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AI as the next political divide
We have a guest post today from our friends at Focaldata, with whom we have done polling before. They have been doing a lot of work on attitudes towards AI and how this is affecting politics on both sides of the Atlantic. In this post, they explore exclusive new polling – with a whole set of fascinating charts on how voters’ views are developing and why. In particular, the authors explore why the debate is currently so much more polarised by party in the US than in the UK, to the benefit of the Democrats. Subscribe Focaldata HQ is located in Shoreditch, east London. To access the office from the Shoreditch High Street Overground station, you have to walk under the bridge at Braithwaite Street. We mention this not as a navigational aid, but because the posters above caught our eye over the summer. Since June, the area has been the centre of a fiercely contested debate around the construction of a data centre on the Truman Brewery estate on Brick Lane, less than 200 metres from our office. It was one of the first ‘US-style’ protest movements around AI data centres the country has seen, and may not be the last. These protests served as the catalyst for our forthcoming report, examining whether AI could become the next political divide on both sides of the Atlantic. We wanted to understand what was driving the emerging politics of AI and whether the dynamics at play in the US offer clues as to how the British debate will evolve. Over the last month, we polled 3,851 people across the UK and US about their views on AI. Our research found striking similarities between the two countries: for instance, both electorates are evenly split on their views towards AI development, with just over a third in favour (37% in each country), a similar number opposed, and the remainder somewhere in the middle or unsure. Statistically speaking, there is no difference in overall sentiment towards AI between the UK and US. Under the hood, demographic patterns also look largely the same in the two countries, with millennials, degree holders, full-time workers and those who describe themselves as financially comfortable more pro-AI than the rest of the country. Despite this convergence in overall attitudes, there is a striking divergence in how much of a politicised issue AI has become. In the US, attitudes are increasingly split by political affiliation and the issue has become the latest front in the seemingly interminable culture war, playing a role in the upcoming midterms. This stark political polarisation of AI has not happened in the UK – at least not yet. In what follows, we test several hypotheses for why the two countries are so far apart on a political basis. Understanding which hypothesis is correct will give us an indication of where the British dynamics go next.
Buccaneers HC on Rookie WR: 'We Really Gotta Use Him.”
Todd Bowles and Zac Robinson aim to unleash Ted Hurst, a dynamic rookie wideout averaging 15.3 yards per catch, to spark Tampa Bay’s offense.
Race for Tarrant County judge a barometer of region’s political dynamic, analysts say
ncumbent Republican Tim O’Hare faces Democratic commissioner Alisa Simmons in the race for Tarrant County judge.
Miami Heat Could Be Tim Hardaway Jr Breakout Season
Tim Hardaway Jr. has long been due for a breakout, and this year with the Miami Heat could be his chance. His NBA career, which began in 2013 with the New York Knicks, has featured dynamic seasons with multiple teams over the last 13 seasons. But there has been something missing until now. About to …
'The New Stanford Prison Experiment' review: A project reimagined for TV
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Darryn Peterson Could Unlock Lauri Markkanen’s Most Dangerous Role Yet
By drawing defensive gravity and facilitating as a playmaker, the dynamic rookie guard can transform Utah’s All-Star forward into a lethal, off-ball threat who punishes scrambled defenses.
Apple's Touchscreen OLED MacBook Pro: Everything We Know
Apple is working on a high-end MacBook Pro, and it's nearly ready to launch. It will have several firsts in a Mac, including an OLED display and a touchscreen. Design Apple hasn't redesigned the MacBook Pro since the launch of the M1 Pro and M1 Max models in 2021, so it's due for a new look. The new MacBook Pro is expected to feature some minor design changes.
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.
2027 Wide Receiver Yuto Kawamura-Johnson Flips Commitment to Michigan
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Streaming’s Biggest Show Returns…and a Buzzy Genre Struggles
(Welcome to my weekly streaming ratings report, the single best guide to what’s popular in streaming TV and what isn’t. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. If you were forwarded this email, please subscribe to get these insights each week.) Obviously, the big news of the week (if not month) is Netflix letting go of executive Bela Bajaria, their chief content officer. I’m going to cover this in my next “Most Important Story of the Week”, but I also have a data angle that I might publish before then. (Too much news this month, am I right?) But first, I have a bonus Streaming Ratings Report issue for you. Today’s article is a bit of a grab bag of topics I’ve wanted to write about, but couldn’t squeeze into the (already very long) Streaming Ratings Report issues. The NFL drives huge viewership numbers, so I’ve got a look at that. A whole bunch of TV shows returned to the traditional broadcast channels, and I have thoughts. And I have a quick look at adult animated shows, since a couple flopped earlier this month. Plus, the Emmys aired earlier this month, and we got some fun data bout how popular those nominated shows are and why I’m not optimistic about the show’s future. That’s a lot, so let’s dive right in. Subscribe Sports - Football Remains the King of Streaming Over the last two Streaming Ratings Reports, I sorta ignored the biggest “show” each week. (I was tempted to say “piece of content” but I know that word bugs folks.) In my database, I call these “specials”, and they sure are special. I speak of the king of American TV: football!!! Streaming football is back and, unlike some other sports, it routinely dominates all viewership. Probably the best way to show this is to update one of my favorite graphics, the “40 Million Hour Club”1 since football games have joined that club each week they’ve premiered: (Yep, that’s the data through 28-Sep, the first four weeks of the season. As a reminder, I take the average minute audience provided by Nielsen, factor out a percentage of linear TV viewers in home markets, and multiply the run time by the three-hour runtime.) Again, the numbers are huge. Let’s start with Netflix. They grabbed the rights to the bonus opening week NFL Kickoff game (which was on YouTube last year) and it put up 18.5 million viewers on average. That nets out to 47.4 million hours of estimated streaming hours. That’s good! Though, notably, it’s well below Christmas Day games from previous years. Compared to other streamers/broadcasters, that’s a bit of a mixed result. On one hand, Netflix’s 18.5 million average is about what YouTube claimed last year, though Nielsen used a bespoke methodology at that time, so I trust this viewership figure more. So that’s good. (The game also shifted from a Friday to a Thursday and that could have helped the viewership as well.) And Netflix continues to best Prime Video in total viewership—as you’ll see next—though Netflix has had much higher-profile (opening week and Christmas Day) games. NBC/Peacock’s opening game the night before averaged 25.1 million average viewers, which is just much bigger than Netflix (or Prime Video). That’s the big caveat to all streaming viewership records: even in success, they can’t compete with traditional linear TV. Previously, I called this my “hierarchy of viewership”, and the data keeps supporting that thesis. The downside for NBC is that this game’s viewership was down compared to previous years, though it may be a counting issue. Here’s a great chart from Sports Media Watch: Indeed, looking at all the opening week games across all windows, Netflix still lags the other primetime windows, but does well compared to the afternoon games: I saw a few folks make the case that streamers still lag traditional broadcasters in reach, and I’d add they really lag compared to “broadcast plus streaming” options like NBC/Peacock, ESPN/Disney+ and CBS/Paramount+. The best data I saw for this came from Samba TV, who charted reach through the 2025 season, and, wow. (Samba TV’s numbers are historically lower than Nielsen’s, so don’t compare their household figures to Nielsen’s hours, but use them as a proxy for the relative reach of the streamers.) The good news is Prime Video is NOT having a down year. Their opening Thursday Night Football game reached 18.6 million viewers (about what Netflix got), but that’s a high for Prime Video on Thursdays and the biggest Thursday night game since 2015. The TNF games the weeks of 21-Sep and 28-Sep continued this streak, getting 43.1 (16.8 million average viewers) and 42.5 total hours (16.6 million average viewers), which were both up from last year. Still, that continues the (typical) season slide: (For those new-to-streaming-football-numbers folks, the viewership declines for Thursday Night Football as the year goes along.) Overall, it appears as if Prime Video is now part of the “football habit”, be it for customers at home or out at places like bars and restaurants. And its viewership is slowly catching up to broadcast. One last chart shows this. Last season, Nielsen started adding out-of-home viewership to the charts, so I try not to do season-to-season comparisons as I did for the first few years. And while Nielsen added Big Data viewing this year, I’m going to compare the last two seasons. Here’s that chart, which shows the season-over-season gains: When it comes to streaming football, we have to keep a few seemingly