemint)Meta can be sued in Kenya over posts related to Ethiopia violence, court rules (Reuters)US to screen social media of immigrants, rights advocates raise concerns (Reuters)In Karnataka HC, Centre defends use of IT Act for takedown notices (Hindustan Times) This episode is brought to you with financial support from the Future of Online Trust & Safety Fund. Ctrl-Alt-Speech is a weekly podcast from Techdirt and Everything in Moderation. Send us your feedback at podcast@ctrlaltspeech.com and sponsorship enquiries to sponsorship@ctrlaltspeech.com. Thanks for listening.

Beginning in June, the Delhi Police intends to expand its use of AI powered facial recognition across the city, integrating the technology with municipal bodies and Resident Welfare Associations in an effort to enhance crime prevention.However, this initiative has raised significant concerns among privacy advocates and digital rights organisations, who fear the potential for misuse and the disproportionate targeting of minority communities.In this episode, we first speak with Upasika Singhal of The Indian Express to understand the scope of the police plans and the details of the implementation.We are then joined by Apar Gupta, co founder of the Internet Freedom Foundation, to examine the broader implications of this move and why facial recognition poses unique risks.Hosted, produced and written by Shashank BhargavaEdited and mixed by Suresh Pawar

After a long wait of sixteen months, the Ministry of Electronics and Information Technology on January 3, 2025, unveiled the draft rules for implementing the Digital Personal Data Protection (DPDP) Act, 2023 —India's first comprehensive data privacy legislation applicable across all sectors of commerce and industry. The government is currently inviting stakeholder feedback on the draft until February 18, 2025, with plans to commence implementation by mid-year. This episode offers a comprehensive understanding of the new rules.  Guest: Apar Gupta, Delhi-based advocate and co-founder of Internet Freedom Foundation. Host: Aaratrika Bhaumik  Edited by Jude Weston

What role did technology play in India's elections, and what impact will the outcome have on tech policy in the country? Joining Justin Hendrix are three experts: Amber Sinha and Vandinika Shukla, both fellows at Tech Policy Press, and Prateek Waghre, the executive director at the Internet Freedom Foundation. Plus, Tech Policy Press program manager Prithvi Iyer sums up the election result.

India's Electronics and IT Ministry issued unexpected guidelines on AI regulations, causing concern among AI developers. The guidelines mainly focus on preventing AI misuse for unlawful content and requiring government approval for experimental AI models. But what are the real intentions behind these regulations, and what is India's stance on AI regulation? To shed light on these questions, we turn to Prateek Waghre, Policy Director at the Internet Freedom Foundation. Aman Taneja, an IP and technology lawyer at Ikigai Law Firm, also joins us on to help us understand possible future approaches to AI regulations in India. In other news, China is entering the whiskey segment, but can it beat India? Tune in to learn more about both the stories! Episode credits:The episode was researched, written, and produced by Shorbori and ManaswiniEdited by Venkat Ananth Mastered and mixed by Joshua ThomasSee omnystudio.com/listener for privacy information.

Watch out for dark patterns lurking in your online shopping cart. Ever seen messages like "Only 2 rooms left!" or "Items in your cart will expire soon" while shopping online? You're not alone! These are called dark patterns. A common design tactic that manipulates or heavily influences users to make certain choices. But they are no longer lurking in the dark, India's consumer protection watchdog is cracking down and putting the spotlight on them but can they be stopped? Host Mugdha Variyar decodes the web of these patterns with a UX designer that weaves them in to lure users and questions the effectiveness of the guidelines with Prateek Waghre, Executive Director of the Internet Freedom Foundation in the latest episode of The Morning Brief podcast!Credit: Yahoo Finance and WION.  If you like this episode from Mugdha Variyar, check out her other interesting episodes on COP28: Another cop or another cop-out?, Idlis & Innovation with iD Fresh Food, ESOP Fables: Risks and Rewards and more!You can follow Mugdha Variyar on her social media: Twitter and Linkedin Catch the latest episode of ‘The Morning Brief' on ET Play, The Economic Times Online, Spotify, Apple Podcasts, JioSaavn, Amazon Music and Google Podcasts.See omnystudio.com/listener for privacy information.

How does technology affect our rights? Do we need protection from the state and Big Tech? Apar Gupta joins Amit Varma in episode 353 of The Seen and the Unseen to discuss his battle for digital rights in India. (FOR FULL LINKED SHOW NOTES, GO TO SEENUNSEEN.IN.) Also check out 1. Apar Gupta on Twitter, LinkedIn, Instagram, IFF and YouTube. 2. Internet Freedom Foundation. (Donate to it!) 3. Apar Gupta's application to the Ashoka Fellowship (effectively a mini-autobiography). 4. IFF Wrapped, Unwrapped -- 2022 year-end event. 5. The Fine Line of Free Speech in India -- Apar Gupta. 6. When lawyers speak, they argue -- Apar Gupta. 7. I Don't Know -- Apar Gupta. 8. The archives of India Law and Technology Blog. 9. Aakar Patel Is Full of Hope — Episode 270 of The Seen and the Unseen (w Aakar Patel). 10. The Life and Times of Teesta Setalvad — Episode 302 of The Seen and the Unseen. 11. Amartya Ghosh on Spotify. 12. Neighbours Envy, Owners Pride -- Onida commercial. 13. Mungerilal Ke Haseen Sapne. 14. Permanent Record -- Edward Snowden. 15. Nehru's India -- Taylor Sherman. 16. The Life and Times of Vir Sanghvi — Episode 236 of The Seen and the Unseen. 17. India's Problem is Poverty, Not Inequality — Amit Varma. 18. The Shallows -- Nicholas Carr. 19. The Incredible Curiosities of Mukulika Banerjee — Episode 276 of The Seen and the Unseen. 20. Why India Votes— Mukulika Banerjee. 21. Vlogbrothers, Tom Scott and Hardcore History. 22. The Techno-Optimist Manifesto -- Marc Andreeson. 23. Zero to One -- Peter Thiel. 24. Narendra Modi interviewed by Rajeev Shukla. 25. Sacred Games. 26. The Road Ahead -- Bill Gates. 27. The Prem Panicker Files — Episode 217 of The Seen and the Unseen. 28. Vladimir Nabokov on Wikipedia and Amazon. 29. The Great Gatsby -- F. Scott Fitzgerald. 30. Ruth Bader Ginsberg on Wikipedia and Amazon, 31. The Notebook Trilogy — Agota Kristof. 32. Episodes of The Seen and the Unseen with Ramachandra Guha: 1, 2, 3, 4, 5. 33. Jinnah -- Jaswant Singh. 34. Gujarat High Court lifts ban on Jaswant's book on Jinnah -- Saeed Khan. 35. Shreya Singhal v. Union of India. 36. Charges dropped against girls held for Facebook post -- PTI. 37. Nikhil Pahwa on Twitter, LinkedIn, MediaNama and his own site. 38. Episodes of The Seen and the Unseen with Nikhil Pahwa: 1, 2, 3. 39. Chandrahas Choudhury on Instagram, Amazon and The Middle Stage. 40. Chandrahas Choudhury's Country of Literature -- Episode 288 of The Seen and the Unseen. 41. Kiran Jonnalagadda on Twitter and Hasgeek. 42. Sedition charges dropped against Aseem Trivedi -- PTI. 43. Justice K.S.Puttaswamy(Retd) vs Union Of India. 44. Hello world - and happy Independence Day! (2016) -- Apar Gupta. 45. IFF on Reddit. 46. Twitter and Tear Gas — Zeynep Tufekci. 47. Radically Networked Societies — Episode 158 of The Seen and the Unseen (w Pranay Kotasthane). 48. Anushka Jain's thread on SRK and digital rights. 49. IFF's Aarogya Setu Infographic. 50. The AgriStack: A Primer -- Rohin Garg. 51. Naushad Forbes Wants to Fix India — Episode 282 of The Seen and the Unseen. 52. The Struggle And The Promise -- Naushad Forbes. 53. Shruti Rajagopalan on our constitutional amendments. 54. The Right to Property — Episode 26 of The Seen and the Unseen (w Shruti Rajagopalan). 55. The Ideas of Our Constitution — Episode 164 of The Seen and the Unseen (w Madhav Khosla). 56. Emergency Chronicles — Gyan Prakash. 57. Gyan Prakash on the Emergency — Episode 103 of The Seen and the Unseen. 58. The Importance of the 1991 Reforms — Episode 237 of The Seen and the Unseen (w Shruti Rajagopalan and Ajay Shah). 59. India's Lost Decade — Episode 116 of The Seen and the Unseen (w Puja Mehra). 60. The Life and Times of Montek Singh Ahluwalia — Episode 285 of The Seen and the Unseen. 61. The Forgotten Greatness of PV Narasimha Rao — Episode 283 of The Seen and the Unseen (w Vinay Sitapati). 62. Why Freedom Matters — Episode 10 of Everything is Everything, hosted by Amit Varma and Ajay Shah. 63. India's Far From Free Markets (2005) — Amit Varma in the Wall Street Journal. 64. Don't Insult Pasta (2007) — Amit Varma. 65. The Matunga Racket (2007) — Amit Varma. 66. One Bad Law Goes, but Women Remain Second-Class Citizens (2018) -- Amit Varma. 67. The Colonial Constitution -- Arghya Sengupta. 68. The First Assault on Our Constitution — Episode 194 of The Seen and the Unseen (w Tripurdaman Singh). 69. Sixteen Stormy Days — Tripurdaman Singh. 70. A People's Constitution -- Rohit De. 71. Subhashish Bhadra on Our Dysfunctional State — Episode 333 of The Seen and the Unseen. 72. Caged Tiger: How Too Much Government Is Holding Indians Back — Subhashish Bhadra. 73. Roland Barthes and John Berger on Amazon. 74. Bombay Progressive Artists' Group and Gond art. 75. Bill Evans on Spotify and YouTube. 76. Night Song and Mustt Mustt -- Nusrat Fateh Ali Khan with Michael Brook. 77. Doppelganger -- Naomi Klein. 78. Automating Inequality -- Virginia Eubanks. 79. The Speaking Constitution --  KG Kannabiran. 80. The Wages of Impunity -- KG Kannabiran. 81. The Good Fight. 82. Court and The Disciple -- Chaitanya Tamhane. Amit Varma and Ajay Shah have launched a new video podcast. Check out Everything is Everything on YouTube. Check out Amit's online course, The Art of Clear Writing. And subscribe to The India Uncut Newsletter. It's free! Episode art: ‘Carrying a Torch' by Simahina.

