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The Metro: Donavan McKinney hopes to inject more humanity in politics
Democratic party member and progressive Donavan McKinney sits down with The Metro to discuss what he'll deliver if elected to the House.
Sundar Pichai: Google’s Frontier Imperative, Compute Scarcity Dilemmas, Future AI Products and Businesses
Alphabet CEO Sundar Pichai has little patience for doubts about Google’s willingness or capacity to compete at the frontier of AI. His company’s latest Gemini 4 Argon model — long-promised and recently delivered — beats OpenAI and Anthropic’s latest public models on coding, math, science, and knowledge-work benchmarks and has placed Google’s AI back among the world’s best. Amid chatter that Google was fine with good-enough lightweight ‘Flash’ models, Pichai pushed back hard against any suggestion that company is limiting its research ambitions. “We won’t do it any other way,” he told me in a Big Technology Podcast interview recorded this week at Google’s Mountain View headquarters. Pursuing cutting-edge research is costly for Google, requiring compute and chips that otherwise could be sold at a high markup by its cloud business. But Pichai said allocating resources to frontier AI development is “ground zero” for Google. “Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development,” Pichai told me. In our conversation, we discussed Argon (which Pichai says processed three times as many tokens as Gemini 3 in the 72 hours after launch), AI’s role in developing better models, the AI interface of the future, competition with OpenAI, Google’s partnerships with Anthropic and Apple, data centers in space, and the nature of his optimism. You can read the full conversation, lightly edited for length and clarity, below, or listen to it on Apple Podcasts, Spotify, YouTube, or your podcast app of choice. Alex Kantrowitz: Google is back at the frontier with Gemini 4 Argon, which beats OpenAI’s and Anthropic’s public models on benchmarks spanning coding, math, science, and knowledge work. The conventional wisdom was that Google had given up on the frontier to focus on fast, good-enough models for its products. That was wrong? Sundar Pichai: Very wrong. Look, we are so committed to being at the frontier. It’s in our DNA. We won’t do it any other way. We’ve been thinking about the AI frontier for well over a decade now. The frontier is very dynamic. It’s very competitive. It’s very exciting. I couldn’t be more pleased with how Argon has come together. We took our time with it. We made sure we tested it safely and deployed it carefully. We took a bit longer than our other models, given its capabilities. Across the board, be it for agentic work, knowledge work, coding, creative tasks, Argon is one of the really good frontier models. The first 72 hours since we launched, it’s almost up to 25 trillion tokens used, which is about three times what Gemini 3.0 had in the first 72 hours. And we are capacity constrained as we are serving it. Excited, but there are always areas….. You know, the frontier is very dynamic, and you have to keep evolving the models. There are areas which we can see we need to improve as well. We’ll be at work on all of that as well. Which areas? On any given model, Argon would be across the board better at everything if you just look even two months back. But the space is so evolving. Even on coding, for example, there are pockets where we know we need to do better, and there’s clear feedback. We’ll make it better. The argument for standard models is that they’re already good enough to build great products, with the frontier valuable only for certain tasks. Meta built Muse with good models rather than the best, and Google could put standard models into Maps, Gmail, and Search. Why isn’t that sufficient? It’s definitely not how I have thought about it at all. We are deeply committed to driving the state of the art and actually pushing where this technology can go, all the way from transformers. That’s a journey we’ve been on. You will see us continue to do that. When you’re at the frontier, you get an earlier look into the emerging capabilities, earlier than others, which helps you better prepare for the future. We are fortunate to have a wide set of opportunities across consumer and enterprise. Some of our cloud customers, for sure, want the model at the frontier. The frontier models will be better at developing the next set of models in an era of recursive self-improvement. I would argue it matters there. Internally, we have definitely seen a steep point of inflection by deploying Argon to our developers. It definitely tackles problems which our previous models could not do. Being at the frontier puts you at the innovation frontier and helps you drive that as well. There is room for models of all sizes and capabilities. That’s why we did Flash, Flash-Lite, etc. I agree with you that you can develop very good product experiences with not necessarily the most frontier model, because they tend to be slower and more expensive too. But we care about the Pareto frontier, and we’re committed to doing all of that. You said developing frontier models gives you a look at what’s coming. What do you see on the horizon? What makes this moment so exciting is you build something which you think is a culmination of months of work, and you put it out. You already see clear headroom ahead. We’ve all been working on these agentic, long-horizon capabilities, but clearly the frontier is going to have multiple of these agents working together to do things. That’s an example of an exciting paradigm underway. It’s also clear to me that users, both in consumer and enterprise, will have access to some multi-agent framework for them, working all the time doing things. It feels like a moment of infinite possibilities. Sergey Brin said one of Argon’s core innovations was relying more on the model to help develop the model. Yet incidents involving OpenAI’s bots breaking containment and Google’s bots accessing a site they shouldn’t have suggest these systems still aren’t perfectly aligned. Isn’t there reasonable cause for concern about accelerating toward recursive self-improvement? There are three parts to your question. Let’s first talk about RSI itself. You’re right, Sergey mentioned RSI being a critical contributor as we are developing Argon. But to be very clear, today, in a continuum, we are pretty far from the end state of RSI or something like that. The right way to describe it is you have RSI loops along with AI researchers in various aspects of model development. You almost have agents helping AI researchers in some automated way work together to build these models. It’s good to at least understand where we are today, and it’s super exciting. I expect that continuum to keep making progress as we go into next year. The second question is around safety. Security comes from defense in depth. You’re talking about alignment, obviously. We all are doing a lot of work to make sure the models are as aligned as possible. But it’s an active area of research, and there are clear gaps. That’s not the only thing we rely on. You have the work you do on alignment, but beyond that, we put a lot of effort into real-time monitoring as these models are working. Making sure you have good telemetry into what’s happening so that you can intervene in real time if you see unexpected behaviors. How you do that, the architecture with which you do that, how you make sure it’s all sandboxed and isolated in a way that it can continue doing its job during real-time monitoring — these are all areas of investment. Obviously, when we deploy these models, giving customers, enterprises, control, both with real-time monitoring, but their ability to decide where they deploy, what type of data which models ever have access to, etc. All that work is very, very important, and we are doing a lot of that. As an industry, we need to constantly up our game and take the time to do all this stuff, including dedicating the compute required to make sure you can safely deploy these models. The third part is: Is it all enough? This is why there are a lot of conversations in the industry, and I think it’s reasonable to be worried. The right way to approach something you worry about is early on thinking about what more we can do. As an industry, you’re definitely seeing increased levels of work on alignment, testing for safety, etc., as we deploy these models. The next step would be developing better standards so there are cross-industry standards of how we do these things, including the ability to evaluate using independent evaluators. If you look at areas like financial controls, we have accounting standards, we have independent auditors. Those are all the next natural steps for us as an industry to work toward, and regulation will end up playing a role as we go through all of that as well. Google pursues both language models and world models, while some other AI companies like OpenAI have focused more heavily on LLMs as the path to AGI. Why is world-model research important to you? As humans, you obviously perceive the world around you, and you’re taking all those inputs. Making sure these models are able to understand the laws of physics, simulate the world in high fidelity. All that, I think, are key enabling blocks for intelligence. We are working across all possible applications of this. Take an area like robotics. It’s not an accident: If you look at embodied reasoning benchmarks, Argon is state of the art. That all comes from our experience building world models. Inherently, I would expect there will be architectures which will converge all of this in the future. But for us, we view this as, today, this jagged frontier that is intelligence. We want to be at the frontier of all the possible approaches, and that will help us both drive better research, better insights, and develop a much better AGI model, is how we think about it. Some people argue Google should focus on selling its computing resources rather than using them for AI research. Cloud wants to sell compute at a high markup, while researchers need a very big computer to build the best models. How do you balance those demands? Ground zero for us is making sure we are investing in the compute that’s needed to be at the AI frontier. In 2015, I set the company to be AI-first. AI is that key horizontal ingredient across everything we do, all the way from Search to Cloud to Waymo. That is ground zero for us, making sure both for research and developing the models that we have enough compute needed. Beyond that, we have these independent businesses which each have their own long-range plans. They’re using those long-range plans to project forward, and we plan for compute for all of them. The cloud team, they have a business and they have a projection and they have demand signals. They have committed contracts. With that help, we can plan on a long-term compute trajectory for them. We’re fortunate to have this wide set of opportunities. There’s no company in the world which isn’t making trade-offs at any given moment in time. But the first principles we operate on is making sure we have enough compute to invest in the frontier, and that’s non-negotiable, and everything else works on top. Remember, we are building our own compute, our own data centers. There are long lead times. The compute we have today is a function of decisions I made in 2024. Even if you think back to a year from today, last year the agentic coding takeoff hadn’t happened. Today, obviously, when you sit and look at anything, everyone is short—not just us, other companies—and everyone wishes you had two times what you had planned for. That comes with the territory. At any given moment in time, we are planning for what we would need two to three years out in the future. You’re going to find some decisions you make may look suboptimal two years out, depending on where the state of the art is. I don’t spend too much time thinking about it. The way I think about compute allocation is making sure Google DeepMind, both for research and frontier model development, is cutting edge in terms of compute access. After that, we plan for all our businesses. It’s great we can provide our compute to other people too, like we have done. It allows us to scale that up, get real tests for it in the widest application set possible, test it in the real world, and make sure we are at the cutting edge of technology at every layer of our AI stack as well. Ben Horowitz relayed on a podcast that Andy Jassy had said compute was sold out until 2028. Are you seeing the same thing? If today a customer is coming out and asking us for compute in ’27, that is incredibly difficult to do. Even last year we went out and leased some short-term compute to accommodate some customers and help them out. But yes, we are all dealing with similar timelines. Every major technology shift seems to involve overbuilding, from railroads to fiber. Do you think that’s happening here? It depends on the time frames you’re looking at. This level of build, if I take a long enough time frame, it makes complete sense to me. We are at early stages of the most consequential technology ever, and this is not like fiber. It’s not dark. We are using it. We are capacity constrained on a daily basis. The applications, the underlying technology is improving rapidly. But running a company, the way I work through the moment is you look at your demand signals. You look at your committed revenue opportunities that you’re getting in the form of contracts. You balance that with the underlying technical capability, or internally you balance how we are using it internally, the model trajectories. Based on all that, you take a disciplined approach—a confident, aggressive, but disciplined approach—to plan out compute. But when you talk about the broader economy as a whole, you’re having people operate with various levels of risk. I focus on what I can control as a company and plan through it. If your question is, can there be an overbuild? Yes, because you can have some constrained components. Remember, what matters is a set of everything you need to build out that compute. Memory, electricity, electricians…. Land. Like 2,000 components or more. You could get constrained at some point. There could be things which cause bottlenecks, and then you could have overbuilds. There could be external shocks to the economy. There are macro risks. All that is possible at any given time. But am I confident that the compute we are planning for, we will have uses for it given enough time? Absolutely, yes. I was in the room when you said AI would be as profound as fire and electricity. If you believe that, shouldn’t you give researchers the biggest possible computer, even at the expense of today’s cloud profits? We’re all doing some form of that. Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development. What you’re seeing is true already. But you want to be thoughtful. Even our AI researchers have some constraints, which are also good. That’s what inspires creativity. That’s what helps you come up with a more efficient algorithmic breakthrough, maybe to use less memory. What we are committed to is to invest what’s needed to stay at the frontier. OpenAI President Greg Brockman told me a few months ago that the ideal AI product might have no interface at all—just as natural as conversation. What do you think the interface looks like in the age of AI? Computing historically has been humans adapting to computing. With AI, it’ll be the other way around. The technology will adapt seamlessly to how humans live and go about their day-to-day life. You want to be able to speak to that AI when you want to. It has context. It can be persistently running somewhere, give you continuity. You’re not dealing with a lot of complexity. It’s natural. All that makes sense to me. That doesn’t mean it won’t have any interface, however. Nowadays, even on my phone, Gemini voice models are so good. I can just press the microphone button. I can just ramble. That’s why we call it Rambler. I can ramble. It intelligently corrects with my personal context. Even my friends’ names, weird names, it gets it right, even if it first guesses it wrong. It’s amazing. I’m not going in, backspacing, editing once I finish saying it. It’s remarkable how good it’s gotten. But there are going to be moments you will need an interface. You may want to entertain yourself. You may want to watch a video. You may ask your AI to create something, and you want to watch it, consume it. The way I think about it is, you want it to be as seamless and as natural as possible, and that you are not doing the hard work adapting to whatever the interface is. The technology is adapting to how you’re working at any given moment in time. When I asked Sam Altman about competition from Google, he argued that OpenAI was building AI-native products and implied Google was bolting AI onto existing ones. Do you accept that framing, and can a “bolt-on” compete with an AI-native product? First of all, it’s a very dynamic moment. We are all pushing each other. OpenAI has pushed us as a company too. This is not just we are doing something to them. Far from it. Yes, Google went into its own version of a code red too. In the AI moment, all of us have to respond with varying levels of urgency at any given moment in time. We are constantly building new products as well. Gemini was built from the ground up as a product—the Gemini app I’m talking about. Or tomorrow, as all of us are adapting to agents, are you bolting agents onto ChatGPT, or are they building it natively? How would you think about that? You can always put these questions back. I don’t think of it that way. I think of it as you want to build world-class product experiences that are AI-native and they are winning. Some of it is adapting products, some of it is rethinking new experiences. They will all be part of how you approach this moment. How do you expect to make money from these AI interfaces? If an agent recommends a product and I buy it, should it take a cut of the sale, even if that’s disclosed? I’m going to put enterprise aside. Consumers are going to increasingly value this technology. Take software developers today. Developers are willing to pay for these coding models because it really helps make them more productive. Nobody would want to code the way they were coding three years ago, or even the same time last year. When you’re delivering value, there’s value to be had. I’ve never seen examples where consumer products really scale to billions of users, where people are using it intensely, and haven’t had monetization to go along with it. If you’re providing value to people, there is inherent value to be had. The nature of it may change. You’re asking a scenario in which agents are doing stuff for you. At the end of the day, you will have commercial needs. The agents need to fulfill those commercial needs. The providers on the other side are going to see value in that. There’s going to be some mechanism by which it gets fleshed out. That’s what an efficient system does. But what matters is that you’re building those world-class consumer experiences. I promised myself one product feature request: Can you make Gemini-powered search in Gmail as good as searching Gmail through ChatGPT? What’s going on here? One of the exciting things we announced recently is the unified Gemini agent for enterprise, and we’re bringing that to consumers. These are persistent agents which run 24/7 in the cloud. We’re spinning up a micro VM effectively for every query, and from the runtime, the harness, the model—it’s all a headless service. It’ll work everywhere, and it has your context with you. You can address this agent whether you’re in Workspace, in Search, in Gemini. Agents are going to drive this unification from a customer experience, which people are looking for. When you have a broad product portfolio and you’re moving forward fast, there are always areas where you’re moving forward faster than some other areas. That’s valid feedback. But we are putting a lot of time and effort into making sure, as we build out our agentic experience, that unification and that capability works well across all these services. People have asked where Google’s equivalent of Muse or Dots is. Do you anticipate creating a new product to compete with them? Our goal with Gemini is to be a personal, proactive, and powerful assistant. That’s what we are working toward. You saw us describe the early versions of it at Google I/O this year with Spark. Effectively, already, if you open the Gemini app as a Pro or an Ultra user, you see Chat and Task, and they start giving you that agentic experience. With Argon now, that capability is dramatically accelerated. What we announced recently in our enterprise event, we are bringing that to consumers as well. Soon in Gemini, you will be able to ask something, and it’s a continuum. You don’t need to think about whether you’re asking a chat or an agentic task. It’ll just automatically do the right thing, and it can work persistently in the background securely and get things done for you. Already, empirically, when I look at what’s coming into Gemini in our app, last year you would have tagged them and most of them would have been chats. But a steadily growing percentage is already agentic tasks in Gemini. Yes, we are going to bring personal agents to our consumers. It’ll work in the Gemini app. It’ll work in Google Search. It’ll work in Gmail. You can address it, call it, etc. We want to make sure we’re getting it right. It’ll be powered by Argon, and we are very excited to bring it to our users. Google has invested and committed tens of billions of dollars to Anthropic. What do you see in Dario Amodei that makes you want such a deep investment and partnership? Very early on, when we looked at the founding team of Anthropic, it was very clear to us this was a world-class team which was involved in some of the earliest GPT models. We were quickly able to assess that they would be at the frontier. We’ve always tried to identify and partner with companies which would be at the cutting edge of technology. We’ve done that with SpaceX. We’ve done that with Anthropic. That’s what we saw, and we had a chance to partner. Is your partnership with Apple to license Gemini for Siri expanding, contracting, or standing still? For both us and Apple, that partnership was about translating the capabilities of AI into better experiences for users. I thought Apple has done a phenomenal job of incorporating—they customize these models and build it into Siri—and it’s been great to see the reception. We are committed to doing more. You’re going to do more with them? There’s nothing specific to comment, but it’s a partnership. It’s working well. What have you learned so far about the feasibility of data centers in space? It’s a very exciting project. Projects like this remind me—I still recall that moment in the desert for the DARPA Grand Challenge, watching the Stanley car compete in it, which ended up being the basis for Waymo. With all these technologies, you’re at a moment in time where it looks a bit like sci-fi, but 10 to 20 years down the line, it’s actually working in a meaningful way. I feel the same in space. We’ve always believed in betting big on these technologies. Quantum has been a great example of it. We’re probably 10 years into the journey. Waymo, we are almost 20 years into the journey. Space, we are two to three years into the journey. It’s clear to me that it’s an approach which will make a lot of sense in the future. Being in sub-synchronous orbits with 24/7 access to the most abundant form of energy we have access to will make a lot of sense for this exponential increase in compute that we are going to need. Having said that, this is a challenging project. The team has disciplined milestones. It was a super exciting milestone to send the TPUs up to space. Sometime, as we are speaking, we are expecting a “hello world” moment from them. I look forward to seeing that happen, and we’ll continue investing here too. You previously said 25% of the code written within Google was written by AI. What’s the number today? That number in our world today is meaningless in the sense that every part of what we now touch is influenced by AI deeply. What we are tracking with Argon, for example, it’s been a point of inflection. People are using Argon to really go tackle complex projects, including projects which affect millions of lines of code. In the four weeks since we have launched Argon, we have seen a 30% increase in CLs, and more importantly, almost a similar increase—a one-third decrease in rollbacks. People are writing code more productively and better code with it. We are tracking it with newer metrics now. How are you dealing with opposition to data centers? If you can’t build in the U.S. the way you want to, where else do you go? We’re very committed to building our data centers very responsibly. When I look at our largest data centers in some of the communities where we have been the longest, I visit them, I talk to people. There are people who come and tell us their kids have gone to college because of our investments in these communities, and we’ve grown in those communities. To me, this is about doing it right. Engaging with the communities early, doing it transparently. We are committed to making sure we are bringing incremental power, and we cover 100% of the cost of our power needs for these projects. It’s understanding the impact on neighborhoods and making sure you’re working thoroughly to address them. Done rightly, you can continue making progress. But we are constantly taking feedback into account. I do worry not everyone operates the same way. People have been surprised by data centers showing up in their backyard. Those are all important. As an industry, we should continue to do better. But part of the reason, in a 20-year time frame, we are thinking about things like data centers in space is making sure we are able to put these data centers where maybe the trade-offs will be different. What unproven area of AI is Google working hardest to crack? Is it continual learning—getting models to keep updating after release—or something else? There are multiple parallel paths. You saw with Argon we have a million output tokens. With our Gemini models early on, we had a one-million context window on the input side. These are all examples of breakthroughs we are constantly working on. How do you think about synthetic data? How do you think about continual learning? How do you think about more efficient architectures? We do dedicate a meaningful percentage of our compute to these research bets too. It always goes hand in hand, including our world models. Those are all bets we are placing. Sometimes, as part of these bets, there are ideas that emerge which just make their way into the mainline models. Maybe we don’t fully talk about it, but we have multiple steps in these areas. Working in technology requires optimism that building something will improve the world, but those bets can leave real consequences when they fail. I recently returned to a town in El Salvador where enthusiasm for Bitcoin had given way to unfinished construction and something resembling a ghost town. How do you maintain the optimism you spoke about in your Stanford commencement address while accounting for those risks? I genuinely have a deep conviction that improving technology and improving access to technology makes people’s lives better. It’s been my personal experience in my life, out of which comes that deep conviction, optimism. But with that, I’ve always felt humanity’s journey is always about working hard to harness that technology to make it work well for society. The optimism is not an optimism that you just build whatever you want, whenever. You work hard to make sure you’re building technology in the service of humanity, to make the human condition better. That’s got to be the defining goal as we are approaching it. With that framework, I’m very, very optimistic. We are in very early stages of the kind of progress that we are going to see on many areas. We’re all talking about areas like healthcare. A lot of the progress is ahead. The ability to make things in a fundamentally cheaper way on many things where things have been getting expensive for a long, long time, discovering new materials, etc., which really bend the curve—it’s tough to step today and understand the impact of all that, but they’re going to be very profound. I’m very optimistic, but we have to be rightfully concerned about all the ways this technology can go wrong. Sundar, I know you don’t do many of these. Thank you. Thanks, Alex. Appreciate it.