contradictory thoughts in our head… First, streaming doesn’t come close to matching broadcast’s reach and, thus, viewership. Second, even with that gap, football is still the biggest “thing” on streaming. It’s very, very popular. Third, while some methodology changes have likely helped Prime Video’s numbers, their viewership does appear to be growing. Lastly, yeah, the NFL started the season off poorly, with week one dragging down the numbers in year-over-year comparisons. However—and again, methodology changes may have helped this—the viewership grew compared to previous seasons over the next couple of weeks. So football is still king. On streaming and off. Television - Adult Animation Continues to NOT Make the Streaming Charts In the last two reports, two adult-animated shows whiffed: Netflix’s animated comedy, Dang! Paramount+’s Sega-video-game-inspired fantasy/comedy, Golden Axe. Neither made the charts, but that’s usually the case for animated shows. I mean, here’s literally every animated show that’s made the Nielsen Original charts since the start of 2025: And one of those shows is G_abby’s Dollhouse_! A kids show! The problem with charts like this is that they don’t give you a sense of how many shows miss the charts. Netflix had at least eleven animated flops, including comedies like Big Mouth (a show everyone assumed was popular in the pre-Streaming Ratings Era), Long Story Short, Haunted Hotel, Mating Season, Strip Law, and Alley Cats, and action shows like Blood of Zeus, Castlevania: Nocturne, Devil May Cry, Splinter Cell: Deathwatch, and Tomb Raider: The Legend of Lara Croft. Prime Video had at least six animated misses, two in the same universe (Hazbin Hotel, Helluva Boss), three more comedies (#1 Happy Family USA, The Second Best Hospital in the Galaxy and Kevin) and an action show (The Mighty Nein). Disney+ had MCU and Star Wars animated misses (Eyes of Wakanda, Marvel Zombies, Star Wars: Visions, Star Wars: Maul – Shadow Lord, and Star Wars: Tales of the Underworld) but I can’t tell how many of those shows were geared towards adults. HBO Max had Harley Quinn and Hulu had Solar Opposites. None of these shows made the charts! That’s a lot of misses! If I remade the chart with all those misses, here’s how it would look: Listen, I know the counter arguments. First, it’s cheaper to produce animated shows than live action. Fair enough, but with viewership this low, even that cheaper price point starts to not matter. Second, just look at the acquired charts. Hit animated comedies can generate viewership for years! Shows like The Simpsons, South Park, Family Guy, and Bob’s Burgers do really, really well. Fair enough, but streaming has failed to recreate the dynamic that Fox has mastered so well. That’s a problem for streaming still. Television - Emmys! The annual Emmys broadcast was a few weeks ago, and I’ve got data on how the nominees performed on streaming, plus hot takes on this year’s viewership (and the big news about the broadcast’s, er, streamcast’s future). We’re just getting started with this issue, but the rest is for paid subscribers of the Entertainment Strategy Guy, so if you’d like to find out… The top Emmy-nominated shows… ...why I’m worried about the future of the Emmys telecast... ...the pros of broadcast television ...and the cons... ...please subscribe! We can only keep doing this great work with your support. Coming Soon! Next week, we’ve got a double issue (since the weeks of 21-Sep and 28-Sep were so light), but then I’ll be all caught up after a deluge of streaming ratings data from Nielsen in September. In the meantime, I’m going to try to take a look at Netflix’s stats to explain why Bela Bajaria is out. But even light weeks give me plenty to talk about. The Great British Baking Show returns to Netflix and Apple TV has a buzzy new star-studded comedy. And Netflix has a controversial-but-appears-to-be-popular new game show. Plus big films like Toy Story 5, Backrooms and The Breadwinner head to streaming. And is East of Eden a hit? After that, The Kardashians return to Hulu, Prime Video has a reboot of Carrie, and Netflix has a horror show, Below. Disclosure Day heads to Peacock, The Housemaid heads to HBO Max_,_ a new Ben Affleck film, Animals, lands on Netflix, and Apple TV has a new John Cena action film based on, checks notes, Hasbro’s Matchbox toys. Okay. Longterm, some interesting TV production news. HBO Max ordered How to Survive Without Me, starring Kaley Cuoco, Joshua Jackson, Ray Romano and Rita Wilson, for fifteen episodes! I love that some streamers (or, at least, HBO Max) are finally ordering TV shows with more than eight episodes. In less wise production news, Landman does not appear to be coming back this year, since it just started production. Frankly, I don’t love this (get your shows out on time) but Landman is so popular, I doubt it matters.
‘Transformational’: Iowa lawmaker reacts to massive steel plant announcement, political landscape in the state
Fox News Digital spoke to Iowa GOP State Rep. Mike Vondran about the political dynamics on the ground in the Hawkeye State leading up to the midterm election as well as the newly announced steel plant in the state.
Ultra-Processed Foods and the Aging Brain: What Does the Science Say?
Eating more ultra-processed foods has been linked to increased risk for dementia and Alzheimer's disease, as well as other non-brain health effects, including diabetes and cancer. But why do these foods affect our brain health?
Cirie Fields and Parvati Shallow discuss who would have won a “Survivor: Micronesia” final 3
The dynamic duo also reveals details of their upcoming Soulmate tour.
With No October Surprise in Sight, Republicans Try to Save Themselves
While midterms historically test the governing party, the current dynamic is particularly striking under Trump.
Margaret Qualley's 'Love of Your Life' is about letting go. But she's standing by those barefoot sandals.
Qualley and costar Aaron Pierre break down the dynamics of their new romantic drama.
Exclusive: AI safety money floods into political races
The safety spending points to the unusual power dynamics in the AI race.
Kelly Clarkson and a Brooklyn store clashed on social media. Behind it, power dynamics loomed
Kelly Clarkson's recent dispute with a Brooklyn store highlights the power dynamics between celebrities and everyday people | WBBM Newsradio 780 AM & 105.9 FM
Kelly Clarkson and a Brooklyn store clashed on social media. Behind it, power dynamics loomed
Kelly Clarkson's recent dispute with a Brooklyn store highlights the power dynamics between celebrities and everyday people | 830 WCCO
Apple Announces $149 HomePod Mini 2 With Siri AI, 'Sound Glow', and Four-Speaker Surround Sound
Apple today announced a new HomePod mini equipped with Siri AI, new colors, and improved audio experiences. The new HomePod mini has an S10 chip that supports advanced computational audio, and Apple says it optimizes dynamic range, loudness, and acoustic performance in real-time. A Sound Glow feature turns the HomePod mini's top into a "visual canvas" that glows and animates in sync with music, reacting to bass and treble.
Should the Miami Heat Claim Lonnie Walker IV Off Waiver?
With roster deadlines looming, the Miami Heat could secure a dynamic scoring spark. Lonnie Walker IV’s explosive bench production offers the playmaking punch needed to ignite Erik Spoelstra’s offense.
AI Agents and the Rise of the Lab-in-the-Loop
Automation and robotics enabled the self-driving lab, but these largely follow pre-defined workflows. In this Q&A, Mark Fish explains how AI agents enable the "Lab-in-the-Loop" approach, which could accelerate life science research.
Vikings Floated in Realistic Trade Idea for Eagles’ Saquon Barkley
The Minnesota Vikings‘ offense is starting to flash what it could be after their Week 5 win over the New Orleans Saints. Nonetheless, one aspect that the team lacks is a dynamic running back to complement their passing game. Aaron Jones Sr. produced in the win over New Orleans as the veteran running back recorded […] The post Vikings Floated in Realistic Trade Idea for Eagles’ Saquon Barkley appeared first on HEAVY.
Scientists Reaffirm “Incontrovertible” Evidence of Human Influence on Climate
In response to a "deeply flawed" US government report, scientists have published an outline detailing the credibility of climate fingerprinting research and advances in the field since 2009.
'Landman' Season 3 Could Make A Major Mistake With Cooper And Tommy Norris
Landman Season 3 has an opportunity to change the show's entire dynamic.
Immune Cell Map Uncovers How Individual Aging Trajectories Diverge
Researchers created an immune aging map showing that a balance between two immune cell types can predict future health. The findings link immune aging patterns to risks of chronic disease, mortality, and unhealthy aging.
Thunder’s Quietest Preseason Development Solves Major Offseason Loss
Sharp-shooting guard Jared McCain is emerging as a dynamic perimeter threat, utilizing off-ball versatility and veteran poise to preserve the floor spacing lost during a transformative offseason.
Evaluating Timberwolves’ Ceiling With New Anthony Edwards, LaMelo Ball Duo
The Timberwolves could be very dynamic this season.
Voters are connecting the dots — and it’s bad news for Republicans
Of all the dynamics threatening the GOP this year, the most menacing may be the connection voters are drawing between their economic frustrations and GOP policies.
Opinion: Kansas may surprise the nation and elect a Democrat to the US Senate. MAGA politics reshaped state.
Opinion from H. Edward Flentje: In 1932, Kansas voters elected Democrat George McGill to the U.S Senate. In the 32 senate elections since then, voters have consistently elected Republicans to represent them.This historic streak makes Democrat Adam Hamilton’s bid to prevail in his challenge to the reelection of U.S. Senator Roger Marshall an uphill climb. However, Marshall’s embrace of MAGA politics has changed the dynamics of the race and given Hamilton a credible shot at a dramatic upset.