This week, Indian legislators approved a data protection law that will govern the processing of data in the country. The bill creates a data protection board and gives the government new powers, including to request information from companies and to issue orders to block content. While there is still work to do to determine how the law will be administered, it joins a range of new tech policy laws and regulations enacted against a backdrop of the increasing centralization of power in India's government.To discuss the bill, Justin Hendrix is joined by Aditi Agrawal, an independent technology journalist based in New Delhi; Kamesh Shekar, a tech policy expert who leads the privacy and data governance vertical at The Dialogue, a think tank based in Delhi; and Prateek Waghre, the Policy Director at the Internet Freedom Foundation, a digital rights advocacy organization based in India.

In this podcast, Prateek Waghre, Policy Director, Internet Freedom Foundation, India, and businessline's V Nivedita discussed about the recent Digital Personal Data Protection Bill in India and its potential implications on data protection, privacy, and the interactions between individuals, organisations, and the government. The conversation detailed on various aspects of the bill, including data protection, consent, obligations on data fiduciaries, penalties for transgressions, exemptions for state entities, and the concept of legitimate uses.  Throughout the conversation, Waghre expressed both positive and negative views about the bill. Some of the positive aspects of the bill mentioned include the introduction of consent requirements for data sharing, obligations on data fiduciaries, penalties for non-compliance, and the right to be notified in case of data breaches. However, concerns are raised about the broad exemptions granted to state entities, the lack of specificity in the bill, and the potential impact on individual rights and privacy.  Waghre pointed out that the bill seems to prioritise data processing over privacy protection, which contradicts the original intent of safeguarding individuals' rights. There is also discussion about the challenges of balance in terms of granting exemptions, legitimate uses, and the potential consequences of these provisions. Additionally, Waghre highlighted the absence of safeguards, the role of the Data Protection Board, and the potential impact on citizens and businesses.  The conversation emphasises that the bill's effectiveness and impact will largely depend on the specific rules that will be defined in the future. The speaker expresses concerns about how certain provisions could be used to favor state entities or large organizations, potentially leading to a lack of privacy protection for individuals. The lack of clarity, specificity, and safeguards in the bill are key concerns that Waghre believes need to be addressed for effective data protection and privacy preservation.     --- Send in a voice message: https://podcasters.spotify.com/pod/show/business-line/message

feedback @ ryan@soulsearching.in Support IFF @ https://internetfreedom.in/donate/ EPISODE LINKS: Apar's Wikipedia : https://en.wikipedia.org/wiki/Apar_Gupta Linkedin : https://in.linkedin.com/in/apar1984 Twitter : https://twitter.com/apar1984 PODCAST INFO: Podcast website: https://anchor.fm/ryandsouza Apple Podcasts: https://apple.co/3NQhg6S Spotify: https://spoti.fi/3qJ3tWJ Amazon Music: https://amzn.to/3P66j2B Google Podcasts: https://bit.ly/3am7rQc Gaana: https://bit.ly/3ANS4v1 RSS: https://anchor.fm/s/609210d4/podcast/rss

This week, Newslaundry's Abhinandan Sekhri, Manisha Pande, Jayashree Arunachalam and Raman Kirpal are joined by advocate and Internet Freedom Foundation cofounder Apar Gupta.To listen to the full Episode, subscribe to Newslaundry. Download the Newslaundry app. Check out previous Hafta recommendations. Hosted on Acast. See acast.com/privacy for more information.

India yesterday notified changes to its information technology rules that now require all intermediaries – such as social media platform providers and internet services providers – to rely on a government-backed fact check unit concerning any content related to “government business,” according to an official statement. Also in this brief, Q1 of calendar 2023 saw startup funding continue to fall, according to data from Tracxn. Notes: India yesterday notified changes to its information technology rules that now require all intermediaries – such as social media platform providers and internet services providers – to rely on a government-backed fact check unit for any content related to “government business,” according to an official statement. The new rules called the IT Amendment Rules, 2023, first proposed in January, now “make it obligatory on the intermediaries to not publish, share or host fake, false or misleading information in respect of any business of the Central Government,” the statement reads. Such information “will be identified by the notified Fact Check Unit of the Central Government,” according to the statement. The statement also says that “the existing IT rules already required the intermediaries to make reasonable efforts to not host, publish or share any information which is patently false and untrue or misleading in nature.” These changes have drawn criticism from human rights campaigners such as the New Delhi-based Internet Freedom Foundation. The new rules “directly and negatively impact online freedom of speech and the right to receive information,” the foundation said in a post on its website. The amendments notified yesterday also included tougher rules on online gaming, especially in regulating online betting. Rajeev Chandrasekhar, minister of state for IT said in the government statement: “Online gaming is certainly a huge opportunity for India and Young Indians. We see the Indian online gaming ecosystem expand and grow into a multi-billion-dollar industry and be an important catalyst to India's One trillion-dollar Digital economy goal by 2025-26, with very clear restrictions on online wagering and betting.” In startup funding news, startups in India raised a total of $1.2 billion in funding in March compared with $598 million in February, according to data from the private markets intelligence provider Tracxn. There were 12 startup acquisitions last month, including Knowledge Lens and Sportido. March saw 87 funding rounds compared with 67 in February. The top funding rounds in March were Lenskart's Series-J round, in which it raised $500 million, PhonePe's Series D, $200 million investment and Mintifi's Series D round in which the supply chain fintech provider raised $110 million, according to Tracxn. There were 58 Seed rounds, 19 Series A rounds, two Series B rounds, and eight Series C+ rounds. FinTech, Retail, and Enterprise Applications were the top-performing sectors in Q1 2023. There were no new unicorns created in Q1 of 2023, compared with 14 in Q1 of 2022. Q1 of 2023 also saw three companies - Robu Labs, Mars Capital, and Homesfy announce their plans to go public.

This week, we're looking at how the internet is regulated in India. We consider what the current landscape looks like, what this means for tech platforms operating in the market and how this is impacting platforms' online counterterrorism and content moderation efforts.Join Anne Craanen as she speaks to Tanmay Singh, Senior Litigation Counsel at the Internet Freedom Foundation. And Jyoti Panday, a researcher at the Internet Governance Project (IGP) at the Georgia Institute of Technology.We unpack the recent legislation - the 2021 Information and Technology (IT) Rules - highlighting how they relate to global trends in regulating online content. Plus, we outline how civic engagement can influence online regulation. You can read a transcript of this episode here.If you want to find out more about Tech Against Terrorism and our work, visit techagainstterrorism.org or follow us on Twitter. To find out more about global online regulation, read our analysis in the Online Regulation Series.

For the fifth year in a row, India topped the world in internet shutdowns, according to an international report by Access Now and KeepItOn Coalition. Why do internet shutdowns happen in a democracy like India? What is the economic, social and academic fallout of such shutdowns? What is the legal recourse for Indian citizens? Apar Gupta, executive director, of Internet Freedom Foundation chats with Takshashila Institution's Sachin Kalbag on these pressing questions. Check out Takshashila's courses: https://school.takshashila.org.in/ Do follow IVM Podcasts on social media. We are @ivmpodcasts on Facebook, Twitter, & Instagram. https://twitter.com/IVMPodcasts https://www.instagram.com/ivmpodcasts/?hl=en https://www.facebook.com/ivmpodcasts/ You can check out our website at https://shows.ivmpodcasts.com/featured Follow the show across platforms: Spotify, Google Podcasts, Apple Podcasts, JioSaavn, Gaana, Amazon Music Do share the word with your folks!See omnystudio.com/listener for privacy information.