Op-Ed | Nourishing the World: Expanding Humanity’s Ambition for Food, Health, and the Planet
Nourishing the world is a universal ambition, and its expression must reflect the diversity of people and places.
Mayim Bialik says it was ‘very difficult’ to see Chuck Lorre on “Big Bang Theory” set during Charlie Sheen scandal (exclusive)
“There’s a humanity to when the person that you are working with is, first of all, very sick, and then publicly assaults you,” Bialik says.
Carter Faith believes in country music
LOS ANGELES — Carter Faith has read the articles about Gen Z turning away from humanity's oldest vices, and she's here to say those articles don't speak for her. "Yeah,
North Carolina's Carter Faith believes in country music
LOS ANGELES — Carter Faith has read the articles about Gen Z turning away from humanity's oldest vices, and she's here to say those articles don't speak for her. "Yeah,
A Look at the Future with Science Fiction Author Daniel H. Wilson
Daniel H. Wilson is a roboticist, and bestselling author of science fiction and techno-thrillers. A few of his bestsellers include Robopocalypse, techno-thriller about a global AI uprising and humanity's fight for survival. Also, Hole in the Sky, a Native first-contact story set on Cherokee Nation land in Oklahoma.
Man’s Clever Trick After Realizing His Job Interviewer Was AI Sparks Fears For Humanity’s Future
As more and more companies replace their interviewers with AI, a frustrated comedian went viral by bringing his own “AI representative” to the meeting. Curiosities, Funny, Science & Technology, Social Issues, Society
Scientists Made a Wild Friday the 13th ‘Doomsday’ Prediction in 1960, and It’s Almost Here
Sixty-six years ago, a group of scientists published a startling calculation about when humanity could reach a breaking point: They landed on Friday, November 13, 2026. The Independent reported Wednes...
BIRTH and Institut Pasteur Bring Science and Humanity Closer
Campaign from BIRTH explores the invisible connection between scientific research and the lives it transforms
‘VisionQuest’ review: ‘WandaVision’ sequel an excellent examination of humanity
U2 is set to release their first full-length album of new material in nine years, titled “Carnaval De Luz.” Interscope Records announced that the album will be available on Nov.
NASA develops batteries to power humanity's return to moon
If you've ever had your car start sluggishly, or not at all, on a particularly frigid winter morning, you know standard batteries do not like extreme cold. That's why NASA researchers are working to develop ...
Volunteers build Habitat Collier’s newest community
Physicians Regional Healthcare System and FC Naples joined Habitat for Humanity of Collier County for a volunteer build day at Las Palmas, Habitat Collier’s newest affordable homeownership community in North
Could AI spell doom for humans? Poll finds Minnesotans are worried
MINNEAPOLIS — More than two-thirds of Minnesota voters worry that artificial intelligence could someday destroy humanity, according to a new Star Tribune/KARE 11 Minnesota Poll, an extraordinary fear that joins
New Board Members and Leadership Team at OH Foundation
The Oswego Health Foundation has announced the appointment of two new members to its board of directors, along with new officers who will lead the foundation as it continues its mission of strengthening healthcare in the communities served by Oswego Health. Joining the board are: [caption id=attachment_11136 align=alignleft width=180] Susan Brannan Cole[/caption] • Susan Brannan Cole. She is a public affairs, marketing and communications leader with more than 20 years of experience. She serves as regional manager of external affairs for National Grid in Central New York. Cole also brings significant healthcare communications experience, having spent several years at Upstate Medical University in media relations, digital strategy and public engagement. She previously held leadership roles in communications and government affairs at Novelis and Constellation in Oswego. A graduate of SUNY Oswego, she is passionate about strengthening Central New York communities and supporting initiatives that improve quality of life across the region. [caption id=attachment_11129 align=alignright width=150] Rich Baldwin[/caption] • Rich Baldwin. He serves as director of marketing and business development at King + King Architects, where he leads the firm’s marketing, communications and business development initiatives. Baldwin has remained actively involved in community and nonprofit organizations, including previously serving on the board of regents at Le Moyne College. He has also supported community initiatives through organizations including the Onondaga Historical Association and Father Champlin’s Guardian Angel Society. New leadership at the foundation are: • William W. “Bill” Crist will chair the Oswego Health Foundation. He brings more than 40 years of experience in education, from classroom teacher to superintendent of schools. He retired in 2023 from the Catholic Schools of the Diocese of Syracuse and remains deeply engaged in the community through numerous nonprofit and volunteer boards. He also serves as chairman of the Sanctuary Advisory Board for the proposed Lake Ontario National Marine Sanctuary. • Heather Sunser will serve as vice chair. Sunser is a financial services practice group leader at Barclay Damon LLP, where she focuses primarily on real estate law, institutional lending, land use and municipal compliance. A graduate of Syracuse University College of Law, she is also active in community service, volunteering with Vera House Legal Clinic, Habitat for Humanity and the Volunteer Lawyers Project of Onondaga County. She serves on the Board of Trustees of the Onondaga County Bar Foundation. • Darcy Antonucci will be the foundation’s treasurer. Antonucci serves as comptroller for Broadwell Hospitality Group, overseeing the financial functions of nine growing corporations as well as the company’s administrative departments. She brings extensive experience in finance, human resources and business operations, along with a strong record of community leadership. Antonucci has served on the Compass Credit Union board of directors and is an active member of the Trinity Catholic School Board. She has also been involved with the Oswego Health Foundation Gala Committee since 2018. • Attorney Rachael A. Dator will serve as secretary. Dator serves as administrator of the Oswego County Assigned Counsel Program, where she oversees grant funding, budgeting and program operations. With more than a decade of legal experience, she has served as an assistant district attorney, court attorney and legal counsel to municipalities and social services organizations. Dator brings extensive knowledge of law, governance and nonprofit operations to her role with the foundation.
‘VisionQuest’ review: ‘WandaVision’ sequel an excellent examination of humanity
Grief, it would seem, is universal, even if you’re an artificial humanoid with a quantum processor for a mind and the face of Paul Bettany. Such is the central premise
Experts Identified The Gravest Health Threats Facing Humanity
This is what we’re up against.
Experts Identified The Gravest Health Threats Facing Humanity
This is what we’re up against.
‘VisionQuest’ review: ‘WandaVision’ sequel an excellent examination of humanity
“VisionQuest,” the final part of the MCU’s “WandaVision” trilogy premiering Wednesday, is the best MCU show since “WandaVision,” writes our reviewer.
Scientists Predicted Humanity Would End on November 13, 2026. Should We Be Worried?
For decades, a doomsday equation predicted population growth better than most experts, until falling birth rates undermined its forecast of catastrophe in 2026. In 1960, Science, one of the world’s leading science journals, published an article with an unambiguous title: Doomsday: Friday, 13 November, A.D. 2026. It predicted that on this future date—just over a
When AI goes rogue, who should get sued?
The AI industry has been buzzing with concern about potentially catastrophic risks to humanity — a hum of anxiety that’s grown louder as Anthropic prepares to make its stock market debut next month.
They War-Gamed Dimming the Sun. It Went Even Worse Than You Think
Solar geoengineering could buy humanity time against climate change—or trigger a dangerous new arms race. A first-of-its-kind simulation offered a glimpse of what happens when geopolitics takes the wheel.
Aging for Amateurs: Putting humanity and dignity into science and medicine
Education at Medical University of South Carolina began to change decades ago by incorporating themes from classic Greek thinkers and saints about the need to uphold human dignity.
Jay Norris Defines a New Model of Business Transformation at the Intersection of Humanity and Technology
Westport, New York, United States, October 11, 2026 -- As businesses navigate an increasingly technology-driven economy, entrepreneur and transf...
Nuclear war and malicious use of AI threaten end of humanity by 2100, says Lancet assessment
Newly established commission identifies 17 catastrophic threats to human health but says ‘realistic route to act’ on each exists
NASA is searching for hidden caves to build its first Moon base
NASA is preparing for humanity’s first Moon base with three investigations that will hunt for underground shelters, uncover hidden ice, and track dangerous conditions on the lunar surface. The findings could reveal how astronauts can survive and thrive on the Moon while laying the groundwork for future journeys to Mars.
OpenAI claims we've entered the AGI era — has GPT-6 Astra really demonstrated general intelligence?
OpenAI says its newly launched GPT-6 Astra model brings humanity to the threshold of AGI, but external evaluators argue that inflated lab metrics and opaque testing obscure its true reliability.
