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Phantom Blade Zero made $223M on Steam and PS5 in five days
Phantom Blade Zero was always going to be a hit. We’ve been banging on about it for months now. Well, the results are in, and Phantom Blade Zero has indeed been a hit. Yesterday, S-Game reported that Phantom Blade Zero has sold 4M copies. As of this morning, our estimates show that Phantom Blade Zero has generated $223M via 4.3M copies sold across Steam (3.1M) and PlayStation (1.2M). This instantly makes Phantom Blade Zero this year’s #10 new 2026 game by premium revenue across Steam, Xbox, and PlayStation – and without an Xbox release to boot. Want more free estimates and insights in your inbox twice a week? Subscribe below! Subscribe Combined, China, Taiwan, and Hong Kong account for 55% of Phantom Blade Zero’s copies sold – 56% of copies on Steam and 50% on PlayStation. But revenue is slightly different. Phantom Blade Zero actually made more revenue outside of China However, due to regional pricing, China, Taiwan, and Hong Kong account for a lower share of revenue, 45%. The three countries account for 40% of Phantom Blade Zero’s revenue on PlayStation, and 47% on Steam. This is due to regional pricing, which you can easily check in our platform: Using the $59.99 USD base price as a starting point, we can see that Phantom Blade Zero costs the equivalent of $40.31 in China (-32.8% of the US price) and $41.80 in Hong Kong (-30.3%). So while Chinese culture is at the heart of Phantom Blade Zero (in terms of theme and player base), it’s actually making more money in non-China markets. In fact, markets outside of China, Hong Kong, and Taiwan account for $123M in Phantom Blade Zero revenues via 2M copies. Even when we remove revenues from these markets from the analysis, Phantom Blade Zero remains a top 20 new 2026 title by revenue across Steam, Xbox, and PlayStation. Want more free estimates and insights in your inbox twice a week? Subscribe below! Subscribe In other words, Phantom Blade Zero is a global hit. It’s not all China – or even majority China, when it comes to revenues. The China spring board helped, but a successful State of Play and – more importantly – positive reviews helped this one land in other markets. Quality sells. China was hyped from the start, but Western players needed more convincing As we wrote back in August, China was always going to show up early for Phantom Blade Zero. Our daily Steam revenue data shows just that, and we can see when S-Game’s banging RPG won over players outside of China: On the day Phantom Blade Zero’s Steam pre-order button went live in mid-August, China accounted for nearly 70% of Phantom Blade Zero’s Steam revenue. The shares hovered around 68% throughout August. This is the hometown-hero effect we’ve covered in the past, with the home market committing first – almost sight unseen – on national pride and a lush-looking trailer alone. Then things get even more interesting. Following the State of Play on August 18, US daily revenue more than doubled (from $72K to $146K), China’s daily take nearly quadrupled ($237K to $892K), and the rest of the world’s revenues also more than doubled. As China spiked so much harder than the others, its share of revenue hardly moved, holding at around 68%. So the by-all-counts-awesome State of Play got non-China markets and the West interested (you can see daily spend jump), but it didn’t move the needle for overall revenue shares. Positive reviews were the Western tipping point. US daily revenue went from $106K on October 25 to $230K when the embargo lifted on the 26th, to $463K on the 27th, to $899K on the 28th. So nearly 8.5x more revenue in four days, boosted by the positive reviews and subsequent word of mouth. When Phantom Blade Zero launched on the 29th, things hit critical mass. On launch day, the US and the rest of the world combined out-earned China for the first time in Phantom Blade Zero’s whole pre-order history. You can see this unfolding pretty nicely in the revenue shifting shares, too. China’s lifetime revenue share sat at 68% in August and was still 65% as late as October 25th, but it dropped to 45% by November 2. Over that same period, the US nearly doubled its share from 10% to 18%, and the rest of the world climbed from 25% to 38%. Want more free estimates and insights in your inbox twice a week? Subscribe below! Subscribe That’s not to say that China sold less – far from it. The West and non-China markets just showed up later, won over by the reviews and word of mouth. However you look at it, Phantom Blade Zero has become one of this year’s highest-grossing premium games. Daily volume seems to be decelerating a bit (which is natural), so subscribe below for more updates on performance. Speaking of performance and deceleration… Gran Turismo 7 is one of PlayStation’s biggest earners While games like Ghost of Yotei, Helldivers 2, Astro Bot, Wolverine (2.7M now, by the way), and even Marathon and Saros tend to get all the headlines (we hold our hand up there, too!), there’s one PlayStation game from the past five years that’s earned more than all of these games: and it’s one that’s rarely talked about in enthusiast circles. Gran Turismo 7, which launched in March 2022, has sold 12.7M copies. This amounts to $840M in revenue, second only to Spider-Man 2’s $1.3B – if we’re talking PlayStation first-party for this generation. Gran Turismo 7 still brings in around 3M players every month (and between 400K and 700K active players per day). It’s also an evergreen seller every year. For example, Gran Turismo 7 generated: $189.7M in 2023 via 2.9M copies $161.3M in 2024 via 2.7M copies $119.1M in 2025 via 1.7M copies This year, Gran Turismo 7 has already sold 1.3M copies, generating $74.7M And there’s more laps to come Every December is comfortably GT7’s biggest month of the year (except launch), and the gap is widening there. December generated 2.1x a normal month in 2023, and by 2025 that had grown to 2.8x. Want more free estimates and insights in your inbox twice a week? Subscribe below! Subscribe As the typical months cool off with age, Christmas always holds strong, so the holiday period is becoming a bigger slice of Gran Turismo 7 yearly revenue. For Gran Turismo 7, the week around Christmas does 3x to 5x a typical week – three years running: Christmas week 2023: $14.7M (4.6x the year’s median week) Christmas week 2024: $9.3M (3.3x) Christmas week 2025: $8.5M (4.6x) These Christmas peaks happened at the full $59.99 (Gran Turismo 7 wasn’t discounted at all in December 2023 or December 2025). And although there was a discount late in December 2024, GT7’s peak week that year still happened at full price. You can really see why PlayStation hasn’t added this one to PlayStation Plus, eh? Say it after me: Subscriptions cannibalise premium revenue! On that note… Let’s take a quick look at how Gran Turismo 7 is doing versus its nearest competitor, Xbox console exclusive and long-running sim racer Forza Motorsport (released in 2023 as a reboot for the franchise, about 19 months after GT7). Forza Motorsport has sold around 1.3M copies across Xbox (75.4% for Xbox console and PC) and Steam (24.6%), grossing $89.9M across those platforms. Launch aligned, and on just PlayStation, Gran Turismo 7 had sold 10.2M copies, generating $676.1M, by that point. In other words, Gran Turismo 7 has sold the same number of copies this year as Forza Motorsport has sold since launch. When all is said and done, Gran Turismo 7’s 2026 revenues will have lapped Motorsport’s lifetime, too. It’s worth noting that Forza Motorsport was not released on last-gen consoles, and under a quarter of Gran Turismo 7’s revenue has come from PS4 consoles. Critically, Forza Motorsport is also on Game Pass, where nearly 7M players have accessed it. Meanwhile, the Forza Horizon series has been performing incredibly in terms of revenue. This year’s Forza Horizon 6 has generated $583.7M across Xbox and Steam despite Game Pass cannibalisation, and last year’s Forza Horizon 5 PlayStation port has generated $383.5M on PS5 alone. So two questions, then: How well is Forza Horizon 6 going to do when it launches on PS5 in January? Hit subscribe to get that in your inbox in January (which is in two months somehow!?) Subscribe 2. Open-world arcade Gran Turismo when? Also, if you like arcade racers, go and play Star Wars Galactic Racer. It rules. Like GOTY material, seriously. The last word Reply to this email – or reach out here – if you have any feedback for the newsletter – or want to request a game for us to cover. [Alinea Analytics boasts the most accurate PC and console estimates in the business. Game makers use our platform to understand their audience, keep an eye on the competition, monitor sales trends, and spot new opportunities. We equip game studios and financial institutions with accurate data and the confidence to make smarter, data-driven decisions. Want to talk about all things games market data? We’d love to chat!]
Who Controls Enterprise AI Agents? Data Platform Vendors Race to Provide the Answer
AI agents are everywhere. Every other news story is related somehow to AI agents. As more companies are starting to use AI agents, keeping track of what they’re doing isn’t so straightforward. Dataiku launched Agent Management in September, and Oracle spent part of its AI World conference in October talking about how businesses can keep […]
‘The Traitors’ star Abby Lee reveals the craziest Traitors-catching strategy we’ve ever heard
‘The Traitors: New Blood’ star Abby Lee just revealed the craziest Traitors-catching strategy we’ve ever heard… and it somehow also involves fruit.
Science fiction writer John Scalzi discusses his novel 'Monsters of Ohio'
In a small town in Ohio, farm animals and people start turning into monsters. But somehow they seem happier that way, in John Scalzi's novel "Monsters of Ohio." He talks to NPR's Ayesha Rascoe.
Curt Cignetti blew it. Indiana’s title defense somehow survived
Curt Cignetti’s clock-management blunder nearly cost Indiana a win over Minnesota and could have put the Hoosiers’ national title defense in peril.
8 Tennis Statistics That Sound Completely Made Up But Are Somehow True
You could almost say that tennis is a perfectly sensible sport until you start looking at the statistics. Spend enough time examining its history, and you will discover that some of the greatest players ever were apparently incapable of winning a match at certain tournaments, that two famous rivals somehow avoided each other on an …
Somehow, The Legend Of Zelda Switch 2 Walmart Fumbled Pre-Order Saga Has Gotten Messier
It sounds like the retailer is holding sales back until next week
A golden age of science is coming
It’s almost hard to remember, but just a few years ago, a lot of very smart people thought that science was in terminal decline. Respected researchers were writing papers with titles like “Are Ideas Getting Harder to Find?”, “Papers and patents are becoming less disruptive over time”, and “Slowed canonical progress in large fields of science”. In 1996, science writer John Horgan even published a book called The End Of Science: Facing The Limits Of Knowledge In The Twilight Of The Scientific Age. The fundamental idea was that the Universe only has so many insights to discover, and that we’ve picked the low-hanging fruit. It was the idea that Joseph-Louis Lagrange expressed when he said that “we cannot find more than once a system of the world to establish.” As the big ideas and the simple ideas get mined out, we’re forced to throw ever more brains at the mysteries of nature just to keep scientific progress going at a fraction of its old pace: It looked like science was hitting a wall. Then along came AI. It’s far too early to tell how much AI will eventually speed up the growth of total factor productivity. But already we can see signs of a speedup in science. Anthropic Founder Jack Clark assembled some of the hopeful data points in a recent lecture: [ Dror Poleg@drorpoleg "If you pick different parts of science, you see the same pattern show up: Progress is accelerating, and it has started to accelerate in the last two years." Jack Clark @jackclarkSF I’m speaking at the IMF in an hour about the singularity and why I believe it has begun and the choices we'll need to make. Watch live here: https://t.co/Hj9HzcXx5h 6:08 PM · Oct 18, 2026 · 21.2K Views 2 Replies · 10 Reposts · 123 Likes ](https://x.com/drorpoleg/status/2111882070376980529) Anthropic is accelerating its investment into drug discovery, and is already announcing some impressive preliminary results: [ BioTender@Junioryu136689 BREAKING: Anthropic unveils early results from six Claude-powered drug development collaborations. • 70% shorter CAR-T signaling domain • ~35,000 antibody designs • >10× tighter antibody binding • 89% less batch-record review time Still largely preclinical. Anthropic @AnthropicAI Over the past few months, Anthropic scientists have engaged in deep research partnerships with six organizations developing new medicines. We've also begun drug discovery efforts of our own. In doing so, we’ve learned much more about how Claude can support the many stages of 9:43 PM · Oct 27, 2026 · 11.2K Views 3 Replies · 24 Reposts · 205 Likes ](https://x.com/Junioryu136689/status/2115197821150495150) Claude also appears to be enabling rapid progress toward a treatment for food allergies. OpenAI, meanwhile, announced a possible breakthrough treatment for neurodegenerative disease. Meanwhile, Google Cloud Chief Scientist Pushmeet Kohli has a list of recent scientific advances that have been enabled by its new Gemini model, including breakthroughs in nuclear fusion reactor design, rare disease research, and quantum computing: [ Pushmeet Kohli@pushmeet Gemini 4 Argon is a step change in model performance. In recent weeks, it has had a transformative impact on the Science projects in our team at @GoogleDeepMind and our external collaborators, and helped make a number of remarkable advances across scientific disciplines. 🧵👇 4:47 PM · Oct 13, 2026 · 36.5K Views 8 Replies · 41 Reposts · 497 Likes ](https://x.com/pushmeet/status/2110049807385702623) But as cool as these stories sound, they’re just very minor, preliminary efforts. There are a number of reasons to think that AI is going to propel us into a golden age of scientific discovery. That age might not last forever — AI might still run into diminishing returns eventually. But the next few decades are probably going to be an absolutely amazing time for human science. The number of “effective researchers” is no longer limited The most important input into science is scientists themselves. Until this year, that meant human brains — talented, highly trained human brains. The number of trained human brains could be increased by sending more people to grad school, but only to a point — the smartest people tend to be sent into the hardest research fields first, and if you 10x the number of researchers, the average quality will go down. This constraint was already starting to bite, as Ekerdt and Wu argued in 2024: We argue that a substantial portion of the downward historical trend in U.S. research productivity is a composition effect resulting from self-selection in researcher ability and the dramatic expansion of the research sector…[W]e find that this composition effect has lowered average researcher ability by between 37% and 53%[.] And of course, low fertility was making the problem worse, because fewer children meant fewer people who were able to become future scientists. AI just blows up this constraint completely. If an AI agent can function as an autonomous researcher, there’s no constraint on the number of researchers in the world — you can just build more of them, by building more computer chips and data centers that enable the running of more AI agents. Whether or not massive hordes of agents can collaborate to solve individual problems much faster, increasing the number of agents allows them to tackle many different research questions in parallel. What’s more, these AI “researchers” can be trained incredibly quickly compared to human beings. A human scientist takes decades to train, and more years to reach the frontier of their research field by diligent reading and conversation. This is the “burden of knowledge”, and it’s commonly believed to be one reason ideas have been getting harder to find — by the time human scientists can get up to speed, they’re often so old that their ideas are no longer novel. AI just annihilates this constraint — it can assimilate the entire literature and reach the frontier of research extremely quickly, and it can also tell human scientists where the frontier lies without forcing them to discover that for themselves. It can also pivot to new research directions more easily than humans can. And there’s also a self-reinforcing economic cycle here. Because scientific advances enable higher GDP, they enable more resources to be invested into the creation of yet more electronic “scientists”. Now that doesn’t mean the amount of scientific research goes to infinity — there may still be some essential bottleneck task that human researchers are still needed to perform. There are some indications that AI’s progress on open-ended conceptual research tasks is slower than in other dimensions, and it may be that humans are still needed to provide some of this long-term conceptual thinking. I’d bet against this being true for much longer, but it might be true for a long time. Even in this most “pessimistic” case, though, the amount of effective capital that scientists can use to leverage their work just went up by a lot. AI eliminates the theory bottleneck Science proceeds by an iterative process of theory and experiment. The theory part of that cycle is typically short, but non-trivial — it took a couple of years after the blackbody radiation spectrum was observed for Max Planck to come up with the quantum hypothesis to explain it, and decades longer before quantum theory as we now know it was created. It took about a year for Watson and Crick to figure out the shape of DNA after the requisite data was gathered. AI will basically eliminate the theory bottleneck entirely — or at least shorten the turnaround time between experiment and theory by an order of magnitude. AI is an absolute beast at math. Recently, an OpenAI model solved some of the most important open problems in computer science, math, and theoretical physics, and no one even batted an eyebrow because that sort of triumph is becoming increasingly commonplace. One of those solutions was a proof that the Standard Model of Particle Physics could be mathematically well-defined — a problem that human theorists had so far been unable to tackle. Not all research relies equally on theory, but understanding novel experimental results almost always involves some important component of either mathematical or spatial reasoning. That part of the task has now been made much, much faster. And on top of that, science is now open to a greater number of humans who aren’t naturally good at theorizing. AI can read the whole literature Much of the work of human scientists involves reading and understanding endless amounts of papers and going to endless conferences and seminars. The purpose of that work is to understand the existing scientific literature. Understanding the literature allows scientists to do the following things: Come up with new ideas for hypotheses to test Avoid doing research that someone else has already done Synthesize approaches from different areas or fields AI can reduce this effort to almost zero. Consider this excerpt from OpenAI’s blog post about their new research into neurodegenerative disease: The team divided the analysis among thousands of AI agents powered by GPT‑Rosalind, an approach we call distributed biological reasoning. The agents examined a whole-brain CRISPR atlas…a dataset showing how gene disruptions affect different types of cells across the mouse brain. Each agent investigated a gene disruption, analyzed cellular responses, searched scientific literature, and proposed explanations for the results. Their reports were combined into a reasoning atlas linking genes, cellular effects, relevant publications, and possible biological mechanisms. The research team estimated that comparable human analysis and literature review, conducted one perturbation at a time, would take months to a year. The agents reproduced findings from human analyses while uncovering additional leads. Their assessments of novelty and scientific value also aligned with judgments from blinded human experts. These findings help prioritize further experiments needed to test the proposed biological mechanisms. Some of these insights point to new leads for understanding brain disease. [emphasis mine] This is one case in which parallel work by a large number of agents really does make a huge difference: [ Haider.@haider1 this is actually insane openai deployed thousands of GPT-Rosalind agents to analyze millions of mouse brain cells in 32 minutes, work that could take human researchers months to a year also the agents uncovered new leads for brain diseases like Alzheimer's and Parkinson's OpenAI @OpenAI GPT-Rosalind surfaced a new lead for drug discovery: could restoring cholesterol transport protect neurons from degeneration? DCTN1 is a gene linked to Perry syndrome, a rare neurodegenerative disorder. In mouse-brain data, disrupting it increased expression of genes involved in 2:41 PM · Oct 21, 2026 · 51.5K Views 26 Replies · 95 Reposts · 1.26K Likes ](https://x.com/haider1/status/2112917197903540516) Not only does instantaneous literature review vastly speed up the research process, but it allows AI to make novel conceptual leaps from combining approaches from wildly different fields of research. AI regularly does this in math research, combining results, approaches, and theorems from far-flung places that no human mathematician would have thought to combine. It can do it in science, too. Much of scientific innovation, historically, has been “recombinant” innovation — scientists applying insights from one field to another. With AI, essentially all research is now cross-disciplinary — AI can read not just the literature on a particular subject, but the literature on a million other subjects that might have produced useful techniques or insights for the problem at hand. Superscience So far, all of the factors I’ve listed are ways that AI can speed up science as it’s already done. I’ve basically described how AI can send gigantic hordes of superhumanly fast, superhumanly well-read, superhumanly mathematically gifted researchers to re-accelerate scientific discovery. But it’s also possible that AI will enable types of discovery — and ways of understanding the natural world — that no network of humans, no matter how large or how brilliant it was or how long it had to work, would ever be able to discover. In a post back in July, I wrote about how that might work: What if there are lots of…aspects of the Universe that [are] too complex to understand in terms of simple laws, but not so complex that they just dissolve into unknowable chaos? It’s possible that we can reliably control these complex phenomena with AI, even if we never reduce them to the kind of principles that we can teach a grad student in a textbook… Another way of saying this is that there may be laws of the universe that humans can’t understand but AI can. I call these “cloud laws” — causal regularities that can be exploited by technology, but which are too diffuse and complex for an individual human being to either intuit or communicate… Perhaps social sciences like economics, sociology, and political science obey similarly complex regularities, and AI can help us find them. Perhaps there are physical processes — plasma, or topological materials, or aerial turbulence, etc. — that obey cloud laws instead of chaos?… [H]uman collaboration is bottlenecked — it’s limited by our ability to intuit patterns at an individual level, and to communicate these patterns from one individual to another. AI, being a computer, just doesn’t have this sort of limitation; it can work with vast, diffuse patterns without having to break them into pieces or simplify them in order to compress them into the tiny pipelines of person-to-person explanation… If much of the Universe turns out to be ruled by cloud laws, we could be on the precipice of a scientific renaissance. In order to discover cloud laws, AI will need huge amounts of data about the natural world. AI figured out human speech by assimilating essentially all of the text humans have ever written. If it’s going to figure out hidden patterns in biology, neuroscience, materials science, etc., it’s going to need similarly massive amounts of data from physical instruments. That data will be far, far more than humans — individually or collectively — would be able to parse, label, characterize, or model. But AI was built to do this. If scientists simply build huge arrays of sensors to measure complex phenomena like the brain, the cell, the economy, etc., they may be able to feed this flood of data to AI directly and bypass human cognitive intermediation entirely. AI would then learn about the world directly, and it might learn things that humans never could. This “superscience”, if you want to call it that, would actually go beyond the kind of science humans have done heretofore. Many of the technologies it yielded would be beyond human comprehension — indistinguishable from magic. But to the AIs, they would make perfect scientific sense. In any case, it seems clear that the scientific slowdown that threatened human progress will now be delayed — at least for a while. Unless humans have somehow found most of the actual exploitable regularities in our Universe, we’re about to enter a new golden age of science. Subscribe Share
Bad interpretation of the Bible creates stupid conflicts between science and religion. (It’s poetry, not a textbook.)