Paolo Banchero Recaps 'Pretty Good' Offensive Performance
Orlando's young star breaks down the team's lethal pick-and-roll chemistry and a high-assist night that signals a shift toward a more dynamic, unselfish offensive identity this season.
One Law of Citation? Scientists Find Shared Rules Behind Science, Law and Patents
A new Nature Communications study shows that scientific papers, U.S. case law, and patents share similar statistical citation dynamics, which a community-centric model with three core mechanisms can reproduce, explain delayed recognition, and better predict future impact.
Ben Affleck shares rare insight into coparenting dynamic with Jennifer Garner: ‘I’m really, really grateful’
Ben Affleck reveals that he and ex Jennifer Garner have a ‘really wonderful’ coparenting dynamic, and devote their energies toward their three children.
Breaking into the Peer-Reviewed Engineering Literature
Editor’s note: We are delighted to present a new series by William Dembski, adapted from his Substack. This is the 14th post. Find the full series so far here, “My Personal History with Information.”…
General Dynamics names next CEO, as Novakovic becomes exec chairman
Phebe Novakovic, General Dynamics' longtime CEO, will transition to executive chairman on Jan. 1, 2027, as President Danny Deep becomes the Fortune 500 aerospace and defense contractor's next leader, the Reston-based company announced Wednesday.
EXCLUSIVE: VP Vance blames Alaska LNG pipeline uncertainty South Korean ‘political dynamics’
“It’s different because you have a president who delivers on his promises,” Vance said, moments before leaving on Air Force 2.
Google sounds really excited about 'massive' feature update hitting Pixel Buds right now
From dynamic ANC, to tap-to-mute for your microphone, to even new Live Translate capabilities, this sounds like one major update!
Lodging Dynamics names new SVP of business development
Hotel management company Lodging Dynamics has appointed Danny Dolce senior vice president of business development. | Danny Dolce will lead the expansion of Lodging Dynamics’ third-party management portfolio, focusing on luxury, premium-branded and full-service hotels in destination-driven markets.
Scientists discover 57 new marine species lurking in the depths of the South Atlantic
A group of scientists in Argentina discovered dozens of new species in the South Atlantic Ocean, shedding new light on one of the world’s most biologically dynamic regions.
Scientists discover 57 new marine species lurking in the depths of the South Atlantic
A group of scientists in Argentina discovered dozens of new species in the South Atlantic Ocean, shedding new light on one of the world’s most biologically dynamic regions.
Scientists discover 57 new marine species lurking in the depths of the South Atlantic
A group of scientists in Argentina discovered dozens of new species in the South Atlantic Ocean, shedding new light on one of the world’s most biologically dynamic regions.
Scientists discover 57 new marine species lurking in the depths of the South Atlantic
A group of scientists in Argentina discovered dozens of new species in the South Atlantic Ocean, shedding new light on one of the world’s most biologically dynamic regions.
Scientists discover 57 new marine species lurking in the depths of the South Atlantic
A group of scientists in Argentina discovered dozens of new species in the South Atlantic Ocean, shedding new light on one of the world’s most biologically dynamic regions.
Scientists discover 57 new marine species lurking in the depths of the South Atlantic
A group of scientists in Argentina discovered dozens of new species in the South Atlantic Ocean, shedding new light on one of the world’s most biologically dynamic regions.
Apple Announces iPhone Duo Apps Can Now Be Submitted to App Store
Apple today announced that apps optimized for the iPhone Duo can now be submitted for App Store approval, ahead of the foldable device launching on Friday, October 23. While existing App Store apps will automatically run on the iPhone Duo, only apps built with the iOS 27.1 SDK or later can dynamically resize to fill the entire space of the inner display, whereas unoptimized apps will have black borders.
Integral Ad Science to Provide Brand Safety and Suitability Measurement in ChatGPT Ads
NEW YORK, October 05, 2026--As artificial intelligence rapidly reshapes digital advertising, marketers face a critical new challenge: ensuring brand safety and suitability within dynamic, generative AI-native environments. Without independent verification, advertising in conversational channels risks creating a blind spot for enterprise brands seeking reliable media quality standards.
Top Links 1245 Jobs in health care. Jobs for women. The US labour market is segmenting. Chernobyl’s radiation and Lenin’s love of literature.
Thank you for your support of Chartbook. Your generosity keeps this show on the road. Elmer Bischoff, Two Figures at the Seashore, 1957 The only really dynamic job-creator in the US economy is health care:
Jobs in health care. Jobs for women. The US labour market is segmenting. Chernobyl’s radiation and Lenin’s love of literature.
Thank you for opening your Chartbook email. Elmer Bischoff, Two Figures at the Seashore, 1957 The only really dynamic job-creator in the US economy is health care: The largest crunch has come in Federal government, which has shed 2.7 m jobs. Source: tchouvkov on Twitter Tech is struggling. [ Joey Politano 🏳️🌈@JosephPolitano The US tech sector continues bleeding jobs in official data released today—overall, employment decreased by 17k last month and is down 69k over the last year That's nearly as bad as the worst of the 2024 tech-cession, and much worse than the 2022 boom or even pre-2020 norms 12:42 PM · Oct 2, 2026 · 15.2K Views 15 Replies · 47 Reposts · 390 Likes ](https://x.com/JosephPolitano/status/2106001807847940232?s=20) The new jobs are all for women. [ Justin Wolfers@JustinWolfers I'm not sure who saw this coming, but so far nearly all the jobs created during the second Trump administration have gone to women. 1:09 PM · Oct 2, 2026 · 33K Views 70 Replies · 146 Reposts · 644 Likes ](https://x.com/JustinWolfers/status/2106008723533533601?s=20) Meanwhile, real wages are being eaten up by modest over-target inflation. [ Heather Long@byHeatherLong The financial pain is real: Wage growth fell to 3% (y/y) in September. That's the lowest in 5 years. Wage growth: 3% Inflation: ~3.4% Inflation has eaten up all wage gains for the average worker since April. Many people are having to make hard choices about what to buy and what … 1:24 PM · Oct 2, 2026 · 37K Views 24 Replies · 275 Reposts · 533 Likes ](https://x.com/byHeatherLong/status/2106012367712620728?s=20) HEY READERS, THANK YOU for opening the Chartbook email. I hope it brightens your day. I enjoy putting out the newsletter, but tbh, what keeps this flow going is the generosity of those readers who clicked the subscription button. If you are persuaded to click, please consider the annual subscription of $60. It is both better value for you and a much better deal for me, as it involves only one credit card charge. Why feed the payments companies if we don’t have to. Subscribe Elmer Bischoff, Bathers, 1960 Americans are disillusioned with higher ed. For contributing subscribers only. Subscribe Where the Chernobyl radiation went. h/t Simon Kuestenmacher aka simongerman600 How Lenin’s love of literature shaped the Russian Revolution - Tariq Ali This, then, was the intellectual atmosphere in which Lenin came of age. His father, a highly cultured conservative, was the chief inspector of schools in his region and much respected as an educationalist. At home, Shakespeare, Goethe and Pushkin, among others, were read aloud on Sunday afternoons. It was impossible for the Ulyanov family – “Lenin” was a pseudonym adopted to outwit the tsarist secret police – to escape high culture. At high school, Lenin fell in love with Latin. His headteacher had high hopes that he might become a philologist and Latin scholar. History willed otherwise, but Lenin’s passion for Latin, and taste for the classics, never left him. He read Virgil, Ovid, Horace and Juvenal in the original, as well as Roman senatorial orations. He devoured Goethe during his two decades in exile, reading and rereading Faust many times. Lenin put his knowledge of the classics to good use in the time leading up to the October revolution of 1917. In April of that year, he broke with Russian social-democratic orthodoxy and, in a set of radical theses, called for a socialist revolution in Russia. A number of his own close comrades denounced him. In a sharp riposte, Lenin quoted Mephistopheles from Goethe’s masterwork: “Theory, my friend, is grey, but green is the eternal tree of life.” Source: The Guardian Elmer Bischoff, The River, 1953 If you’ve scrolled this far, you know you want to click: Subscribe
'The Outsiders' review: A dynamic staging at the Hollywood Pantages
'The Outsiders,' winner of the 2024 Tony for best musical and based on the classic S.E. Hinton novel, has its L.A. premiere at the Hollywood Pantages Theatre.
“Dawson’s Creek” creator Kevin Williamson says star James Van Der Beek ‘started out as a brat’
Williamson poignantly reflected that his dynamic with the late star was like “Dawson talking to Dawson.”