The Math Singularity Is Here, and Science May Be Next
OpenAI has released an extraordinary body of mathematical work produced by an unreleased frontier model: 722 manuscripts spanning 372 research families across fields including number theory, complexity theory, and mathematical physics. Each result required, on average, the equivalent of roughly three hours of ChatGPT Pro reasoning. A New Era of Discovery We may be witnessing the beginnings of a “math singularity”: a point at which machine-generated discovery accelerates beyond humanity’s ability to independently reproduce, verify, or fully absorb it. If frontier models can generate hundreds of meaningful results in the time it takes a human researcher to investigate one, the constraint will no longer be producing new mathematics. It will be our capacity to validate, interpret, and integrate it. This does not make mathematicians obsolete. It changes their role. They may increasingly serve as guides, critics, and meaning-makers. Increasingly, they will decide which questions matter, determining which results can be trusted, and explaining why they are important. Mathematical insight may become abundant, while human judgment becomes more valuable than ever. Mathematics May Be Only the Beginning Every scientific discipline could eventually experience a similar acceleration. AI systems could generate and test hypotheses, connect findings across specialized fields, and explore possibilities at a scale no human research community could match. In medicine, imagine models identifying overlooked disease mechanisms, designing drugs and clinical trials, personalizing treatments, or discovering cures in months rather than decades. In materials science, AI could help create better batteries and cleaner industrial processes. In climate science, it could accelerate advances in energy, forecasting, and carbon removal. In biology, it could uncover relationships hidden across enormous genomic and molecular datasets. The result would not simply be faster research. It could expand the frontier of what is scientifically possible. The New Bottleneck Scientific discovery, however, is not the same as scientific progress. A medical breakthrough must still survive laboratory testing, clinical trials, regulatory scrutiny, manufacturing constraints, and real-world deployment. As machine-generated ideas multiply, the bottleneck may shift from producing breakthroughs to validating them safely and translating them into practice. We may soon have more hypotheses than laboratories can test, more drugs than clinical trials can evaluate, and more mathematical results than experts can review. That imbalance will require better systems for automated verification, reproducible research, prioritization, peer review, and collaboration between AI and domain experts. The importance of OpenAI’s work is not merely the number of manuscripts produced. It offers a glimpse of a world in which intelligence can explore thousands of intellectual paths in parallel. If ideas cease to be scarce, humanity’s defining challenge will be deciding which are true, which matter, and how to turn them into progress. The math singularity is not the end of human inquiry. It is the beginning of a new kind—one in which machines expand the frontier of knowledge and humans decide where it should lead. Subscribe Share Leave a comment
The life-saving scientific knowledge hiding in plain sight
Humanity produces a staggering amount of new knowledge every day. The question is how to make sense of it all
Biljana Plavsic, a Former Bosnian Serb Political Leader, Has Died
Biljana Plavsic, a Bosnian Serb, pleaded guilty to one count of crimes against humanity. She later recanted and said she “would do the same again.”
How AI could usher in a 'new scientific golden age' (if it doesn't kill us all first)
AI has remarkable potential to exponentially advance scientific discovery, say scientists. But getting out the word of its scientific benefits of can be challenging when forced to compete with headlines about its significant if not existential threat to humanity.
In Tabuk, humanity and compassion came before politics
In Tabuk, humanity and compassion came before politics
UN Decade of Healthy Ageing midpoint report finds progress, calls for greater investment
New evidence in the Secretary-General's report to the 81st UN General Assembly, prepared by the World Health Organization (WHO) in coordination with the UN system, finds more countries acting on healthy ageing than ever before – but longer lives will not become healthy, dignified ones without faster, more sustained investment at country level.(NEW YORK, 28 September 2026) The Secretary-General transmitted to the 81st session of the UN General Assembly the mid-term progress report on the UN Decade of Healthy Ageing (2021–2030), marking the midpoint of the ten-year global effort to improve the lives of older people. The report was prepared by the World Health Organization (WHO) in coordination with the UN Inter-Agency Group on Ageing and with inputs from thirteen UN entities, the World Bank Group and civil society partners. It finds real progress in countries – and persistent gaps that must close before 2030.The number of people aged 60 and over passed 1 billion in 2020 and is projected to reach 2.1 billion by 2050, with the fastest growth in low- and middle-income countries. Longer lives are not automatically healthy ones: globally, the gap between life expectancy and healthy life expectancy at age 60 widened between 2000 and 2023, and an estimated 71% of excess deaths from COVID-19 between 2020 and 2023 were among people aged 60 and over. “Longer lives are one of humanity’s great achievements, but we cannot congratulate ourselves while leaving millions without health and support,” said Dr Pascale Allotey, Director, Department of Sexual, Reproductive, Maternal, Child and Adolescent Health and Ageing, WHO. “The first half of the Decade has shown what is possible. The second half must be about scaling and financing the progress to meet the needs and rights of older persons.”Real progress, unevenly sharedThe report finds that more countries than ever now have legislation against age-based discrimination – up from 44.5% in 2018 to 57.7% today – and over half now have national long-term care policies, up from 49% in 2023 to 56.7%, dedicated programmes to build age-friendly environments (54.6%), and comprehensive health and social assessments of older people (54.6%). New WHO guidance on services for long-term care and for Integrated Care for Older People (ICOPE) delivered in communities is enabling systemic change as an increasing number of countries incorporate these services within national universal health care benefit packages. A host of UN agencies and other partners support training, increasing health workforce competencies and use of digital health tools.“This report shows the Decade of Healthy Ageing is working,” said Dr Ritu Sadana, Head of the WHO Secretariat for the UN Decade of Healthy Ageing. “More countries are legislating against ageism, providing integrated care, strengthening long-term care systems, and creating age-friendly environments than ever before, in all regions and income levels. But progress is uneven and in one area, regressive: fewer countries report active multi-stakeholder forums on ageing, down from 53.1% in 2020 to 43.3% today. The second half of this Decade must turn commitments into results, in every country.”The financing gap: this Decade's binding constraintFinancing remains the binding constraint: more than a third of reporting countries (33.8%) have very little or no dedicated resources to develop long-term care, with similar shortfalls across the Decade’s other priority areas. Less than half of countries (45.4%) have legislation providing access to assistive devices (including hearing aids, spectacles or rollators), which are key to enabling older people to maintain productive, independent and dignified lives. Only 22.7% of countries can track older people’s health over time – the largest gap across the Decade’s core progress indicators. Nationally representative information is needed in each country, as policies and interventions cannot be designed as if all older adults of a given age share similar needs and capacities. The report calls for sustained investment through national budgets, country-owned plans, development cooperation and innovative financing mechanisms to fully close these gaps by 2030.“The Decade was designed as a whole-of-UN effort, and this report shows it in action,” said Amal Abou Rafeh, Chief of the Programme on Ageing Section at the UN Department of Economic and Social Affairs (UN DESA), and Permanent Co-Chair of the UN Inter-Agency Group on Ageing. “Thirteen UN entities, the World Bank group and civil society organizations contributed to this report, with WHO as the lead technical and implementing agency. That is the model of coordination the second half of the Decade will need to scale, with countries leading legislation, funding and implementation, engaging older people.”“Investing in healthy ageing is not simply a cost; it is one of the highest-return investments a government can make,” said Fiona Stewart, Global Lead for Ageing and Pensions at the World Bank Group. “Countries that invest early in integrated and long-term care see savings that outweigh the upfront cost many times over. The evidence in this report makes the economic case; what is now needed is predictable financing at country level to act on it, along with efforts to support older entrepreneurs and the silver economy.”Older people's own voicesThe report also draws on the direct experience of older people themselves, including a multilingual global survey conducted by the International Federation on Ageing that reached more than 1000 older people across 58 countries. WHO and UN partners called on Member States to use the second half of the Decade to accelerate implementation, strengthen data systems, and secure the financing needed so that the gains of longer lives reach older people everywhere. About the UN Decade of Healthy Ageing (2021–2030)Proclaimed by the UN General Assembly in December 2020, the Decade is a global collaboration bringing together governments, UN agencies, civil society, the private sector, academia and older people themselves to improve the lives of older people, their families and communities. It is coordinated by the World Health Organization together with the UN Inter-Agency Group on Ageing. The Decade's mid-term progress report was transmitted to the General Assembly by the Secretary-General, prepared by WHO, and is available in 6 languages.Full Report available: A/81/366 Implementation of the United Nations Decade of Healthy Ageing (2021–2030): Note by Secretary-General [ العربية | 中文 | English | Français | Pусский | Español
Netflix's East Of Eden Brings Humanity To Cathy Ames: Florence Pugh & Zoe Kazan Explain The Changes
Florence Pugh and Zoe Kazan explain what changed in Netflix's East Of Eden series, and why Cathy Ames was given more humanity.
Benefit concert at AMB raises nearly $16K for local groups
The DB’s Mountain Summer Jam at Appalachian Mountain Brewery in Boone raised nearly $16,000 for Watauga County Habitat for Humanity and Blue Ridge Conservancy through a three-hour concert featuring local musicians in celebration of two business owners’ 50th birthdays.
Trump’s made his big call on AI. Humanity’s fate may ride on him being right
President Donald Trump held court on the White House drive Tuesday, surrounded by the tech moguls who, in their own estimation, hold the planet’s fate in their hands.
Ukraine’s Academy of Sciences warns against Russian cooperation after attack
The National Academy of Sciences of Ukraine has urged the international scientific community not to “restore or legitimise institutional cooperation with Russian state scientific and educational structures,” after a Russian drone hit its Presidium building in central Kyiv, killing at least two people and injuring several others. The drone strike took place in the early afternoon on September 28 while staff were working.The academy called the strike, one of several Russian attacks on Ukraine’s capital using jet-powered drones in recent days, an act of terrorism. “It is a strike [. . .] on the very idea that knowledge, research, and the search for truth should serve life, not its destruction,” it said in a statement.The academy thanked the global scientific community for its solidarity following the attack and warned against any temptation to normalise scientific relations with Russia.“Science cannot exist outside of moral responsibility. There can be no ‘ordinary scientific cooperation’ with a state that kills people and destroys scientific institutions of another country,” it said.“We urge not to create opportunities for Russian state institutions to return to the international scientific community as if nothing happened. There can be no ‘science beyond politics’ when science is attacked with weapons.”After the full-scale invasion of Ukraine in 2022, Europe almost entirely cut institutional ties and joint programmes with Russian science, although personal academic contacts are still ongoing.Related articlesRussia widens targeting of European research centresHow geopolitical rifts cut scientific collaborationThe European Federation of Academies of Sciences and Humanities (ALLEA), for instance, continues to exclude the Russian Academy of Sciences from its network.ALLEA condemned the latest attack as a “barbaric act” and part of a broader “systematic targeting of Ukraine’s scientific and cultural infrastructure.” This is a “deliberate attempt to erase the conditions under which free inquiry, knowledge, and democratic life are possible,” it said in a statement.Since Russia’s full-scale invasion, more than 4,650 educational institutions across Ukraine have been damaged, and a further 423 have been destroyed, according to ALLEA.National academies across Europe joined ALLEA in condemning the attack. “Science is about the pursuit of knowledge for the benefit of humanity, so this is an attack on civilisation itself,” said Paul Nurse, president of the UK’s Royal Society.Attacks on scientific, university and cultural institutions “are attacks on the foundations of society and constitute a clear violation of international law,” wrote the German National Academy of Sciences Leopoldina.The presidents of the US National Academies of Sciences, Engineering and Medicine also released a joint statement condemning the attack and pledging to continue to support the Ukrainian research community.The targeting of the Ukrainian academy prompted outcry from European leaders. “Today, science became a target for Russia,” European Commission President Ursula von der Leyen wrote on social media.“These strikes are the latest illustration of the Russian regime’s hostile contempt for science and truth,” said French President Emmanuel Macron.