Scripture functions best when it stays in its lane. The authors of the Christian scriptures were writing the gospel. The gospel was meant to be “good news” for all, not bad news for most. But somehow…
Toy Story 5, Backrooms and The Breadwinner Vie to Become the Second Biggest Film This Year...
(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.) Often, people blame “data” for ruining Hollywood, when I’d argue that hype (which can often be debunked by data) is often worse, as you can see in these two headlines. To use a common meme, here’s how it started: and how it’s going: Earlier this year, I read countless (and I mean countless) articles (in almost every mainstream media outlet) about how Heated Rivalry was a huge hit and that it “heated” interest in hockey. But Heated Rivalry wasn’t a huge viewership hit compared to the hype: [ ](https://entertainment.substack.com/p/you-cant-eat-buzzdid-heated-rivalrys) [ You Can’t Eat Buzz…Did Heated Rivalry’s Buzz Translate into Actual Viewership? ](https://entertainment.substack.com/p/you-cant-eat-buzzdid-heated-rivalrys) Entertainment Strategy Guy · Jan 22 [ Read full story ](https://entertainment.substack.com/p/you-cant-eat-buzzdid-heated-rivalrys) In this case, the hype (Heated Rivalry is really popular) belied the data (It didn’t make the top ten charts, meaning it wasn’t a huge hit.1) Even worse, every time I write about this, I get a lot of negative feedback, hence why I only sparingly mention the show these days or add lots of caveats when I write about it, but this just further cements the hype. But companies, and the executives leading them, have to determine strategy based on reality, not media coverage. The NHL committed real marketing dollars to a campaign that didn’t work. Sure enough, the latest NHL season opened to under a million viewers. At some point, you have to focus on what the data says, because real dollars are at stake. And that’s why we have the Streaming Ratings Report! To provide and analyze cold, hard data. Luckily, this week, I can be positive and take a look at a huge opening on streaming, along with a very buzzy horror film that customers kind of like, but don’t really love. And a comedy that tried to rebound on streaming. Today, I’m covering two weeks—21-Sep and 28-Sep—so we have a lot to discuss (nearly 5,000 words worth), including a series of film misses for Netflix, another argument for weekly-released TV shows on streaming, another sitcom tries to avoid the comedy curse, Netflix has two new game shows (one powered by AI), Reacher falling off the charts after a huge run, Prime Video tries its hands at the romcom game**,** a look at the WNBA’s big season, a big night for the VMAs on CBS and MTV, all the flops, bombs and misses, and a whole lot more. (Reminder: The streaming ratings report focuses on the U.S. market and compiles data from Nielsen’s weekly top ten viewership ranks, Luminate’s Top Ten Data, JustWatch and Reelgood interest data, Samba TV household viewership, company datecdotes, Netflix hours viewed data, Google Trends, and IMDb to determine the most popular content. While most data points are current, Nielsen’s data covers the weeks of September 14th to October 4th, 2026. You can find a link to my terminology here.) Subscribe Film - Two Hits and a Miss Come to Streaming… Three very interesting films came to streaming in one week, and I like comparing them since they show the range of theatrical films. One was a huge blockbuster, one was popular, and one was neither. One is a horror film, a buzzy genre; one is a comedy, a struggling genre; and one is an animated family film, the king of the box office. One went to a tiny streamer (HBO Max), one went to a second-tier streamer (Disney+), and one went to the biggest (Netflix). So… If you just went by box office, you’d expect Backrooms—the $197 million grosser, and partner of Obsession for “YouTube Horror Summer”—to dominate on streaming. If you read this report, though, you know that horror films don’t do great on streaming, and that’s the case again. Backrooms opened at 3.8 million hours according to Nielsen, and had 3.9 million hours in its second week. Here’s how that stacks up to other HBO Max films: 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… ...why I don’t buy Backrooms budget… …two new games shows arrive on streaming… …another sitcom struggles… ...another argument for putting out shows weekly on Netflix... ...and a whole lot more, nearly 5,000 words more... ...please subscribe! We can only keep doing this great work with your support. If you want an idea of just how much content you’d get in a full issue, check out this older issue. Coming Soon! Next week, I’ll be taking a look at the eighth season of Hulu’s The Kardashians, answering the question: will this show ever make the charts? If Mormon wives can make it, surely one of social media’s most popular families can as well. Also, Prime Video has a new horror show based on popular IP, Carrie, Netflix has a horror show starring Josh Hartnett, Below, and Apple TV has a UK import, Small Prophets. Plus a bunch of movies like Disclosure Day heading to Peacock, The Housemaid coming to HBO Max, Ben Affleck’s latest on Apple TV, Animals, and Matchbox the Movie on Apple TV, a John Cena action comedy inspired by Hasbro’s toy cars. The week after is even busier! I’ll look at another IP-based horror show, Crystal Lake, a new MCU show on Disney+, VisionQuest, season two of The Lowdown on FX/Hulu, the fourth seasons of The Diplomat on Netflix and Tulsa King on Paramount+, another season of Love is Blind, and four straight-to-streaming films: Netflix’s Sacrifice (starring Chris Evens, Anya-Taylor-Joy, Vincent Cassel, John Malkovich, Salma Hayek. Charlie XCX), Apple TV’s Tenzing (starring Tom Hiddleston and Willem Defoe), Prime Video’s Love of Your Life (Margaret Qualley) and Masterplan (Stanley Tucci) and a whole lot more, somehow. Long term, here’s some huge IP news: a Game of Thrones movie is coming to theaters, Game of Thrones: Aegon’s Conquest in 2029, while Jon Watts (who helmed three of the most recent Spider-Man movies) is directing the next Star Wars trilogy, to be written by Simon Kinberg. I’m cautiously optimistic for both. It feels obvious to say that making good movies matters, but for bets this big (Star Wars is on a swoon, Game of Thrones hasn’t been to theaters yet), the quality has to be there.
David Hamilton powers Brewers to World Series
Is everything in baseball actually about the Red Sox, even when it’s not about the Red Sox? Somehow I feel like the answer is yes. The Milwaukee Brewers defeated the Los Angeles Dodgers last night to complete a four-game sweep of the NLCS and reach their first World Series since 1982. The first out of […]
Entertainment RX: Matthew Gilbert's recommendations for the grieving
Entertainment RX is an entertainment-guided advice column offering things to read, listen to, or watch that somehow address — or, in some cases, distract from — the issues readers write in about.
Three Positives From the Week of October 4th
Here’s hoping it can somehow get better than a double-record-breaking week.
The Sometimes-Awkward Art of Asking for a Second Opinion
A doctor has recommended a course of action that is invasive, expensive, or somehow different from what you'd prefer. Is it OK to get a second opinion? The answer is yes. Here’s how to make the ask a little less awkward.
No Man's Sky is somehow coming to mobile, and Hello Games says it's partly thanks to Light No Fire
No Man's Sky is coming to iPhone and iPad devices with every single update, and "some of those changes have come from Light No Fire."
‘SNL’ cut ‘Shape of Water’ sketch was makeup vet’s ‘biggest heartbreak’
‘SNL’ makeup vet Louie Zakarian detailed a ‘Shape of Water’ sketch. Pete Davidson ‘somehow broke his arm that week,’ he recalls.
Winning Ugly
Sometimes in the NFL it’s really about surviving. There are weeks where your team desperately needs a win. It doesn’t matter how you get that win. You just have to get it, someway, somehow. The Jets faced one of those moments in Week 5 against the Cleveland Browns. A loss would have sent the team […]
Eagles' Jalen Hurts Somehow Rises in NFL QB Rankings Despite 'Ugly' Week 4 Numbers
How is this possible?
GTA VI leaks continue with a lengthy (and very nude) gameplay video
Somehow, Cyberleek returned with more GTA VI footage.
Ole Miss vs Vanderbilt: A CFB27 Simulation
Someway, somehow, EA Sports has the Vanderbilt Commodores ranked 18th in the polls. Not how the Vandy season has gone in real life. The game simulations are never 100% accurate, but that one seems a little wild. Well, for the second straight contest, Ole Miss is headed on the road, and in the video game […]
Who Won August and September: Original Films or Franchises?
(Welcome to the Entertainment Strategy Guy, a newsletter on the entertainment industry and business strategy. I write a weekly Streaming Ratings Report and a bi-weekly strategy column, along with occasional deep dives into other topics, like today’s article. Please subscribe.) I just heard someone say that if you’re reading a pundit or data analyst, and they don’t tell you that they got anything wrong, they’re not a pundit but an “influencer”. I agree with that. You have to tell your audience when you get things wrong, or they won’t (or shouldn’t) trust you as much. Today, we’ve got another edition of “What I Got Right, What I Got Wrong”. In general, I’m patting myself on the back (and patting very hard) about a few things like IP at the box office, LIV golf, horror films, crowdfunding movies, superheroes, and old people going to the theaters. That said, I also made a couple of data mistakes on the streaming bubble popping and HBO’s datecdotes, so I’m not perfect. But first, I need your feedback... Subscribe Follow-Ups: What Should We Call Mid-Budget Movies Which Aren’t Cinematic Enough for Theaters But Are Too Expensive to Make Money on Streaming? After I asked for feedback on what we should call straight-to-streaming films that are too big to pencil out on streaming but not really big enough to resonate in theaters, I got some great suggestions from you all, including... “Moldilocks” from John Aboud “Little Big Indie” from Travis Frick1 “Midflicks” from Jonathan Funke. “Extra-Medium” from Jona Nwuke. (Read the explanation in the footnote.) Between these and Brandon Katz—who suggested “Bermuda Budget Triangle”, “The Platform Gap” and “The Distribution Deadzone”—we’ve got some excellent suggestions. And they’re better than my suggestion, the “Streaming Budget Dead Zone”, so let’s take a poll! The winning entry becomes the new term. Loading... RIGHT: LIV Golf is Fully Bankrupt…Is Anyone Else Next? A few years ago, I was always a bit perplexed at all the articles I’d read praising LIV Golf and their strategy to disrupt the PGA. LIV Golf, a brand new professional golf league, offered PGA stars ten times what they made on the PGA Tour to join their new league. And folks praised this strategy for its initial “success” in that a lot of big names did indeed leave the PGA. Yeah, of course the players came over. LIV Golf paid them so, so, so much more! But LIV Golf hadn’t discovered a way to increase potential revenue. So think about this in basic business terms… They paid much more in costs… …but had no real way to increase revenue. That’s not a strategy! That’s deficit financing. It won’t work unless you bankrupt the competition (and then turn around and pay those same golfers much, much less). It’s not a sustainable strategy and only lasts as long as the company/person/nation backing it decides they’re cool with losing money. For LIV Golf, that meant Middle East oil wealth, in particular Saudi Arabian money. Clearly, the current Iran War has hurt Middle East finances, so they need to trim their more exorbitant spending. And LIV Golf was part of that trimming. This should be a major warning for others. TGL’s parent company, TMRW Sports, just got a $1 billion valuation, despite TGL’s (the indoor golf league) horrible TV viewership of less than half a million viewers per match. Unrivaled, the women’s basketball league, just secured a $650 valuation, despite its horrible TV viewership and a new rival (Project B) entering the scene next year. To relate this to streaming, Hollywood should ask which streamers may have wealthy patrons funding their losses. (Let’s be clear: Google, Amazon and Apple.) Could those patrons lose their appetite? For Amazon, probably not. But Apple has a new boss, so maybe! WRONG: My Analysis of the Streaming Bubble Was Missing a Week I’m going to be congratulating myself a lot today, but I make mistakes too, like this data goof. When I last compiled the data on the decline in TV shows, I was missing one week at the end of June. If you look at the first image, you can see that one week was mislabelled as “July”. Mainly, this image got updated to show a 27% decline, not 29%: This change doesn’t really impact the overall analysis, but it is two percent better. By the way, through the third quarter, the decline increased and it’s now a 30% decrease since 2022. (I’ll write/visualize this in an upcoming article.) But I want you to trust me and my data. Especially these days, when many people are using LLMs that I know are inserting faulty data into their charts, I want to keep earning my audience’s faith. So that’s the accurate data. RIGHT: IP Remains Very, Very Popular In July, I wrote a giant (and I mean giant) article on Backrooms, Obsession, and the box office, going over what we know, what we don’t know about what works in theaters, looking at YouTubers, IP, the horror genre, comic book movies, and a whole lot more. The month of August really tested a lot of my theses and, being honest, mostly supported my arguments. Let’s start with IP. Looking at 8-Aug (the weekend after Spider-Man: Brand New Day came out) to 18-Sep (the weekend that Resident Evil came out, which I think provides a nice bookend to this time period), there were seven films based on pre-existing IP: Resident Evil (2026) ($126 million) Practical Magic 2 ($65 million) _Insidious: Out of the Furthe_r ($65 million) Coyote Vs. Acme ($59 million) Paw Patrol: The Dino Movie ($53 million) Tony ($15 million) Super Troopers 3 ($7 million) Compare those to the notable original films from the past month—I actually could have included more movies, but here are just thirteen, bringing us to an even twenty films—including.... The End of Oak Street ($54 million) Buddy ($26 million) Mutiny ($15 million) By Any Means ($15 million) The Dog Stars ($14 million) Runner ($14 million) One Night Only ($11 million) Hope ($8 million) Spa Weekend ($7 million) The Uprising ($6 million) Teenage Sex and Death at Camp Miasma ($6 million) Onslaught ($3 million) Eli Roth’s Ice Cream Man ($2.8 million) Here’s that in chart form: Five of the top six films in this time period were all based on IP. I made a big chart of films that grossed over $200 million at the box office before Spider-Man: Brand New Day and The Odyssey hit theaters. Let’s update that chart! By the way, if you want to see how I categorized each film—so another bar chart—here it is: I know that many of my fellow critics/pundits/analysts dislike films based on IP and how Hollywood is making so many of them. And I’m sympathetic to this point of view. As I’ve written many, many times before, you need a balance between existing franchises, new IP, and original films. And Hollywood clearly needs to make more films like Resident Evil (a well-made film from a visionary director) and fewer Practical Magic 2’s (which didn’t get critical or customer buzz). But at some point, critics and pundits need to contend with what audiences are telling them: Movie-goers aren’t showing up to original films. Audiences are speaking with their dollars, telling you they want more IP and franchises. You can try to convince studio heads to make fewer IP-based films and franchises, but the data and numbers aren’t there. Instead, critics need to work harder to convince audiences to show up for original films. Aim your ire/concern at the average person, not studio heads.2 Because they’re just making the films that audiences are telling them to make. WRONG: Original Horror Films Didn’t Break Out I’ll be honest, even though I wrote an article casting some skepticism on the horror genre in July, if you asked me to make a prediction, I would have predicted that, in August, a new, original horror film would have blown up. No, seriously, I just assumed that Obsession and Backrooms presaged a change in audience behavior. But none of the buzzy new original horror films from August—Teenage Sex and Death at Camp Miasma, Onslaught (not an action film in spite of the ads), The End of Oak Street, Eli Roth’s Ice Cream Man, or _Buddy—_broke out. To be clear, exactly one of those films (Buddy) had good “ROI”, but again—I try to be specific in my language—none were “popular” in any broad sense of the word. None of them will be “saving” movies theaters like Backrooms or _Obsession_helped save the summer. The new Insidious film and Resident Evil, both based on IP, were far and away the biggest horror films since July. (We’ll see if this changes in October/Halloween season.) RIGHT: Stay Skeptical about Crowdfunding... I’ve long been skeptical about crowd-investing platforms as one of Hollywood’s saviors, mainly because there’s so much hype/buzz. People need to stay more skeptical about more things, explaining both the potential upside but also the downsides. In particular, the media often hypes crowdfunding at the start and never checks in on the actual results after they’ve come in later. And August gave us our first update! _Ice Cream Man—_directed by Eli Roth—grossed $6 million off of a $5.5 million budget. This is a production of The Horror Section, which was one of the first “crowd investing” studios with 2,400 investors, which means that 2,400 investors probably lost money. They certainly aren’t getting as great of returns as if they had just invested their dollars in the stock market. Hopefully Stiletto (Tagline: “Someone’s Going to Make it Rain Blood!”) does better next month. WRONG: Another Data Goof Here’s another data error. When the first episode of House of the Dragon came out, HBO put out that it had 21.5 million viewers in the first three days, and I read that to mean in the US…but no, it was global. So my US-only datecdotes charts shouldn’t have included it. We never got US-only numbers for the first episode, but for the final episode, HBO put out that it had 11 million US viewers. (And that global dropped to 21 million viewers.) Here’s the updated chart (which I’ve since used in the Streaming Ratings Report): Still, this show is absolutely huge. RIGHT: Superhero Films Remain Very, Very Popular After Supergirl flopped, I read a few takes that “comic book movies are going the way of the Western”. Post-Spider-Man: Brand New Day, that take didn’t age well. To be fair, I have a very nuanced take on the superhero genre right now; it’s down right now, for a lot of reasons. But it’s not “dead”. Maybe _Spider-_Man is just a really popular character? I saw that take, and it’s a fair counter-argument. (But pundits arguing that superhero movies were dead should have mentioned this $1.5 billion counter-argument…) But is it just Spider-Man? The next Avengers film already has $50 million in pre-sales (and I was skeptical that that film would do well) and the Avengers: End Game re-release topped the box office two weekends ago (over three original films). And I wouldn’t bet against Batman or Superman. So maybe it’s just Spider-Man, Batman, Superman and the Avengers. Oh, and Deadpool, of course. And Black Panther. And Wolverine. And probably the X-Men. Plus a well-made Wonder Woman or the Hulk film could break out. But that’s it! It’s just those ten characters/teams. Oh, what’s that? Lanterns is also doing well on HBO? (See previous section…) To be fair, I’m actually pretty sympathetic to the argument that more popular characters—like Spider-Man and Batman—anchor more popular films. In fact, I made that exact argument three years ago when I first wrote about the “Marvel-cession”. In many ways, you can blame The Guardians of the Galaxy for fooling Marvel Studios (and the rest of us) into believing that any character could pop. It turns out, the list of iconic characters is probably smaller than most people think. But it’s probably too early to say that superhero films and comic book movies are dead unless “death” means a slight decline over a longtime. RIGHT: Who Killed Theaters? Old People I get frustrated whenever I see headlines or analysis about how young people are “returning” to theaters. As I’ve detailed(for years), young people have always powered the US box office, despite narratives about “kids these days” and their “phones”. Really, what’s changed post-2020/pandemic is that old people aren’t going to the movies nearly as much. This summer, I saw a movie (from an older director) in a theater near a retirement community, and multiple older people at the theater were talking about how this was their first time seeing a movie in years. I dislike personal anecdotes, so YouGov can fill in the data, best summarized by this headline: “Who killed movie theaters? Not the youths”. According to them, 64% of people aged 18-29 have seen a movie in the last year, but only 30% of 65-and-older. 20% of 18-29 have seen a movie in theaters in the last week and 42% in the last month. Here’s the polling data: Most concerning? Many Americans (17%) think theaters are a worse or much worse experience than watching films at home. Slight WRONG: Hadestown Opens Big A live theater capture of the Broadway musical, Hadestown, made $20 million at the US box office, which begs the question: was I wrong to be skeptical about musicals a few years ago? Yes and no. On the one hand, $20 million is a far cry from being “popular”, so yeah, the genre isn’t that popular overall and Hadestown is one of the more popular musicals from recent years (i.e. the “Taylor Swift Data Fallacy” in action). On the other, I doubt filming this cost all that much, and I don’t think that they spent much on marketing, so this is a good source of ancillary revenue. Smaller Updates WRONG: As I mentioned in a Streaming Ratings Report, I underestimated the budget for Enola Holmes 3. It probably cost more like $50 million, if not more. But... I’m not sure that it really matters? At sub-10 million hours, prices have to come down to make this work. WRONG: Netflix is giving Ink a 27-day in theaters! To quote the kids/YouTubers these days, let’s go! Now I might actually have a chance to see Danny Boyle’s latest in theaters. I’d complained about this in a “Coming Soon” section, but I was heartened to read that Netflix is giving multiple films longer theatrical windows this year. RIGHT: Netflix is sending 4-5 films per year to theaters. Netflix is slowly but surely sending more and more films to theaters, as I cautiously predicted earlier this year. For now, it’s just three big films and a number of awards contenders, but still, this is great news. And they’ll be releasing box office grosses! Just this week, Ted Sarandos confirmed that KPop Demon Hunters 2 will come to theaters (and my guess is it performs in the box office top ten at a minimum). WRONG: Angel has 3 million subscribers! How do I know this? Well, they told Deadline, who reported it. I marked this as “wrong”, since they’ve doubled their subscribers in one year but, you know, they don’t really have a hit film to speak of and they’re still losing money. WRONG: Furious was only renewed for one more season. I accidentally wrote “two more seasons” in my latest “Renewals, Cancellations, Un-Orders and Removals Update”. RIGHT: House of David is ending with its third season. In July, Prime Video renewed House of David for a third season, as I just wrote in my latest “Renewals and Cancellations” report. Well, now it’s ending after that third season. Why? As I’ve been writing, its viewership wasn’t great. I got feedback that this show didn’t cost very much, but it cost enough that its limited viewership didn’t save it. WRONG: Adults was a Hulu original! So I missed Adults when it first came out last year; I saw that it aired on FX and just assumed that it was a linear-first program. Turns out, it aired three episodes on FX, but binge-released the rest of its episodes the next day on Hulu. Huh. So I should have covered it last year! But I just wrote about it. 1 “When I was a kid in the 90s, if you wore a t-shirt to school that wasn’t too big and also wasn’t too small, but somehow didn’t quite fit, we’d say you were wearing an “extra-medium” shirt.” 2 As always, a huge exception is Disney, which barely makes anything original anymore.