‘India: The Modi Question' is a two-part documentary series by the BBC about the Prime Minister Narendra Modi and his relationship with the Muslim minority in India. The government has used the emergency provisions of IT Rules 2021 to take down the documentary from websites as well as social media posts with links or snippets of the documentary. Screenings of the documentary in universities around the country have been disrupted by university administration and police. There are two petitions in the Supreme Court challenging the blocking of the documentary by the government. In February, there was an Income Tax survey at the BBC office in Delhi in which employees' phones were taken and laptops were scanned by the IT Department. This is part 1 of a miniseries on The Suno India Show examining how the Centre is limiting public access to information with laws and amendments. For this episode about the blocking of the BBC documentary, host Suryatapa Mukherjee spoke to Tejasi Panjiar an Associate Policy Counsel at the Internet Freedom Foundation. IFF is an NGO that advocates for digital rights and liberties, dealing with online freedom, privacy, net neutrality, and innovation. MIB adviser's tweets declaring online ban Centre Violated Citizens' Right To Know By Blocking BBC Documentary On Modi : N Ram, Prashant Bhushan & Mahua Moitra Tell Supreme Court IT(Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021 English.pdf Section 69A in The Information Technology Act, 2000 BBC documentary ‘blocking': Ruling in The Leaflet's case becomes basis for challenge'Emergency': From John Cusack to Prashant Bhushan, the List of 50 Tweets the Modi Govt Has Censored There is no ‘ban' on the BBC Modi film, why are universities clamping down on it? | The News Minute Finding 404: A Report on Website Blocking in India | SFLC.in Indian tax authority raids BBC after critical documentary | CPJ Asia Editors Guild India statement Public Feedback On Fact Checking Will Strengthen IT Rules: Minister See sunoindia.in/privacy-policy for privacy information.

On September 10, Newslaundry and the Internet Freedom Foundation hosted FoE Con 2022, a forum that brought together media personalities and leading voices in the legal sphere to map the media and regulatory framework in contemporary India.The panel discussion titled “Negotiations with Security Laws” was moderated by Vakasha Sachdev, lawyer and editorial lead of Logically. She was joined by Hartosh Singh Bal, journalist and political editor of the Caravan, and Vrinda Grover, human rights lawyer and activist.The panel discussed the sedition law and why it needs a moratorium, how the National Security Act is misused, and why India needs law to protect against communal and targeted violence. “Doing the job of journalism is more difficult today than it has ever been at any point of time in our history,” Hartosh said. “The laws are secondary to the political atmosphere that exists.” Hosted on Acast. See acast.com/privacy for more information.

On September 10, Newslaundry and the Internet Freedom Foundation hosted FoE Con 2022, a forum that brought together media personalities and leading voices in the legal sphere to map the media and regulatory framework in contemporary India.The panel discussion “Court Stories” was moderated by Abhinandan Sekhri, founder of Newslaundry. He was joined by lawyers Rebecca John and Sonam Gupta, and Alt News cofounder Pratik Sinha. The panel discussed how press freedom in India is impacted by the misuse of laws, how journalists are at the receiving end of threats on social media, and the legal strategies available to tackle these issues. Rebecca remembered how when she started out as a lawyer, she was told “lawyers and journalists would never be touched because they have the potential to hit back”. Hosted on Acast. See acast.com/privacy for more information.

On September 10, Newslaundry and the Internet Freedom Foundation hosted FoE Con 2022, a forum that brought together media personalities and leading voices in the legal sphere to map the media and regulatory framework in contemporary India.The panel discussion “Lessons from the Emergency” was moderated by independent journalist Neha Dixit. She was joined by journalist and author Kalpana Sharma and senior advocate Chandra Uday Singh. Kalpana explained how orders at the time “were more or less against publications and not individual journalists”. The discussion spanned how the Emergency played out, its repercussions, and the role of journalism throughout. Hosted on Acast. See acast.com/privacy for more information.

While talking about Fabulous Lives of Bollywood Wives, Nainika asks Rajyasree what she would do if she was a Bollywood wife:Rajyasree: See, when I was young, I had hair like you. So, I'd get this hair again. Like suddenly I'd have a shock of hair. I'd go to Dubai and I'd come back with a shock of hair.Nainika: Okay, fair. But that's a one-time investment?Rajyasree: Then I'd go to France and I'd come back like 20 shades fairer. ‘What happened?' I'd say, ‘Oh, there's no sun out there, I don't know.'Nainika: (laughs)Rajyasree: Then I'd go somewhere else, my figure would be – like, I don't know – like when I was 23. ‘How did...?' No, I ate healthy. I just became slim again. Rajyasree and Nainika burst out laughing.This and a whole lot of stuff awful and awesome as Rajyasree Sen and Nainika Rathore review season two of web series Delhi Crime and Fabulous Lives of Bollywood Wives; the drama surrounding the film Don't Worry Darling; and the Venice press screening of the film The Whale.PS: Abhinandan interrupts the podcast recording. Also, join us on September 10 at 12pm for FoE Con 2022, where Newslaundry and Internet Freedom Foundation bring together news professionals and legal minds to map the media and regulatory framework in contemporary India. See more details here.Write to us at newslaundry.com/podcast-letters. Our GDPR privacy policy was updated on August 8, 2022. Visit acast.com/privacy for more information.

India's data protection bill has been the subject of much debate over the past 4 years. The bill was recently withdrawn by Union Minister for communications and information technology Ashwini Vaishnav citing the need for changes based on the review by the Joint Committee of Parliament. There has been pushback against some sections by civil society organisations and tech companies. In this episode, Bharath Reddy speaks with Prateek Waghre and Tejasi Panjiar from Internet Freedom Foundation on the complicated legacy of the bill and the way forward.Suggested readings:1. Privacy Harms (Danielle Keats Citron and Daniel J. Solove) 2. Privacy as a Public Good (Joshua A.T. Fairfield & Christoph Engel)3. IFF's Data Protection Bill BriefYou can follow Bharath Reddy on twitter: https://twitter.com/bharathredYou can follow Prateek Waghre on twitter: https://twitter.com/prateekwaghreYou can follow Tejasi Panjiar on twitter: https://twitter.com/TPanjiarCheck out Takshashila's courses: https://school.takshashila.org.in/You can listen to this show and other awesome shows on the IVM Podcasts app on Android: https://ivm.today/android or iOS: https://ivm.today/ios, or any other podcast app.You can check out our website at https://shows.ivmpodcasts.com/featuredDo follow IVM Podcasts on social media.We are @IVMPodcasts on Facebook, Twitter, & Instagram.https://twitter.com/IVMPodcastshttps://www.instagram.com/ivmpodcasts/?hl=enhttps://www.facebook.com/ivmpodcasts/Follow the show across platforms:Spotify, Google Podcasts, Apple Podcasts, JioSaavn, Gaana, Amazon MusicDo share the word with you folks!

With the Covid19 pandemic receding, India's government is planning to revamp Aarogya Setu into a major national health app. But there are grave concerns around the date safety and security of its several million users. All this, in the backdrop of rampant data breaches in India and the absence of data protection laws. What will the government do? Host Anirban Chowdhury talks to Apar Gupta, Executive Director at the Internet Freedom Foundation, and Suraksha P, Special Correspondent, Technology Bureau at EconoWith the Covid19 pandemic receding, India's government is planning to revamp Aarogya Setu into a major national health app. But there are grave concerns around the data safety and security of its several million users. All this, in the backdrop of rampant data breaches in India and the absence of data protection laws. What will the government do? Host Anirban Chowdhury talks to Apar Gupta, Executive Director at the Internet Freedom Foundation, and Suraksha P, Special Correspondent, Technology Bureau at Economic Times. Credits: National Informatics Centre (NIC) Here's a previous episode on the govt cancelling its data protection bill:http://www.ecoti.in/XjO0fb94mic Times. Credits: National Informatics Centre (NIC) Here's a previous episode on the govt cancelling its data protection bill:http://www.ecoti.in/XjO0fb94

On several instances, people in India are asked to submit their unique identification cards such as PAN cards and Aadhar cards. However, there have been occasions when this private information is leaked into the public domain, thus leading to some misuse of this information. In this episode of The Wire Talks, our host Sidharth Bhatia talks to Apar Gupta. Founder of Internet Freedom Foundation, lawyer, activist and writer on technology from India. Apar gives his take on it. The duo talks about the Private Data Information Bill which was targeted to address this issue, however, was later withdrawn.Follow Apar Gupta on Twitter @apar1984Follow Sidharth Bhatia on Twitter and Instagram @bombaywallah and https://instagram.com/bombaywallahYou can listen to this show on The Wire's website, the IVM Podcasts website, app on Android: https://ivm.today/android or iOS: https://ivm.today/ios, or any other podcast app.