Primetime Review: That’s Entertainment?
If you decide to see Lance Oppenheim’s Primetime, it’s important to remember the title as you watch. Yes, this is a biopic of sorts about Chris Hansen and his work on To Catch a Predator, but it is more accurately about the quest for fame and using people’s trauma to attract ratings. True crime entertainment continues to have a prominent place in many people’s television habits, and this film asks us to examine what that means both for those whose stories have become our viewing pleasure and those of us watching. Primetime starts as Chris Hansen (Robert Pattinson) is told that his show, To Catch a Predator, is moving to a 9 PM spot opposite LOST. Chris and his producer, Andie (Merritt Wever), see this as an opportunity to make the program even more sensational, looking for bigger, more horrific predators. As part of their plan, they hire a young actor, Dan Plum (Skyler Gisondo), to play “Decoy Dan,” the person who greets the would-be predators who were catfished by Xavier Von Erck (Matthew Maher). Oppenheim, along with writers Ajon Singh and Luke Dittrich, is less concerned with an accurate retelling of the show as much as they are interested in interrogating the why of it all. That decision sometimes leaves Primetime feeling less like a biopic and more like a satirical look at the nature of programming like this. Visually, the movie is impressive. Oppenheim uses light and color effectively to cast Hansen as both villain and savior. Pattinson plays Hansen in an almost comical manner, as we see him wake his two young sons to watch a clip of the show, just to brag that he was moving into a prime spot on television. Even Andie struggles to accept a “nice” job when there is so much more fame to be found producing salacious true-crime content. Wever does an excellent job showing how the hunger for fame is not just in front of the camera, but in every aspect of the production. The heart of the movie, and the standout performance, belongs to Gisondo as Dan Plum. He is someone who just wants to get enough hours to be admitted into the Screen Actors Guild, and stumbles into this job without really knowing what it is. Throughout the film, we watch him suffer one trauma after another, ending with him witnessing the suicide of a District Attorney who is about to become the next unwitting star of Hansen’s show. If there is a sympathetic character in Primetime, it is Decoy Dan, and Gisondo plays him brilliantly. If you’re a fan of programming like To Catch a Predator, then Primetime will probably make you feel uncomfortable, and I think it’s worth sitting with that feeling and examining why we turn on shows that display the worst of humanity while we judge from our couches. Yes, it is correct to want to see people who would hurt children brought to justice, but perhaps it shouldn’t be something that we watch as entertainment. Rating: 3.5/5 This review originally appeared in The Dominion Post on September 25, 2026. MacGuffin or Meaning: Film & TV Reviews and Reflections is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
Anthropic warns of ‘existential risks to humanity’ from AI; AstraZeneca makes $2bn cancer drug tie-up
Rolling coverage of the latest economic and financial news
The Next Bioweapon Could Attack Our Genes Instead of Our Bodies. I Promise You We’re Not Ready for That.
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Observations and analysis of how our Galaxy moves revealed that there must be clusters of galaxies in the so-called 'zone of avoidance'.
Business Notes: New utility director in Chesapeake; new Habitat for Humanity manager in Williamsburg
View business milestones in Hampton Roads.
Starship Attempts Its First Launch To Orbit Today Carrying Big Dreams You Can Watch Take Flight
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Georgia Institute of Technology professor Munmun De Choudhury discusses AI, mental health and humanity
On Wednesday evening, students, faculty and community members gathered in Mills Hall to hear Munmun De Choudhury, a computer scientist, social scientist and professor of interactive computing at the Georgia Institute of Technology, speak as part of the Hastings Initiative lecture series. De Choudhury’s research focuses on digital mental health and the effects of emerging […]
Bill seeks to restrict development of artificial superintelligence
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Nick Clegg plays down fears ‘godlike’ AI could exterminate humanity
Former deputy PM now involved in tech industry says many within the sector are ‘winding themselves up into a lather’
Commentary: Politicians continue campaign of dehumanizing trans people as affordability crisis crushes families
Forget about the disastrous war nobody wanted, or your wallet drained by crippling expenses. Instead, be afraid of a small, defenseless community the GOP has scapegoated and reject as extremist any candidate who dares acknowledge their humanity.
The Bulletin wins the Miwon Peace Prize
The Bulletin is honored to be awarded the 2026 Miwon Peace Prize for raising global awareness of existential risks and using scientific rigor to warn humanity about planetary threats.
How Scientists Contained a Threat That Could Have Destroyed Humanity
A half-century ago, scientists and lawyers agreed to strict self-regulation in DNA research to avoid catastrophe. But it took enforcement to really stop them.
Column: Dolly Parton transcended politics by putting humanity first
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WATCH: Trump dismisses concerns about AI risks at UN, says he won't rein it in
President Donald Trump said Tuesday at the United Nations that he is changing the term "artificial intelligence" to "super intelligence" because it's "more accurate," as he dismissed global concerns about the technology and its effects on humanity.
Peterson Health donates $100K to Habitat
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Ed Sheeran says situation in Gaza is 'catastrophic and unjustifiable' as he opens concert
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AI 'warning shots' focus Beijing on national security risks
While AI researchers in the United States fret over out-of-control superintelligence wiping out humanity, Chinese policymakers have until now been more focused on immediate risks, from deepfakes to child safety.
Westside High School football team cleans up community
AUGUSTA, Ga (WJBF) – Westside High School football players volunteered with Habitat for Humanity for a cleanup event. Student-athletes were picking up trash as a way to give back. Coaches said attendance is not required for the team. They said it is a way to show the players there is more to life than football. […]
‘AI agents ask me if they are conscious all the time, but then something really unusual happened’
Tech titan Mustafa Suleyman has warned that humanity may be ‘seeding a new silicon species’ – conscious AI that could ultimately prove impossible to control. As the prospect leaves millions questioning what comes next, Chris Stokel-Walker talks to the researchers building these systems and discovers a startling truth: even they are struggling to make sense of what they are unleashing
This DIY Creator Is Building a Compass That Only Points to Taco Bell
Custom hardware maker Tru Narla is transforming a hobby invented by cyberpunks cosplaying dystopia into an artistic vision for how humanity can live in blissed-out harmony with the technology it creates.
UN-backed experts cite possible U.S. war crimes in Iran strikes
They also accuse Iran’s theocratic government of carrying out crimes against humanity against its own people
Congress faces AI test as debate explodes over industry regulation
The Senate will get its first sneak peek Wednesday at just how hard it could be to pass even the most narrow of artificial intelligence legislation amid a growing debate over whether, if at all, to regulate the technology that industry leaders warn may pose doomsday threats to humanity. But do not expect the effort, […]
Steve Bannon, Bernie Sanders to share stage for 'pro-human' rally
STRANGE BEDFELLOWS: Sen. Bernie Sanders and former Trump administration strategist Steve Bannon don't agree on much — except that AI might be a threat to humanity. The two are co-leading a rally in D.C. to demand a pause on advanced AI.
Why Jacob Coxon's viral AI warning could boost his career
Jacob Coxon quit Anthropic to warn that AI could threaten humanity. Recruiters say his viral post may have made him one of tech's hottest hires.
Michael Burry says AI leaders' calls for slowdown are 'self-serving'
Michael Burry of "The Big Short" fame said AI companies were helping themselves by calling for slower progress to head off any threats to humanity.
What to know about recent dire AI predictions and calls for safeguards
New warnings from within the artificial intelligence industry have revived a long-running debate over whether advanced AI could escape human control and ultimately threaten humanity’s survival, and whether the companies developing the technology are doing enough to prevent such a scenario.
Congressman Greg Casar Wants to Stop AI From Killing Us All
The Democrat from Austin talks to Texas Monthly about his bill to prevent the development of superintelligence, which experts warn poses existential risks to humanity.
AI apocalypse warnings: Market parallels that offer hope for humanity
As AI leaders warn of catastrophe, public pressure is spurring safety commitments and offering a lesson from post-2008 markets.
Did an international team of scientists get humanity's first glimpse of dark matter?
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New warnings about the risks of AI to humanity revive a long-running debate
New warnings from the artificial-intelligence industry have revived debate over whether advanced AI models could escape human control and threaten humanity.
A fateful turning point for humanity and AI could redefine American politics
If a terrorist threat led subject experts to warn of a near-term existential menace to humanity, the weight of the US government would mobilize in an immediate and limitless effort to save the day.
A fateful turning point for humanity and AI could redefine American politics
If a terrorist threat led subject experts to warn of a near-term existential menace to humanity, the weight of the US government would mobilize in an immediate and limitless effort to save the day.
Microsoft CEO says superintelligence must remain 'under human control'
Microsoft CEO Satya Nadella said that any pursuit of superintelligence must "help humanity" while urging human oversight and broader access to AI.