WHO joins Pre-COP31 to advance climate action that delivers for people’s health
The World Health Organization (WHO) is joining Pacific leaders, governments and partners at Pre-COP31 in Fiji from 5 to 8 October to advance health priorities in climate action and strengthen the Pacific voice ahead of the 31st Conference of the Parties (COP31) to the United Nations Framework Convention on Climate Change (UNFCCC).COP31, to be held next month in Antalya, Türkiye, marks an important step for global climate and health action. Health is one of the 10 priority themes of the COP31 Action Agenda, “Dynamic and Resilient Health Systems”, and a dedicated Health Day will take place on 9 November, the first day of COP31. The inclusion of health reflects growing global recognition that climate action and health are closely connected. The climate crisis is affecting population health globally. Across the WHO Western Pacific Region, which includes Pacific island countries and areas, the consequences of climate change include extreme heat, cyclones, floods, rising sea levels, food and water insecurity, infectious diseases and disruptions to essential health services. The Pacific in particular faces additional challenges. A recent review of 76 hospitals in 14 Pacific island countries found that 62% of health facilities are located within 500 metres of the sea or a river, leaving them particularly exposed to flooding, storm surges and sea-level rise.Bringing Pacific priorities to the global climate agendaThe Pacific Pre-COP31 provides an important opportunity for Pacific countries and partners to consolidate regional priorities and bring the experiences and leadership of Pacific communities into global climate discussions.Pacific countries have been advancing practical approaches to protect health in a changing climate, including strengthening climate-resilient health systems, improving preparedness for extreme weather events, building resilient health infrastructure and mobilizing climate finance for health. “This Pre-COP is an important moment for the Pacific, bringing global climate discussions to a region that has long been at the forefront of the climate crisis. It provides an opportunity for Pacific countries and areas to set their priorities, experiences and leadership on the global stage, and to ensure that the realities of Pacific communities are genuinely reflected in the decisions made on climate action,” said Dr Saia Ma’u Piukala, WHO Regional Director for the Western Pacific.Throughout this week, WHO will co-convene and participate in high-level discussions and events focused on climate and health, climate resilience, adaptation, financing and implementation. “Climate finance is essential for resilient and healthy Pacific communities,” emphasized Dr Mark Jacobs, WHO Representative to the South Pacific and Director of Pacific Technical Support. “We must ensure that financing reaches the people, communities and essential services most exposed to climate risks, supporting locally defined priorities and investments.”WHO will work with partners to strengthen the integration of health considerations across climate policies and investments, including national climate plans and resilience initiatives.Health as a driver of climate actionAmid the risks to health and pressures on health systems, well-strategized and implemented climate action can deliver significant health benefits. Investments in clean energy, sustainable transport, resilient infrastructure, food systems and nature-based solutions have proven to reduce health risks while contributing to climate mitigation and adaptation.“Climate action is truly an investment in health. Cleaner energy, healthier food systems and climate-resilient health services can protect lives while building stronger communities. We now need to turn these opportunities into action and make health a core part of climate investments,” said Dr Sandro Demaio, Director and Head of Office, WHO Asia-Pacific Centre for Environment and Health in the Western Pacific Region. “These benefits demonstrate that climate action is not only about reducing future risks. It is also an opportunity to improve lives today while building healthier, safer and more resilient societies.”At COP31 next month, WHO will also support the Health Pavilion, which will bring together the global health community and partners to advance health and equity within climate negotiations. With COP31 poised to move health higher on the global climate agenda, WHO will continue working with countries and partners across the Western Pacific Region and globally to strengthen climate-resilient and low-carbon health systems, and ensure that climate action protects and improves people’s health.____________________Media contactsElizabeth Bennett, WHO Asia-Pacific Centre for Environment and Health in the Western Pacific Region, elizabeth.bennett@who.intJulia Dongwhan Shin, WHO Asia-Pacific Centre for Environment and Health in the Western Pacific Region, dong.shin@who.intWHO Western Pacific Communications, wprocom@who.int
Scientists discover 57 new marine species lurking in the depths of the South Atlantic
A group of scientists in Argentina discovered dozens of new species in the South Atlantic Ocean, shedding new light on one of the world’s most biologically dynamic regions.
Why Fun Is Serious Business: Boston’s Push To Build a More Vibrant, Competitive City
Boston public policy leaders and business advocates argued that a dynamic, cultural nighttime economy will help the city attract and retain talent while supporting local businesses.
Flick’s Barcelona and the value of entertainment
What makes a TV show or movie ‘entertaining’?An exciting and dynamic cast roster? Some compelling writing? A creative head pulling all these strings together in one direction? What about a hooked ...
Flick’s Barcelona and the value of entertainment
What makes a TV show or movie ‘entertaining’?An exciting and dynamic cast roster? Some compelling writing? A creative head pulling all these strings together in one direction? What about a hooked ...
Flick’s Barcelona and the value of entertainment
What makes a TV show or movie ‘entertaining’? An exciting and dynamic cast roster? Some compelling writing? A creative head pulling all these strings together in one direction? What about a hooked audience? Take one look at FC Barcelona 2026/27, and how is the season so far any different? Or if it is lacking any […]
Lewis Hall Allowed To Shine Under Matthias Jaissle’s New System
The England international is thriving as a dynamic playmaker, trading rigid defensive duties for a versatile role that maximizes his technical composure and aggressive attacking instincts.
AROUND THE LAKES: Geneva Theatre Guild announces 49th season
GENEVA — The Geneva Theatre Guild has announced its 49th season, a dynamic year of theater that celebrates local talent, classic storytelling, and the Guild’s long tradition of community‐driven artistry.
Wolff: “It’s difficult to cope” for Russell seeing Antonelli pace
The Bahrain GP in Malaysia represents a crucial moment in the Championship for Mercedes, who introduce a series of long-awaited upgrades to the W17. These updates are the first major aerodynamic changes for Mercedes in several months, who are finally responding to the developments from other teams - most notably McLaren. Despite the relative delay …
Former UCF F Keyshawn Hall Granted TRO, Gains Eligibility
A New York court ruling clears the path for the dynamic "Big Guard" to join Rick Pitino at St. John’s, bolstering the Red Storm’s offensive arsenal.
O'Neill Institute Announces New Leadership and Two New Centers, Ushering in a Dynamic New Era for Health Law
Bert Brandenburg joins as Executive Director, Liz Stokes as Managing Director, alongside launch of new centers on AI and Women’s Health WASHINGTON, D.C... October 2, 2026 — The O’Neill Institute
Studying Science in an Anti-Scientific Time
This Chronicle Review Deep Cut was first published in 2025. By Julianne Werlin Thanks for reading The Chronicle Review! Subscribe for free to receive new posts and support my work. Subscribe The last two decades have not been kind to science studies. Already bruised and battered by the “science wars” of the 1990s, by the 2000s sociologists of science — who had long argued that science had to be understood in its human context — were encountering the funhouse-mirror version of their own views in right-wing critiques of climate scientists. It was enough to give some prominent scholars pause. “Was I wrong to participate in the invention of this field known as science studies?” asked Bruno Latour, the most famous sociologist of science in the world, in 2003. “Should we apologize for having been wrong all along? Or should we rather bring the sword of criticism to criticism itself and do a bit of soul-searching here: What were we really after when we were so intent on showing the social construction of scientific facts?” In response, Latour proposed a change of method and attitude. Science studies, now chastened and contrite, would no longer seek to strip facts of their authority, but to enrich and enhance them. What this meant in practice was never fully clear. But his diagnosis of problems resonated, even if his solutions did not. Latour’s exercise in public hand-wringing signaled a shift in mood. By 2016, with the first election of Donald Trump, the idea that skepticism of science was a right-wing position, not a left-wing one, had become a commonplace, discussed eagerly in The New York Times. For liberals, vaccine denial during the Covid era and Trump’s second-term attacks on the funding of scientific research, covered extensively in these pages, added a new urgency to the defense of science on both practical and principled grounds. There was little appetite for a sociology or philosophy of science that emphasized the messiness and missteps of the scientific process rather than its integrity and triumphs. The distinguished historian of science Peter Dear’s new book, The World as We Know It: From Natural Philosophy to Modern Science (Princeton University Press, 2025), which seeks to tell the story of 18th- and 19th-century science for a general public, may seem comfortably remote from these bitter contests. In its 16 short chapters, Dear draws swift, sure sketches of major discoveries from Newton to Einstein, ably guiding the reader through debates on stellar nebulae, animal taxonomy, atomic chemistry, evolution, and other flashpoints in the history of science. But though a work of history, Dear’s book must still negotiate our polarized present. In a blurb on its back cover, the historian of biology Lynn K. Nyhart alludes to the “present moment, when scientific knowledge is being swamped by misinformation and its institutions are under siege.” Dear himself, in his conclusion, refers to the “yard signs” and “bumper stickers” that proclaim “Science Is Real.” One antidote to both anti-science propaganda and to reductive slogans in science’s defense is a robust history and philosophy of science: exactly what Dear’s scholarship has long offered. But his new book illustrates how difficult such work has become. Dear, an emeritus professor of history at Cornell University, is best known as a creative and philosophically minded historian of the Scientific Revolution. His edited volume The Literary Structure of Scientific Argument (1991) analyzed the rhetoric of Galileo’s thought