India just nixed its critical data protection bill that took five years to draft. Why? What will the new data protection laws be like? How will the govt balance the privacy of its citizens and the interest of Big Tech? Host Anirban Chowdhury talks to Surabhi Agarwal, ET's tech editor; Amar Patnaik, MP, and member of the Joint Parliamentary Committee on the bill; and Prateek Waghre, policy director at Internet Freedom Foundation. Credits: NDTV, Bharatiya Janata Party, ANI News, CNBC-TV18, cpac, NBT WORLD, OneTrust & CNBC Television Credits: CNBC-TV18

According to Dutch cybersecurity firm Surfshark VPN, India had the second highest number of data breaches in the first half of 2022.  And on Friday, a Ukrainian cybersecurity researcher claimed that sensitive personal data of 280 million Indian citizens allegedly from the Employees' Provident Fund Organisation database surfaced online.  Each record allegedly included personal information like full name, nominee details, marital status, address, bank account numbers, Aadhaar details, income levels etc. India currently lacks a sound legislation for data protection. After five years in the making, the bill that was designed to protect the privacy of Indians, the Personal Data Protection Bill 2019, was withdrawn by the government on Wednesday. The government assured to table a new bill soon. A committee led by former Supreme Court Justice BN Srikrishna, constituted in August 2017, submitted the draft PDP Bill 2018 the following year.  On December 11th, 2019, the Ministry of Electronics and Information Technology tabled the PDP Bill 2019 in Lok Sabha. The same day, it was referred to a Joint Parliamentary Committee, which tabled its report two years later, on December 16, 2021.  IT Minister Ashwini Vaishnaw said the bill was withdrawn because the panel suggested 81 amendments and 12 major recommendations.  The bill had alarmed big technology companies like Meta and Google, who feared it could increase their compliance burden, data storage requirements and restrict cross-border flow of data.  As the bill provided large exemptions to government departments, several privacy advocates said it would allow agencies to abuse access to data. The parliamentary panel also said that non-personal data should be included in the purview of the bill, which originally focused only on individual privacy in tune with the 2017 Supreme Court verdict that held Right to Privacy as a fundamental right. Speaking to Business Standard, Tejasi Panjiar, Associate Policy Counsel, Internet Freedom Foundation says, there is no denying the bill was imperfect. But it went through long consultation and review process. What should've taken us forward brought us back to square one, he says.  The delay has consequences for Indian consumers and companies alike Salman Waris, Managing Partner, TechLegis Advocates & Solicitors, says consumers will be the ultimate sufferers as their data is at risk. Govt may bring two bills for personal and non-personal data. India's outsourcing industry will face hurdles while serving global clients.  The government says it is working on a “comprehensive legal framework” after considering the parliamentary panel's report.  Meanwhile, the Internet Freedom Foundation has argued that the existing legal vacuum on data protection is an infringement of the fundamental right to privacy.  Whether or not the new bill addresses the existing concerns raised by companies and privacy advocates, the wait for a personal data protection law in India gets longer.

India is the world's most populous democracy, and also one that is facing challenges. This week we focus on the Indian government's efforts to create a  bureaucratic apparatus to enforce what appears to be an ever more frequent number of requests for social media platforms to remove content deemed inappropriate for one reason or another. And for this week's episode, I'm joined by the author of a https://techpolicy.press/indias-it-rules-new-amendments-a-threat-to-freedom-of-expression/ (recent piece on this subject), Angrej Singh, who is interning with Tech Policy Press this summer. Angrej helped to pull together the panel of experts-- all based in India-- that you'll hear from today, including: Neeti Biyani, Policy and Advocacy Manager, Internet Society Tejasi Panjiar, Associate Policy Counsel, Internet Freedom Foundation Apar Gupta, Executive Director, Internet Freedom Foundation

The Indian government has recently asked VPN service providers to register and record certain information about its users for a period of at least 5 years.   This was one among the several new directives issued by CERT-In, or Central Emergency Response Team, which is India's national agency that looks into matters of cybersecurity.   The new directives are slated to come into effect from June 27 this year. However, experts say that these rules raise serious privacy concerns, especially the ones about VPN service providers But before moving ahead, let's understand what a VPN really is. VPN or a Virtual Private Network establishes a secure and encrypted connection between a user and the internet.   VPN helps users hide their browsing history, IP address and geographical location, as well as their web activities and the devices being used. In a connected world, it's of immense use to journalists, whistleblowers and activists. Now let's understand how the new rules pose challenges to a VPN user's privacy?   CERT-In's new rules require VPN service providers to collect and store certain ‘accurate' information for a period of at least five years, even after a customer has cancelled his/her subscription. The ‘personal' information to be collected and stored includes names, IP addresses, emails, contact numbers and purpose for using the VPN service. Data centres and cloud service providers will also have to abide by these directives Non-compliance of these norms can attract a jail term of up to one year.   Many VPN service providers offer a no-log policy, where they promise to not collect or log traffic that passes through their servers and users' online activities. But the new government directives ask the service providers to store information that is sensitive, personal and identifiable in nature.   Another provision raises the possibility of VPN providers being made to store usage logs, which include a person's browsing activity, for a rolling period of 180 days. All organisations are mandated to maintain logs of their ICT or Information and Communication Technology systems in India according to the new regulations. The Internet Freedom Foundation said that the ambiguity over what is covered under “all their ICT systems” leads to concerns such as the government or private enterprises having access to more data than necessary.   Talking to Business Standard, Apar Gupta, Executive Director, Internet Freedom Foundation, says ‘No-logs' VPN providers will be forced to exit the Indian market. The 180-day log retention rule on ICT systems is ambiguous and the new rules will end up undermining cybersecurity, he says. This puts personal data is put at risk of leak and data collection requirement is counterintuitive, he says adding that no data protection authority to ensure data is used for cybersecurity purpose.    Three VPN service providers, Surfshark, ProtonVPN and ExpressVPN, have told a US tech publication that they don't plan to follow India's new rules on data collection. All three reportedly expressed intention to continue with their no-logs policy. The US tech magazine quotes ProtonVPN saying India's new requirements will erode civil liberties and make it harder for people to protect their data online. Experts also questioned how these data collection and retention requirements will help in improving cybersecurity. Moreover, localisation requirements also raise concerns about surveillance, especially in the absence of a dedicated data protection authority.

Only a few days ago, Elon Musk's bid to buy Twitter was thought to be long shot but his offer has ben accepted by the social media platform. The billionaire will now pay a cool $44 billion to take the company private. In his statement on Tuesday, 26 April Musk said he wants to "make Twitter better than ever by enhancing the product with new features, making the algorithms open source to increase trust, defeating the spam bots, and authenticating all humans." The announcement also confirmed many of the details that had already been reported — or tweeted — about the transaction. However, it has also left many unanswered questions, most pertinently— how will a privately held Twitter operate? And is Elon Musk's idea of “free speech” right for a platform like Twitter ? Joining us today to discuss all this is Apar Gupta, the Executive Director of the Internet Freedom Foundation. Host and Producer: Himmat Shaligram Editor: Shorbori Purkayastha Music: Big Bang Fuzz Listen to The Big Story podcast on: Apple: https://apple.co/2AYdLIl Saavn: http://bit.ly/2oix78C Google Podcasts: http://bit.ly/2ntMV7S Spotify: https://spoti.fi/2IyLAUQ Deezer: http://bit.ly/2Vrf5Ng Castbox: http://bit.ly/2VqZ9ur

On March 28, the government introduced a new Bill in the Lok Sabha – the Criminal Procedure (Identification) Bill, 2022. The Opposition vehemently opposed it, going so far as to seek a division of votes. But it failed to defeat the introduction of the Bill, as it could muster only 58 votes against, with 120 votes in favour of the Bill. On the face of it, the Bill proposes to empower police and prison authorities to take “measurements of convicts and other persons for the purposes of identification and investigation in criminal matters”. The term “measurements” includes finger-impressions, palm-print impressions, foot-print impressions, photographs, iris and retina scan, and even biological samples. Criticism from the Opposition has broadly followed two strands. One thread argues that the Bill violates certain constitutional principles and guarantees and that it goes beyond the House's “legislative competence”. The other set of criticisms dwell on the fact that it gives too much power to the executive, with very little accountability, raising the temptation for abuse of this law's provisions. So, does India really need a Bill of this kind, and how does the current draft of the Bill fare when assessed against constitutional norms? Guest: Apar Gupta, Executive Director at the Internet Freedom Foundation, a Delhi-based non-profit that conducts advocacy on digital rights and liberties Host: G. Sampath, Social Affairs Editor, The Hindu Edited by Ranjani Srinivasan

In 1920, when the British were still in power, they introduced a law named the “Identification of Prisoners Act.” This allowed the police to take and store footprints and fingerprints of conflicts.  Now, 102 years later, this bill has not only been revived in a new avatar but its powers and scope has been expanded to questionable extent. On 28 March, the Centre introduced the Criminal Procedure (Identification) Bill, 2022 which proposes to allow the police and prison authorities to collect, store and analyse physical and biological samples, including retina and iris scans. But this is not only limited to convicts but also to those that police consider suspects of a crime. More so, the law allows for the personal and biological data once collected to be stored for the extent of 75 years. The bill met with fierce criticism from the Opposition, including Congress and TMC, calling it “draconian” and a "direct violation of the Fundamental Right of an individual". And in the absence of a data protection framework in India, the proposed bill also raises questions on how it will impact fundamental rights like privacy and self-incrimination. But, what does the law exactly propose? Why are members of the Opposition against it? And how will it affect the ordinary citizen? In today's episode, we break down this new bill with the help of Apar Gupta, the executive director at the Internet Freedom Foundation. Host and Producer: Himmat Shaligram Editor: Vakasha Sachdev Music: Big Bang Fuzz Listen to The Big Story podcast on: Apple: https://apple.co/2AYdLIl Saavn: http://bit.ly/2oix78C Google Podcasts: http://bit.ly/2ntMV7S Spotify: https://spoti.fi/2IyLAUQ Deezer: http://bit.ly/2Vrf5Ng Castbox: http://bit.ly/2VqZ9ur