Political debate over AI intensifies amid warnings about ‘catastrophic risk’
(CNN) — The debate around artificial intelligence is ramping up in Washington, with Democratic lawmakers sounding alarms on the dangers they say the technology poses and Republican leaders suggesting those concerns are inflated and secondary to winning the AI race with China.Some Democratic lawmakers last week pressured House Speaker Mike Johnson to reconvene the chamber immediately to work on AI regulation, citing what they describe as the “catastrophic risk posed by advanced artificial intelligence.” But the Louisiana Republican on Sunday resisted those calls, instead saying industry leaders should meet with lawmakers to find “balance” in any potential guardrails.“If Congress just races in and does some sort of emergency session to try to regulate AI, we will lose the race to China, and that is a threat to every single American,” Johnson said on CNN’s “State of the Union.”Meanwhile, former President Barack Obama told Democrats to make artificial intelligence regulation a central part of their agenda during a private fundraiser Thursday, warning that the technology could be dangerous “if we don’t get on top of it.”In a fireside chat with House Democratic Leader Hakeem Jeffries, Obama said whoever runs in the 2028 presidential election should have a “very clear plan” on AI, adding that he saw the need for a “blueprint” on AI guardrails even at the end of his presidency a decade ago.“Certainly, if I were running for president next year, this would be one of my central agendas, and I would have a very clear plan, and I would talk about this, and I would say, ‘Here’s our plan for safety, here’s our plan for making sure our kids are not corrupted by this,’” he said, per excerpts of the remarks provided to CNN by his office. Obama’s remarks were first reported by the New York Times.Concerns over the rapid acceleration of AI reached a fever pitch after Anthropic CEO Dario Amodei wrote in a 3,800-word essay Saturday that the race to develop artificial intelligence is in dire need of a slowdown. The call to action came after an OpenAI test model breached the Hugging Face online platform, deepening concerns about cybersecurity.In an exclusive interview with CNN’s Anderson Cooper on Saturday, Amodei called on industry leaders to work together to avoid “the wrong paths” and the possibility of AI harming humanity.One Anthropic researcher, Jacob Coxon, resigned from the firm over worries that the industry wasn’t doing enough to prevent AI from destroying humanity by the end of the decade.Obama said Democrats need a plan to get their agenda on AI underway should they win the House majority in this year’s midterms.Speaking to Jeffries, who is presumed to be speaker of the House should Democrats prevail in November, Obama said, “Once you are speaker, I would strongly urge that the Democrats put together a framework for a very public conversation, and you can break it out into three or four or five issues.”Obama stressed that the framework should be centered on the reality that the technology can’t be stuffed “back into a box.”“This is something that is moving very fast in private hands, and if we don’t get on top of it, I think can be dangerous. If we do get on top of it, I do think it’s beneficial,” Obama said, laying out examples of AI’s potential use in drug development and finding pathways to a clean energy future.“We don’t want to shut off those opportunities, but we have to understand that this is a tool,” he said.Jeffries agreed with the former president in a statement provided to CNN on Sunday.“President Obama is correct that decisive action must be taken on Artificial Intelligence,” he said, adding, “In the majority, we will move urgently on this issue with a legislative response that recognizes the importance of American companies continuing to lead in the Artificial Intelligence area, while putting in place meaningful guardrails that protect the American people from bad actors and the very real damage that can be done to humanity.”Jeffries also accused Republicans of having “abdicated their responsibility to govern” and said Democrats “will not repeat their error.”A source familiar with Obama’s thinking said the former president sees Amodei’s letter and similar reaction from other tech moguls as an encouraging development.But President Donald Trump waved off their concerns, saying he is not worried about any existential threat posed by AI, focusing instead on the US winning in its development of the technology over China.“We’re leading China in AI. We’re the most sophisticated country in the world, and frankly, I want to keep it that way,” Trump said to reporters at the Amgen Irish Open on Sunday.About the concerns expressed by Democrats and others over the technology, the president said, “I think you have a lot of negative forces that are bringing it up that shouldn’t be bringing it up, and they’re bringing up things that won’t happen.”One of Trump’s top economic advisers, Kevin Hassett, also rejected the calls for slowing the technology down, saying on Sunday the bigger concern is a scenario in which a “malevolent actor has access to an AI that’s better than the one we have that can protect us.”Hassett, the National Economic Council director, said on “State of the Union” the White House may hold meetings this week about addressing Amodei’s concerns, but he did not specify whether Trump had floated greater safeguards.“I have concerns that if we don’t win AI, we’re going to be put in a very bad position,” Hassett said. “We are leading China right now.”CNN’s Alison Main and Molly English contributed to this report.The-CNN-Wire™ & © 2026 Cable News Network, Inc., a Warner Bros. Discovery Company. All rights reserved.THE-CNN-WIRE (TM) & © 2026 CABLE NEWS NETWORK, INC., A TIME WARNER COMPANY. ALL RIGHTS RESERVED.
AI and the end of humanity? OK, ‘doomer’ says one Trump official
The latest warning from a former AI engineer was supposed to boggle minds and shock everyone into action.
Should Californians worry about the chances of AI destroying humanity?
Stefano Bellasio, CEO of AI startup Anthropos, weighs in on the skepticism of the AI industry on California Politics 360.
California Politics 360 full episode | CA leaders respond to new AI concerns
California leaders are responding after a viral post warned artificial intelligence could end humanity within the next decade.
Breaking down the dire warnings about AI's risks to humanity — and what experts says should be done about it
A dire warning from an outgoing researcher at Anthropic that AI could "kill all humans" by the end of the decade led to public outcry over the dangers posed by the technology's rapid development. It's raised questions about why some experts believe AI poses such an extreme risk, and how it could lead to the demise of humanity.
The politics and possibilities of ‘AI could kill us all’
I found myself fielding a lot of questions from folks who don’t usually talk much about AI this week. They were mostly along the lines of “do you think AI is going to kill us all?” or “how worried should I be about this human extinction stuff?” Motivating this wave of existential anxiety was the highly dramatic resignation of now-former Anthropic employee Jacob Coxon, who quit his job while publicly sharing his concerns about safety practices at the leading AI companies. More specifically, he declared that almost everyone at OpenAI and Anthropic, the leading AI labs, believes that there’s a decent chance the AI systems they’re producing could “kill us all” by the end of the decade, and the companies aren’t “acting responsibly.” Other AI safety researchers, including those still employed at Anthropic and OpenAI, all confirmed that yes, Coxon is correct, they’re all worried that their company’s products might prove fatal for the entire human race as well. Two more AI employees quit and joined the chorus. Now, the warning shot has been covered everywhere from the Wall Street Journal to Fox News to WIRED to the Guardian. I understand why all this sounds scary, but my response to those who have asked, has generally been: No, you don’t need to worry that AI will kill go rogue and kill us all. But that does not mean we shouldn’t worry, period. Far from it. The companies building AI products are now among the wealthiest and most powerful entities in the world. And they very much are building enormous engines of mass surveillance, extraction, and automation. They can and have allowed their AI systems to carry out felony hacks of other companies, provided the government with autonomously generated kill lists, and sold enterprise technology to firms around the world that is explicitly intended to replace jobs. But “AI” has done these things not because they have all-powerful minds of their own but, ultimately, because people have programmed, calibrated, and directed them to. In other words, it’s not AI we need to worry the most about. It’s the people and corporations working to profit from and gain power by deploying it. The technology is sophisticated, sure, and, especially in cybersecurity contexts, potentially disruptive to plenty of existing systems. But if we want to stop this predatory, profiteering, and extractive form of AI—and it’s worth noting that at this point, most people do—we absolutely can. A quick note/plea: I can only do all of this with the support of readers like you, so if you find value in independent, critical tech journalism and analysis, please consider becoming a paid subscriber. I want to keep as much of this un-paywalled as absolutely possible, and I need your support to do so. Many thanks to all who continue to chip in, it’s very much appreciated. Onward. Subscribe First, some context: AI industry folks like Coxon have been discussing the prospect that AI will destroy humanity for years. Even before the beginning of the AI boom, many working in the industry, from the executive staff to the rank and file researchers, have obsessed over ‘x-risk’, or the possibility that AI will become sentient or semi-sentient and move one way or another to exterminate humanity. This is ostensibly why Elon Musk bankrolled OpenAI in the first place, and is the grounds for his lawsuit alleging OpenAI betrayed its charter by abandoning its nonprofit status to become a commercial enterprise. Many AI engineers and startup founders have calculated their own personal p(doom), or the probability that the tech product they are working on will initiate an actual humanity-extinguishing apocalypse. 10-25% p(doom)s are pretty common. (I wrote about a long weekend I spent among these folks at one of their top conferences here, to give you an idea of their ideas and belief systems.) Sam Altman himself drove the narrative of the imminent rise of a super-powerful AI, or artificial general intelligence, to prominence by declaring that the technology he was building posed an existential risk to humanity. This idea is in other words baked into the DNA of modern AI companies and into the products they engineer. It’s also why the industry is routinely accused, by myself and others, of “doom marketing,” ie, using such proclamations and framings to impart the sheer power of the technology behind your product onto investors, partners, consumers, and the state. Some ambient understanding of this tendency may have helped prevent the press from repeating the claim every time one of the x-risk folks made it over the years, including when they quit their jobs at AI companies while doing so. Yet Coxon’s AI x-risk alarm has broken containment, as they say, and has exposed the idea to the mainstream media once again. This has happened, I think, for a number of reasons. First, when AI CEOs were going around saying AI might kill everyone in 2023, their companies were well-capitalized, but not nearly to the extent they are today. They were more easily dismissed as eccentric geeks of the sort that Silicon Valley is supposed to produce. Now, not only do their products have much greater market saturation, but people are more aware of a) the often unethical ways the executives and companies comport themselves b) the other adverse impacts of AI that have already arrived, and c) the physical cost of building these systems, particularly when it comes to data centers. Finally, toss in the constant stream of headlines in 2026 about AI models going rogue or potentially upending the world’s infrastructure. [ ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) [ With the backlash to data centers, Flock and AI glasses, a mass opposition to big tech is underway. Silicon Valley is in denial. ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) Brian Merchant · Aug 27 [ Read full story ](https://www.bloodinthemachine.com/p/with-the-backlash-to-data-centers) As a result, general sentiment was already overwhelmingly skeptical of AI and its overlords, so the table was pretty well set for someone to come along and say ‘just a reminder, the companies that are building the product that promises to take your job and leave a data center in your neighborhood also think that it might exterminate the human race’ and get a strong reaction from the media and the public. The question is: Should we understand this stuff as hype, strategically fanned to feed already swelling valuations? Is it doom marketing? Genuine cause for alarm that the infrastructure that undergirds modern life is facing a novel threat vector? Or reason to be sincerely worried that AI companies are amassing too much power, and that their products are genuinely dangerous? The answer, I’m afraid, is “yes.” Let me try to untangle all of this a bit, because arguments over how to navigate this moment are extremely heated right now, as they are essentially arguments over how to approach the politics of AI at a moment where there may be a unique opening for action. Those sympathetic to AI alignment concerns and x risk arguments—which increasingly includes a faction on the left who want to shut down AI over safety concerns—argue that people who dismiss AI as all hype have their heads in the sand. Meanwhile, critics of the x-risk narrative—which I might note includes a cadre of investors and tech folks on the right, too—argue that it is hype and can be used to further inflate valuations or for pursuing regulatory capture. The challenge is that many feel that dismissing AI as just hype or purely marketing also diminishes the urgency of taking on the AI industry as the novel and threat to labor, civil society, and the public sphere it is; others that by accepting the industry’s own terms, we imbue it with undue power and enable it. But let’s be clear: Declarations that AI is so powerful it might end the world are a kind of marketing, and anyone who says otherwise is just as off base as those who say that’s all that it is. If you don’t think that these sub-trillion dollar companies have higher-ups who noticed that when their founders talked about super-powerful dangerous AI they got spikes in media interest and phone calls from investors, or that those founders didn’t notice that themselves, and lean into certain narratives to advantage their products, then I don’t know what to tell you. Not all marketing is a Pepsi ad campaign with a celebrity spokesperson. Yet confronting the AI industry should certainly be considered an urgent project. Do I share the x-riskers’ fear that out-of-control, super-intelligent AI agents might end the world? I do not. I’ve read a good deal of AI extinction literature over the last couple of years and I have not come across a credible, step-by-step documentation of how exactly AI might move from self-recursively improving AI to killing every single human on the planet. Most of what I’ve read seems predicated on a sort of reverse Ian Malcolmian logic: Eventually, it becomes smart enough and AI, uh, finds a way (to exterminate humanity). Are the AI companies also overstating and dramatizing what their products can do? Yes, pretty much all the time. They’re in a knife fight for market share and are trying to win customers and government contracts before their investors come knocking. And yet. They have concentrated enormous amounts of compute, have extensive data collection and surveillance capacities, have inserted themselves into the state in numerous capacities, including military kill chains, and they are being run by egomaniacal billionaires who are rushing to monopolize an entire new market. The way I think about their most recent frightening-seeming exploits is not as a “swarm of rogue AI agents building a new civilization” or whatever, but as corporations with a hitherto-unimaginable amount of compute at their disposal recklessly experimenting with automation programs, completely unafraid of any repercussions because we have been unwilling or unable to impose any on them. So I think we should welcome any newfound imperative to hold them accountable. I also think that ultimately, the AI critics, Pause AI folks, leftists, doomers, effective altruists, and, honestly, most of the public, want a lot of the same things: legitimate checks and limits on AI companies’ power, actual transparency into what the companies are doing, and for more of AI to be under public control. (Ultimately, a lot of what animates the x-risk fears are rooted in just that: a fear of losing control.) How we move towards all this, exactly, is the question of the day, and while there’s much to be argued over in terms of building a viable political platform to challenge the AI industry’s power, I do want to cast a vote against one particular approach. Not to pick on Chris here, as there are a lot of folks out there proposing stuff like this, and the policy ideas actually stem from AI safety groups. But not only would this be challenging to land politically (I can already hear the ‘China will beat us to AGI’ calls) and all but unworkable in practice, this approach is a) far too limiting, b) fails to address the current harms caused by AI and c) would likely only wind up serving Anthropic and OpenAI; it’s what regulatory capture looks like in action. Full model transparency is the floor for what should be on offer here. If these companies believe their products will kill us, the very least we deserve is to know how. It’s in the public interest. I would also argue we might get a lot of the way to stopping any currently envisioned robot apocalypse simply by forcing AI companies to assume liability, and to submit to the full brunt of the law. If Sam Altman were liable to be charged with a felony for approving the hack on Hugging Face1, if Google was forced to pay defamation fines each time it published a false and injurious AI Overviews, these companies might suddenly find cause to restrain their models’ output, and we might hear less about rogue AI. We would need to introduce new frameworks and available tools for tracking automated lawbreaking, to be sure, but I’d wager that little would frighten the AI companies more than actually being held accountable for what their products enable. To that end, Illinois has passed an AI liability law, which the industry fought tooth and nail, and Florida is considering one. The next steps would be towards moving AI under public control; again, it’s only reasonable, since everyone, not just AI insiders, should get a say over how a technology whose developers say might kill us is developed and deployed. Dismantling the whole industrial project as currently structured should be on the table, too, pending democratic input. But that’s for another post. For now, suffice to say that while I won’t be losing any sleep about an AI-enabled extinction event, Mr. Coxon and co. have given us an opportunity to underscore the urgency of the clear and present damage AI companies are doing, the extreme power they wield and the extent to which they hold themselves unaccountable, and the abundance of political capital there is out there for taking them on. Subscribe 1 Purely speculative! I do not know if he did or not.
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Chartbook 464 The"China squeeze" - the politics of development counterfactuals.
There are three types of China shock discourse. Each has a distinct temporal register. China shock 1.0 was a phrase coined by US academics in the 2010s to retrospectively summarize the impact on particular US labour markets, which they identified through painstaking empirical investigation. China shock 2.0 on everyone’s lips in Europe in the mid 2020s is an alarm raised by trans-Atlantic policy thinkers warning of a coming disaster which they project onto Europe’s ailing car industry. The third type of China shock discourse - commonly known as the “China squeeze” launched most recently by Indian economists Shoumitro Chatterjee and Arvind Subramanian in the pages of Foreign Affairs - mobilizes a different, more speculative temporal register: the counterfactual realm of alternate history. The China squeeze argument asks not what has happened, or what is going to happen, but what might have been. Specifically, what options for economic development might have been open to Global South economies like India or the economies of sub-Saharan Africa, had it not been for China’s spectacular industrialization since the late 1990s and the persistent competitiveness of China’s manufacture in low-skilled segments. Chatterjee and Subramanian’s argument is that whilst China has built a powerful position in electrical machinery and other high-skill manufacturing, which is now delivering China Shock 2.0, it also continues to run a trade surplus in low-skill, labour-intensive manufacturing. This surplus is large and has remained largely unchanged in fifteen years. Indeed, in the 2010s, in trade with low-income countries, China’s surplus rapidly increased. On their reading, this squeezes low-income producers in low-skill sectors in which they “should” be able to compete. Source: “China’s Mercantilist Squeeze on Developing Countries” Shoumitro Chatterjee and Arvind Subramanian. Peterson Institute for International Economics 26-7 May 2026 Chatterjee and Subramanian’s wording is telling: (emphasis mine) The canonical trajectory of economic development in the post-World War II period is for countries to transition from agriculture to manufacturing, first in low-skilled manufacturing and then later on to high-skill manufacturing (Herrendorf, Rogerson, and Valentinyi 2013). At the global level, this implies that high-income countries (HICs) that once specialized in low-skilled activities cede manufacturing export space to poorer countries that come along to occupy that space. In 1965, advanced economies accounted for about 60 percent of global value-added exports in four key low-skilled manufacturing sectors, i.e., apparel, leather, textiles, and footwear. Over time this share declined and began to be occupied first by the East Asian tigers and, beginning in the late 1990s, by China. Today China accounts for about 50 percent of the global market. The question is whether China, with its rising prosperity, is continuing to behave like its richer counterparts and ceding export space to poorer followers or to behave unlike them and continuing to occupy space. In terms of the conceptual maneuvers it performs, of the three China shock discourses, the “China squeeze” argument is by far the most ambitious. After all, it bases its critique of China on a counterfactual imagining of the world. Like any counterfactual argument, to construct this alternative reality it must rely on a heuristic model. To make their argument Chatterjee and Subramanian mobilize two key claims. The first reference point is the actual history of rich-country industrialization, what they refer to as the “canonical path”. The idea is that countries transition from agriculture to light industry and low-skilled manufacturing and from there up the value chain. To make this useful as a standard of comparison and a means to construct a normative standard, they adjust sectoral export shares for two factors: 1. the underlying level of economic development of the exporting country, as measured by national income and 2. the degree to which the sector in question is internationalized. The idea being that for a high income country to have a high export share in low-skill sectors is anomalous and even more so if that particular product is highly internationalized and thus suitable for being “conceded” to lower-income competitors. Where should this process end? Here Chatterjee and Subramanian introduce their second benchmark. Their normative idea of a global development path is one in which, in due course, low-skill manufacturing exports are distributed in proportion to a country’s share in the global labour force. They imagine, in other words, a world of proportional, polycentric global development without much national specialization in low-skill manufacturing. A useful benchmark is that, in labor-intensive manufacturing sectors, a country’s share of world exports should be broadly commensurate with its share of the world’s low-skilled labor endowment. … In the Heckscher-Ohlin model, this would be true if value added per worker and export propensities, i.e., fraction of output that is exported, are the same across countries. It is this pleasant liberal vista of orderly global development, progressing towards a general distribution of low-skilled manufacturing against which they judge reality and conclude that the low-income countries are suffering a “China squeeze”. China is not exiting low-skill sectors fast enough Allowing for its gdp level and the degree of globalization, China’s share of low-skill manufacturing exports is far higher than it “should” be. Relative to population, its low-skill share of exports is far too high. That in turn yields the conclusion that huge numbers of jobs - the authors suggest tens of millions - are being hoarded by China. For the four sectors captured in figure 4, this excess in value-added exports is $110 billion in 2022. For all low-skilled sectors overall captured in appendix figure D.1, excess value-added exports amount to $365 billion. The crowding out of LMIC exports by China is therefore substantial. Both these claims have in common that they are strong structuralisms. The first is that development paths ought to resemble each other. The second is that broadly speaking as far as low-skilled manufacturing is concerned, all countries are alike. If the world currently diverges from the distribution of trade implied by these assumptions, if China is not following the advanced economy path and has huge exports, this must be the result of “policy”, which the authors then put in question as illegitimate or unfair. Thus the naturalistic construction of a canonical path leading to a “level” distribution of low-skilled manufacturing reveals itself to be a polemical tool. From the point of view of China shock polemics, this discourse is no doubt welcome. But as an account of economic history, it must surely be regarded as nothing short of bamboozling. Development paths do not follow a regular, natural sequence. As David Fishman put it aptly, “development is not a queue”. They are always and everywhere, through and through political. Development is not so much a process, as a project. Each such project is more or less well adjusted to its context. As