experiments to brilliant effect. Discipline and Experience: The Mathematical Way in the Scientific Revolution (1995) was a major contribution to the analysis of scientific experiments in early modern Europe and beyond, while Revolutionizing the Sciences: European Knowledge in Transition, 1500-1700 (2001), now in its third edition, remains one of the best overviews of the profound epistemological upheavals of 16th- and 17th-century science. But Dear has also ventured into later periods. Nearly two decades ago, in The Intelligibility of Nature: How Science Makes Sense of the World (2006), he turned to the 18th and 19th centuries to sketch a history and theory of scientific knowledge. Aimed at a generalist audience, Dear’s simple prose belied serious philosophical ambitions. Science, Dear argued, has two aspects: “natural philosophy,” the quest to understand the true nature of the universe, and “instrumentality,” the applied skills and technologies that allow us to manipulate the world for human advantage. Both strands are ancient, but the innovation of the phenomenon we call “science” was to yoke them together. As Francis Bacon wrote, “Human knowledge and human power meet in one; for where the cause is not known, the effect cannot be produced,” an insight typically abridged to “knowledge is power.” Or, in Bertrand Russell’s characteristically blunt phrase, science has two functions, “1. to enable us to know things, and 2., to enable us to do things.” So far, so conventional. But Dear took issue with this familiar story in one respect. Bacon’s formula implied that theory and practice could be fused in a single method. In fact, Dear argued, the quest to understand nature and the desire to manipulate it were coupled only loosely. They could come together, but they could also pull apart. Focusing on natural philosophy, the “knowing” half of the scientific circle, he used a series of case studies from cosmology, taxonomy, chemistry, electromagnetism, and quantum theory to show how theories changed over time, in dialogue with practice, but never reducible to it. Take the case of matter, the basic substrate of the physical world. In the 18th and 19th centuries, scientists not only disagreed about what it was, but also about how well it could be known. In 1789, the chemist Antoine Lavoisier dismissed speculation about the atomic composition of chemicals as “discussions entirely of a metaphysical nature,” as he sought to orient chemistry away from philosophical abstraction and toward laboratory results. But in the 19th century, atoms returned with a vengeance in the atomic chemistry of John Dalton, who wanted to explain the underlying structure of nature. It was not just that Dalton and Lavoisier had a different set of experimental results, or even a different theory, Dear showed. What counted as an explanation had changed. In arguing that scientific theories depended on their intelligibility to human beings with complex arrays of beliefs and commitments, Dear was in sympathy with science studies. Key figures such as the sociologist Steven Shapin emphasized the importance of psychological mechanisms like trust in the formation and acceptance of scientific ideas. But in focusing on the scientific pursuit of knowledge, not its politics or economics, Dear resisted the more cynical perspective of some of his colleagues. The Intelligibility of Nature strikes a very different note than Shapin’s collection of a few years later, Never Pure: Historical Studies of Science as If It Was Produced by People With Bodies, Situated in Time, Space, Culture, and Society, and Struggling for Credibility and Authority (2010), to name just one example. Walking a very fine line, Dear depicted science as driven at once by complex social dynamics and by the intellectual power of real discoveries. It was a testament not only to his own acumen but also to the vitality of the field that he was able to do so. Nearly two decades later, The World as We Know It returns to the questions broached in The Intelligibility of Nature. Like Dear’s earlier study, it begins with the Newtonian cosmos and ends with debates between Einstein and Bohr on quantum physics. Beyond its terminal figures, many of the same characters appear in both studies, including the naturalists John Ray and the Comte de Buffon; the chemists Étienne François Geoffroy, Antoine Lavoisier, and John Dalton; as well as Charles Darwin and Michael Faraday, among others. Its subject is nearly identical: As in The Intelligibility of Nature, The World as We Know It considers natural philosophy as opposed to instrumentality, here defined as the “desire to create a picture of what the world is really like — the world as God knows it — rather than simply having instrumental or operational control over it.” The two books also overlap in insights — and sometimes even in language. The reader who has learned in The Intelligibility of Nature that Buffon’s method of classifying animals “reflected his belief in the importance of the senses and empiricism in learning about nature (a doctrine associated with Newton and the philosopher John Locke)” will experience a sense of déjà vu on reading, in The World as We Know It, that the classification “reflects Buffon’s commitment to the epistemological stance of Newton and his philosophical underlaborer John Locke, who stressed the role of the senses in creating natural knowledge.” Later in the passage, we read that, “because of its stress on understanding the ways of life of animals in their environments, Buffon’s approach could almost be labeled (anachronistically) as ‘ecological.’” And again, “an anachronistic way of putting it would be to say that Buffon recommends an ecological mode of understanding.” Likewise, in The Intelligibility of Nature we read of Dalton that he was initially drawn to meteorology, and that: He did a bit of experimental work on these things, especially having to do with the water-holding capacity of gases, but his real interest lay in understanding what, at an underlying natural-philosophical level, was really going on physically.” Whereas, in The World as We Know It: He did experimental work on these things, especially concerning the water-holding capacity of gases — although not at a very refined level quantitatively — but he was continually trying to develop a theoretical conception of what was happening physically. The final full chapter of each book closes on the same resigned note. Intelligibility: These days, most serious work on the natural philosophical underpinnings and implications of quantum mechanics is performed not by physicists but by philosophers of science. Among scientific practitioners themselves, Bohr’s attempt to use instrumentality as sufficient grounds for a respectable science has met with a high degree of success. And again, in The World as We Know It: Bohr’s and Einstein’s concerns are now questions that are mostly discussed by philosophers of science rather than by physicists themselves. The marginalization of these sorts of questions amounts to the demise of natural philosophy, at least in physics, in the 20th century. Quantum mechanics “works,” and that’s good enough for most scientists who encounter it. Examples could be multiplied. When handling the same subject matter, some echoes are inevitable. Scholars should not feel that because they have written “Isaac Newton died in 1727” in one book, in the next they must describe him as perishing, expiring, or meeting his maker. But the repetitions of language and arguments (not to mention six reproduced images) threaded throughout The World as We Know It are more extensive than that. They should have been caught by Princeton University Press or its reviewers, and revised. Because the two books have so much in common, it is easy to see where they diverge. The World as We Know It is a less theoretical work than its predecessor. The sociology of knowledge that organized The Intelligibility of Nature has been reduced in scale and folded into readings and examples. The taut interplay between history and theory, which gave the earlier study so much interest, is there, but it is subtle. In the earlier book, the case studies demonstrated theoretical claims about the character and development of science. In the later work, each narrative of discovery is an end in itself. Insights emerge from the history, but they do not control the organization of the study. With the theory muted, it can be hard to understand the logic uniting Dear’s sprawling history of more than two centuries of scientific knowledge. The 16 brisk chapters cover an enormous amount of material. But the closer the volume edges to comprehensiveness, the more obvious the missing elements become. A chapter on “Institutions and Pedagogy,” describing the birth of the research university, illustrates the problem. Inserted roughly halfway through the book, the unnumbered chapter is designed as an “entr’acte,” in acknowledgement that it does not fit the study’s organization around scientific discoveries. Yet as Dear is well aware, no general history of the development of modern science can bracket its 19th-century institutionalization and professionalization. It was the 19th-century university, after all, that gave us the “scientist,” a term coined by the Cambridge philosopher William Whewell. Dear’s history of scientific discoveries implies a wider social and institutional history, but it remains largely subterranean, only occasionally extruded under the pressure of the narrative. It must be said that the balance is not all on the side of the earlier study. There are some advantages to the more historical, less theoretical organization of The World as We Know It. Dear’s accounts of paradigm shifts are remarkably lucid, no small accomplishment given that they span fields and centuries. He makes excellent use of the wealth of new scholarship on Darwin and his influences, to which he has himself contributed. It is satisfying to see puzzle pieces from Buffon’s natural history, Georges Cuvier’s animal taxonomy, Thomas Robert Malthus’s demography, and Charles Lyell’s geology recombined seamlessly in the Darwinian jigsaw. Likewise, Dear’s discussion of stellar nebulae, divided between chapters two and 15, shows vividly how Newton, Kant, Herschel, and Hubble reimagined insights and observations as they sought to discover whether the diffuse light that filtered through early telescopes was a glowing, gaseous substance or discrete but distant stars. Yet despite such pleasures, the book remains a more modest work than The Intelligibility of Nature. Dear has clearly not changed his views about the history of science. But in the two decades that have elapsed, the discipline and the world around it have changed, making it harder to write a sociologically and philosophically ambitious history of science for the general reader. That is a shame, because in the age of Silicon Valley and biotechnology, both the reciprocity and the tensions Dear identified between the epistemological and instrumental ambitions of science are more evident than ever. In recent years, some of the most exciting new books on the history of science in early modernity have focused precisely on this pressure point. Important studies such as Pamela H. Smith’s From Lived Experience to the Written Word (2022), James Poskett’s Horizons: The Global Origins of Modern Science (2022), and Vera Keller’s The Interlopers: Early Stuart Projects and the Undisciplining of Knowledge (2023) all shed new light on how early modern science negotiated the relationship between its instrumental and epistemological ambitions, or in Russell’s phrase, knowing and doing. There is every opportunity for a philosophically informed approach to draw new insights from this wealth of material. Dear, unfortunately, has not done so in The World as We Know It. But for future scholars of the history of science, his body of work over nearly four decades may provide just the model. Julianne Werlin is an associate professor of English at Duke University. 