To make the most of next week before the deadline, we have a discount coupon for Hafta listeners. Use code to get a flat 20 percent discount on annual and three-year plans. Check out our Christmas offer here​​.Timecodes:3:45 - Headlines6:35 - Parliamentary proceedings40: 33 - Anti-conversion bill1:17:12 - Punjab1: 32: 40 - Duty to laugh1: 35: 35 - Subscriber letters2: 09: 46 - RecommendationsThis week on NL Hafta, Abhinandan Sekhri, Manisha Pande, Raman Kirpal and Jayashree Arunachalam are joined by Apar Gupta, writer and Executive Director of Internet Freedom Foundation, and Nitin Pai, columnist and co-founder of Takshashila Institution. The discussion starts with the parliamentary proceedings and how much attention goes into passing a bill in India. Nitin comments that the only way parliament should decide on passing bills is by some sort of “feat of force like wrestling or tug of war because it has come to that”. “Do people meet up in state legislatures before clearing any bill? No, they are not voicing the concerns,” he says. Apar points to facts. “Only one out of five bills is sent to the standing committee for approval. It's inefficient and can be made better by all means.” Abhinandan compares the legislative procedure with precedents and opens the discussion with the “unhealthy process” that exists. Jayashree adds, “All institutional checks and balances are just for show, when they (BJP) got tired with the show; they got it adjourned.”The discussion then shifts to the anti-conversion bill passed by the Karnataka government and its implications, along with references to the recent attacks on churches, which Abhinandan calls “dog whistles for the cultural agenda of BJP, because this is all they have”. The panel sifts through the governance style and gains made through the same in south India. The conversation moves to the issue of sacrilege in Punjab, the lynching cases and the recent blast in Ludhiana. The panel also talks about a statement by a Madras high court judge on the “duty to laugh”. This and a lot more, only on NL Hafta.Tune in! ​​ See acast.com/privacy for privacy and opt-out information.

On today's episode, we have two interesting updates for you. With things getting back to normal people would rather rather Zoom out and Meet people. Meanwhile, India could potentially have new data protection laws. And to answer some of the important questions, we invited Apar Gupta, Executive Director of The Internet Freedom Foundation to have a detailed discussion about data protection with Dinesh Narayanan, editor and co-founder at The Signal. Rajneil Kamath is your guide through both these stories.

Facial recognition technology is a contentious and controversial subject all over the world. It enables law and order forces to identify faces and check them against databases, except that the technology has in-built biases because of which minorities and other marginalised communities suffer. There are other issues with it as well. A new worldwide campaign 'Ban The Scan' has been launched by Amnesty International and the Delhi-based Internet Freedom Foundation (IFF), a digital liberties organisation, is leading it in India. The campaign demands that police stop using this tech. The IFF has files an RTI request asking the police in Hyderabad, where it is apparently being used, to reveal its database. Thus far, the police have not complied.On this episode, Sidharth Bhatia is joined by Anushka Jain, lawyer and policy researcher, Associate Counsel: Surveillance & Transparency at Internet Freedom Foundation, who is interested in disruptive technologies such as facial recognition and artificial intelligence. She is the one spearheading the Ban The Scan campaign on behalf of the IFF. She joins Sidharth to talk about the issues and dangers of this kind of tech are, and why facial recognition by machines is so sinister and perhaps shouldn't be allowed to proceed, and how it affects all of us.Follow Anushka on LinkedIn: https://www.linkedin.com/in/anushka-jain-a0396b175Follow Sidharth Bhatia on Twitter and Instagram @bombaywallah and https://instagram.com/bombaywallahYou can listen to this show on The Wire's website, the IVM Podcasts website, app on Android: https://ivm.today/android or iOS: https://ivm.today/ios, or any other podcast app.

Stating that the Centre can't get a free pass every time by stating “national security”, the Supreme Court on 27 October appointed an external committee to investigate the allegations of unauthorised use of the Pegasus spyware on citizens. After weeks of back and forth between the Centre, the petitioners, and the court on Pegasus, the apex court sharply noted in its order that the “vague denial from the government is not sufficient”, and that it had no option but to set up a panel to examine the allegations made by the petitioners. The court's stern observations on the issue comes after hearing a clutch of petitions, which requested a probe into the allegations of the Centre's use of the spyware on over 142 Indian citizens.  The revelations regarding the use of spyware were made after a consortium of media organisations around the world reported in July, the use of the spyware on prominent politicians like Congress leader Rahul Gandhi, 40 Indian journalists, and several private citizens. However, the Centre has to date refused to take a clear stand on whether it has purchased or used the spyware. And given the Centre's stonewalling on this issue, how significant are the observations made by the court? Will an expert committee be able to unearth the answers that the court has been unable to do so thus far? What powers will this committee have? Joining me today to discuss the significance of the order and also what functions the expert committee will possess is  Tune in! Host and Producer: Himmat Shaligram Guest: Apar Gupta, the Executive Director of the Internet Freedom Foundation, and Gunjan Chawla, Programme Manager of Technology & National Security at the Centre for Communication Governance at NLU Delhi. Editor: Shelly Walia Interviews: Vakasha Sachdev, The Quint's Legal Editor. Music: Big Bang Fuzz Listen to The Big Story podcast on: Apple: https://apple.co/2AYdLIl Saavn: http://bit.ly/2oix78C Google Podcasts: http://bit.ly/2ntMV7S Spotify: https://spoti.fi/2IyLAUQ Deezer: http://bit.ly/2Vrf5Ng Castbox: http://bit.ly/2VqZ9ur

You may think that it's been an unsteady week for Facebook, with all its platforms like Facebook, WhatsApp and Instagram going dark for six hours on 4 October, affecting billions around the globe. But, this wasn't the worst thing to happen to Facebook this week. Based on a trove of over 10,000 documents provided by a whistleblower, The Wall Street Journal over the past few weeks revealed that Facebook fully understands how its products influence and harm society. And just a day after the outage, the crisis deepened after the whistleblower, Frances Haugen, a former Facebook employee, came forward and testified before the US Congress and gave lawmakers a candid view on how the company functions and its efforts to keep people hooked on the platform despite knowing its ill effects. For example, in an internal study by Facebook, the company knew the negative impact Instagram has on teenage girls, how certain algorithms designed to make the platform a healthier place were actually having the opposite effect and the fact that Facebook senior management, including CEO Mark Zuckerberg, knew all of this. In this episode, we break down what exactly was revealed by the whistleblower, its impact and also answering the bigger question-whats next for Facebook? Are more stringent regulations in its future? and what would they be? Host and Producer: Himmat Shaligram Guest: Apar Gupta, Executive Director of the Internet Freedom Foundation. Editor: Shelly Walia Music: Big Bang Fuzz Listen to The Big Story podcast on: Apple: https://apple.co/2AYdLIl Saavn: http://bit.ly/2oix78C Google Podcasts: http://bit.ly/2ntMV7S Spotify: https://spoti.fi/2IyLAUQ Deezer: http://bit.ly/2Vrf5Ng Castbox: http://bit.ly/2VqZ9ur

How will India's new liberalised drone rules impact the industry? And where are they left wanting? Skye Air Mobility co-founder Swapnik Jakkampuddi, Internet Freedom Foundation associate counsel for surveillance and transparency Anushka Jain, and Tech for Wildlife founder-director Shashank Srinivasan join host Akhil Arora to discuss just that. We talk about how the Drone Rules 2021 do away with unnecessary and time-consuming security clearances, and are much easier to parse than the old ones — but it's worth noting that these are still early days, and there's a lot they leave out, including basic stuff such as the legality of DJI drones (the most popular in the world) or counter-drone measures (can you shoot down a drone if it flies over your property?). Read: Drone Rules 2021 announced Additionally, the new eased regulations have made misuse of drones much easier, be it on an individual peeping-tom level or via the police who are taking to new technology more and more. There are major questions over privacy, data security, and mass surveillance — none of which are addressed by Drone Rules 2021. And you may face many legal hurdles in taking someone to court over being surveilled by drones. This vacuum isn't just harmful to fundamental rights of humans, but also other species. We delve into the need for more clarity over e-waste disposal, better enforcement for protected areas like national parks, and ensuring that drones do not further expand the divide between oppressed communities and the authorities. We also touch upon the medicine-from-the-sky trials currently being undertaken. Follow Gadgets 360 on Facebook, Twitter, Instagram, and YouTube. Write to us at podcast@gadgets360.com Chapters Intro (00:00) Fewer restrictions (01:25) What about privacy? (05:45) Working with locals (09:59) Tech > Enforcement (12:25) Still early days (15:27) Scope for misuse (20:05) Wildlife conservation (27:32) Legal hurdles (33:03) Outro (39:27) Photo credit: Kushal Medhi