I Put Netflix’s #7 Show on as Background Noise; Within Minutes, I Was Hooked
I put Netflix’s #7 show on as background noise and somehow ended up completely invested. Despite its rough reviews, there may be more to this new series than meets the eye.
007 First Light's First DLC Out Now, Adds New Game Plus
The 007 First Light Extended Operations DLC launches for free today, and adds five different missions to the TacSim mode, along with New Game Plus, new outfits and a photo mode that was somehow missing from the game at launch.
Good science requires much more than evidence
Empiricists believe that scientific theories are true only if they make correct empirical predictions: if we can't verify these predictions, then there is no reason to expect that they tell us anything about reality. However, Professor of Philosophy at King's College David Kyle Johnson argues that this is mistaken. In response to Bas van Fraassen, who has written on this subject for the IAI, he argues that we have many reasons for believing a theory to be true, such as it being parsimonious and having large scope — qualities which have been used throughout the history of science as criteria for judging theories. In 2024, Princeton philosopher Bas van Fraassen wrote a short article for IAI News entitled “Science Does not Describe Reality: The Limits and Benefits of Explanation.” At the time, I was working on two projects (a science book and a Great Course) that, when completed, would (among other things) defend science’s ability to describe reality. I wanted to write a response to van Fraassen, but the projects demanded too much of my attention. But now that those projects are complete, I am in a position to explain the objections to van Fraassen’s thesis. Summarizing van Fraassen’s argumentIn a nutshell, his argument is this: What scientists do is make predictions based on theories and then invite others to test to see whether those predictions are borne out. “If theory T is right, result R should happen in experimental condition C.” Many think that running an experiment that shows that R happens in condition C is proof that theory T is true (and should be believed). But, van Fraassen argues, that R happened in condition C is only a reason to think that R happens in condition C. That’s the only observable, or empirical, result we can actually see, so that is all that we are really justified in believing. (The underlying theory that made that prediction still may or may not be true.) That is why he calls those who accept his position “empiricists.”Before I explain what is wrong with this position, let me explain what it gets right. What van Fraassen Gets RightFirst, a theory correctly predicting the results of an experiment is not, strictly speaking, “proof” that the theory is correct. The basic line of reasoning is this:If the theory T is true, result R should happen. Result R did happen. Thus, theory T is true.In other words:“If T then R. R. Thus, T.”This is a deductively invalid, fallacious mode of reasoning, called “affirming the consequent.” Those premises do not guarantee that the conclusion follows. “If I am in Pennsylvania, then I am in the USA. I am in the USA. Thus, I am in Pennsylvania.” Clearly that argument doesn’t guarantee its conclusion; neither does the above argument.However, science is not a deductive method of reasoning; it is an inductive one. And inductive arguments merely try to raise the probability of their conclusion, not “prove” them for certain. Thus, the fact that an experimental result doesn’t prove a theory is true is irrelevant; it’s not supposed to. That is not what scientific reasoning is about.___If the hypothesis that something exists clearly provides the best explanation for what we can observe, then the belief that it exists is what is rational.___Second, it’s also true that a single experimental result doesn’t provide enough justification to believe that a theory is true. Scientists do not come to a consensus about whether a theory is true by looking at a single experiment; they look at all the evidence to determine where the preponderance of evidence points. The mere fact that I am in the USA raises the probability that I am in Pennsylvania, but not nearly enough to conclude that I am in Pennsylvania. However, if I am also regularly encountering people wearing Eagles and Phillies hats and seeing advertisements for Founding Father tours, I probably am. In the same way, a theory successfully predicting the outcome of one experiment is not enough to conclude that it is true; but if a theory makes a wide variety of predictions that are all vindicated by multiple experiments, performed by many different groups and people, all actively trying to prove the theory false (which is what good scientific experiments are designed to do)—that is a good reason to conclude that the theory is true. In other words, if you repeatedly try to prove something false but can’t, that is a very good indication that it isn’t. The problem of underdeterminationIn reply, those whom van Fraassen calls “empiricists” often point to the “problem of underdetermination.” For any given theory that makes successful predictions about what happens in experimental conditions, there are countless other possible theories that make exactly the same predictions—and since they do, the experimental evidence in question is just as much reason to accept any of those theories as it is to accept our original one. Thus, the argument goes, we have no way of knowing whether our original theory is true, or one of the other “predictively equivalent” theories is true. SUGGESTED VIEWING How Occam's Razor changed the world With Johnjoe McFadden As an example of underdetermination, philosophers often offer this example. The evidence of fossils seems to provide reason to conclude that the universe is quite old; ancient fossils are what the “ancient universe” hypothesis predicts. But it’s also possible that God created an ancient-looking universe 200 years ago, complete with a “fake” fossil record for us to find, to make it look old. The existence of fossils is what that theory predicts too. So, the argument goes, the fossil record can’t be used as evidence that the universe is ancient; the fossil record supports the “200-year-old ancient-looking universe” theory just as much. The problem of underdetermination points out that, for any theory with supporting evidence, we could invent another completely different theory that predicts exactly the same evidence, and thus undermine that evidence’s ability to support the original theory.But this “argument from underdetermination” betrays a fundamental misunderstanding of what scientific reasoning is and how it works. To explain, let me use another rather strange (but very real and commonly discussed) philosophical thought experiment called “The Grue Problem.” The “Grue” ProblemSuppose I want to know what color emeralds are, so I observe a few, see that they all appear green, and form the theory that “all emeralds are green.” I thus predict that the next 100 emeralds I find will also appear to be green. And let’s say that happens, and so I thus conclude that my theory that all emeralds are green is true. Now, one might rightly point out that I don’t know for sure that all emeralds are green—I have not seen them all. Maybe some I haven’t found yet are blue. Fair enough. After all, we used to think that all swans were white, until we found some black ones. But let’s say that I go on a quest and collect every emerald in the universe—and, for the sake of the argument, let’s say I can do this, and can even know that I have every one of them. So, I collect them all, look at them all, and verify that they all appear green. Can’t I now rightly conclude that all emeralds are green?Inspired by the problem of underdetermination, a friend might argue that I cannot.Sure, they all appear green now—but there could be another kind of color called “grue.” Something is grue if it is green up to a certain point in time, but then spontaneously turns blue. And there could be an infinite number of “shades” of grue. Something that is one shade of grue will turn blue at noon today, but something that is another shade of grue will turn blue at noon tomorrow, etc. So yes, the emeralds appear green now; and since they haven’t turned blue yet, they are not some “past” shade of grue. But they might be some “future” shade of grue (e.g., they may turn blue at noon tomorrow). And since all future shades of grue are consistent with “being green up to this point in time,” the evidence you have is completely consistent with the notion that all emeralds are some future shade of grue, rather than green. Indeed, that they would appear green until now is what the “some future shade of grue” hypothesis predicts. So, we have just as much reason to conclude that all emeralds are some shade of grue as we do to conclude that they are green.You’re probably thinking “It’s not equally possible that the emeralds are grue; they are obviously green.” You are right! But explaining why your instinctive reaction to my friend’s argument is correct will help inform why van Fraassen’s “empiricist” is wrong and science actually does describe reality.The main mistake my friend makes is in thinking that the “empirical evidence” (of all the emeralds appearing green) is (or even should be) all I am using to draw the conclusion that all emeralds are green. It is not. I am also considering known facts about how colors typically work; things don’t usually change color, and when they do, they don’t do so suddenly, without cause, and all at once. So, even though the simple evidence of the emeralds all appearing green up to this point is consistent with them being some future shade of grue—that is even what the grue hypothesis “predicts”—it is still exceedingly unlikely that they are. The hypothesis that they are green is much more likely. Understanding science refutes the problem of underdetermination The misunderstanding about science that the “empiricist” pointing to “the problem of underdetermination” makes is similar to the one that my friend made. Science is not just about considering experimental evidence; in fact, it’s not even just about considering empirical evidence. As Ernan McMullin and many other philosophers of science have pointed out, the inference that makes science is “inference to the best explanation” (sometimes called “abduction” or “retroduction” by McMullin). While, depending on the circumstances, scientists use many different kinds of reasoning, science as a whole is, simply put, the process of considering multiple competing explanations and comparing them to certain criteria—explanatory criteria (the kinds of things explanations must be and do, by definition, to be a good explanation)—to see which explanation is the best.And these criteria do not deal only with empirical results. Yes, successful predictions raise the probability of a hypothesis, but it’s also the case that the more new assumptions a theory makes, the less likely it is to be true; every new assumption presents an opportunity for the theory to be false. (The fewer assumptions a theory makes, the simpler or “more parsimonious” it is said to be.) Likewise, the more existing evidence a theory contradicts, the less likely it is, because in order for a theory to be true, every piece of evidence it contradicts has to be somehow faulty. (The fewer established theories a new theory contradicts, the more “conservative” it is said to be.) And, obviously, the more something explains, the better explanation it is. (This is called having “scope.”) If a theory raises unanswerable questions, it’s not expanding our understanding, and thus is not wide-scoping. Scientists consider all these things when deciding which theory to accept, because the theory that adheres best to these explanatory criteria is most likely to be true.___the mere fact that a theory’s predictive success is why it “sticks around” or “becomes accepted” in the scientific community is not a reason to be skeptical about its truth.___The reason the grue hypothesis is no good is because it invents an entirely new kind of color—not just a new shade, but an entirely different category of color (a different way colors work)—and thus is not parsimonious. It raises unanswerable questions about how and why emeralds would just spontaneously change from green to blue (and thus does not have wide scope). And it contradicts what is already well established about how color works (and thus is unconservative).The theories that the problem of underdetermination points to do the same thing. Yes, the theory that God created an “ancient-looking universe” (complete with an ancient-looking fossil record) two hundred years ago is also consistent with the empirical evidence (of a fossil record) that presently exists; but that theory is monumentally unparsimonious (it requires many extra assumptions about infinite entities) and not wide-scoping (it raises unanswerable questions about why God would do such a thing). So, I can rationally conclude that it is false.Indeed, the history of science includes many examples of theories that were rejected because they lacked parsimony and/or scope, even before their falsity (and the truth of their competing theory) was confirmed by observation. As I point out in my book, geocentrism was rejected by the scientific community because it lacked parsimony, almost 200 years before the observation of parallax confirmed that the Earth moves around the sun. And the continuum theory of matter was completely rejected by 1860, because it couldn’t explain chemical reactions or organize matter into a periodic table, even though the experiments that eventually confirmed atomic theory weren’t even proposed until the 1870s. Solving the best of a bad lot problemIn response, the “empiricists” are likely to object, this time pointing to the “best of a bad lot” problem. “We have no reason to conclude that an explanation that has been shown to be better than others is true because we have no guarantee that the true theory was among those that we were considering.” If you have a “lot” (a collection) of poor explanations, even the best one is not true.The responses to this problem, however, are numerous. Peter Lipton argues that the set of hypotheses that scientists consider are not just randomly selected and thus unlikely to contain a theory that is true; they use existing knowledge to home in on what is most likely to be true. A doctor trying to explain abdominal pain is not going to bother wondering whether demons are causing it; they are going to stick with things like appendicitis and kidney stones, because they are most likely. Further, despite its name, inference to the best explanation is not just the process of comparing hypotheses and accepting the best one; we also want one that is a good explanation in its own right. If it’s not, we are going to keep looking until we find an explanation that is. And while that process does not guarantee that we will come across the exact truth, it’s very likely that the theory that emerges as the best will be at least approximately true, and thus we will be justified in believing it. And lastly, as I point out in my book, although many theories not based in scientific evidence (like geocentrism and continuum theory) have been completely overturned, science almost always progresses by the refinement of scientifically established theories—not their replacement. (Although our sun is not the center of the universe, heliocentrism was our first step in understanding the Earth’s true place in the universe.) So even if a theory we accept today may not be completely right, accepting it is a step on the journey toward the complete truth. The example of atomic theoryNow, it’s worth pointing out that most empiricists are not skeptical of all scientific theories; they are only skeptical of the ones that hypothesize the existence of “unobservables.” It’s not like they think that round Earth, heliocentrism, and germ theory are just useful (but untrue) “instruments” for making predictions about how to most efficiently navigate the seas, predict planetary motion, and treat diseases. They admit that the Earth actually is round, that the planets revolve around the sun, and that germs exist and cause disease. These facts and entities can be observed; the theories that suggest they exist are true. It’s only when theories start hypothesizing the existence of unobservables—like electrons, or quantum fields—that can’t be observed directly, that we should start doubting the theories’ truth. And to be fair to van Fraassen, in this published work, he doesn’t really say that we should doubt the truth of such theories. Only that scientific reasoning does not rationally force us to accept them as true. Skepticism, or agnosticism, he argues, is warranted. SUGGESTED READING Science is based in metaphor By Andrew Reynolds But the history of atomic theory throws a monkey wrench into that argument. Atoms used to be unobservable; again, scientists first accepted the theory that they exist because it had such grandiose explanatory power. But then atoms were seen with electron microscopes. They thus moved into the category of the observable. But this didn’t substantially change anything about what scientists were justified in believing; it certainly didn’t change any “atomic skeptics’” minds. It just confirmed what everyone already knew! If the hypothesis that something exists clearly provides the best explanation for what we can observe, then the belief that it exists is what is rational. The fact that the thing itself is not technically observable does not make doubting its existence rational.What’s more, the atoms were seen with an electron microscope. But electrons are themselves unobservable. How can an electron microscope reveal an atom if electrons are not real? This leads us to what is famously known as Hilary Putnam’s “miracle argument.” It’s (not) a miraclePhilosopher Hilary Putnam’s miracle argument is somewhat famous. Basically, he argued that a scientific theory being able to repeatedly make successful predictions—even about unobservables—without being at least approximately true would require a “miracle.” In other words, it would be such an improbable occurrence that it could not rationally be believed—the better explanation for why scientific theories about unobservables make the right predictions is because the unobservable entities and structures they hypothesize exist.Van Fraassen has addressed this argument. Indeed, in his original article, where he references Alison Gopnik’s point about orgasms not being “necessary for procreation” even though the desire for orgasm “drives the creation of progeny,” he is pointing to his own argument about how organisms are not naturally selected by evolution to get true beliefs; to the extent that belief-forming processes are selected for, the ones that are selected are the ones that are useful for survival—not the ones that produce true beliefs. In the same way, van Fraassen argues, scientific theories are accepted, not because they are true, but because they aren’t falsified; they make successful predictions; that’s what makes them “stick around.” So, the fact that they make successful predictions (and thus became accepted) is not a reason to think they are true.This argument is similar to C. S. Lewis’s “argument from reason,” which he used to argue against evolution: “The truth of evolution undercuts our ability to know that it is true.” Lewis’ argument famously failed; Elizabeth Anscombe, by Lewis’s own admission, demolished Lewis in a debate on the topic, and I have explained elsewhere why modified versions of the argument fail as well. In short, it’s because it fails to recognize that a belief-forming process can make an organism more likely to survive because it reliably produces true beliefs. It is therefore not the case that beliefs generated by naturally selected belief-forming processes are automatically false or unjustified.In the same way, the reason a theory “sticks around” could be because it’s not falsified, because it “makes correct predictions.” But the reason it makes correct predictions is most likely because it is true. (In pointing this out, I am echoing the arguments of Musgrave, Lipton, Psillos, and Kitcher, who refuted van Fraassen’s argument and analogy long before his 2024 article.) It would be a huge coincidence that it could do so without being true. And that is the point of Putnam’s miracle argument. Thus, contrary to van Fraassen’s suggestion, the mere fact that a theory’s predictive success is why it “sticks around” or “becomes accepted” in the scientific community is not a reason to be skeptical about its truth. ConclusionLet me close by saying something about the fact that empiricists don’t doubt the truth of all scientific theories, just the ones that hypothesize unobservables. In today’s society, this theory is dangerous to espouse publicly. The nuance between being skeptical about all of science, and just the highly technical theories about unobservables, is guaranteed to be lost to the average reader. And there is so much unjustified skepticism and doubt about the findings of science and experts that a headline like “Science Does Not Describe Reality” could easily fuel the anti-science movement, worsen climate change denial and cause the next pandemic.This is why I believe it was important to still respond to van Fraassen’s article, a full two years after he wrote it. Not only, as I have argued, does it represent a philosophically inaccurate view of how scientific reasoning works and what scientific reasoning can do, but it is a dangerous view to boot. It should thus be rejected.
Entertainment RX: Cancer treatment, concern for a gender-fluid grandchild
Entertainment RX, a new column from former Globe TV critic Matthew Gilbert, is an entertainment-guided advice column offering things to read, listen to, or watch that somehow address — or, in some cases, distract from — the issues readers write in about.
Woman Says She Was Threatened After Using a Nearby Business’ Bathroom: ‘The Front Desk Dude Has Serious Issues’
Taylor, or @adyaguilera2.0 on TikTok, posted a video about the time she used a bathroom and was met with hostility. Somehow, the interaction escalated after a man who worked at a nearby business had p...