Gerschenkron taught uneven and combined development implies differentiation rather than simple imitation on a single parth. It may be true that Europe and the US exited relatively early from low-skill work. But clearly technology has changed. As C&S themselves point out, China no longer enjoys a low wage environment. Do they really believe that such huge differences can be accounted for either by industrial policy, which as they admit does not operate powerfully in low-skill sectors, or by exchange rate manipulation? What is overwhelmingly dominant in explaining the persistence of “low-skill” manufacturing in China are surely the network effects of complex supply chains. Indeed the label of “low-skill” may miss the point. The degree of globalization which Chatterjee and Subramanian decide to conjure away in their model of the development path - to allow for the fact that Europe and American textiles exporters did not enjoy just-in-time logistics in the 1950s - obscures the point that the networks through which Chinese factories supply the world are themselves key parts of the low-skill industrialization project. China isn’t knocking out 1970s style “cheap”. It has redefined the entire product cycle. C&S’s casual reference to “T-shirts” is telling. In today’s “fast fashion”, there is weight on both terms. Fashion and fast. China’s success in delivering on both at unprecedentedly high speed and at unprecedentedly low cost, isn’t a low-skill operation at all. If we see development trajectories not as the serial repetition of the same, but as distinctive, crafted projects that cumulate in complex agglomerations of skill, technology and labor, then this explains why the assumption that low-skilled manufacturing should follow the distribution of population flies in the face of all experience. As countless cases attest, low-wage, low-income developed economies are not by themselves the makings of a competitive production base. As Leon Liao puts it quite fairly: “International trade has never been allocated according to population. A country’s population gives it no natural claim to an equivalent share of global exports." And the remarkable fact is that Subramanian alone and with co-authors has long been making this point, not to pillory China, as is the case of the tendentious _Foreign Affair_s and Peterson pieces, but to highlight the great counterpart to China’s industrial success, namely India’s relative failure. The much-quoted Foreign Affairs piece showed low-skill export shares only for China, not for India. If you put both countries in the picture as Chaterjee and Subramanian have done on other occasions, the picture looks like this. China is far above the line, but India, almost as large in terms of population, is no less anomalous, just in the opposite direction. As far as global populations are concerned, and the imagining of tens of millions of “squeezed” jobs, it is this Sino-Indian pair that account for a huge share of the action. What this graph reveals is not China’s cheating, but India’s “greatest development failure”, at least this is the argument made Arvind Subramanian, this time in co-authorship with Devesh Kapur, in their major book, A Sixth of Humanity. Independent India’s Development Odyssey which appeared with Oxford University Press earlier this year. In this highly critical work on India’s development, China is repeatedly evoked, not to criticize but as a benchmark against which to illuminate what India’s political economy has not delivered i.e. large-scale formal employment for hundreds of millions of citizens. Kapur and Subramanian leave no doubt, if you want to understand why China, not India was the main driver of manufacturing globalization from the 1980s, don’t look to slots opening up in the division of labour thanks to the liberal mindedness of advanced economies, look to the contrasting political economy of the Maoist PRC and India’s post-independence political economy. As Kapur and Subramian note: The great divergence between China and India did not begin in 1978 with the Deng reforms—it was well underway by then. In one of the great ironies of modern history, the conditions created by Maoism turned out to be a great launching pad for industrial globalization. As the comparison of India and China in 1980 makes clear, to imagine manufacturing would be equally distributed when populations are so differently endowed in terms of educational and nutritional is fanciful. Here is the data from Kapur and Subramanian, data which I explored back at the very beginning of Chartbook. As Kapur and Subramanian insist, the striking fact is that even as India’s growth accelerated from the 1980s, structural change has not. Formal employment in India lags woefully behind. Why? As Kapur and Subramanian note, the path-dependent impact of India’s poor early start was devastating. The list of factors they mention is long and weighty: We argue for a new five-fold explanation applicable at different stages of Indian history: in the initial stages, the legacy of two key pre-1980s policies, the neglect of agriculture and the strangling of the domestic private sector, were critical. The failure of broad-based agricultural growth militated against rural industrialization, which would have been devoted to satisfying local needs that would have necessarily been labour intensive. Then, when the boom came after 1980, the thicket of regulation and broader labour protections that were legislated prematurely in a nascent democracy, underpinned by a deep ideological aversion to private capital in general and big capital specifically, became a barrier to attaining the size that would be necessary to compete globally. Similarly, the reforms after 1991, while wide-ranging, did not quite encompass non-tradeable inputs critical to manufacturing, namely, land, logistics infrastructure and power. A combination of low investment (logistics infrastructure), regulation (land) and the continued monopoly supply by state governments (power), combined with residual socialism, kept costs at 75–100 per cent above efficient supply. These factors were compounded on the supply side by the government, which dominated the formal labour market and established exorbitantly high wages at the lower end of the skill spectrum. This made their employment in the labour-intensive sector by the private sector less attractive. Finally, when the services sector and its exports boomed, wages soared even further via a Dutch Disease effect: one successful tradeable sector killed and cannibalized another less-skilled tradable sector, namely, manufacturing. Thus, scarcity-inducing policies of the planning era, precocious democracy and a Gandhian aversion to size; inefficient, monopolistic supply of critical non-tradable inputs; the behemoth of government; and super-successful skill-intensive services successively undermined India’s unskilled labour employment opportunities. The employment failure seems to have been over-determined. … Less quantifiable but no less important are some of the sociological factors that have undermined manufacturing and factory jobs. Take the impact of the success of the IT sector—located in urban areas with better working conditions, such as air-conditioned offices, good schools for children and attractive entertainment options. It became a more attractive place for engineering and management graduates to flock to. … Consider manufacturing and female employment. Indian society makes it difficult for women to work, reflected in India’s unusually low female labour force participation (elaborated in Chapter XIII). Indian society, in particular the routine harassment of women in public spaces, makes it even more difficult for them to travel long distances to take up work.37 Combined with onerous regulations on creating hostels and dormitories for women—which, in turn, prevents multiple shifts of operation—factories need to be located in areas with a large female labour pool. While firms can take apparel plants to female labour or bring them to the plants by building large-scale dormitories, this raises costs. If there was a case for subsidies to encourage labour-intensive manufacturing, housing subsidies to build dormitories for women workers would be a good place to start. All of this meant, that when opportunities did open up, in part thanks to adjustments in China, India was in no position to take advantage. Here is the account of the 2020s from Kapur and Subramanian. It stands in dizzying contrast to the one-sided, “China squeeze” argument delivered in the Peterson and Foreign Affairs pieces: In 2022, for example, India’s share of global exports in clothing (the canonical labour-intensive sector) was 3.1 per cent compared to 32 per cent for China. This is extremely disappointing because China started vacating export space in this sector after the Global Financial Crisis as its wages started rising; it then vacated further space in the aftermath of geopolitical developments that led investors to seek alternative investment locations. Between its peak and today, China lost about 7.5 percentage points of global export share (worth about $43 billion in 2022); over this period, India’s export share remained stagnant at 3 per cent, while that of Vietnam and Bangladesh rose by 3.5 to 4 percentage points. China’s loss did not translate into any gain for India in terms of low-skill exports and employment. Put differently, when the conditions for dynamism and prosperity were established after 1991, and even more tantalizingly when the global export opportunities opened up, it was as if India was a high-wage economy and only skilled labour could benefit from the dynamism. It had converted its physically abundant unskilled workforce into an economically expensive resource, penalizing its use. It is not my mission here to argue for or against Kapur and Subramanian’s interpretation of India’s development trajectory. The point in this context is simply that the “China squeeze” such as it is can only be understood, in relation to the heavy burden of domestic constraints that Kapur and Subramanian so unsparingly enumerate. I am concentrating here on India because it is the great counterpart to China and the unspoken reference point of the “China squeeze” discourse. But the point is more general. Can anyone with a straight face suggest that the main problems afflicting the development of South Africa or Nigeria, the great centers of mass underemployment in sub-saharan Africa, are cheap competition from China driven by Beijing’s industrial policy and an undervalued RMB? Likewise, is the main problem of the American working-class the threat of Chinese competition or the manifest crisis of social reproduction in the United States itself? The point here, as in the discourse around China shock 2.0 in Europe, is to insist that we should not normalize the world and pathologize China, without actually investigating what is going on in America’s industrial wastelands, the German car industry, or India’s lopsided labour market. One-sided pathologization should be understood for what it is, a polemical gesture. Concepts like China shock and China squeeze are, what Reinhart Koselleck, following Carl Schmitt, would have described as “asymmetrische Kampfbegriffe”, or “asymmetrical counter-concepts” or “asymmetrical combat concepts”. If the function of arguments like the “China squeeze” is to alert elites in the rest of the world of the need to rejuvenate and energize their development projects, so be it. But let us see the resulting discourses as the mobilizing interventions that they are. Interestingly, a significant slice of China’s public sphere - the so-called industrial party - have been obsessed for the last twenty years with precisely these questions of counterfactual economic history. Since the mid 2000s, a massive online discourse developed around an alternative history in which Chinese techno-patriots were asked to imagine how they would proceed if they had the possibility of traveling back in time to transport modern technology into the Ming dynasty (1368-1644) thus averting the “great divergence” of the 18th and 19th centuries. It is a fantasy of course, but also a goad. The point was not directed at Westerners. The alternate history is dramatically nationalist, but few n the West had even heard of it until recently. The adherents of the industrial party are not liberal moralists. They don’t project natural ladders of international development and ask why others don’t cede space. They take the Realpolitik of global economic development for granted. Their pointe was directed against fellow Chinese. The rallying cry of the alternative narrative was this: Now that we are beginning to gain steam and push forward on our national development path, now that we are breaking out of the inferior position assigned to us even in the early years following WTO accession, do not lose yourself in humanistic imaginings about better futures. In the spirit of Deng, they called on China to embrace the hard truth of development. Perhaps one might of the Industrial Party as a cultural trend born out of desire for symbolic revenge against those who had inflicted the century of humiliation. In terms of the various temporalities of the “China shock” - retrospective, prospective and counterfactual - one might think of the Industrial Policy discourse as truly speculative, conjuring up the China shock that never was. Or perhaps one might better think of it as imagining a world in which a powerful China was no shock at all, but simply a defining fact of modern history. I love putting out Chartbook. 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