In this episode, I'm talking with Sukhnidh Kaur about a range of tech policy issues - from data governance, platform regulation, free speech and private power, and most importantly - about her work as the Digital Literacy fellow at the Internet Freedom Foundation. If you're buzzing in and around the Indian tech policy scene, chances are that you've seen Sukhnidh's brilliant explainer videos about complex legal and technological issues which she did on behalf of IFF. We talk about how she broke down these complex issues into accessible chunks of media, how memes can help generate awareness, and why we need people other than lawyers in Indian tech policy. In the later half of our conversation, we talk about how she approached these issues of tech policy coming from a space of Instagram influencing, about how the platform i.e. Instagram itself is evolving, and about how can organizations cultivate sustained change making movements. Sukhnidh is on twitter as @skhndh. References: 1. Sukhnidh's Privacy 101 explainer video: https://www.youtube.com/watch?v=Ykl8bcxFdxo&t=21s&ab_channel=InternetFreedomFoundation 2. Anja Kovack's piece on Identity and data: https://deepdives.in/when-our-bodies-become-data-where-does-that-leave-us-906674f6a969?gi=c62f48e15b67 3. Sukhnidh's Medium page: https://sukhnidh.medium.com/

Recently, media organisations across the world published a series of reports exposing Pegasus, a spyware developed by NSO Group in Israel. They found that governments have been using Pegasus to spy on their own journalists, activists and opposition leaders. Amnesty International's forensic team has confirmed these findings. After mounting global and national pressure, the NSO has temporarily blocked several of its government clients from using its spyware.  Earlier in 2019, researchers from the University of Toronto had contacted lawyers and activists from the Bhima Koregaon case, alerting them to the presence of Pegasus on their phones. Among the 300 phones suspected to be infiltrated in India, forty belong to journalists. The Supreme Court will be hearing a plea from senior journalists against the hack.  On this episode of The Suno India Show, reporter Suryatapa Mukherjee spoke to Anushka Jain, associate counsel of Surveillance and Transparency at the Internet Freedom Foundation. This is a deep dive on what makes Pegasus special, whether it is accommodated by our laws on surveillance, and how it is affecting Indian citizens.  Additional reading: NSO Group: What we know about the secretive company behind the Pegasus spy software.  Indian Activists, Lawyers Were ‘Targeted' Using Israeli Spyware Pegasus  See sunoindia.in/privacy-policy for privacy information.

On July 6, Father Stan Swamy, a Jesuit priest and tribal rights activist died in custody. Last year, he was arrested in a case related to 2017 Bhima Koregaon violence in Pune. Father Swamy had Parkinson's disease and was detected with Covid-19 in May.  Why is it hard for someone as old as Stan Swamy to get bail. Suno India's Menaka Rao spoke to advocate Abhinav Sekhri, a criminal lawyer based in Delhi, and is on retainer with Internet Freedom Foundation. He writes extensively on criminal law and runs a blog called Proof of Guilt. He recently wrote a paper on the bail regime in the country and how it is antithetical to the core principle in our criminal justice system- that an accused is innocent until proven guilty.  Show notes: Elgaar parishad case: Stan Swamy dead The Bailable v. Non-Bailable Classification in Indian Criminal Procedure by Abhinav Sekhri :: SSRN https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=2801004 The Proof of Guilt The Unlawful Activities (Prevention) Act The Narcotic Drugs and Psychotropic Substances Act, 1985 National Investigation Agency vs Zahoor Ahmad Shah Watali on 2 April, 2019 Union Of India vs KA Najeeb on 1 February, 2021 NCRB report: Sedition cases up in 2019 but conviction at all-time low Arrested activists: 67% ended in acquittal or discharge under UAPA Acts See sunoindia.in/privacy-policy for privacy information.

An international group of news publications are reporting that a spyware known as Pegasus has been used to spy on politicians, journalists, and activists in at least 10 countries. Reports from the group, which includes The Wire in India, The Guardian in the U.K., and Washington Post in the U.S. among others, suggest that in India, at least 40 journalists, sitting Cabinet Ministers, and holders of Constitutional positions were possibly subjected to surveillance. The Pegasus spyware is graded as a cyberweapon and NSO states that its clients include only authorised government entities from various countries. This leads to some problematic inferences, particularly in India where the target list includes Opposition leaders, social activists from leftist organisation, journalists who have written against the government and constitutional officers who have reportedly not toed the government line. In this podcast, we discuss the constitutionality of electronic surveillance in India and whether the laws that govern them are robust enough. Guest: Apar Gupta, lawyer and Executive Director of the Internet Freedom Foundation. Host: P.J. George

The infamous Israeli spyware Pegasus has kicked up a storm once again.  Over 300 Indians may have been spied on using this dangerous software that can allow a hacker to gain access to pretty much everything in a person's phone including encrypted messages. This egregious breach of privacy was reported by The Wire in a collaborative investigation conducted along with several other international media houses like The Guardian and The Washington Post that found a leaked database with 50,000 phone numbers from across the world, believed to be linked to persons of interest listed by the clients of the NSO — the Israeli firm that sells the Pegasus Spyware. From the first tranche of reports that came on 18 July, we know that 40 of the 300 verified numbers from India belong to journalists from some of India's top media houses like the Hindustan Times, India Today, Network18, The Hindu, The Indian Express and The Wire.  The spyware is also believed to have been used on numbers belonging to at least nine rights activists, lawyers and academics who have been arrested in the Bhima Koregaon case. The second tranche of reports, that came on 19 July, state that PM Modi's political adversary Congress leader Rahul Gandhi and political strategist Prashant Kishor's numbers were also added to the list. Ironically, even the recently sworn in IT minister Ashwini Vaishnaw who is defending the Centre from allegations of spying is on the target list along with MoS Prahlad Patel. Former Election Commissioner Ashok Lavasa and India's leading virologist Dr Gagandeep Kang have featured on the list of potential targets as well. While the NSO claims that it only sells the spyware to "vetted governments", the Indian government has dismissed the reports saying that they are not only 'bereft of facts but also founded in pre-conceived conclusions'. But at a time when our smartphones have become a primary device that stores a lot of our personal data, what does the use of the Pegasus spyware on Indian journalists, opposition leader and other citizens say about the state of surveillance? Who is answerable for this grave assault on privacy? Tune in! Producer and Host: Shorbori Purkayastha Guests: Shashi Tharoor, Senior Congress leader and Lok Sabha MP,  Mishi Chaudhury, Lawyer and the Legal Director and founder of the Software Freedom Law Center, Apar Gupta, Executive Director of the Internet Freedom Foundation. Editor: Shelly Walia Interviews: Anthony Rozario, Mehab Qureshi Music: Big Bang Fuzz Listen to The Big Story podcast on: Apple: https://apple.co/2AYdLIl Saavn: http://bit.ly/2oix78C Google Podcasts: http://bit.ly/2ntMV7S Spotify: https://spoti.fi/2IyLAUQ Deezer: http://bit.ly/2Vrf5Ng

In this episode, I, Kamayani Sharma, am in conversation with Shukla Sawant and Annapurna Garimella, Founder Trustees of the Culture Workers Support Trust, an organisation set up in 2019 to and I'm quoting them directly “spread awareness among culture workers about their rights and responsibilities". We discuss the modes and methods by which labour in India's vast culture sector can start to organise and collectivise, how stakeholders across public and private sectors can come together for worker-oriented solutions to entrenched problems and how forms of workplace violence including gender & caste-based harassment (as that embodied by the #MeToo movement in the art world) cannot be delinked from broader issues of labour rights such as wage security and equitable contracts. We also discuss how in the network capital-dominated industries of the arts, legislative and judicial processes are necessary to enforce fair work conditions. Click here to access the Image+ Guide & view the material being discussed in the podcast: https://sites.google.com/view/artalaap-podcast-resources/episode-10. Credits: Producer: Tunak Teas Design & artwork: Mohini Mukherjee Marketing: Dipalie Mehta Images: Culture Workers Support Trust Additional support: Kanishka Sharma, Amy Goldstone-Sharma, Raghav Sagar, Shalmoli Halder, Arunima Nair, Jayant Parashar Audio courtesy: Vernouillet by Blue Dot Sessions [CC BY-NC 4.0] References: Christine Ithurbide, 'Beyond Bombay art district: Reorganization of art production into a polycentric territory at metropolitan scale', Belgeo [Online], 3 | 2014, 19 Dec. 2014. - and Soraya Hamache, 'Art and Cinema Industries in India: Norms, Workers and Territories', Workshop at Kiran Nadar Museum of Art, New Delhi, Centre d'études Inde et de l Asie du Sud, Newsletter No. 13 (Summer 2016), https://sites.google.com/site/ceiasnewsletter/-newsletters-20152016/newsletter-no-13---summer-2016/art-and-cinema-industries-in-india-norms-workers-and-territories. - and Tejshree Savara, 'Legal Handbook for the Artist Community in India', UNESCO in partnership with New Delhi Office, Sept. 2020. Kavita Singh, '2019 Arts & Museum Summit Keynote 3: Museums, New Locations, New Definitions', Asia Society Delhi, 12 Oct. 2019. John Rawls, 'A Theory of Justice', The Belknap Press of Harvard University Press, (1971) 1999. 'Google Spreadsheet Reveals How Much the Art World Earns', Frieze, 4 Jun. 2019. 'Journalist Priya Ramani not guilty in MJ Akbar defamation case, rules Delhi court', Scroll.in, 17 Feb 2021. Press Trust of India, 'Delhi Police interrupts India Art Fair after complaint of anti-CAA paintings; artwork was about India's women, clarify participating artists', Firstpost, 3 Feb. 2020. 'Indian Journalists Union defends media's right to report on MeToo allegations', Internet Freedom Foundation, 23 Jan. 2020. Ophelia Lai, Subodh Gupta Settles Defamation Case Over Instagram #MeToo Allegations, ArtAsiaPacific, 3 Mar. 2020. Benita Fernando, 'What is ailing the ‘people's biennale'?', Livemint, 29 Mar. 2020.