The Beclowning of Scott Bessent
One iron law of current politics is that nobody who associates themselves with Donald Trump emerges with a shred of credibility. For some, that’s not a big loss — it’s not as if anyone respected Pete Hegseth even before he decided that the key to military success in an age of drones and AI was more testosterone. For others, however, the costs are real. I’m old enough to remember when Marco Rubio was widely considered a reasonable, thoughtful politician. Right now, however, my candidate for the biggest loser is Scott Bessent, the Secretary of the Treasury. Bessent started out with significant reputation to lose: When Trump selected him, this was the headline in the Financial Times: Jason Furman, Barack Obama’s chief economist, described him as a “credible Treasury secretary who has a real understanding of the global economy”. But Bessent has now transformed himself into the Baghdad Bob of bonds. Three weeks ago, after intervening (for reasons that remain somewhat unclear) to support the Japanese yen, Bessent boasted about his ability to move markets and dared investors to bet against his, declaring “I am the house now.” He then tried to push long-term interest rates down, buying 30-year U.S. Treasuries in a move some have compared to paying down part of your mortgage by running up your credit card balance. Here’s how that’s going so far: To get some perspective on how high interest rates have gone, here’s a longer-term perspective: We haven’t seen interest rates this high since the fading days of the dotcom bubble. Why are interest rates hitting new records? The backdrop, as I argued in last Sunday’s primer, is the huge AI-driven investment boom; more on that next week. But the immediate cause of the latest interest rate spike was Trump’s rejection of an Iranian proposal to end the war. This rejection sent crude oil prices, which for a while had fallen considerably, shooting back up: It’s notable, by the way, that oil prices remain high even though a significant amount of oil is now being shuttled through the Strait of Hormuz by night, on smaller vessels. That’s an interesting story, which has a lot to do with the fact that oil from the Hormuz shuttle runs must be transferred to larger vessels before being shipped to markets in Europe and Asia; around 15 percent of the world’s large crude carriers are now parked off the coast of Oman, waiting to be tanked up. This is creating a shipping crunch: But that’s a topic for another day. For now, the point is that with oil still high and refined products, especially diesel, still close to record levels, inflation will remain elevated. And this in turn means that the Federal Reserve will keep short-term interest rates high, an expectation that is feeding into longer-term rates. Hence Bessent’s bond-market humiliation. The truth is that Bessent might not have been able to get interest rates down even in the best of circumstances. But he certainly won’t get anywhere as long as Trump keeps believing that he can somehow convert his Iran debacle into a triumphant victory. And Trump will keep believing that as long as he is surrounded by sycophants who tell him what he wants to hear. Sycophants like, for example, Scott Bessent, who is predicting the imminent collapse of the Iranian economy, possibly within two weeks. Bessent is right to say that the embargo on Iranian oil exports is placing the country under great economic strain. But his implicit prediction that this will quickly produce a deal that Trump can call victory looks no more plausible than his boasts about the bond market. The big question now is, why would anyone with a reputation to lose work for Donald Trump? As the beclowning of Bessent shows, joining the Trump team won’t just damage your reputation; it will utterly destroy it.
Scientists Squeezed a Leg Bone and Somehow Helped the Brain Heal
Controlled shinbone compression triggered bone cells to release neuroprotective signals, improving brain injury recovery in animal studies, per Nature Neuroscience.
R-Rated 80s Slasher Proves Nothing Can Stop Aerobics
An 80s slasher turns a fitness club into a bloodbath while somehow keeping the aerobics classes running like business as usual.
Justin Herbert Gives Vague Answer to Crucial Chargers Question
The Los Angeles Chargers somehow lost Sunday in Buffalo even after the defense forced five Bills turnovers. Justin Herbert and the offense managed a total of 16 points on a day when Josh Allen had zero touchdown passes and two interceptions.This drops the Chargers to 0-3 on the season with very little hope of a […] The post Justin Herbert Gives Vague Answer to Crucial Chargers Question appeared first on HEAVY.
Best Pokémon TCG deal: 30th Celebration Elite Trainer Box for below market price
Amazon somehow still has stock.
After nearly 19 years in development hell, Ubisoft's Beyond Good & Evil 2 is somehow still showing signs of life
Ubisoft Bordeaux narrative director Rik Godwin has shared an update on Beyond Good & Evil 2's progress.
Who on Earth Could Start Game 162 for the Astros?
There are three games remaining in the 2026 regular season, and somehow the Astros control their own destiny in the American League West. The Astros have won two of three games this week despite not having a starting pitcher complete three innings. Hunter Brown will start Friday’s game in West Sacramento, with Hayden Wesneski likely […]
SFHHA Newsline September 2026 – Healthcare Is Becoming a Consumer Business—Whether Hospitals Like It or Not
I recently read an article in Becker’s Hospital Review that purported to identify the top ten geriatric hospitals based on a report from U.S. News & World Report. Despite having our fair share of geriatric patients here in South Florida, somehow we didn’t make the list. That got me thinking. For generations, healthcare operated under […]
'On the verge of something' - fans on season so far
Transfer window was obviously a car crash but really positive signs from Hayden Hackney and Tyler Dibling in particular means we are feeling positive. Most Evertonians are waiting for that to turn somehow, but if we can keep Jarrad Branthwaite fit especially, I think we have good times ahead. Standout moment so far was that debut goal for Ainsley Maitland-Niles!
Distant time crystals can somehow fall into the same rhythm
Researchers have shown that multiple time crystals inside a semiconductor can synchronize their oscillations, much like pendulum clocks gradually falling into the same rhythm. The coupling is carried by spin-polarized electrons, allowing time crystals separated by up to 40 micrometers to lock to a common frequency. The discovery reveals surprisingly long-range connections between these exotic spin systems and could help researchers develop future spin-based devices.
Scientists want these 5 'maxxing' trends dead
The “-maxxing” trend promises that extreme optimization of your sleep, appearances, fitness, diet, or wellness routine will somehow unlock a better version of you. But when health advice becomes a competition to optimize every single thing, real science often gets lost. Our scientists break down the -maxxing trends they really want you to stop—and what the evidence actually says.
Packers win bizarre overtime game despite almost impossible offensive stat
Green Bay produced only one successful third-down conversion and fewer than 200 yards, yet somehow escaped with a victory.
Matthew Gilbert to launch arts advice column for life’s dilemmas, Entertainment RX
Entertainment RX, a new column from former Globe TV critic Matthew Gilbert, is an entertainment-guided advice column, offering things to read, listen to, or watch that somehow address — or, in some cases, distract from – the issues readers write in about. (Don’t worry, we won’t use your name.)
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
Rebels in the Pros: NFL Week 1
Football is in full swing now, but somehow the fall weather is lagging behind, by a lot. The college football season just wrapped up its official week two and the NFL is now fully underway after wrapping up a high scoring week one. A few weeks ago we ran through the league to see where […]
Seeing red in Manchester derby
In the Manchester derby there were two huge calls and, again, VAR somehow managed to get both wrong. Well, the first was at the very least morally wrong as opposed to totally wrong by the letter of the law. Bruno Fernandes sneakily kicked Phil Foden while the Manchester City man was defenceless on the ground.
John McEnroe reacts as Alexander Zverev beats Ben Shelton and wins the US Open title
Alexander Zverev is the newest US Open champion, having endured an arduous two weeks in New York and somehow come out on top. Whilst the...
Friday Morning Lights: Mexico High School
Watch a compilation of NewsChannel 9’s Friday Morning Lights at Mexico High School MEXICO, N.Y. (WSYR-TV) — It’s been a year already? Somehow, someway, it’s Friday Morning Lights time. This morning, our crew went to Mexico Central School District, where we set up shop at their high school’s football field. Although it was unusually chilly, many […]
FBS vs. FCS Games Need to Be Banned
Enough is enough. FBS teams should not be playing FCS teams anymore. If you need evidence, just look at what happened Thursday night. No. 7 Miami absolutely slaughtered Florida A&M 77-7 , and somehow the final score doesn’t even explain how ugly this game actually was. Miami led 49-0 at halftime and 77-0 at the…
Fact check: Trump, RFK Jr. and others make false claims on night 2 of GOP convention
(CNN) — President Donald Trump delivered another rapid-fire series of false claims on the second night of Republicans’ midterm convention on Thursday. Health Secretary Robert F. Kennedy Jr. did his own barrage of wrongness. And various other speakers uttered statements that were untrue, misleading or missing critical context.Here is a fact check of some of the assertions from the final day of the convention. This is not intended as a comprehensive list of Thursday’s falsehoods.Trump’s many false claimsTrump made numerous false claims, some of which he also made in his longer speech Wednesday.Trump claimed that there were “no empty seats” in the Dallas arena as he spoke Thursday, which was visibly untrue. CNN White House correspondent Alayna Treene, who was there, wrote in a live chat right after Trump made the claim that “I’m looking at rows of empty seats” and that “the idea that there are ‘no empty seats’ is just laughably untrue,” though she also said the room was mostly full. Trump has for years made false claims about supposedly never having had an empty seat.Trump further inflated one of his favorite fictional figures, claiming Thursday that “$22 trillion” in investment has come into the US; on Wednesday, he had put it at “over $20 trillion,” and even that lower figure has no apparent basis in reality. As of the time he spoke Thursday, the White House’s own website claimed there had been “$11.2 trillion” in “major investment announcements” this term, not “over $20 trillion,” and the White House figure was itself a major exaggeration of actual investment.Trump, talking about elections, lied that “there’s never been bigger cheaters” than Democrats; there is no basis for broadly describing Democrats as election cheaters. For the second straight night, Trump falsely claimed that the Biden administration allowed “25 million people” to pour into the country, though that number is nowhere close to correct. Trump again falsely claimed that former President Joe Biden and other Democrats “created the worst inflation in American history,” though even peak Biden-era inflation, 9.1% in June 2022, was far from the all-time record of 23.7%; it was a 40-year high, but the rate then fell sharply before Trump returned to office.Trump also baselessly claimed that Democrats would “defund the police” and give “voting rights and welfare to 25 million illegal aliens” if they won the midterms. Republicans will still control the White House in 2027 and 2028 and the president would be in position to veto any such changes if a Democratic-controlled Congress sought to make them, but there is no indication that Democrats want to do so. Also, even groups favoring strict immigration policies estimate that the total undocumented population is far less than “25 million” or even 20 million.As he did Wednesday, Trump claimed the US now has the world’s lowest prescription drug prices. The assertion is so broad that it is unclear what exactly Trump is referencing. But experts told CNN they highly doubt that the prices for brand-name drugs in the US are generally less than they are in other countries, and the Trump administration has not provided details to prove the claim.“It’s tough to claim that you’re getting the lowest prices anywhere in the world and then also not have any evidence to support that,” said Andrew Mulcahy, a senior health economist at RAND, while Diederik Stadig, senior healthcare economist at financial institution ING, said, “To say that the US now has the lowest drug prices in the world is at this moment not true.”And as he did Wednesday, Trump said “more Americans are working today than ever before” – which is true but nearly meaningless, since the number of people working in the US generally rises over time simply because the population rises over time.“There are more Americans working because there are more Americans. That’s the entire analysis,” Justin Wolfers, a University of Michigan professor of public policy and economics, wrote in his newsletter in August.RFK Jr.’s false claims on the pandemic, Trump’s record and moreFalse claim about Democrats and the 2024 electionKennedy unsuccessfully ran for the 2024 Democratic presidential nomination before withdrawing to run as an independent and then eventually endorsing Republican candidate Donald Trump. In Kennedy’s Thursday convention speech, he complained of how the Democrats handled the nomination race.At one point, he said, “For the first time in history, they cancelled their own convention. No voter ever cast a primary ballot for Kamala Harris, no elected delegate was ever consulted; the party of ‘No Kings’ simply anointed a queen.”Kennedy is entitled to express unhappiness about how quickly Democratic leaders coalesced around then-Vice President Harris after Biden unexpectedly dropped out of the race in July 2024, after the primaries were over and less than four months from Election Day. But it’s not true that the party canceled its convention or that delegates didn’t get any say.The convention was held; it was a four-day event in Chicago in August 2024. Democratic convention delegates officially nominated Harris in a virtual roll call vote in advance of the convention. It’s true that Harris was the only candidate on the roll call ballot, but that’s because she was the only candidate who gathered enough delegate signatures to appear on the ballot.It’s clear that party elites’ backing of Harris played a key role in the unusual nomination process. But Kennedy’s specific allegations that the convention was abandoned and delegates were cut out of the process are not true.False claim that Democrats closed ‘every church’ during the Covid-19 pandemicWhile attacking Democrats, Kennedy claimed that, during the Covid-19 pandemic, “They closed every church in our country for a year.”It’s not true that every church in the country was closed for a year, nor even that every church in a Democratic state was closed for a year.Every state issued some type of guidance or order about social distancing during the Covid-19 pandemic, but many states – including some led by Democrats and some led by Republicans – incorporated religious exemptions into those limitations on social interactions.According to a Pew Research Center analysis from April 2020, 15 states allowed religious gatherings to continue without a limit on their size. That set of states included Colorado, Michigan and Pennsylvania, which all had Democratic governors. And at least two states with Republican governors, Alaska and Idaho, were among the states that prohibited religious gatherings at least briefly.False claim that Trump ‘ended nine wars’Trump has repeatedly claimed that he has ended “eight wars.” Kennedy went one higher on Thursday, declaring, “President Trump has ended nine wars.”That’s false. Trump hasn’t even ended eight wars.Trump’s list of eight includes two situations that were never actually wars during his tenure: a diplomatic dispute between Egypt and Ethiopia and a mysterious supposed situation between Serbia and Kosovo. The list also includes a war, involving Rwanda and the Democratic Republic of Congo, that hasn’t actually ended despite a peace agreement brokered by the Trump administration.In addition, the list includes the war between Israel and Hamas, but Israel continues to conduct frequent attacks in Gaza despite a US-brokered ceasefire agreement. And it includes the brief 2025 conflict between Israel and Iran, though Israel proceeded to join the US in starting another war against Iran in 2026.Claim about reversing a decline in longevityKennedy speaking of the Trump administration, claimed Thursday: “We have now reversed a 30-year decline in longevity. “Kennedy referenced preliminary data that he said he had received from the US Centers for Disease Control and Prevention this week, but it’s unclear what metric of longevity he’s referring to.CDC data shows that US life expectancy had been steadily increasing for decades before a sharp drop during the Covid-19 pandemic. Life expectancy had already started to rebound in 2022, under the Biden administration, and reached a new record high in 2024 before Trump’s second term began.Preliminary data shared by the CDC in July suggests that life expectancy probably hit another record high in 2025.CNN has reached out to HHS for clarification on Kennedy’s comments.Claim that Democrats ‘lost 360,000 children’Speaking about Democrats, Kennedy said: “They somehow lost 360,000 children and they turned our federal government into the biggest child trafficking operation in world history.”Trump and other Republicans have made similar claims. But there’s no basis for the assertion that Democrats “lost” so many children or that the federal government was engaged in human trafficking.A 2024 report from the inspector general for the Department of Homeland Security said Immigration and Customs Enforcement had reported that more than 32,000 unaccompanied migrant children failed to appear as scheduled for immigration court hearings after being released or transferred out of custody between fiscal years 2019 and 2023 – a period that, notably, includes two years and four months under the first Trump administration. The report also said that 291,000 unaccompanied migrant children during this period were not given notices to appear in court.The report said that ICE had “no assurances” these children “are safe from trafficking, exploitation, or forced labor.” But it did not say all the children were actually “lost” and did not definitively assert that any of them were trafficked – let alone that the government was somehow involved in a trafficking operation. And, again, the report spanned parts of both a Republican administration and a Democratic administration.Aaron Reichlin-Melnick, senior fellow at the American Immigration Council, told CNN in 2024: “Long story short, no, there are not 320,000 kids missing. 32,000 kids missed court. That doesn’t mean they’re missing, it means they missed court (either because their sponsor didn’t bring them or they are teenagers who didn’t want to show up). The remaining 291,000 cases mentioned by the (Office of the Inspector General) are cases where ICE hasn’t filed the paperwork to start their immigration court cases.”Vance on inflation, crime and taxes on Social SecurityA false claim about the media and Biden-era inflationVice President JD Vance mocked the media during part of his speech on Thursday. But he made a false claim about Biden-era inflation while lampooning how the media supposedly challenged him over another false claim on that subject.Vance said: “The president and I would go during a campaign, we’d say, ‘You know, inflation is as high as it’s been in 100 years,’ and the fake news would say, ‘No, no, no, it’s as high as it’s been in 68 years.’ That ain’t good, ladies and gentlemen.”Mainstream journalists, at least, wouldn’t say that inflation under Biden was as high as it had been “in 68 years.” Rather, CNN and others noted that peak inflation under the Biden administration, 9.1% in June 2022, was the highest in about 40 years.Vance is entitled to make his general point that this correction still doesn’t make Biden-era inflation sound good, but his specific number was, again, wrong. And he didn’t acknowledge that inflation fell sharply under Biden after hitting the 40-year high, declining to 2.9% in Biden’s last full month in office, December 2024, and 3.0% in January 2025, when Trump and Vance were inaugurated.The rate was 3.4% in July 2026, the most recent month for which data is available.Trump didn’t end taxes on Social SecurityVance claimed, “We’ve ended taxes on Social Security.” Several other convention speakers, including Rep. Lisa McClain of Michigan, Rep. Ryan Mackenzie of Pennsylvania and Ohio House candidate Derek Merrin, similarly said the administration has achieved “no tax on Social Security.”It hasn’t. The big domestic policy bill Trump signed in 2025 did create an additional, temporary $6,000-per-year tax deduction for individuals age 65 and older (which phases out for individuals earning $75,000 per year or more), but as the White House has implicitly acknowledged, millions of Social Security recipients will continue to pay taxes on their benefits even before the temporary new deduction expires after 2028.The Social Security Administration said in 2025 that “the bill ensures that nearly 90% of Social Security beneficiaries will no longer pay federal income taxes on their benefits.Claim about violent crime rate under BidenWhile criticizing the Biden administration, Vice President JD Vance claimed Thursday that the US “became a country where violent crime exploded, unless, of course, you could afford private security.”But violent crime did not explode under Biden. In fact, as FactCheck.org reported last month, data collected and published by the FBI shows that the national violent crime rate was at a lower level in 2023 and 2024, the last two full calendar years of Biden’s term, than it was in 2020, the last full calendar year of Trump’s first term. The year 2020 was highly unusual in many ways – violent crime jumped amid the Covid-19 pandemic – but Biden nonetheless left office with violent crime lower than it was when he took over. In fact, the 2024 violent crime rate was even lower than the 2019 rate under Trump before the pandemic.There was an increase in violent crime during the earlier part of Biden’s term. But given the subsequent decline, it’s misleading at best to claim violent crime “exploded” with no further context.Asked earlier this month about Trump’s similar previous claims to have reversed a Biden-era upswing in violence, crime data expert Jeff Asher said in an email: “No, crime began dropping significantly in 2023 during the Biden administration. Murder fell at record rates in 2023, 2024 and 2025 and, while 2026 may not feature a record decline nationally, it is still on track to see a sizable double-digit decline this year. Violent crime similarly fell nationally in 2023 and 2024, though the drops were more muted than the decline that was recorded by the FBI in 2025.”Other GOP speakersMike Johnson’s false claim about the inflation Republicans inherited from BidenSome other speakers at the convention took aim at inflation under Biden. House Speaker Mike Johnson claimed that “Republicans inherited from the Biden administration record-high inflation.”That’s not true. The inflation rate was 2.9% in Biden’s last full month in office, December 2024, and 3.0% in January 2025, when Trump took over. That’s lower than the most recent rate, 3.4% in July 2026, and nowhere close to the all-time record of 23.7%, which was reached in 1920, or the highest point of Jimmy Carter’s presidency, 14.8%, which was reached in 1980.Johnson correctly said moments later that inflation reached “a 40-year high of 9.1% inflation” under Biden. But a 40-year high is not an all-time record. More importantly, Johnson didn’t explain that 9.1% was much higher than the rate Trump inherited or that the 9.1% rate occurred in June 2022, with roughly two-and-a-half years left in Biden’s term.The cumulative increase in prices from the beginning of the Biden administration to the end was also not the highest in US history. Federal figures show that beginning-to-end inflation under Biden was less than half of that during Carter’s term.What Johnson left out of his claim about a congressional resolutionWhile attacking Democrats as extreme, Johnson said: “Just last week, nearly every Democrat in the House of Representatives voted against condemning socialism and Marxism. They voted against it.”But the resolution didn’t use the word “Marxism.” And Johnson didn’t mention that the resolution wasn’t only about condemning socialism. Rather, it contained other language that Democratic leadership said was the focus of the party’s opposition to the resolution.The resolution’s first provision said it “condemns and denounces socialism in all its forms, including the Democratic Socialists of America, and opposes the implementation of socialist policies in the United States.” But its fifth provision said it “calls for enactment of the SAVE America Act,” Trump’s favored elections bill, which contains various provisions opposed by many Democrats.So while it’s very possible many Democrats would have opposed the resolution even without its expression of support for the SAVE America Act, the call to pass this elections bill served as a poison pill that ensured most Democrats wouldn’t support it.“House Resolution 1490 explicitly calls for enactment of the so-called SAVE America Act, which is the top legislative priority of far-right extremists,” Democratic House leader Hakeem Jeffries said in a statement last week.A New Mexico candidate left out key context in an attack on his opponentGreg Cunningham, a Republican House candidate in New Mexico, used some of his Thursday speech to criticize his Democratic opponent, Rep. Gabe Vasquez. Cunningham said of Vasquez: “He even voted against a resolution honoring the sacrifices and service of the brave men and women in law enforcement who protect, every day, our communities.”But Cunningham left out important context about the resolution. While its focus was expressing support for law enforcement, its preamble contained statements praising the Trump administration and criticizing “leftist activists,” “progressive politicians” and “sanctuary city policies” for allegedly making law enforcement less safe.In other words, a House member might vote against such a resolution, as the vast majority of Democrats did, because they disagreed with conservative components of it, not the general expressions of support for law enforcement. (CNN has reached out to Vasquez’s campaign and House office for comment on his vote.) It’s common for parties to write resolutions in a way that would make it difficult for opponents to support but would open those opponents to campaign attacks if they voted “no.”An Ohio candidate’s misleading attack about Democrats and votingMerrin, the Republican candidate running against Democratic Rep. Marcy Kaptur for a House seat in Ohio, claimed in his speech, “While Democrats talk about letting illegal immigrants vote in our election, Republicans fight for proof of citizenship, photo ID and fair elections.”It’s a big country, so it’s possible some Democrat somewhere is talking about letting undocumented people vote in some election. But Merrin’s claim is misleading at best. There is no proposal from Democrats in Congress to let undocumented people vote in the 2026 midterms – the election Merrin appeared to be referring to when he said “our election” – or vote in future federal elections.CNN has reached out to Merrin’s campaign for an explanation of his claim.House Majority Leader Steve Scalise invoked a similar theme in his speech Wednesday, claiming that Democrats had voted last week “to allow illegals to vote in our federal elections.” But there was no congressional vote on letting undocumented immigrants vote in any elections.Rather, there was a vote on the non-binding Republican resolution that included multiple provisions, including one that “reiterates the notion that American elections are for American citizens only,” one supporting Trump’s favored elections bill and one denouncing socialism.Opposing that multi-clause resolution doesn’t necessarily mean someone supports voting by any non-citizens, let alone non-citizens in the country illegally.This article has been updated with additional items.CNN’s Deja Oliver contributed to this report.The-CNN-Wire™ & © 2026 Cable News Network, Inc., a Warner Bros. Discovery Company. All rights reserved.