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The Alternative for Germany (AfD), classified as far-right by German authorities, made history by becoming the largest party in the state parliament, winning 43.8 per cent of the vote — twice its share in the previous election. The Christian Democratic Union (CDU), which had governed the state continuously for 24 years, won just 17.2 per cent, its worst result ever in Saxony-Anhalt. On the night the results were announced, the atmosphere at the CDU gathering was unusually calm. There was neither shock nor argument, as if the defeat had long been expected. Several veteran party members who had spent years working in the state government said: “Defeat is not a bad thing. It is time to make changes.” This state election has not only upended Saxony-Anhalt’s political landscape, but also laid bare the deep tensions between Germany’s traditional party structure and model of governance, on the one hand, and an increasingly polarised society on the other. Its repercussions are already being felt at the federal level, making Saxony-Anhalt a useful case study of the broader trend towards political polarisation and realignment in Europe. Governing Difficulties after Electoral Victory The most immediate consequence of the election is a historic setback for the mainstream party order that took shape in post-war Germany. In Saxony-Anhalt, the AfD has leapt from a peripheral party to the largest political force in the state. Its electoral base has expanded beyond the traditional category of “marginal protest voters” to take on the characteristics of a cross-class coalition. The party has not only consolidated its support in rural areas, but also attracted many middle-class voters and even members of the social elite with stable jobs, their own homes, and substantial incomes. It has thus evolved from a “protest party” into one with the potential to govern. Despite its commanding lead in the vote, however, the AfD faces an institutional obstacle to governing the state: the mainstream parties’ long-standing “firewall” against it. Neither of the two potential routes to forming a government appears likely to break the current political deadlock. The first would be a coalition of establishment parties, led by the CDU and bringing together the Social Democratic Party (SPD), the Greens, the Left Party (Die Linke) and the Sahra Wagenknecht Alliance (BSW) in a cross-camp government. In terms of parliamentary arithmetic, such a coalition could prevent the AfD from forming a government and preserve the outward stability of the traditional political order. Yet these parties are fundamentally divided over key issues including immigration, the energy transition, economic management, and cultural and education policy. Coalition negotiations would therefore be extremely difficult, and even if a government could be formed, it would most likely prove short-lived. More importantly, an alliance of establishment parties aimed at keeping the largest party out of government would play directly into the AfD’s narrative that “political elites are suppressing public opinion”. It could deepen perceptions of political unfairness, further strengthening the AfD’s political capital, and creating a dynamic in which “the more it is suppressed, the more people vote for it”. Ulrich Siegmund, the AfD’s candidate for state premier, has said that if efforts to form a government fail because other parties refuse to cooperate, the AfD will push for a fresh election, which he believes could deliver the party an absolute majority of seats. This points to more intense political battles ahead. The second option would be a coalition between the AfD and the BSW. Together, the two parties would command a simple majority in parliament, making this, on paper, the quickest route to forming a government. The BSW is the only elected party that has not ruled out cooperation with the AfD, and the two parties share some common ground, including on policy towards Russia. There is therefore a degree of political basis for cooperation. Were such a coalition to materialise, Germany would see its first state government jointly formed by a party defined as far-right and one with a far-left background, creating what might be called a “bipolar anti-establishment alliance”. Such an outcome would fundamentally break with the ideological boundaries of post-war German party politics. It is worth noting that even if the AfD ultimately fails to enter the state government, its roughly 47 per cent share of parliamentary seats would give it a powerful blocking minority. Without its consent, major decisions requiring a two-thirds majority — including constitutional amendments, significant budgetary adjustments, and state-level institutional reforms — would be extremely difficult to pass. Therefore, whoever ultimately forms the government, the AfD will be an unavoidable force in Saxony-Anhalt politics, with a direct influence on the state’s legislative process. Systemic Failures in Germany’s Governance Model The Saxony-Anhalt election result reflects a systemic failure of Germany’s post-war mainstream-party model of governance to adapt to rapidly changing socioeconomic conditions. It stems from multiple, mutually reinforcing structural tensions and highlights the existing political system’s difficulty in adapting to “an increasingly polarised society First, collective anxiety has replaced individual material hardship as a central driver of political mobilisation. The rise of the AfD can no longer be explained simply by poverty or social marginalisation. Its increasingly cross-class electoral base suggests that what is driving voters towards the party is, above all, concern about the broader direction of society. This anxiety about the future of the political community goes beyond individual gains and losses. In political discourse, economic anxiety has become closely intertwined with immigration, while immigration and refugee issues are, in essence, questions of social fairness. This perception turns conflicts over the distribution of social resources into negative assessments of governing parties, providing a broad social basis for far-right political narratives. Second, regional disparities and East German identity have undermined the strategy of addressing eastern Germany’s structural challenges at the regional level. More than three decades after German reunification, eastern states such as Saxony-Anhalt have experienced periods of economic growth, but their underlying economic structures remain weak, and household incomes and wealth remain significantly below those in western Germany. At the same time, they continue to face population outflow, an ageing population, labour shortages, and other structural challenges. At a deeper level, historical experiences — including the collapse of the former East German economic system, mass unemployment during the transition, and the westward shift of decision-making power over major issues — have left some residents with a sense of being “second-class citizens” and of being excluded. For years, the German government treated the “syndrome” of reunification as a regional problem to be gradually addressed at the local level. That approach is becoming increasingly unsustainable, as regional development disparities emerge as a core structural factor shaping national politics. Third, the erosion of institutional trust is perhaps the most decisive factor. AfD supporters tend to distrust establishment institutions, including parliament, government, and the mainstream media. Their concerns about economic security, pensions, and social fairness are significantly greater than the social average. Increasingly, their support for the AfD reflects not an expectation that the existing system can be improved, but a search for an alternative to the current political order. Such a systemic deficit of trust will be extremely difficult for the traditional parties to repair in the short term. Fourth, a generational shift in political mobilisation has amplified political polarisation. Unlike traditional parties, which rely heavily on offline rallies and mainstream media coverage, the AfD has developed a social-media mobilisation strategy built around “raising an issue — identifying who is responsible — offering a simplified solution — building a shared identity”. It turns complex social tensions into concise political narratives, rapidly channelling public sentiment into political support. The contrast on the eve of the election was particularly telling. The establishment parties, together with trade unions and churches, organised an offline march attended by more than 10,000 people, but its reach was largely confined to those present and to traditional media coverage. The AfD held a much smaller indoor event, yet livestreaming on TikTok, YouTube, and other platforms, combined with the involvement of online influencers, gave it a reach and mobilising capacity far beyond that of the march. The contrast illustrates how the traditional parties’ methods of political mobilisation are increasingly struggling to keep pace with a political environment transformed by changes in media technology. A Microcosm of Structural Political Change in Europe The shockwaves from the Saxony-Anhalt election quickly travelled beyond the state to the federal level. Calls for political accountability followed immediately after the results were announced. The governing CDU and SPD are now under enormous pressure, while Chancellor Friedrich Merz and Vice Chancellor Lars Klingbeil face an unprecedented test. Political polarisation in Germany is no longer simply a regional phenomenon. The post-war model of multiparty government by establishment parties is breaking down and being reshaped. Viewed in a broader European context, the Saxony-Anhalt election is part of a continent-wide wave of party polarisation, mainstream-party decline, and rising right-wing forces. Far from an isolated phenomenon, it is a microcosm of the structural political changes unfolding across Europe. Weak economic growth, cultural tensions over immigration, and declining trust in institutions are fuelling the rise of right-wing forces in several countries, challenging the liberal internationalist order established in post-war Europe. As a core member state of the European Union, Germany’s ability to adapt its political system and the direction of its politics will have profound implications for both European integration and the evolution of the international order. Subscribe [ Pekingnology China’s Germany watchers take stock of Berlin’s uneasy turn On 7 December 2025, nearly 50 Chinese scholars and policy researchers gathered in Beijing for the 2025年德国形势年终研讨会 “2025 Year-End Seminar on the Situation in Germany… Read more 9 months ago · 31 likes · 1 comment · YIRUI LI and Yuxuan JIA ](https://www.pekingnology.com/p/chinas-germany-watchers-take-stock?utm_source=substack&utm_campaign=post_embed&utm_medium=web&embedding_publication_id=1151841) [ Jiang Feng on Germany's 2025 and beyond: no easy exit ](https://www.eastisread.com/p/jiang-feng-on-germanys-2025-and-beyond) Yirui LI and Yuxuan JIA · Jan 24 The following is an op-ed by Jiang Feng, published on 29 December 2025 at Shanghai Observer 上观新闻, the digital platform of Jiefang Daily, the official newspaper of the Shanghai Municipal Committee of the Communist Party of China (CPC). [ Read full story ](https://www.eastisread.com/p/jiang-feng-on-germanys-2025-and-beyond)