One Take Show is honoured to host Mr. Krishnesh Bapat and Mr. Tanmay Singh. Krishnesh is a lawyer practising in New Delhi. Tanmay is an Associate Counsel for the Internet Freedom Foundation. Internet Freedom Foundation: The IFF is an Indian digital liberties organisation that seeks to ensure that technology respects fundamental rights. Their goal is to ensure that Indian citizens can use the Internet with liberties guaranteed by the Constitution. Their expertise in free speech, digital surveillance and privacy, net neutrality will help us to champion freedom in the digital age. They spur grassroots membership through public campaigns and take them towards institutional engagement with regulators, legislative bodies and courts. They were originally a group of volunteers who worked on the SavetheInternet.in the campaign. In order to make a meaningful and lasting contribution towards a free and open Internet, they banded together to incorporate an organisation, set up to support research regarding the online freedoms and rights of Indian citizens. They are incorporated as a public charitable trust registered in New Delhi and are granted exemptions under Sections 12A and 80G of the Indian Income Tax Act. https://internetfreedom.in/

Fake news and misinformation are hampering India's battle with the coronavirus pandemic. Right from the origins of the virus to unproven alternative cures to efficacy of vaccines, a wave of mass anxiety has washed over the country's social media. While most misleading messages spread through online platforms, experts say senior leaders and influencers have also played a role in fuelling traditional sentiments that prefer alternative therapies to modern medicine. This has increased vaccine hesitancy, especially in rural India, and led to political as well as medical misinformation. Conspiracy theories and false claims not only spread rapidly, they also prompt people to take action in real life - often with severe consequences. What kinds of fake news have dominated India's coronavirus landscape? What role can tech companies play to keep this in check? And is the government a bigger stakeholder in fighting the fake news menace? Presenter: Devina Gupta Contributors: Pratik Sinha, co-founder, Alt News; Apar Gupta, executive director, Internet Freedom Foundation; Dr Vasundhara Rangaswamy, microbiologist, primary care physician

In this episode, I'm joined by Apar Gupta, executive director and founder of Internet Freedom Foundation. IFF works on a range of issues including net neutrality, free expression, privacy and innovation through advocacy and strategic litigation. We talk about how IFF was born out of save our internet movement and how it works to advance democratic visions in a digital society. We also talk about how technology impacts our liberty and freedom, and how Apar's passion to work for public interest led him to leave his quite successful practice to establish IFF. Apar is on twitter as @apar1984

On 3rd February, the Parliamentary Standing Committee on Science and Technology submitted its report on the DNA Technology Regulation Bill in the Rajya Sabha. If passed, the bill will set up a national DNA database in the country for the first time. The Bill aims to identify and store the DNA of offenders, suspects, undertrials, missing persons and unknown deceased persons. Public relations agency Ogilvy India and government affairs consultancy firm Gordon Thomson Honeywell have been supporting the Bill with their campaign #DNAfightsRape. Although the Bill goes much beyond sexual assaulters alone, the #DNAfightsRape campaign focuses on how it could benefit sexual assault victims in particular.  In this episode, we explore how DNA is used in criminal investigations and how the science of DNA is addressed by the Bill. Our reporter Suryatapa Mukherjee speaks to Shreya Rastogi, founder of Project 39A at National Law University, and Rohin Garg, Associate Policy Counsel at Internet Freedom Foundation. You will also hear speakers from Ogilvy's webinar, Dr GK Goswami, the Inspector General of Police in Uttar Pradesh, and Vanessa Lynch, a senior government affairs consultant at Gordon Thomas Honeywell and the founder of The DNA Project and The DNA Project Africa. Standing Committee Report on DNA Bill  Being an editorially independent platform, we rely on you to help us bring in untold stories that have the potential for social change. Do consider supporting us! See sunoindia.in/privacy-policy for privacy information.

On 3rd February, the Parliamentary Standing Committee on Science and Technology submitted its report on the DNA Technology Regulation Bill in the Rajya Sabha. If passed, the Bill will set up a national DNA database in the country for the first time. It would indefinitely store the DNA of offenders, suspects, undertrials, missing persons and unknown deceased persons. Two members of the Standing Committee filed dissent notes. AIMIM president Asaddudin Owaisi and CPI leader Binoy Viswam said that the report does not address privacy concerns and possible targeting of vulnerable communities. Both advised compliance with the Supreme Court's Puttaswamy judgment on privacy rights. In this episode, we examine these arguments. Our reporter Suryatapa Mukherjee speaks to Rohin Garg, Associate Policy Counsel at Internet Freedom Foundation. He was one of the experts consulted by the Standing Committee for its report. Puttaswamy v. India Standing Committee Report on DNA Bill  Being an editorially independent platform, we rely on you to help us bring in untold stories that have the potential for social change. Do consider supporting us! See sunoindia.in/privacy-policy for privacy information.

Internet data and voice were both shutdown for months in Kashmir, after the removal of Article 370 in August of 2019, that has given Kashmir some autonomy. This action split the state into three parts. Since then, the local governments have implemented internet shutdowns more often - the latest being in Haryana and on the outskirts of Delhi where farmers are currently protesting. In addition to that, recent orders to Twitter to take lock several accounts have added another dimension to the government's move to curb the internet.On this episode, Sidharth talks to Devdutta Mukhopadhyay, a young lawyer who's part of the digital rights platform 'Internet Freedom Foundation'. Devdutta has studied and written about internet lockdowns in india which are getting more frequent and bigger in terms of geography and duration. She shares her views on how Twitter cannot really reveal what the reason behind accounts being locked down are or who the order has been sent by, and, if ignored, they can be imprisoned for at least 7 years, why it's important for companies like Twitter to give more time in getting more resources and content moderation in India and not only first world countries. Devdutta also touches upon how internet shutdown are different in Kashmir in comparison to most other states, how in Kashmir 18 out 20 districts don't have access to 4G, how, while there were internet shutdowns during the COVID-19 pandemic, most of the doctors couldn't practice telemedicine and faced problems due to curbing of the internet, and even that there has been no academic season for 2 years. The economic cost of internet shutdowns in India have cost around $2.8 billion dollars. Devdutta also talks about the failures of our education system and how schools should teach children how to spot misinformation, because as internet penetration increases, internet shutdowns will occur time and again, but also how the government can use the internet to prevent internet penetration. All this and a whole lot more on this episode, so do tune in.Follow the Internet Freedom Foundation on Twitter: internetfreedomFollow Sidharth Bhatia on Twitter and Instagram @bombaywallahbombaywallah and https://instagram.com/bombaywallahYou can listen to this show on The Wire's website, the IVM Podcasts website, app on Android: https://ivm.today/android or iOS: https://ivm.today/ios, or any other podcast app.

Social media platforms Twitter and Facebook are at a crossroads over whether to uphold freedom of expression or follow the government's orders to take down several accounts in the wake of the farmer protests. Apar Gupta, Executive Director of Internet Freedom Foundation and ET's Anumeha Chaturvedi explain what's happening.

Following widespread criticism, the Kerala government decided early this week to put on hold an Ordinance that gives unbridled powers to the police to arrest anyone expressing or disseminating any matter that it deems defamatory. However, the move to introduce such a law in the first place shows that State governments believe that existing laws are not adequate to deal with social media abuse. We discuss to what extent is this true. Guests: Rishab Bailey, a lawyer working with the National Institute of Public Finance and Policy, an autonomous research institute established by the Ministry of Finance; Vrinda Bhandari, a litigating lawyer in Delhi. She is Of-Counsel for the Internet Freedom Foundation, and specialises in the field of digital rights, technology, and privacy Host: Jayant Sriram You can now find The Hindu's podcasts on Spotify, Apple Podcasts and Stitcher. Search for Parley by The Hindu. Write to us with comments and feedback at socmed4@thehindu.co.in

In the third episode of Jack of all knowledge, I talk to Anushka Jain of the Internet Freedom Foundation to understand the usage of Facial Recognition Technology in India and the various problems associated with it. We also talk about how FRT is a tool in creating a culture of mass surveillance which has harmful consequences such as the chilling effect on protests, dissent and the free speech of people. Link to the Notion document with all the research Resources: https://www.notion.so/Facial-recognition-Technology-in-India-and-the-threat-to-Privacy-Ep-3-Jack-of-all-knowledge-4736ba3285284ea5bb622600d87cffda

Today on The Leaders' Brief - While India's ban on Chinese applications was welcomed by some who saw it as a stern message to Beijing, the popularity of some of these apps has created inroads for new security threats. Apar Gupta, Executive Director of the Internet Freedom Foundation, explains why. Chinese companies, including Alibaba and TikTok owner ByteDance, are gradually looking towards Singapore to ease their business troubles from obstacles being created by the Trump administration's Clean Network Initiative. The Australian government recently announced a $3.7 million grant to the national news agency, Australian Associated Press, as part of its pandemic-related assistance to regional journalism. The investment comes as part of Canberra's Public Interest News Gathering Program, which began in May, and brings the total amount invested towards supporting media organizations and public interest journalism to $40 million. About egomonk: Website | Facebook | Twitter | LinkedInegomonk is a global intelligence platform delivering asymmetric outcomes by bringing organizations closer to the communities they want to serve and the leaders they wish to influence. If you wish to collaborate with us then email us at contact@egomonk.com.