Angel Reese Is Getting Way Too Good to Ignore
At some point, we have to stop calling Angel Reese a “future star.” She is already a star. Reese has taken her game to another level with the Atlanta Dream, averaging 16.1 points, 12.4 rebounds, 2.8 assists and 1.8 steals per game this season. And somehow, she still feels like one of the most underrated…
College Football Has Completely Lost Its Mind
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Week 1 Reminded Us Why College Football Is the Best
College football is officially back. And somehow, Week 1 already gave us enough storylines for an entire season. The biggest statement came from LSU . Lane Kiffin’s debut couldn’t have gone much better, as No. 11 LSU absolutely destroyed Clemson 51-10 in Death Valley. LSU piled up 644 yards while holding Clemson to just 145.…
Six decades of politics (but little government)
The first aired episode of “Star Trek,” entitled “The Man Trap,” premiered on September 8, 1966 — 60 years ago today. I’m actually editing a political science fiction issue of The Forum right now, and it’s prompted to me think a lot about the ways that Trek deals with politics and government and what it’s offered us as commentary. The @smotus report is a reader-supported publication. To support this work, please become a paid subscriber. Subscribe The original TV series ran from 1966 to 1969. It had a loyal but modest following, but the audience grew substantially with the series in syndication for years after that. The franchise developed its first motion picture in 1979, followed by five sequels, and then a whole other series of films built around the “Next Generation” series that first aired in 1987. In recent decades, several more TV series have built up around it, including the current “Strange New Worlds,” now in its fourth season. Throughout the past six decades, the franchise has offered us a good many insights into US politics and international relations, although often disguised as science fiction yarns. The original series was largely a Cold War fable, with the United Federation of Planets (a stand-in for the US) perpetually at odds with the Klingon Empire (a stand-in for the USSR). The “Let That Be Your Last Battlefield” episode (1969) posited a planet divided into two races, largely indistinguishable to outsiders, but nonetheless constituting a brutal racial hierarchy. “Patterns of Force” (1968) showed a struggling planet where the leader had attempted to construct a benevolent dictatorship — literally Nazism without bigotry — and found that authoritarianism could not exist apart from hierarchy and oppression. (Relatedly, I’d put “Star Trek VI: The Undiscovered Country,” high on a list of dad films about the end of the Cold War, near “The Hunt for Red October.”) Get 20% off for 1 year Indeed, the original series itself was something of a political statement, with a multi-racial crew running the Enterprise, a diverse and largely peaceful Federation mostly free from want and oppression, and protected by Starfleet, an armed force whose scientific mission was at least as important as its military one. Famously, when Nichelle Nichols wanted to walk away from the role of Uhura on the original series, none other than Martin Luther King, Jr. met with her and urged her to remain on the show, discussing the importance of viewers seeing an intelligent Black woman as part of the command team three centuries hence. Later series in the Trek franchise offered a good deal of political commentary on their own, but probably none as explicitly and incisively as “Deep Space Nine,” which ran from 1993 to 1999. The episodes surrounding the Dominion War, especially the “In The Pale Moonlight” (1998), showed the compromises, sacrifices, and moral rot associated with winning even a just war — probably better than any series would until “Andor” (2022-25). In “Far Beyond The Stars” (1998), Captain Benjamin Sisko is somehow transplanted to the role of a science fiction writer in 1950s New York. The writer is frequently sidelined and his ideas stolen because publishers don’t want to credit a Black writer. Several series have depicted the secretive Section 31 — an unacknowledged black ops security force operating within Starfleet. These episodes often end up using Section 31 as a foil to show the dangers of a lawless group within a lawful society, even (especially) when that group posits itself as essential for everyone else’s freedom to continue. The current “Strange New Worlds” has played with a few political themes. I found the first two seasons of this show among the best that the Trek franchise has produced in decades, but this season and the last have really been struggling for ideas. Yet one interesting thread is the idea that the diplomatic and enlightened leadership style of Captain Christopher Pike will not work in all situations. “A Quality of Mercy” (2022), which I wrote about here, puts Pike in the middle of a battle with a Romulan vessel in an alternate timeline, and finds that Pike’s conciliatory style would actually make a lengthy and deadly war more likely, while a quick and more violent approach might have prevented the war. This season’s opener, “Valles Marineris,” shows a pre-lightspeed civilization locked in a war to the death with a neighboring planet. The idea of an alliance or a federation hasn’t even occurred to them — their ship’s commander is curious but doesn’t see it as an option. For a franchise as political as “Star Trek,” one thing we almost never see is the government. We get occasional glimpses of Starfleet’s council — mostly uniformed people at a rectangular table — but almost no sense of how the Federation is governed. Are there elections? Who is in the legislature? How much power does the president have? What kind of factional divisions do they wrestle with and how? The shows and films are pretty silent on this. We’ve seen a few military tribunals within Starfleet, but little about how civilians deal with crime and injustice. With recent years seeing some of the franchise’s more interesting plot lines and casts, it seems clear that Star Trek is still full of energy and ideas. Given the erosion of American democracy and the reshuffling of the international order, there’s no shortage of material for future shows to comment on. I’m not sure we should toast to 60 more years, but cheers to a show that continues to teach us about ourselves. Share
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The new "science golden age" looks suspiciously like a grift
This edition of PN is made possible by paid subscribers. Become one ⬇️ 🚀 Subscribe to PN 🚀 The Trump regime is trying to usher in a “Golden Age in Science” where scientific research is run like a Trump family business, artificial intelligence is all that matters, profit is everything, and expertise is for chumps. Or at least that’s the vision emerging from a new 123-page “Report to the President” from Michael Kratsios, the Director of the White House Office of Science and Technology Policy. In a normal administration, you could probably skip over learning about a science policy document — but this is no normal administration, and this is no normal science policy document. Instead, it’s Trump’s attempt to end the actual golden age of science that was kicked off in 1945 with the publication of '“The Endless Frontier” by Vannevar Bush. [ ](https://www.publicnotice.co/p/harmeet-dhillon-portland) [ Harmeet Dhillon demonstrates danger of posting through it ](https://www.publicnotice.co/p/harmeet-dhillon-portland) Liz Dye · Jul 29 [ Read full story ](https://www.publicnotice.co/p/harmeet-dhillon-portland) Bush, at President Franklin Delano Roosevelt’s request, laid out a vision of federal support for science that centered on funding universities to do basic research, saying that as long as those institutions were “vigorous and healthy and their scientists are free to pursue the truth wherever it may lead, there will be a flow of new scientific knowledge to those who can apply it to practical problems in Government, in industry, or elsewhere.” Kratsios’s report is supposed to be the successor to Bush’s, and even apes the format, but this isn’t really a document about science policy. It’s one about ending science research as we know it in favor of shoveling cash at big tech companies. While it might be temping to wave this away as an aspirational policy document, Trump has already begun to shift billions in research funds to AI projects and has taken a hatchet to science funding across the board. He’s teed up the shift Kratsios proposes here, and since neither Congress nor the Supreme Court seem inclined to stop him from doing whatever he wants with taxpayer money, it isn’t doomering or hyperbole to say we are staring down the barrel of a world where the only “science” the government intends to support is for-profit tech and defense advancements. Science for dummies Part of how you can tell this isn’t a document about science is that you are immediately faced with an absolute wall of business-speak of the worst sort. Did you know we must “tightly couple our science and technology enterprises to ensure that groundbreaking ideas invented in the United States are rapidly prototyped, tested, manufactured, and scaled domestically”? You do now! That tone isn’t surprising, because Kratsios has no background in science or research. He has a bachelor’s in political science and spent most of his career working for Peter Thiel at Thiel Capital. After a stint in the first Trump administration as Chief Technology Officer, where he also did not do any science, Kratsios was tasked in 2020 with overseeing the Pentagon’s research budget for a brief time, a position that, as the Wall Street Journal put it, “carries a great deal of power in terms of dictating investment allocations.” He spent the Biden years at Scale AI as “head of strategy,” which you will also note is neither a science nor a research job. But Scale AI has contracts with the Department of Defense and, as the Washington Post wrote in 2023, “has been aggressively pitching itself as the company that will help the US military in its existential battle with China.” And now you have the necessary background for our new golden age, which is going to be a golden age of taking money away from scientists and universities and giving it to companies like Scale AI. A note from Aaron: Working with brilliant contributors like Lisa takes resources. If you aren’t already a paid subscriber, please become one to support our work. 👇 Subscribe In a genuinely galling move, Katsios spends a lot of time slamming universities because of “administrative burdens on researchers” and the “well-documented inefficiencies” in academia, the message being that those damn universities waste the time of amazing researchers with paperwork. Except it’s the administration that is attempting to impose inefficient, unnecessary burdens on those researchers with a proposed Office of Management and Budget rule that would require senior political appointees to approve every science grant and ensure it aligns with Trump’s personal priorities. Researchers would also have to seek prior government approval to attend conferences or publicize their research. And political appointees could terminate any grant at any time if they feel like it. [ ](https://www.publicnotice.co/p/omb-rule-science-funding) [ The murder of expertise ](https://www.publicnotice.co/p/omb-rule-science-funding) Lisa Needham · Jun 11 [ Read full story ](https://www.publicnotice.co/p/omb-rule-science-funding) But when it comes to AI, we’re going to “restore permissionless innovation.” The report proposes to give lucky ducky innovators a pile of cash up front for grants lasting five years or longer, saying “awards should be fully-funded in year one, with all resources earmarked upfront, to minimize administrative burdens and reduce pressure for researchers to generate intermediate results to secure continued funding.” Yeah, wouldn’t want to have to make the Very Special Tech Bros show results or get money parceled out year by year like the plebes at universities. The report also proposes that we should have “fast grants” with “simplified applications requiring just a few pages of writing” because that is definitely how science works, just writing a bit off the dome and getting some cash. [ ](https://www.publicnotice.co/p/trump-ai-action-plan-altman-llms) [ Tech elites are turning AI into ChatGPTrump ](https://www.publicnotice.co/p/trump-ai-action-plan-altman-llms) Paul Waldman · July 29, 2025 [ Read full story ](https://www.publicnotice.co/p/trump-ai-action-plan-altman-llms) Oh, and we should have prizes and challenges, where multiple teams compete. The proposed prizes include incentives like “advance procurement commitments,” which means the federal government agrees to buy whatever is being developed. There’s also “regulatory fast-tracking,” making sure all those great AI thingies don’t have to wait too long to be unleashed on a market. These aren’t incentives to do science. These are incentives to develop things with tax dollars that you can then sell to the government for more tax dollars. In the suggestion that might be the most unhinged, the most very opposite of how both government and research work, our new age will include “golden tickets.” That’s where an individual reviewer in an agency — yes, just one person — can “recommend unconventional proposals that may not pass consensus-driven review panels” because somehow this will “surface valuable ideas too divisive for committees and attract higher quality reviewers by empowering them to exercise independent scientific judgment.” Yes, that’s saying that a random person in an agency should be able to shovel money at some idea even if it can’t pass a review panel, and that the opportunity to do so will attract better employees because apparently all the best minds in science are chomping at the bit to be allowed to unilaterally fund AI research based on their personal vibes. But that isn’t at all how actual science works, and actual scientists aren’t unhappy about review panels. They work collaboratively, not siloed in some secret race to create the next AI chatbot. A 2020 study by the National Bureau of Economic Research examined whether peer review panels succeed in helping agencies predict which research ideas will best advance science. Peer review was better at finding “diamond in the rough” applicants than a single government program official. How about that. Trump always wants a taste It’s painfully clear that what Katsios is trying to do here is turn the whole of government science research and funding into the sort of “move fast and break things” paradigm that is the hallmark of big tech. That method works to line the pockets of tech executives, but it isn’t science. There’s a reason the government funds different kinds of research than private tech companies do. What Katsios either fails to understand or deliberately ignores is that the federal government is the main funder of basic research precisely because it can take a long time for it to bear fruit and is not intended to be profitable as such. “Basic” here does not mean rudimentary or simple, but rather research that is designed to advance scientific knowledge instead of achieving a specific outcome or product. Big tech companies don’t widely fund that sort of research, because it doesn’t make them money. Industry dollars account for only about 20 percent of basic research funding, while the government contributes around 60 percent. Big tech companies and startups do, however, rely on and benefit from that basic research. A 2019 study found that 35 percent of all patents obtained by venture-backed startups from 1976 to 2016 cited federally supported research. Basic research funded by the NIH contributed to every single drug the FDA approved from 2010 to 2016. [ ](https://www.publicnotice.co/p/trump-saudi-nuclear-deal) [ The Saudi nuclear farce and governance by whim and meme ](https://www.publicnotice.co/p/trump-saudi-nuclear-deal) Noah Berlatsky · Jul 27 [ Read full story ](https://www.publicnotice.co/p/trump-saudi-nuclear-deal) Unlike inventing the next ChatGPT, actual science is slow and iterative. Government funding of research that, on its face, would not appear to lead to any big new invention is actually what underpins those big new inventions. If the government hadn’t funded research into desert lizard venom, we wouldn’t know about semaglutide, and we wouldn’t have Ozempic. If research scientists hadn’t studied how bees optimize nectar foraging within a colony, we wouldn’t have the algorithm that assigns internet traffic across computer servers. The report assiduously ignores that a symbiotic, profitable relationship between the federal government, universities, and private companies already exists. Each federal research dollar generates about $1.50 to $3.00 in long-term economic benefits. The $36 billion the government awarded in NIH research funding in fiscal year 2025 generated $94 billion in new economic activity. Trump’s proposed new golden age is intended to strip those billions from universities, resulting in the dismantling of departments and the shuttering of labs. But Katsios has a plan for that: Universities should just become trade schools to churn out no-show STEM degrees! “Require universities and community colleges to embed practical technical training and externships into STEM curricula. Let hands-on experience and industry credentials count toward degrees.” It’s quite the feat to, on the one hand, strip schools of funding for scientific research while simultaneously demanding to control what is taught and, oh, also, colleges need to give degrees to employees at big tech companies just for being employees at big tech companies. The new golden age would also exacerbate the brain drain Trump’s policies have already caused. Nature found that in the first quarter of 2025, US scientists submitted 32 percent more job applications abroad than in 2024. A March 2025 poll by Nature of roughly 1,600 scientists found that over 1,200 said they were considering leaving the country. Europe is investing $565 million to make it a “magnet for researchers” and provide funding for scientists who relocate. The new golden age is also about embedding Trump’s xenophobia into the fabric of American science. The report complains of an “over-reliance on foreign students” that “creates a security challenge our institutions are ill-equipped to address” and that a “reliance on foreign talent sidelines American students.” This is, to put it mildly, nonsense. International students pay far higher tuition and often receive no financial aid. Their tuition dollars are what make it possible for American students to get financial aid. In the 2023-2024 school year alone, international students contributed $43.8 billion to the US economy and supported over 378,000 jobs. Those 1.1 million international students accounted for only six percent of the total number of students in higher education that year, but were such an economic engine that for every three international students, one job was created or supported. It’s impossible not to wonder whether part of Trump’s loathing for universities and their leading role in scientific research is that there is no way for him to corrupt the process and make money off it in the same way he can by giving millions and billions to Silicon Valley types who, in turn, give him millions in cash. There’s no way for his children to invest in universities that the government then gives no-bid contracts to, fattening the family’s bottom line, which is pretty much the Trump sons’ current venture capital practice. Trump and Katsios’s view of science is narrow, cramped, and wrong. We’re not in a crisis, we’re not a failed state. We’ve been a science superpower for decades, and the only thing that threatens that is Donald Trump. Tech bros are already living high off the hog in this administration. They don’t need any more of our tax dollars. Hopefully this new golden age never comes to pass. Thanks for reading Public Notice. This post is public so feel free to share it. Share We’ll be back with more tomorrow. If you appreciate today’s PN, please do your part to keep us free by signing up for a paid subscription. 🚀 Subscribe to PN 🚀 Thanks for reading, and for your support.