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Research funders are asking how they can stop confidential scientific ideas in grant proposals from leaking out through large language models (LLMs), for example if reviewers use AI to help them judge applications. Last week, a row erupted in mathematics after OpenAI announced it had solved a notoriously difficult problem, only for another mathematician to demand answers over whether the company had used ideas he had fed into its models. The spat, and the broader issue of idea leakage through AI models, was discussed by funders at an R&D policy conference held in Paris on September 14. At worst, it threatens to undermine the correct attribution of breakthroughs, one of the foundations of modern science. The mathematics dispute around OpenAI is “certainly something we're looking at” Jason Gallo, head of the newly established Office of Metascience at the US National Science Foundation (NSF), told the Blue Sky Forum, hosted by the Organisation for Economic Co-operation and Development. The controversy started on September 8, when OpenAI announced it had cracked a mathematical problem that had gone unsolved for 90 years. Using a swarm of AI agents, millions of dollars’ worth of computing power and a new internal model, the company said it had finally proved that a long-used formula for modelling fluid dynamics breaks down under certain conditions. However, Tristan Buckmaster, a New York University mathematician who had been independently working with collaborators on the same problem using OpenAI’s Codex tool, hit back with a statement questioning whether the company had snooped on his Codex sessions to gain an advantage. OpenAI has always denied it looked up the “specific user data” of Buckmaster and colleagues. However, the company initially admitted that “while unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models,” although its proofs “differ significantly” from Buckmaster’s. The firm later said that, following an investigation, it concluded that Buckmaster’s Codex prompts “could not have influenced the [OpenAI] system in any way, including through training.”Funder concernYet OpenAI’s initial admission that its model might have ingested Buckmaster’s ideas, then spat them out to its own mathematicians, has scientistsworriedthat their work could leak out if shared with AI. Some AI tools give users an opt-out option to stop their sessions from training the model. If such guarantees can be trusted, this gives scientists some confidence they can use an LLM to develop an idea without the risk of it leaking out.But there’s a bigger potential vulnerability. To win money to investigate ideas, scientists have to share them with funding bodies. These grant proposals are normally kept strictly confidential, to prevent other scientists from scooping them, or to protect commercially valuable intellectual property. To preserve this confidentiality, when the NSF uses AI models, “we have to be sure that it's not making server calls out to an external party, leaking that data,” said Gallo to delegates in Paris. Leaks through reviewersHowever, funders normally use external academic reviewers to assess proposals. And there are growing worries that these reviewers are feeding grant ideas into AI models to help them make a judgement. Research funders have noticed that peer review reports and funding recommendations have “suddenly become much longer, more detailed and complex,” said Diogo Machado, head of the data science unit at Technopolis, a science and technology-focused consultancy. “The sense is that reviewers are increasingly using generative AI in their review work, even where guidelines sometimes forbid it,” he told Science|Business. “This is very difficult for funders to control or prove.” Happening at scaleThis sharing of confidential proposals with AI models is “happening at scale already,” said James Wilson, executive director of the Research on Research Institute, based at University College London, during the debate in Paris. In response, Gallo said the NSF had “strict guidance” around the uploading of proposals to AI models. But he added the NSF was mulling new types of assessment to make sure applicants were truly the originators of their ideas, such as following a short-form proposal with an oral presentation, which would allow the foundation to “really interrogate the investigator on their intellectual contribution.” Related articlesHow can Europe cope with a flood of AI-assisted research grant proposals?The risks and benefits of AI in screening research grant proposals Viewpoint: AI could make scientific overload worse“For us as funders, a lot of the ways to ensure that the application remains the applicant's own intellectual contribution, those ways are quite regressive,” Peter Clifford, head of strategy at Research Ireland, told delegates. “They're maybe ten or 15 or 20 years old, and they don't scale particularly well.” Disputes over the origin of ideas are as old as modern science. Isaac Newton and Gottfried Wilhelm Leibniz spent more than a decade arguing over who invented calculus, for example. And long before LLMs emerged, academics would agonise over how much of their early work to reveal at conferences, in case their colleagues scooped them, Jack Leahy, a senior metascience advisor to the UK government, told delegates. But AI was “accelerating” the “problems of the system,” he said.
What Does the Science of Climate Change Really Look Like?
Editor’s Note: This is the second in a three-part series on how the Right should think about environmental and climate policy. Read Chris Barnard on Reclaiming Environmental Policy from the Left. More than a decade ago, the world’s governments negotiated and signed the Paris Climate Agreement, committing to hold global warming well below 2 degrees Celsius. In the following years, climate had immense cultural power. Greta Thunberg emerged. Fortune 500 companies established net-zero plans. The U.S. got the Inflation Reduction Act. Then the pendulum swung back. President Donald Trump returned to the Oval Office, speaking of green energy as a “scam” and carbon footprints as a “hoax” and on all matters of international policy emphasizing bilateral engagement and power over globalism and cooperation. The technology companies that had been at the forefront of net-zero pledges and green leadership discovered the importance of all-of-the-above power to their visions for artificial intelligence and began quietly postponing or removing their targets. On the left side of the political spectrum, rising concerns about inflation and cost pushed climate lower down in the stated priorities of voters and stump speeches of politicians. The moment is ripe for a reset on the politics of climate change and for conservatives especially to chart a course that acknowledges and addresses the real challenges in plausible ways. So what should we think about climate change as we enter a post-peak climate era? If it is neither an apocalypse nor a hoax, what will hold up as a durable view of climate change? And how does it project onto the concerns and priorities of the right-of-center’s emerging coalition? New to Commonplace_? Subscribe below to get the magazine in your inbox._ Subscribe A Solid Foundation As the politics and economics of climate careened over the past ten years, the physics carried on regardless. In 2015, the year the Paris Climate Agreement was adopted, the world emitted 41.2 gigatonnes of carbon dioxide. By 2025, emissions had risen only 2.4%, to 42.2 gigatonnes, because falling emissions from land use offset increasing emissions from fossil fuels. But slow growth in annual emissions is not rapid decline, let alone net-zero, so carbon dioxide kept accumulating in the atmosphere, going from 399 to 426 parts per million. Global temperature kept rising too, from about 1.1 degrees Celsius above the 1850–1900 average in 2015, to 1.4 degrees above it in 2025. None of this should surprise anyone. Even most prominent skeptics, like the authors of the 2025 report commissioned by the Trump administration’s Department of Energy, accept the basic physics. Carbon dioxide added to the atmosphere at industrial volumes accumulates and traps heat that would otherwise escape to space. That heat warms the upper ocean and increases temperatures at the surface. Increased ocean heat and melting of land ice cause sea levels to rise. Changes in the climate become noticeable to us as subtle shifts in temperature and precipitation, seasons arriving early or late, changes in the surrounding ecosystem, and weather extremes. The much more meaningful debate is not about whether these things are happening, but about what it all means for human societies. (While it is a proxy measure of overall risk, no one experiences global surface temperature.) This debate invokes at least three interesting questions: how much today’s warming is showing up in regional climate trends, how much more warming we should anticipate, and how extreme weather events can be understood in the context of climate change. Recent scientific advances give us new insights into each of these, but there is still much to learn. This is the context in which the next generation of conservative leaders will be the first to deal with significant climate change as a fact, not a forecast. It will be with them for their entire careers. Our evolving scientific picture of climate change will come from weather and climate records stretching further into the past, new kinds of observations in the present, better modeling tools for the future, and simply more time to observe the emergence of climate signals and their tangible effects on ecosystems and communities in the United States and around the world. The policy landscape will be shaped by not only the impacts of changes in the climate, but also by the ways in which societies respond and by the emergence of new technologies for both altering the trajectory of emissions and adapting to new climate realities. Global climate records now show the fingerprints of warming in different phenomena around much of the world. The IPCC, in its most recent assessment report, documents warming trends over all land regions, even as natural variability adds substantial variance to local trends. And the highest temperature extremes have become more intense and frequent, almost everywhere, since the 1950s. Scientists are highly confident that these changes are attributable to human influence. But confidence in detecting trends and attributing them to human influence degrades across heavy precipitation events; drought trends are heterogeneous and not attributable to human activity with great confidence. For hurricanes, tornadoes, and other severe storms