Facial recognition technology and its applications have been advancing, even in the absence of adequate privacy laws. Facial data is personal, sensitive, and potentially permanent - and it is being used for a wide range of applications in India and around the world. But are we addressing the challenges that come with this technology? Anushka Jain from the Internet Freedom Foundation joins Rohan Seth to talk about the problems with facial recognition and the impact it can have on privacy.Project Panoptic is scheduled to launch on September 1. Here are links to IFF's work on facial recognition:https://internetfreedom.in/we-have-written-to-the-government-seeking-a-3-year-moratorium-on-government-use-of-facial-recognition-technology-in-india-projectpanoptic/https://internetfreedom.in/iffs-legal-notice-to-the-ncrb-on-the-revised-rfp-for-the-national-automated-facial-recognition-system/https://internetfreedom.in/update-on-iffs-projectpanoptic/You can follow Anushka on twitter: @anushkaj11(https://twitter.com/anushkaj11)You can follow Internet Freedom Foundation on twitter: @internetfreedom(https://twitter.com/internetfreedom)You can follow Rohan on twitter: @thesethist(https://twitter.com/thesethist)You can listen to this show and other awesome shows on the IVM Podcasts app on Android: https://ivm.today/android or iOS: https://ivm.today/ios, or any other podcast app.

In the First Episode of our Second Season, Pranav Tanwar and Saurabh Pandey discuss with Apar Gupta, Lawyer and Executive Director, Internet Freedom Foundation on issues of transparency and legality of ban on 59 Chinese Apps under Section 69A of the Information Technology Act. Follow us at:- Website: www.ijlpp.com Twitter: https://twitter.com/IJLPP1 Facebook: https://www.facebook.com/ijlpp/ LinkedIn: https://www.linkedin.com/in/ijlpp/ Youtube: https://www.youtube.com/channel/UCLcI-YL1XZ9GVS9ho5yxwww/featured For doubts, queries and feedback: info@ijlpp.com About IJLPP: Indian Journal of Law and Public Policy (IJLPP) is a blind peer-reviewed, bi – annual, law and public policy publication. It is a student reviewed and edited Journal based and operated from New Delhi and comes out with two editions i.e. Summer and Winter in each of its volume every year. We, at IJLPP, seek to create a platform where there is a flow of ideas and thoughts regarding issues which mutually relates to policy making and law. This journal is our solemn effort to promote erudite discernment and academic scholarship over this relationship, in a way which is not mutually dependent on each of these fields but which is mutually exclusive and independent. The focus has been to give a multi – disciplinary approach while recognizing the various effects of law and public policies on the society.

The IFF is an Indian digital liberties organisation that seeks to ensure that technology respects fundamental rights. IFF's goal is to ensure that Indian citizens can use the Internet with liberties guaranteed by the Constitution.Become an IFF Member https://internetfreedom.in/become-an-iff-member-today/1.Introduction of all 2.The Business model of IFF 3. Long term objectives IFF wants to achieve 4.The Mood of the nation when it comes to data privacy. 5.Managing RTI in the current crisis 6.MKSS Story 7.The biggest gap between public policy and public 8.Any instance when IFF was successful in changing public perception 9.Net neutrality movement 10.The big challenge around Arogya Setu 11. Is contact tracing necessary? 12.Legal challenges around Arogya Setu 13. Was the government response on Arogya Setu satisfactory? 14.Difference between Arogya Setu and other International Apps 15. Was Arogya Setu under RTI? 16. Is Arogya Setu being used commercially? 17. How was Vahan Data app used during Delhi Riots 18.Status of Data privacy laws in India? 19.Surveillance Capitalism 20.Best case practice from across the world 21. What changes do we need in our privacy laws? 22.Gov of Kerala vs Sprinklr 23.How can health data be compromised? 24. Can we monetize our data? 25.Eye-opening cases that IFF has fought 26.Dowry Calculator 27.http://www.dowrycalculator.com/ 28.Section 69 A IT Act 29.Shreya Singal Vs Union of India 30.J&K internet shutdown 31.Anuradha Bhasin vs Union of India 32.Challenges in J&K with lack of Internet 33.Interventions in UP and Assam during internet shutdowns during NRC CAA protests 34. Should we be worried about facial recognition? 35. How do you see the digital rights movement evolving? 1. सभी का परिचय 2. IFF का व्यवसाय मॉडल 3. दीर्घकालिक उद्देश्य IFF को प्राप्त करना चाहता है 4. जब डेटा गोपनीयता की बात आती है तो राष्ट्र का मूड। 5. मौजूदा संकट में आरटीआई का प्रबंधन करना 6. एमकेएसएस स्टोरी 7. सार्वजनिक नीति और जनता के बीच सबसे बड़ा अंतर 8. जब आईएफएफ सार्वजनिक धारणा को बदलने में सफल रहा तो कोई भी उदाहरण 9. शुद्ध तटस्थता आंदोलन 10. आरोग्य सेतु के आसपास बड़ी चुनौती 11. क्या संपर्क अनुरेखण आवश्यक है? 12. आरोग्य सेतु के आसपास कानूनी चुनौतियां 13. क्या आरोग्य सेतु पर सरकार की प्रतिक्रिया संतोषजनक थी? 14. आरोग्य सेतु और अन्य अंतर्राष्ट्रीय ऐप्स के बीच अंतर 15. क्या आरटीआई के तहत आरोग्य सेतु था? 16. क्या आरोग्य सेतु का व्यावसायिक उपयोग किया जा रहा है? 17. दिल्ली दंगों के दौरान Vahan Data ऐप का इस्तेमाल कैसे किया गया था 18. भारत में डेटा गोपनीयता कानूनों की स्थिति? 19. निगरानी पूंजीवाद 20. दुनिया भर से सबसे अच्छा मामला अभ्यास 21. हमारे गोपनीयता कानूनों में हमें किन बदलावों की ज़रूरत है? 22. केरल सरकार बनाम स्प्रिंकलर 23. स्वास्थ्य डेटा से समझौता कैसे किया जा सकता है? 24. क्या हम अपना डेटा मुद्रीकृत कर सकते हैं? 25. आईएफएफ ने जो आंखें खोली हैं, वे लड़े हैं 26. दहेज कैलकुलेटर 27. http://www.dowrycalculator.com/ 28. धारा 69 एक आईटी अधिनियम 29. श्रेया सिंघल बनाम भारत संघ 30. जम्मू और कश्मीर इंटरनेट बंद 31. अनुराधा भसीन बनाम भारत संघ 32. इंटरनेट की कमी के साथ जम्मू-कश्मीर में चुनौतियां 33. NRC CAA विरोध प्रदर्शन के दौरान इंटरनेट बंद के दौरान यूपी और असम में हस्तक्षेप 34. क्या हमें चेहरे की पहचान के बारे में चिंतित होना चाहिए? 35. आप डिजिटल अधिकार आंदोलन को कैसे विकसित होते हुए देखते हैं?

Internet access is an essential part of many of our lives. And in 2019, there are more than 500 million broadband internet connections in the country. While celebrating this success, we also need to ask how our rights and freedoms must be protected on the internet. Net neutrality, internet shutdowns, website blocks, online censorship, and free speech are critical issues as almost all of India comes online. Apar Gupta joins host Pavan Srinath The Pragati Podcast is a weekly show on public policy, economics, and international relations. Apar Gupta is a Supreme Court Lawyer and the Executive Director of the Internet Freedom Foundation and was one of the key people behind the Save the Internet campaign. Follow The Pragati Podcast on Instagram: https://instagram.com/pragatipod Follow Pragati on Twitter: https://twitter.com/thinkpragati Follow Pragati on Facebook: https://facebook.com/thinkpragati Subscribe & listen to The Pragati Podcast on iTunes, Saavn, Spotify, Castbox, Google Podcasts, AudioBoom, YouTube or any other podcast app. We are there everywhere. You can listen to this show and other awesome shows on the new and improved IVM Podcast App on Android: https://ivm.today/android or iOS: https://ivm.today/ios You can check out our website at http://www.ivmpodcasts.com/