After World War II, a few snakes reached Guam; they now number up to 30,000 per square mile, and scientists found 19,000 hidden genetic changes
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Nintendo says it has no legal duty to pass its U.S. tariff refunds on to consumers
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In Retrospect: Poland, Russia, Europe
In April I spent a few days with Zryw, a Polish non-profit organization that recruits young people to enter politics and public life. Their aim is to build a new generation of civic leaders in Poland. I’ve followed their evolution from the beginning; my son is one of the founders. (“Zryw” means “impulse” or “burst of speed” in Polish). Julie Chmielewska, one of Zryw’s leaders, interviewed me at the event. Here is the conversation, lightly edited for grammar and context: Julia Chmielewska: Assuming that culture shapes institutions, could we conclude that some cultures are more prone to authoritarianism? Anne Applebaum: I don’t think so. Every culture, every nation, and every country has the potential for change. When we look at history, we can see that nations do change. Poland has changed, for example, from the 1980s to today. There’s a completely different mentality here than the one I encountered when I first visited, in 1988. The current generation sees the world through a different frame. So no, I don’t believe that certain nations are doomed to authoritarianism, or to anything. Of course, there are political and cultural traditions, but they can always be challenged. JC: So do you think there’s something intrinsic in human nature that pushes people to democracy, freedom? AA: I think there is something in human nature, a deep instinct, that pushes people towards freedom, yes. People who live in authoritarian countries – and I’ve heard this from them over and over again – sooner or later find themselves angered by a feeling of helplessness. They can see the unfairness of crooked courts, irrational political decisions. They naturally dislike the fact that somebody has all the power while they have none. In those circumstances, people who have no political background at all sometimes are politicized just by that frustration. I’m thinking of Svetlana Tikhanovskaya, for example, who was a Belarusian housewife, until the circumstances of her husband’s arrest forced her to become a politician. I met a woman who is a Uyghur from China, and who had come to live in Turkey. After several of her family members were arrested, she too was propelled into a political role. These kinds of experiences make people interested in democracy or political reform, even if they thought they didn’t care. I also think that the opposite is true: some people instinctively prefer homogeneity, order, hierarchy. They don’t like the confrontation of opinions or the noise of debate, and they lean towards a single leader or a unified regime. I think that most of modern history is shaped by the clash between those two different sides of human nature. JC: Which force do you find more powerful today? AA: I think they both have a lot of power and there’s no way of predicting who wins. Even in countries that seem very shut off or stuck in an authoritarian system can change. We’ve seen that happen. And vice versa, I think democracies can also begin to fail and slide into authoritarianism. So it’s very important not to be complacent in either direction. JC: I want to go into your history and your experiences. You’ve lived in Russia during a time of incredible change in the late 80s, and then you came back to do research in post-Soviet Russia. AA: I was a student in Russia just before the collapse of the Soviet Union. I then traveled and worked there extensively in the 1990s, and I met people who really were full of hope. They hoped that Russia could become a democracy, or at least a place that guaranteed freedom of speech, freedom of the press. These weren’t ideas that came from Washington. Although now the narrative in the Kremlin is different, I met many people who were working towards exactly that kind of transformation. A friend of mine ran a series of seminars – once a year, and then later several times a year, in cities all over Russia – designed to get people to discuss politics in new ways. She invited young politicians and journalists, as well as foreigners. I went to many of them, in Moscow as well as Volgograd and Novosibirsk. Over two decades, hundreds of people came to these seminars, and all of them wanted Russia to be different. I remain convinced that many Russians still want Russia to be different. It’s just that the old system, in the form of Putin, a representative of that system, returned. The KGB reimposed their power. And this wasn’t because of something to do with culture, this was to do with money and politics, and who was in charge. JC: You’ve partially answered my question... I wanted to ask whether that excitement of the 1990s was an exception from the Russian historical norm which has been rather authoritarian? AA: Of course, if you look at the history of Russia since the 18th century, there have always been liberal groups, reformers and revolutionaries. There were the Decembrists, in the early 19th century, and the rural populists later on, who tried to organize the peasantry. A significant group of liberal Russians appeared at the turn of the 20th century, people like the father of the writer Vladimir Nabokov, who was a Russian politician before the revolution. These groups were small in number, but sometimes had a broader significance. The Russian dissident movement in the 1950s and 1960s actually invented the modern human rights movement. It was their idea to hold the leaders of the Soviet Union accountable for the language they used, to remind them of the treaties they had signed and the promised they had made. They created the Helsinki group, for example, that held Soviet leadership to the language of the Helsinki Treaty, which formally ended the Second World War and which contained guarantees of human rights, at least on paper. That idea spread to Eastern Europe, and similar tactics were used here in Poland. (Benjamin Nathans recently wrote a great book about the Soviet dissidents, To the Success of Our Hopeless Cause) JC: But seemingly, even if they do ever get power, they could never hold on to it. AA: We don’t know, because they have never really had power. But in any case, we also don’t know what will happen in the future. There is no reason to assume that Russia will forever be condemned to totalitarianism. Even during the first fifteen years of Putin’s regime there was some form of democratic politics. Only when the full-scale war began did he bring everything to an end: he shut down all remaining independent organizations and killed his most important opponent, Alexi Navalny. But does that mean he is popular, that he enjoys legitimacy? Even now, we don’t really know what Russians think about him, or about the war. There is no way of doing real polling in Russia because nobody will answer an independent pollster over the phone. JC: Do you think that the flock of young people, especially young men, who fled Russia after the start of the war represent a continuation of liberal movements that refuse to partake in the authoritarian state, or do you think they are moving for the sake of self-preservation – “I don’t want to go to the army, so I leave”? AA: I’m sure it’s both. I actually know many people who left Russia for political reasons either in the very last years before the war, or else just after the war began. JC: And do you see a change in the young generation versus the old one that have fled? AA: It’s hard for me to say because the people who I know were mostly already politicized. I do know some younger people who left, but most of them were already either active in the opposition, or working as journalists. Many of them very self-consciously think of themselves as maintaining Russian culture abroad, just as in the 20th century the Soviet dissidents or the anti-communist White Russians once thought of themselves as people who maintained the true Russian culture, outside of Bolshevik Russia. JC: Let’s move on to Poland. One of your first experiences with Poland was reporting on Margaret Thatcher’s first state visit, in the autumn of 1988. You followed her around the farmers’ market. AA: She was making a symbolic gesture. She wanted to welcome free markets, but the only one she could really visit was the farmers’ market at Hala Mirowska. JC: And I want to talk about this area because today you can look out of any window in that district, Mirów, and see rows and rows of skyscrapers. How does it feel to see a country built from the ground in such a short time, both politically and economically? AA: You know, when you’re living in a period of dramatic change, it’s always hard to know whether the change is positive or negative. The transformation in Poland created winners and losers, as well as new classes of people, new political movements of different kinds. At the time, it sometimes just felt like turbulence. Now, we can look back at the 1990s and early 2000s in Poland and see in retrospect that the country was headed in towards prosperity and European integration. In around 2009 or 2010, I remember speaking to a woman who worked cleaning government offices, and who asked me if her daughter should study in Amsterdam or in London. This seemed to me to be a real transformation, and it happened very fast: within a few years, Poles stopped feeling like second-class Europeans, and a generation of younger Poles appeared who had no qualms about crossing borders. JC: We again live in turbulent times. Do you think we’re heading towards positive outcomes? AA: I can’t make predictions, because everything that happens tomorrow depends on what people do today. Also, history doesn’t have a trajectory. It doesn’t move in a particular direction. You only think it does afterwards. As I said, you can look afterwards at Poland in the 1990s and you could say this was a period of great progress. But not everybody at the time saw that. Sometimes people are very wrong about a given country’s trajectory. I remember people writing about Ukraine in the 1990s, about how dangerous it was that Ukraine was independent, that this was going to be an anti-semitic state, that Ukrainian nationalism was going to come back... and although you can say many bad things about Ukraine, the country made many bad choices, actually it became a pretty tolerant state which now has a Jewish president and until recently a Muslim defense minister. JC: In the 1990s Poland’s and Ukraine’s GDP were roughly similar. Ukraine was even a bit richer. So the starting point was similar for both of these countries, but they’ve turned out very, very differently. Even if we stop in 2014. Why do you think Ukraine “chose East”? Was it external influence? AA: No, I think Ukraine was in a different position. First of all, central and eastern Ukraine had been part of the Soviet Union since the 1920s, and had therefore experienced a longer period of occupation, repression, Sovietization and even Russification. Ukraine did not have, as Poland did, an alternative elite: a large cadre of economists and politicians, who already had some experience in opposition politics and in independent thinking. In Poland, the transformative finance minister, Leszek Balcerowicz, had already thought about how an economy might be decentralized before he took office. We can argue about how successful he was, but at least he was prepared to try something new. In Ukraine, people weren’t prepared. For one, there hadn’t been much space even for an illegal opposition in the previous couple of decades. Ukraine was also in many ways still emerging from colonial occupation. For the previous couple of centuries, many of the most capable Ukrainians had moved to Russia, and the first generation of leaders in independent Ukraine tended to be former Soviet apparatchiks. They didn’t immediately seek to become closer to western Europe. Instead, they looked for some kind of economic and political “third way” and an accomodation with Russia. Ukraine became stuck in this position, half-in, half-out and became pretty profoundly corrupt. JC: The Polish alternative elite had a vision of where they wanted the country to go. I think the general perception now is that this vision ends with the next election, right? Is this a natural process of gaining power? AA: Their vision, and it was shared by the time by politicians who now call themselves both left and right, was that Poland should join the EU and NATO, as fast as possible. My husband (Radek Sikorski) was in the very first government that said it wanted to join NATO. At the time this was taken very badly in Washington: the demand for NATO membership absolutely came from Poland, not from the US. But even then, in the early 1990s, many Poles already understood that the Russian sphere of influence would grow once again, that it was important to become part of the transatlantic alliance and an integrated Europe as fast as possible: NATO, the EU, the Council of Europe, all of the trading and security alliances. That consensus lasted through several different governments and over many years, even governments containing former communists. For twenty years, right, left and center disagreed about many things, but they all agreed on the direction that the country should go. In retrospect, that consensus created the basis for prosperity in Poland. JC: And regarding the Polish-Ukrainian relations. We know that antagonisms, e.g. the myth of Wołyń [a massacre of Poles that took place in what is now Western Ukraine, in 1943] are increasingly used in Polish political discourse today. In Ukraine, nationalist historians make heroes out of UPA, the Ukrainian revolutionary army, which is held responsible for this tragedy. Where do you see a start for burying the hatchet? Is the reconciliation of our nations possible? AA: So here’s a strange thing: For more than a decade after they both gained independence, Poland and Ukraine participated in a number of projects that were designed to solve exactly these kinds of Polish-Ukrainian differences. Books were published that were jointly written by Polish and Ukrainian historians, monuments were built. These projects were successful: If you’d asked me this question in 2010, I would have said that there are no real historical issues between Poland and Ukraine, that the two countries had mostly reconciled. For a number of reasons, this began to shift. In Poland, children and grandchildren of victims of the Wołyń massacre felt their tragedy hadn’t been fully recognized. In Ukraine, nationalist groups wanted the UPA partisans who had fought against the Soviet Union recognized for their heroism, despite the fact that some in this broad and not well-defined group were also linked to Wołyń. In both eastern Poland and western Ukraine, the memory of the ethnic cleansing that took place there in the late 1940s - Poles were moved West, Ukrainians East - to accomodate new borders has left feelings of displacement and bitterness. The wave of Ukrainian immigration, which started before the war, may have provoked some of this. But don’t underestimate the role played by Russia, which has always wanted to create discord between Poland and Ukraine, and pumps out propaganda to that effect in both countries. Vandalism on both sides of the border, damage done to cemeteries and monuments, is sometimes carried out by provacateurs working for Russia, just to create bad feelings. The Polish-Ukrainian conflict also hides a different reality: although there are real grievances and bad memories, the truth is that the biggest tragedies both nations experienced in the twentieth century were inflicted by the Soviet Union and Nazi Germany. That should unite these two countries, not divide them. JC: This week (19.04.2026 – Ed.) in Hungary we saw that using historical narratives to create grievance has no longer worked. Are you optimistic about the direction after Orban’s loss? AA: The Hungarian election was really important because it shows that people can actually resist powerful, dominant propaganda. The ruling party Fidesz controlled all of the TV, 90% of the newspapers, the constitutional court, the bureaucracy... and yet people had the nerve to vote against it and resist it. It’s also an important election because Hungary created a huge network of well-funded think tanks and foundations that were funding other far right groups and projects. So that loss is going to have a knock-on effect in other places too, maybe even in Poland. JC: What you’ve said about resisting propaganda reminds me of one of the interviews you did about talking to Russians in the post-Soviet era who claimed that people knew that the system was lying. Why do people choose to believe in these regimes anyway? AA: Because it’s useful. Stephen Kotkin, an American historian, once described how people would learn how to “speak Bolshevik”: It was just a language that you needed to use in order to get by in society. If you didn’t talk the way the regime wanted you to talk, then you might have problems, or lose your job, or your kids would not get into university. It was a way of getting along. Communist Poland was similar, at least in the early years. When I was writing a book about the Sovietization of Eastern Europe after World War II, I met a lot of people who wanted to talk a lot about the war, when many of them had done really heroic things. But almost nobody wanted to talk about the decade afterwards, between 1945 and 1956. This was when you had the short period of terror, violence and Polish Stalinism. To stay safe, people felt the need to just go along with what others were saying, or stay out of politics, or use communist jargon without necessarily believing it. I don’t judge them for it, and I wouldn’t describe all of those people as collaborators. It’s easy to feel moral certainty in retrospect, because we know that communism ended. But if you were living in 1949, it might not have been clear to you that communism was going to end. In very repressive societies, maybe about 10% of people who are really evil – collaborators, torturers. Maybe 10% of people are really brave and who find ways to resist. And then around 80% of people have kids, they have parents, they have to have jobs and they’ve had to get through it somehow. Strange though it may sound, I’ve found that the work I did on that book is now very useful in explaining some of what’s going on in the United States today. There are plenty of members of the Republican Party in Congress who know perfectly well that Donald Trump says many things that aren’t true. But they avoid criticizing him because it’s inconvenient, because they would get in trouble, because someone would attack them on the internet. So actually you don’t even need mass terror to get people to conform. JC: Is Gen Z reinventing agency? AA: We’ll see. In any generation you can find groups of people who want agency. If you live in a society that’s unfair, for example where a tiny number of people have captured most of the wealth, then at a certain point people rebel. This is always easier for younger people, who have you have less to lose. The question now is how the internet will affect the relationships between citizens and the state, and how it will change organizations. The “Twitter revolutions” people spoke about as early as 2008-9, mass protests organized online, have often proved to be very superficial. Although you can easily join something just by clicking, the work of creating a real movement requires physical participation. Successful mass movements of the past, for example the Civil Rights movement in the United States, were built by people who had spent many years together. They had participated in non-violent workshops together. They practiced and prepared. Just using the you can get everybody to show up at a certain moment, but then when the protest is broken up, nothing happens. It’s also true that the repressive regimes have more recently learned how to use the internet to undermine leaders and movements. Most of all, they now understand how to make people cynical. The form of propaganda that most modern authoritarians use - and I think the Russians really pioneered this - deploys sneering cynicism. Instead of praising the rulers, the regime propagandists mock the opposition movement leadership for being supposedly corrupt or sexually degenerate, with the goal of undermining any kind of idealism. JC: MAGA grew on the internet? AA: MAGA is a real grassroots movement. They had symbols, red hats, they showed up at rallies. But you’re right that the cynicism, the sarcasm and the distrust that the movement embodies came originally from the internet, and this is different. Fifty years ago, most European political parties had a social base in real organizations, in trade unions for Social Democrats, in church groups for Christian Democrats. As people stopped going to church and as the trade unions became smaller, the social base of these parties disappeared. Now people who wouldn’t have known one another in the past meet on the internet and create new movements, many of which don’t last. JC: Is history ending? Going in stale circles? AA: History never ends. In truth, human beings want contradictory things at the same time: order and freedom, stability and change. These things are never resolved, and when a society swings too far in one direction, people always push it the other way. But each time that happens, the result is different. Certainly it is true that we are now in a period when old philosophers and ideas from the 1930s are undergoing a revival. Carl Schmitt, who was a philosopher who was very influential on the Nazis, is back as an influence on both the far left and the far right, once again inspiring people to think that all politics has to be existential, that all politics is about defining and defeating enemies. In the US, some are also bringing back dominionism, the idea that we need a Christian and not a secular state. It’s also true that we are living through a more fundamental shift. The old left-right divide, which was mostly about the size of the state, is much less important now. Instead, we are arguing about more fundamental things: what are our rights, what protects our freedom. Or how much power do we want to give small elites, versus how much power to give ordinary people. In America a small group of very wealthy people now control information, because they control the social media platforms and AI, which means they determine what people will read and learn. Finding a way to preserve preserve zones of autonomy and independent thinking, this is going to be the main task for the next generation. JC: What is the one book that a person interested in Central Europe should read? AA: You could read my book “Iron Curtain: the Crushing of Eastern Europe” which tells the story of how the Soviet Union imposed its culture on the region. Or read Tim Snyder’s history of the region, “The Reconstruction of Nations: Poland, Ukraine, Lithuania, Belarus 1569-1999.” And everyone should read “The Captive Mind” by Czesław Miłosz, which describes exactly the phenomenon we were talking about: why do people collaborate? I joined Scott Galloway and the brilliant Fiona Hill in a discussion about the wars in Ukraine and Iran, the future of global power, and what these conflicts reveal about America's role in the world. Scott told us that this was the 400th edition of his podcast, which is quite a number: My friend Francesco Chiamulera runs a brilliant series of literary events, Una Colline di Libri, A Hill of Books, in the Prosecco Hills, a region of vineyards and elegant hill towns in the Veneto, north of Venice. We did an event in Vittorio Veneto and also drove and biked around the countryside. Buy Autocracy Inc Buy Iron Curtain Open Letters, from Anne Applebaum is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
The cult of objectivity has broken consciousness science