there is even less confidence in trends or their relationship to climate change. In general, a fair summary of the evidence is that for well-observed phenomena, like surface temperature or heavy rainfall, with a clear relationship to warming, our multidecadal observations are consistent with human influence overcoming natural variability over long time periods and extremes increasing. For regions that are sampled more sparsely, or phenomena with a higher noise-to-signal ratio, we will need to observe them longer to understand the magnitude of the climate signal or improve dynamical understanding using models and observations together. But for Climate For those who can’t wait, we also have new techniques that attempt to understand the role climate change has in influencing particular extreme events. When the climate is changing and disaster strikes, it is natural to ask whether that disaster was somehow “caused” by climate change. For scientists and policymakers acting in good faith, answering that question helps develop a more accurate picture of the problem, how it may be getting worse, and what preparations we should be making to respond to it. It may, at some point, give some weight to how liability is assigned by courts or adaptation funding is distributed by society. But how we ask this question is extremely important. It is easy to get the analysis wrong by discounting the role that meteorology plays. As meteorologist Theodore Shepherd explained in a clear 2016 review of climate attribution methods, “if a weather or climate event is truly extreme in the present climate, then perforce it requires unusual meteorological conditions, which means that climate change is at most a contributing factor.” Share Scientists have two ways to probe climate as a contributing factor, both of which have entered media coverage of extreme weather events. One asks a probabilistic question: How much more likely is a particular event (e.g., a temperature record over a particular area) amid global warming? The answer involves using historical records and computer simulations to estimate the likelihood of such an event in both a changed and a preindustrial climate. The findings are less about the specific event, and more about events of that nature. The other question is: How has the changed climate affected the specific event in question? Here, scientists try to understand what a similar event would have looked like in the preindustrial climate. This is sometimes called the storyline approach, where the story is the specific meteorological details of the event. These methods offer ways to test the intuition of scientists about real weather extremes. In late June and early July of 2021, a persistent high-pressure ridge, or heat dome, set up over the Pacific Northwest and an extraordinary heat wave affected the area from Oregon to British Columbia. For six days, it shattered temperature records across the region and hundreds died from heat-related causes, in an area where such high, and persistently high, temperatures were well outside of experience and many live without air conditioning. Scientists have studied its connection to climate change using multiple approaches. This specific event was created by a rare combination of meteorological factors, a strong high-pressure ridge created the conditions for extreme heat, which occurred on top of higher average temperatures in the region from global warming. Probabilistic analyses showed that climate change increased the likelihood of such an event by at least 8-fold to more than 100-fold. One standout example found that such an event had effectively zero probability of occurring in the preindustrial climate. The enormous range in these assessments reflects how hard it is to estimate probabilities of events at the tail of the historical record. Estimates of the effect on the temperature of the event are more clustered. A recent review paper documents how multiple methodologies have found a positive influence, roughly 1-2 degrees Celsius of an anomaly that exceeded 15 degrees, of climate change on the temperature magnitude of the event. Multiple studies have investigated and found some positive influence of climate change in other extreme events. Attribution studies found climate likely increased the heavy rainfall that accompanied Hurricane Helene in North Carolina and surrounding regions in 2024. The extensive fires that struck Los Angeles in 2025 illustrate how the causal chain can become messy, though. Studies do detect a positive influence of climate on the event’s likelihood, but while climate change likely contributed to underlying aridity, it would not have played a role in the heavy winds or land practices that preceded disaster. These event attribution studies will become more common for extreme, or damaging, weather events. They can be produced quickly, and often are reported before peer review. As the Pacific Northwest heatwave example shows, when multiple methods converge on a positive attribution, the finding should probably carry some weight even if you have to be careful about accepting the results from a single study. I expect that as climate change proceeds and the climate thus departs further from a preindustrial counterfactual, the influence will become more detectable across a variety of extreme events and more easily identified. This will be used to cast blame, but can also be used to inform how communities and society adapt to ongoing change. We May Still Be Surprised One positive development, insofar as less climate change is better, has been that our central estimates for future climate change should probably be revised downward. Mostly, that is because the high-end warmings that scientists regularly analyzed about ten to 20 years ago, driven by high emissions throughout the twenty-first century, now appear to be somewhere between unlikely and impossible. At one time, the upper end of mainstream climate projections extended well into 4 to 6 degrees Celsius of warming by the end of this century, which, models suggest, would have wrought enormous real-world damage. Current energy and policy trends now point toward 2.5 or 3 degrees. Damages and risks are commonly modeled as increasing steeply with more warming, so this is already a better-than-previously-expected outcome for the climate (which is independent of the physical response to emissions). But we should maintain a wide range for plausible outcomes and prepare for the possibility of being surprised. Emissions trajectories are subject to deep uncertainty, the physical climate response is still developing, and whatever change occurs in the climate will then be mediated through unpredictable economic, social, and political institutions. Over the past decade, the pace of warming surprised some keen observers and appeared to accelerate, though not yet outside the range of expectation provided by climate models. The reasons for that apparent acceleration are being actively studied (as was the apparent pause in warming from 1998 to 2012), but no single driver has emerged. Some blame it on the El Niño, variability which would have no bearing on climate. Some think it is a result of factories in East Asia and global shipping fleets cutting aerosol emissions, which in the strongest version of the argument would indicate higher climate sensitivity to carbon-dioxide emissions. Others are more measured, not yet ready to draw solid conclusions as to whether climate projections require revision. We will have to see. Long-Term Thinking Climate change asks us to think over long time scales. But the pace of human-driven warming is compressing a large global change into a century. Changing weather patterns and extreme events are already causing adjustment costs and damages and will do more. Adaptation will help, but it is not free. For some communities, these costs will erode livelihoods and well-being, and may force migration. Are we prepared for large-scale managed retreats in the United States? Thankfully, American wealth, geographical diversity, and moderate climates may leave us better prepared than many around the world. But wealthy countries can still suffer serious disruption from narrowly concentrated costs, even if they appear entirely manageable in aggregate. Readers of Commonplace are familiar with the challenges of rapidly adapting to economic forces. The displacement that came from the China Shock is barely perceptible in aggregate GDP and employment data, but it affected millions of people and those people were far less mobile than economic models tended to assume. Deindustrialization rippled through the nation with enormous effects for not only our economic vitality, but also our national security. The forces surrounding climate change may not be so different; the world gets richer and must accept some diffuse costs. Those may be modest overall, but cause all manner of unpredictable effects with which policymakers must cope. In the case of the China Shock, our faith in a growing pie served us poorly. We’ll need to do better on climate. Leave a comment
“Survivor” star Kellie Nalbandian and wife Gabby were cast on “99 to Beat ”during honeymoon
The dynamic duo also names the Survivors that should play next.
North Carolina’s Southeast welcomes new Director of Business Development Savannah Taylor
Savannah TaylorSavannah Taylor, a career economic development professional, has accepted the role of director of Business Development at North Carolina’s Southeast. She officially started in the position on Sept. 14.“North Carolina’s Southeast’s success has long been based on strategic collaborative engagement and leadership among our team and with our partners, so a key aim was to find someone who aligned with those dynamics,” said NCSE President Steve Yost in a press release. “Savannah has strong experience for this position through her previous roles in local economic development, research, and policy development, and it became clear that she would be an excellent match in helping to advance the mission for our 20-county region. We couldn’t be more excited to welcome her to the Southeast.”Before joining the Southeast team, Taylor lived and worked in Georgia as an economic development project manager for the City of Marietta and as public policy & research manager and research director for the Georgia Chamber of Commerce Foundation. She has successfully led public policy and strategic project initiatives related to statewide community development and has served on several special committees, including the Metro Atlanta eXchange for Workforce Solutions Research Committee and the United for ALICE Georgia Research Advisory Committee. “After previously working at the state and local level in Georgia, I knew I was looking for a local or regional organization as my next step,” said Taylor in a press release. “I wanted to find a highly collaborative environment, and that led me to North Carolina’s Southeast.”Taylor graduated from Georgia College & State University with dual degrees — a B.S. in Economics and a B.A. in World Languages and Cultures. “I’m really looking forward to interacting with the organization’s partners and all of the local developers,” said Taylor in a press release. “Overall, I think I’m most excited for the new adventures with all the hiking and biking and everything else there is to explore in the region. I hope if anyone has any recommendations, they’ll share them!”