With 22 competing theories and no consensus in sight, the science of consciousness is lost. In this exclusive IAI interview, Berkeley psychedelics researcher and bestselling author of a new book on consciousness Michael Pollan insists that even though consciousness lies beyond traditional forms of scientific investigation, we should resist becoming dualists who see it as something radically different from ordinary stuff in the world. Instead, he makes the case for reimagining science itself: it must stop reaching for objective descriptions of physical reality, and instead embrace subjectivity as the indispensable core of all inquiry. Alasdair Craig: How did your experiences with psychedelics get you interested in consciousness?Michael Pollan: One of the things that happens on psychedelics is that they foreground consciousness. What formerly seemed perfectly transparent and ever present—and yet, non-existent, as water is to fish—suddenly you see it. The metaphor I use in the book is that psychedelics sponge the windscreen. Suddenly you realize: wow, there’s a windscreen, there is this phenomenon that’s mediating my relationship to reality. This is not an unusual realization on psychedelics. I think a lot of people are called to think about consciousness after psychedelic experiences. So that was the proximate inspiration for A World Appears: A Journey Into Consciousness (2026).And then there was a more specific way in which psychedelics influence the book. That was a particular experience I had on psilocybin. I had the sensation that the plants in my garden were conscious and returning my gaze, with their own point of view and agency, and I got curious as to how to evaluate an insight like that. I mean, what’s the truth quotient of insights you have on psychedelics? And I was reading William James—who, of course, wrote beautifully about mystical experience—and he said, we can’t judge the metaphysics here, but we should pay attention to two criteria: (1) How useful is it to think this is true? He was a pragmatist, of course. And (2) can we subject it to other ways of knowing to validate it? Because maybe we should treat these insights as hypotheses. And that’s kind of how I approach psychedelics, as a great generator of hypotheses, but they need to be tested against other ways of knowing. And so that led me down this long path exploring the science of plant intelligence and plant sentience.AC: I love your phrase, “smudging the windowpane of conscious experience.” So do you now start to think, actually, even when I’m not on psychedelics, I’m just seeing a screen all the time, which is not reality, but rather is my conscious experience, behind which reality is hidden?MP: Well, you know, not when I’m brushing my teeth and making breakfast! But yes, in meditation, certainly. I mean, one of the things you realize is that my experience happens to be this way now, but it could be another way. And many things can affect it. My morning coffee changes the screen in various ways, sharpens certain things.___The only tool we have to understand consciousness is consciousness.___There’s this wonderful metaphor in Aldous Huxley’s book, The Doors of Perception, where he thinks we channel consciousness, and that what the brain does is edit it, and there’s a reducing valve. And psychedelics open the reducing valve wider. I don’t know that I’m ready to buy into the idea that consciousness exists outside brains, but I do love that metaphor because there are times when you are more conscious than others. I know I’ve switched from window pane to valve, but you know, a camera aperture can open wider or narrower. And I do have a sense of that. I have a sense of when I’m being less conscious, and when I’m being more conscious, by which I mean, you know, more present, taking in more sensory information. So when you start thinking about consciousness as a matter of degree, that changes things also.I think when we scroll on social media, obviously, we’re conscious. But minimally so, because we don’t have to generate our own thoughts. We’re basically taking these little hits from other people and thinking their thoughts.The process of writing this book made me kind of relativize everyday consciousness as just one type, which is exactly what William James said. Normal consciousness is one type, separated by the flimsiest of screens from the other types.AC: If we stick with the metaphor of the smudge on the window that you get when you take psychedelics, it seems like we’re saying that consciousness has become like an object that you’re looking at, right? You’re looking at the smudge and that just is consciousness. But sometimes we’ll talk about consciousness as a state that you’re in, rather than an object you can perceive. You’re either conscious or you’re not conscious. So it’s difficult to really know what sort of thing we’re talking about when we talk about consciousness, right?MP: Yeah. When you say that consciousness is an object, what’s the subject? Consciousness also? The only tool we have to understand consciousness is consciousness. So we’re in a closed loop and when we get a perspective on consciousness, we’re not achieving any distance from it. That’s one of the problems with studying consciousness. Science is predicated on an objective, God’s eye view of things, and you never get that. There’s no such thing. SUGGESTED VIEWING The brain filters consciousness With Àlex Gómez-Marín But, yeah, there is this sense, I think, that consciousness is something you can approach. Certainly, when you’re writing and trying to recreate a conscious experience, it’s a fiction, but you’re standing back from it, and looking at it. But there’s no real subject-object distinction.AC: That’s so interesting, because when philosophers start talking about consciousness, they often talk about what they call “qualia”, which is their word for the felt experience of, say, the color red. And I think that way of speaking often makes us think of the qualia as an object, which you can see out there: the redness of red. But, as you say, we also want to collapse the subject-object distinction when we talk about consciousness. So there’s something strange going on here…MP: Oh, yeah, there are many strange things going on! *AC: Let’s talk about the varieties of consciousness. Apart from perceptions, there are, pains, emotions, thoughts, and so on. What is it that holds all this diversity together so that they all count as instances of consciousness? What is it that they all have in common?MP: Yeah, that’s a really good question. I mean, there is sensory information, right? Which we perceive coming from the world outside ourselves. And then there’s internal information, which is what’s called interoception. And this is very important too. This is where feelings come from—what are sometimes called homeostatic feelings—that are intended to get the brain to keep us in these narrow ranges of temperature and glucose and so on. That’s a very important part of consciousness. And according to some researchers, who I think are probably right, this is where consciousness begins, with these very primal feelings, like hunger and thirst and warmth and itch, and things like that. And then there’s this third thing, which is our thinking about thinking.And what holds all this together is, I think, the sense of self. Consciousness generates a self: it is probably an organizing principle. All this stuff is happening to the self. It’s a construct, I think, but it is very useful. It can connect all these different streams of consciousness to a single being or a place, metaphorically speaking.* AC: The first half of your book is about the science of consciousness. Is consciousness just another thing, like black holes or the origin of life, which we don’t yet understand, but which we should have every hope that science will one day get to the bottom of, or is there something special about consciousness that makes this unlikely?MP: It depends how you define science. As we define science now, it’s going be very difficult. Science since Galileo has had a set of rules or assumptions, which is that the proper remit of science is to deal with the objective, quantifiable, third-person world. And the physical sciences have done amazing work under that set of limitations. Galileo—for tactical reasons, not for philosophical reasons—said science should not deal with the soul, which at the time was what consciousness was considered to be. So what is subjective, what is qualitative, what is first person, we’re going to leave to the church, he said. And this was a good agreement, and it probably kept many scientists from getting burned at the stake. But it leaves science in an awkward spot, now that it wants to venture into that territory of qualities, of first-person experience. And I don’t think it has the proper tools. I think it will have to add to its toolkit in some way, and find a way to bring in phenomenology, or lived experience and introspection, which science is usually dismissive of.The challenge—we alluded to it earlier—is that the only tool you have to study consciousness with is consciousness. And what I mean by that is, the whole scientific enterprise is a manifestation of consciousness. As much as scientists like to flatter themselves with this idea that they attain a godlike perspective on what they study, when it comes to consciousness, there’s no such thing. And it’s fine for all the things you can step outside of and study from that perspective. But two areas it won’t work are consciousness and cosmology.___It could be that we live in this anomaly of not believing nature is conscious. And maybe psychedelics are teaching us something we’ve forgotten.___With cosmology, too, you have to study the universe from inside the universe. It’s not that cosmologists haven’t made progress. We know a lot about the age of the universe and expansion and things like that. But we can’t penetrate what happened before the Big Bang. We just don’t have the tools because we can’t stand outside.The fact that there are 22 full-scale theories of consciousness tells you all you need to know: we’re kind of lost. And I was surprised to find that we are more lost than I thought we were when I started this. I thought that there’d be leading theories, or that we had experiments that we could conduct that would nail some of this down. And the fact is, we don’t.So, I don’t know if science can solve it. But, of course, we can change the rules of science. A really influential book for me was a book called The Blind Spot, by two physicists, Marcello Gleiser and Adam Frank, and a philosopher, Evan Thompson. It’s a reminder that science is a social practice. It’s organized in a certain way and it can be organized in a different way. But it has this huge blind spot at the center of it, which is its failure to recognize that it is a form of consciousness itself, and it doesn’t have a good way of taking account of lived experience.AC: On the one hand, I think you want to resist traditional dualism, which would say that consciousness is something magical, something supernatural, right? But on the other hand, you’re accepting that there is this division in reality between the stuff that you can investigate objectively and measure, and so on—the stuff that science has been good at finding out about—and consciousness, which, for some reason, you can’t objectively measure. Some would take this to suggest that the dualism is actually right. Is there a way of reconciling these two strands of your thinking?MP: To call it magical is full of value judgement. I mean, you could just say immaterial. The interesting thing is, I think, that intuitively we’re all dualists. And I don’t know whether that’s because we’re children of Descartes and other cultures are less dualist than we are. Or it may be because that’s how consciousness feels. It feels different than the body. It feels separate from the body. But I don’t think we should trust that intuition.AC: So let’s think about ways that science might be changed to get at consciousness. I suppose the starting point would be the way that you begin the second half of your book. You have this nice line from William James, where he says, “We now begin our study of the mind from within.” Could you give us some sense of the ways of studying the mind from within? What does this involve?MP: I don’t know what that science looks like. But one of the points I’m making is that it depends on the humanities. I found that I learned as much, if not more, about consciousness, from reading novels and poetry. There is a sense of the fullness and complexity of consciousness that you don’t get in any scientific account. I interviewed this stream-of-consciousness writer and I approached her as an expert on consciousness, and she is. So I think that dialogue is really important.I’m reading Ben Lerner’s new novel, Transcription. Just read the first page of this novel: it’s a man falling asleep on a train, going to conduct an interview, and there is the experience of being in the train, facing backwards, there’s the view outside, but there’s a reflection of himself through which he’s seeing outside. There’s the memory of dropping his kids off at school. All this is going on in one moment of consciousness. Scientists aren’t going anywhere near that. But I think it’s useful for them to think about. That’s where we’re trying to go: like, how does such a layered experience happen? You know, it also makes you wonder, could a computer ever do this? And it gives you some doubt.*AC: Before we get to computers, perhaps we could talk briefly about plants. How did you come to feel that they are sentient?MP: Well, it was a psychedelic experience, and it’s not unusual on psychedelics. In fact, there’ve been studies about how people become animists during psychedelic experience. Their belief in animism arises after a single psychedelic experience.You know, most scientists would say this is all a myth. But we have only 400 years of the age of enlightenment and science. Before that, we were animists, and if you go around the world, most indigenous cultures are still animists, and children are animists, by and large, until they go to school. So it could be that we live in this anomaly of not believing nature is conscious. And maybe psychedelics are teaching us something we’ve forgotten.As I said, I wanted to test this idea, and see whether there was conventional scientific evidence for it. And there’s fascinating work going on in a field that calls itself—in a rather cheeky way—plant neurobiology. These are people who fully realize there are no neurons in plants, but they’re trolling conventional botanists! And they’re doing experiments that are demonstrating that plants can learn and remember, which is kind of amazing: how do you store a memory without neurons? They’re finding plants that can solve problems, that can hear and see. In fact, they have 20 senses to our five or six. For example, a bean plant looking for something to twine, and given a pole within eight inches or so of it, knows where that pole is and will aim its spiraling reach at that pole. What is that about? Is it bouncing signals off of it?One of the spookiest things is the fact that the same anesthetics that put us out put plants out. You might think that plants are already out, but they’re not. They’re just slow. If you take a plant with a fast behavior, like a Venus flytrap, and give it an anesthetic, it will stop reacting. So you have to ask yourself, what is lost when the plant is anaesthetized? Some state of alertness, of awareness, of its environment, of reactivity. I’m not prepared to call that consciousness, but maybe it’s sentience—which is a simpler form of consciousness, and involves the ability to sense what’s going on in your environment and assess what’s good and bad for you and act appropriately. That may be a universal quality of life.AC: Let’s turn from plants to AI. You point out that LLMs are trained on the internet rather than direct interactions with reality. You put this really nicely when you say the internet is not the world so much as a shadow cast by the world. So LLMs are living in this kind of shadow world, or in Plato’s cave, as you put it. What’s the significance of this for AI consciousness and moral consideration? And, to recall the beginning of our conversation, if we’re stuck behind a veil or screen of consciousness, are we also stuck in a kind of shadow world?MP: I don’t think they’re the same shadow worlds because our world includes nature and other people. And even if it’s mediated in some ways... There is a reality out there, and we are in relation to it, through consciousness. There’s friction with it. What’s missing from the LLMs is that friction with the real world. There’s more to the world than human representation, which is what they’re dealing with. And that means that so far, AI is a cultural technology for combining thoughts we’ve already had. SUGGESTED VIEWING Cracking the code for thought With Roger Penrose, Sabrina Gonzalez Pasterski, Max Tegmark, Güneş Taylor Genuine creativity is more than collage. A lot of what AI does now is tantamount to collage, putting this with that and you know, that’s part of art, certainly. But there are also genuinely new ideas that come into the world that don’t come in through manipulating the representations we already have. So it remains to be seen whether AIs can be truly creative in that more radical sense.But my arguments against AI becoming conscious have to do with the fact that the idea of AI consciousness is based on this faulty metaphor that the brain is a computer. There are dimensions in which the brain is like a computer—it certainly does its share of computation. But computers have this sharp distinction between hardware and software, and brains don’t. In a brain, hardware and software are identical. Every memory is a physical change to the brain. Brains are not interchangeable in the way computers are. So this idea that you could take the consciousness out and somehow run it on another substrate, a silicon substrate, seems foolhardy.Anyway, it’s a more extended argument, and I may be wrong. And when we move to computers that aren’t based on silicon—neuromorphic computers and things like that—all bets may be off.AC: Regarding your point about LLMs being stuck in the world of our representations—the internet or whatever—and not being able to interact with reality, are these representations, the world of the internet, themselves part of reality? We’ve created the internet, but it’s still a real thing that exists. And so while the LLMs may be trapped within that part of reality, they’re nevertheless within reality and interacting with it and so on. So it’s not obvious that there’s a barrier there to them becoming conscious and being creative.MP: Yeah, I mean, if our consciousness is built out of human culture, which is what we’re talking about with all those representations. But I tend to think consciousness comes a bit more out of nature and friction with the natural world, but...AC: So there’s a fundamental divide between the natural world and human artefacts?MP: And we lose track of that, and especially people in this computer world. You know, the people who are creating these AI systems, my guess is they’ve been into video games since the age of three, and they didn’t go outside a lot. And their own contact with nature is somewhat limited. I could be wrong, it’d be a very interesting thing to ask, all the wizards of AI, whether they like to go fishing and hiking and do things like that. Or were they on computers from a very early age? I interviewed Blake Lemoine, the Google engineer who came to believe that LaMDA, the Google LLM out at the time, was conscious and deserved personhood. It was very clear that he didn’t see a distinction between this bubble in which he lived and the real world. And I think we’ve all been distanced from the natural world, and this is taking us even further away. But it’s still there, you know, and we still have bodies, and we’re still mortal, and we don’t live in a simulation.AC: I think that’s a great place to finish. Michael Pollan, thank you very much!
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14 years after being announced, Star Citizen hits $1 billion in funding.
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Your mum said it first! 5 health tips now backed by science
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‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field
‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field ‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field A field that once seemed like a direct path to stable, lucrative work is becoming less certain under AI, students and faculty told Spectator. By Ria Vasishtha and Arjun Menon May 3, 2026 Shanying Liu / Deputy Illustrations Editor Asia Genawi, SEAS ’29, first encountered artificial intelligence during her sophomore year at her high school in Indiana. Back in 2023, policies on AI varied widely—even within the same district—and some schools had no guidance at all. As Genawi began to see the effects of AI trickle into her classroom, she turned to guidance from her home state’s Department of Education, which she said she found “outdated and inaccessible.” Genawi spent the rest of her high school career dedicated to the issue, including writing a 15-page memo exploring varying AI policies across Indiana schools, which she sent to every Indiana state senator and representative whose contact information she was able to find. She later helped draft a bill that would have required public high schools to establish and share their own AI policies with students in an accessible format. But with so many other bills already awaiting referral, hers never made it to committee. When Genawi arrived at Columbia to study computer science, she found that the gaps she had spent years trying to address in Indiana had followed her there. Many students and professors were also grappling with what AI meant for the field. Across Columbia’s undergraduate schools, computer science has become the most popular major—accounting for around 11 percent of degrees awarded in Columbia College, 32 percent in the School of Engineering and Applied Science, and 12 percent in the School of General Studies in 2024. While the number of computer science majors in SEAS grew from 166 to 173 during the 2024-25 academic year, the total number across the three schools fell around 4.5 percent from 393 to 375, driven by declines at Columbia College and General Studies. At Barnard, it has grown to become the second most popular major as of 2025, up from third the year prior. The number of degrees awarded have grown fivefold since 2016. Faculty members and students in the department told Spectator that the surge in the major’s popularity has been driven in large part by its apparent promise of a secure, well-paid career path. However, they noted that the recent rise of generative AI has compromised the sense of stability that once defined the field, even as interest in technical skills among students persists. According to data from the Federal Reserve Bank of New York in 2024, out of 74 majors tracked, computer science had the fifth highest unemployment rate among majors at 7 percent, while computer engineering had the second highest at 7.8 percent. “Anecdotally, people are moving away from CS as a major,” Daniel Bauer, a senior lecturer in the computer science department, said. “They’re still taking some of our classes, right, because they think they need that, but they’re instead majoring in other things.” Bauer described a field that had shifted from what he called a “nerdy outlier discipline” to one that “everyone needs,” a sign that technical skills have become a baseline expectation across industries with the emergence of AI. “A lot of people thought, ‘Oh, it’s a guaranteed path to a stable income. You get a six-figure job right out of your undergrad,’” Bauer said. Now, companies may see AI as a way to reduce demand for entry-level programmers, especially in what he calls “code monkey jobs,” roles where a large number of employees are “just writing out code nine-to-five.” Chris Murphy, a senior lecturer in the computer science department, described the current moment as the convergence of two forces: the downturn of the job market and generative AI coming onto the scene. “Things kind of started to really pick up in 2014, 16,” he said, recalling the years after the weaker 2010 market. Murphy added that this was also a period where “students were getting more experience outside of class than they were inside of class” through internships, jobs, and side projects. Murphy suggested that the earlier momentum helped make computer science feel like both an academic program and a reliable pathway into work. That feeling is harder to sustain now as the industry reconfigures, which is a shift that students are seeing firsthand. Rebecca Yu, SEAS ’27, said that during a recent internship in Big Tech, she saw that “every single tech company was racing to integrate” large language models. She added that her manager said her intern class was the first to complete their assigned projects, which she attributed to the increased efficiency that comes with AI. Frank Liu, SEAS ’29, said that with AI lowering the barrier to coding, companies now expect everyone to write code. “A lot of companies outright say if you’re not using coding in your job, you might get fired for not being productive enough,” Liu said. Yu similarly expressed that students increasingly have to accept AI being a part of industry workflow, adding that many also “make use of it to maximize their productivity.” Richard Li, CC ’28, described a “franticness” among his peers as the pace of change accelerates. He explained how “some new tool” is released regularly, noting that tools rise and fall in prominence within weeks. He has come to believe that he doesn’t need to “match that speed all the time” and keep up with every development. Li has learned that AI tools allow him to “take a breath” and “get back into the loop much easier than before” when he needs to. While some companies specifically target Columbia when hiring, sending representatives to campus career fairs and recruiting large numbers from Columbia, a computer science degree cannot be treated as a static credential, Yu described. “You can’t just get your degree and stop learning after that. You have to always be learning,” Yu said. “That is something you basically have to expect for your job.” AI has not only affected students’ decisions to major in computer science, but also reshaped how the subject is taught. Across departments, faculty members no longer treat work done outside the classroom as a reliable measure of understanding, shifting instead toward in-person exams, quizzes, and attendance checks. While homework once made up as much as 60 to 70 percent of a student’s grade in computer science classes, Murphy said that breakdown has since flipped, with exams and quizzes now accounting for the majority. “The assumption—especially among pessimists—is that they’re using it to do their homework,” Murphy said. “They take the homework assignment. They put it into generative AI. Out comes the solution. Submit solution. The end.” Murphy said that faculty members ranged in their responses from fully prohibiting AI use to actively teaching students how to effectively work with AI. He said he shifted his approach this year after his teaching assistants called his belief that students weren’t using the technology “naïve,” and now permits students to use AI on assignments. His surveys of students in his introductory classes have told a more complicated story than the one so-called pessimists offer: Around 60 to 70 percent of students who reported using AI said they used it to have concepts explained to them, to clarify assignment instructions, to generate test cases, or to create practice questions. “Those are all ways that you might have had a tutor in the past to do that, and now you have this AI essentially as your tutor,” he said. Bauer has taken a different approach, teaching students how to use AI productively without sacrificing the core principles of the discipline. “People who are trained to actually use AI tools productively, while being in charge of designing the overall project, will be very much in demand in the next couple of years,” he said. Over the past year, a working group of computer science faculty has been redesigning the introductory and intermediate programming sequence to integrate generative AI as both a subject and a tool, representatives from SEAS wrote in a statement to Spectator. The effort is “coordinated” across the department, “not course-by-course,” with a systematic assessment of how AI integration is affecting student outcomes underway to shape the next round of changes. The goal, the department explained, is for students to be able to “read, verify, and reason about code, whether they or a model wrote it.” Tony Dear, senior lecturer in the computer science department, is piloting individualized AI feedback in a discrete mathematics course, while a machine learning course is also testing a Socratic AI dialogue system designed to “guide inquiry rather than supply answers,” the statement reads. Beyond individual courses, SEAS funded seven cross-departmental faculty projects in generative AI this past academic year, spanning biomedical engineering, chemical engineering, industrial engineering, and computer science, according to the statement. This phenomenon extends beyond the computer science department. SEAS’ new AI minor, which it announced in November 2025, reflects the University’s attempt to adapt. The minor is specifically designed for noncomputer science majors and aims to provide “essential AI knowledge” while emphasizing practical and responsible use across disciplines, according to the SEAS website. At the center of the minor is AI in Context, a course taught by a team of faculty from the departments of computer science, applied mathematics, philosophy, music, literature, and the Writing Center, the representatives told Spectator. Bauer described it as targeted at students who want to bring AI into fields like economics or biology, rather than as a path into software engineering itself. At the graduate level, SEAS announced a new Master of Science in artificial intelligence in February, with the inaugural cohort starting in the fall. While recognizing how AI has helped them navigate coursework, students also described its rise as isolating, even among members of the Application Development Initiative, one of Columbia’s largest computer science clubs. “As people start to ask AI for questions that they would normally ask students and members, it starts to isolate people” Li said. Alexa Kafka, BC ’27, echoed Li’s sentiment, pointing out that computer science has always been a collaborative discipline with code reviews and pull requests, even as AI makes independent work easier. Despite this, Kafka noted that she hasn’t been to office hours “in at least a year.” Bauer added that faculty are exploring long-term solutions to the assessment problem. “One of the things that we’re trying to do at the department or school level is to maybe move towards computerized testing facilities,” Bauer said, referring to ideas in the department to revitalize computer labs as an alternative to pen-and-paper exams. “We have to accept that this is the reality, for better or worse.” But more exams, students say, does not mean better learning, nor does it reflect how computer science is actually done. “Code is so variable and can be approached in so many directions, there’s never just going to be one correct answer. There can be multiple optimal solutions,” Kafka said. Students also expressed concern that the shift toward exam-heavy grading pulls focus away from the applied, project-based work that better reflects both discipline and industry expectations. ADI has tried to respond more quickly than the curriculum can. Through a vibe coding workshop this past semester, club members said they wanted to help students understand not just that AI exists, but how to use it deliberately. “Vibe coding” refers to the practice of prompting AI to write code for a task or project, and has become widespread enough that ADI felt the gap in formal instruction was worth addressing, according to Sophia Huang, BC ’29. The workshop introduced students to the concept of context engineering, which Shaina Sahu, SEAS ’27, described as not just writing a prompt, but optimizing “the rest of the relevant information that you would feed into the model.” Without that, students said that AI-generated code can fail at scale or introduce difficult-to-detect bugs. Genawi said the shift toward AI has changed what it means to be good at computer science. “I think the shift has kind of gone towards what can you create and what can you do, instead of, what do you know,” she said. Indeed, during ADI DevFest, its annual hackathon, Li said more teams are trying to complete their projects than in years past. While sign-ups have historically outpaced submissions, Li said this is beginning to change because teams “have a tool that completes the vision for them.” While many students see AI as an equalizer that lowers the barrier to entry for coding and technical work, Murphy said it also creates new equity concerns inside the classroom around who can afford stronger tools and who already knows how to use them. “The equity issues I worry about are students who have access to paid versions of things versus free versions of things,” he said. Although popular AI models like ChatGPT and Claude have free versions available, both have paid models that can reach over $100 per month, which output different qualities of code. Murphy also pointed to differences in prior exposure to AI literacy itself. “Students who go to high schools or K-12 education, where they’re taught AI literacy, prompt engineering, context engineering, they understand how to do this, as opposed to students who go to schools who don’t teach that,” he said. “Then they come in, and then they’re somehow expected to know how to use these tools.” For Genawi, those disparities begin long before students arrive on campus. “It’s very interesting to consider how lucky you were geographically,” she said. “To be born where you were is influencing your ability to get access to these spaces.” Students like Yu, though broadly apprehensive about the future of computer science, are not without hope. “I’m optimistic, because I think if you’re truly passionate about CS, there will definitely be a place in the field to do something you want to do,” she said. Senior Staff Writer Ria Vasishtha can be contacted at ria.vasishtha@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Staff Writer Arjun Menon can be contacted at arjun.menon@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Want to keep up with breaking news? Subscribe to our email newsletter and like Spectator on Facebook. Produced with Spectate by Emily Ta
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Shaky political science: using "simulated" elections over real-world elections
[Dear DSOS readers – this article is the latest in our “Shaky Political Science” series. In our 38 page report, “Shaky political ‘science’ misses mark on ranked choice voting,” released in early December, we examined over 40 studies focused on ranked choice voting. We found that many of these studies suffered from puzzling research methodologies, poorly constructed surveys, unrealistic simulated elections, cherry picked data, and faulty analyses that often were contradicted by results from real-world elections (a link to our full paper is here). Here are links to the first three articles in our series: the first one summarizing the overall results of our report, the second one analyzing a study co-authored by University of Minnesota academic Larry Jacobs, which was one of the most error-prone of all the research we reviewed in our report, and a third article showing an admirable example of two political scientists holding two other political scientists accountable for their flawed, sloppy research]. In this fourth article in our “Shaky Political Science” series, we shine a spotlight on seven studies that were web-hosted and funded by New America’s Political Reform Program and its Electoral Reform Research Group (the ERRG is an ad hoc committee headed by New America’s Political Reform Program and joined by the American Enterprise Institute, the Unite America Institute and Stanford University’s Center on Democracy, Development, and the Rule of Law). This research consortium has been led by Lee Drutman, senior fellow with New America’s Political Reform Program. These seven studies are simply not credible from any objective standard about how political “science” is supposed to illuminate our understanding of either ranked choice voting or politics in general. The feature that six of these seven studies have in common is that they all used surveys – artificial, simulated elections -- to attempt to say something cogent or interesting about ranked choice voting (RCV) elections. None of them used real world data from actual RCV elections – either the 1000+ elections in the US or the many thousands of elections from places like Australia, Ireland and elsewhere where RCV has been used for 100 years. While a few of these studies conclude with some mixed positives about RCV, our analysis here is content neutral. The idea that, with a political reform like RCV, you can ask respondents in a mock, artificial election to vote with that method, with only the barest of explanation about how RCV works or its likely impacts (i.e. no spoiler candidates, majority winners, voters liberated to pick their favorite candidates, coalition-building), and then ask them their thoughts/reactions about voting in that system, with fake candidates and no real campaigning, no real exposure to an actual election or actual candidates, rests on some very puzzling assumptions. The findings of these seven studies actually are contradicted by the findings from many other studies based on real-world RCV elections. These New America studies also failed to list the real-world RCV studies in their own citations, instead including those studies that reinforced their conclusions. The seven studies featured in this article were chosen because they form a cohesive cohort which precisely illustrates one of the main points of our research paper, namely that using surveys, i.e. artificial elections, or mathematical/theoretical models, instead of real-world data, is in fact “shaky political science.” Below are summaries of our analysis of five of the seven New America studies. You can read our complete analysis of all seven studies at our paper, “Shaky political ‘science’ misses mark on ranked choice voting.” Choosing to “Vote As Usual” by Andre Blais, Carolina Plescia, and Semra Sevi. New America. (Blais et al., 2021). This study, web-hosted and funded by New America’s Political Reform Program and its Electoral Reform Research Group, used two surveys in which respondents completed ballots for simulated elections using plurality, approval, RCV and point (Score) voting. In both cases the authors provided the respondents with only minimal explanation of each method. For example, the entire explanation for RCV was “For this vote, rank the candidates from your first to your last choice (you do not need to rank them all). This is called the ranked vote.” That’s it. The study did not provide any context or explanation to survey respondents about why she/he might want to rank multiple candidates. Participants were not even told that ballots would be tabulated using an “instant” runoff, not to mention any description of RCVs ability to eliminate the spoiler effect or liberate voters to rank their favorite candidates without fear of helping the “greater evil” candidate to win. That’s like taking an iPhone back in time to 1970 and asking someone if they like it better than their rotary phone without explaining how it works. Their first survey targeted states that held 2020 Super Tuesday Democratic primaries and used the real candidates’ names in the survey; the second survey used fictitious candidates. In other words, they surveyed respondents who had only ever participated in plurality elections, had no history or background with using RCV or any of the other methods, had no clue about its likely impacts, and did not communicate how the alternative methods would be counted, and then asked them: “How satisfied are you with using each system?” Predictably, the winner was plurality elections, the system used for president, Congress, gubernatorial and state legislative elections – in other words, the method they have been using, year after year, all their voting lives. With so little explanation of RCV and its impacts, this study is simply not credible in discovering anything useful about real-world RCV elections. It merely shows that a basic voter education campaign is needed when adopting a new election system. Additionally, the result contradicts many other post-election surveys following real RCV elections, asking opinions from voters who had just participated in a RCV election, that showed a great deal of satisfaction with RCV (see details on that in Studies 22-25 in our paper, as well as the four studies cited in the review for Study 28). Share Other studies on “satisfaction” and “understanding” make similar mistakes, in terms of basing their surveys on inadequate explanation to respondents and lack of education about context. How could any survey ever hope to measure accurately, in essence simulate a real-world election, without actual campaigning candidates, the media writing about those candidates, organizations endorsing candidates and voters being inundated with crucial information? More than anything, what these “studies” based on surveys show is that if you ask voters about something they don’t know very much about, and fail to adequately educate them, their responses will unsurprisingly reflect their confusion. Equally puzzling is that New America’s Electoral Reform Research Group, headed by political scientist Lee Drutman, found this to be a credible enough study that they not only published it but highlighted it in Drutman’s own discussion of research related to ranked choice voting. This pattern was repeated in study after study featured by New America’s Electoral Reform Research Group. For example in Ranked-Choice Voting and Political Expression: Voter Guides Narrow the Gap between Informed and Uninformed Citizens by Cheryl Boudreau, Jonathan Colner, and Scott MacKenzie, the researchers based their analysis on a survey which found that respondents who were asked to vote in a simulated RCV election, with minimal explanation of RCV or how it works, displayed less evidence of being informed about how to use RCV effectively, with the least informed voters ranking fewer candidates. As pointed out under the study above, in a real election voters are informed by a wide variety of methods, including public education by the election administration, by interested political groups, the media, and the candidates themselves who benefit from voters being aware of how to vote in the new system. In Support for Ranked-Choice Voting across Race and Partisanship by Joseph Anthony, David C. Kimball, Jack Santucci and Jamil Scott, the researchers used respondents from different parties and races voting in simulated plurality and RCV elections, who indicated their satisfaction with each voting method. Instead of using real world election results, the authors fell back on the easy, armchair and less reliable academic research methodology of making up mock elections. As with the other studies, little explanation was given of how RCV works or what its implications might be (electing majority winners or eliminating spoilers, for example). Unsurprisingly, this study found that respondents were not very satisfied with RCV. However, when the authors added an explanation that RCV has a tendency to elect more women and people of color, they found that this greater explanation increased the preference for RCV. The more voters were familiar with it, and the more they understood potential positive impacts – surprise! -- the more they were open to switching away from the status quo. Of note, the results from this study are thoroughly contradicted by a number of other studies whose data was obtained from real RCV elections with real voters. Those studies show a great deal of satisfaction with RCV. More “fake election” research An interesting wrinkle on this “research by fake elections” approach, which only served to illustrate how unreliable such “research” can become, was taken in Ranked-Choice Voting, Runoff, and Democracy: Insights from Maine and Other U.S. States by Joseph Cerrone and Cynthia McClintock_,_ also web-hosted and funded by New America’s ERRG. It gets high marks for creativity, but an eye-roll for thinking this could possibly add anything meaningful to our understanding of real world RCV elections. This study tried to determine whether RCV, plurality or two-round runoff elections provided greater voter satisfaction and acceptance of election results. To determine that, the authors conducted a survey asking if voters were satisfied with a fictional newspaper report of an election, with three different versions given to respondents – plurality, runoff and RCV, with variations of Republican/Democrat winners and variations of “come-from-behind” winners,” i.e. candidates not initially in first place but who win the “runoff.” Again, a minimal explanation of RCV or how it works was given, and the survey showed that respondents had the greatest unfamiliarity with RCV than the other methods. The unsurprising result? Respondents were much more satisfied with “come-from-behind” victories in a traditional two-round runoff election than in RCV, even though RCV is also a runoff system but with a single round of counting. Interestingly, the dissatisfaction with RCV disappeared for those who were more familiar with RCV. In fact, among those respondents who were “very familiar” with RCV, they were equally satisfied with RCV, runoff and plurality. Surprise, surprise. Again, what this study revealed, more than anything, is not only the inadequacy of the explanation for RCV given by the authors of this study, but the failure of the research format itself, thinking that such an artificial mock election could somehow simulate what actually happens in the real world in a real RCV election. Those four studies reviewed above are fitting examples of inadequate and shaky political “science.” Other studies reviewed in our paper from the New America/Electoral Reform Research Group cohort which also used mock elections included: Ranked-Choice Voting is an Acquired Taste by Joseph Anthony and David C. Kimball. New America. (Anthony et al., 2021). Ranked-Choice Voting is No Refuge for Extreme Candidates by Melissa Baker. New America. (Baker, 2021). Also included in this New America cohort is Does Ranked-Choice Voting Reduce Racial Polarization? by Yuki Atsusaka and Theodore Landsman, which actually did use real-world election results data but applied an odd and unconventional methodology to the data which relied on shaky assumptions and non-real-world scenarios that were too divorced from reality. To determine levels of “racially polarized voting,” the researchers imagined “ethnic parties,” by which they mean political parties for each ethnic group, which was especially odd since the election data they were using came from nonpartisan RCV races. But then they made an even odder assumption, namely that since race and ethnic characteristics of studied voters were not available, the authors tried to infer that information based on who voters selected and the racial make-up of voters in each district. This amounted to little more than vague and ambiguous guesswork dressed up with a bunch of mathematical equations used to give it a veneer of scientific appearance. Indeed, it seemed to assume racial polarization in order to prove racial polarization. Based on this questionable methodology, the authors concluded that RCV doesn’t reduce racial polarization. But the premise of this study missed an obvious reality: since RCV incentivizes more candidates to run and can result in more diverse fields of candidates, one would expect more racially-polarized voting in voters’ top rankings, not less, because more voters would have someone on that ballot who represents their racial or ethnic identity and more freedom to vote for their real first choice. By encouraging more diverse candidates and eliminating the spoiler effect, RCV facilitates voting for a favorite candidate of your own race and then selecting a second choice with the best likelihood of winning. The real measure is what voters do with their additional rankings – do they consider other candidates and vote “for the best of the rest”? This study didn’t tell us anything useful about that. But readily available data shows this is common in real RCV elections, and candidates act on this knowledge by engaging with voters outside their racial group. So the authors of this study failed to consider or account for what actually happens in real-world elections, and their conclusions are tainted by this failure. New America has contributed a great deal over the past 2.5 decades to our understanding of many policy areas, including politics and political reform (full disclosure: Steven Hill, one of the authors of this article and of the “Shaky Political Science” research paper and series, is a former senior fellow and former director of New America’s political reform program, 2005-2010). So it was especially disappointing that New America funded and published such a large batch of dubious studies about ranked choice voting. The stated praiseworthy goal of its Electoral Reform Research Group was to inspire new academic research about ranked choice voting that would shed light and help the public better understand the impacts of RCV. Instead, the ERRG research did just the opposite. It produced dubious research that created more confusion and misinformation. In so doing, New America’s political reform program contributed to “shaky political science.” Steven Hill and Paul Haughey Share Upgrade to $5 subscription Thanks for reading DemocracySOS, a reader-supported digital portal for the pro-democracy movement. Subscribe for only $5 per month to receive full benefits and to support our work. Subscribe
Kingdom Come: Deliverance 2 director "really proud" the gay romance he pushed for, which is somehow totally different to "woke" games' representation, is up for awards
Kingdom Come: Deliverance 2 director Daniel Vávra has tweeted that he's proud of the game's gay romance storyline in totally normal fashion.
This Action Crime Thriller Just Shot to #1—and the Cast Is Absolutely Loaded
A star-studded crime thriller has quietly climbed to the top of Prime Video’s most-watched list, but, somehow, it flew completely under the radar. Find out more about the chart-topper here.
“AI polls” are fake polls
A few weeks after Donald Trump’s second presidential win, I took the train up from London (where I was living at the time) to Oxford to attend a conference on polls and forecasts of the 2024 election. Most of the attendees were pollsters or academics, but I also watched presentations from Aaru and Electric Twin, two companies that do what is interchangeably called synthetic sampling, silicon sampling, or synthetic audiences. Stripped of startup jargon, that means they use large language models (LLMs) to simulate responses to public opinion polls by having AI agents take on the role of survey respondents. I had already heard of Aaru thanks to some articles with eye-catching headlines like “No people, no problem: AI chatbots predict elections better than humans” in the months leading up to Election Day. The founders were making some big, some might even say far-fetched claims, such as: “within two years, we will simulate the entire globe — from the way crops are grown in Ukraine to how that impacts production of oil in Iraq, trade through the strait of Malacca, and elections for the mayor of Baltimore.” When Semafor asked Aaru’s cofounders — Cameron Fink and Ned Koh — about my boss, they said “we respect all those who came before us.” Nate (as he so often does) shared his thoughts on Twitter: Fink and Koh were relatively good-natured about this back-and-forth when we spoke at Oxford. They even offered to mail me one of the t-shirts featuring Nate’s quote they apparently had made. I never took them up on the offer, which I now somewhat regret. These synthetic sampling companies fell off my radar for a while, but they do still exist. In fact, Aaru recently received a $1 billion valuation. Is what they’re doing anywhere close to the most important frontier in AI development? Not by a longshot, especially when Anthropic just developed a model so adept at exploiting software vulnerabilities that it’s only being released to 40 companies. Still, silicon sampling is increasingly finding its way into public polling. Axios reported in March that “a majority of people trust their own doctors and nurses” based on findings from Aaru — without mentioning that the “people” in that sentence were actually LLMs. Around the same time, the Public Sentiment Institute “boosted” their online sample of 373 real survey respondents with 114 AI agents.1 (Spoiler alert: even the co-founder of Electric Twin doesn’t think that’s a particularly defensible approach.) Polling companies like Qualtrics and Ipsos are also developing synthetic data panels. So, what should we make of these … “polls”? Let’s get one thing out of the way: whatever they are, they’re not polls in the way that term is usually defined. Subscribe You can’t replace polls with AI On one hand, using LLMs to essentially make up fake survey respondents sort of sounds like the dumbest idea ever, one that will at best imperfectly replicate real polls while introducing all sorts of biases. On the other hand, with LLMs improving at a remarkable, perhaps even alarming rate, maybe that means I’m a dinosaur at the ripe old age of 24 because I still want to rely on polls that talk to actual people. I’m not going to argue that synthetic samples are completely useless. In fact, as I’ll return to later, there is evidence that some techniques can replicate topline survey results quickly and cheaply. But the marketing from certain companies can be slightly optimistic. “No traditional poll will exist by the time the next general election occurs,” said Fink in 2024. We’re just 206 days away from the midterms, and based on the fact that I still have to collect a bunch of polls every day, I’d say he should have run that prediction by a sample of AI agents before the interview.2 To see why synthetic samples can’t replace polls, here’s a quick primer on how they work. The simplest version of these models involves taking a LLM (like ChatGPT or Claude), giving it a demographic profile (e.g., a white, college-educated woman who lives in Utah and makes $70k a year), and then asking it to respond to a survey question. You repeat that process a few thousand times using different demographic profiles and end up with a sample of synthetic survey responses. The actual models used by private companies are more sophisticated than this, usually because they incorporate more hypothesized demographic characteristics for each agent and provide them with extra information. Aaru, for example, feeds agents a diet of news and information they’d be likely to consume, while Electric Twin incorporates their customers’ proprietary data about the audience they’re trying to replicate. The way Ben Warner, the co-founder of Electric Twin, explained it to me was “we have a large amount of data on […] for instance, 5,000 people. Can we make an accurate prediction of how they would respond to another question?” Still, it should be obvious why synthetic samples can’t replace polls. Polling is fundamentally a data collection process. We might use surveys to make predictions by feeding them into election forecasts, but the main purpose of a poll isn’t prediction, it’s gathering new data about what people think and how they feel. Silicon sampling, on the other hand, produces no new data. It’s simply a model: you input LLM training data, demographic prompts, and a bunch of other information, and it spits out a prediction for what a poll would say. We love models here, but models aren’t polls. That difference is an important philosophical sticking point for most pollsters I talk to. “I think politics should stay away from [synthetic sampling], because we’re trying to […] represent the voice of the people,” said Natalie Jackson, a vice president at GQR Insights. Democratic pollster John Hagner told me: “I think I’m just incredibly skeptical of this idea. I don’t think it’s research. At that point, you’re asking the machine to tell you what you already believe.” Hagner has seen some presentations of early synthetic sampling experiments, but so far, “if it’s being used in a campaign, people are keeping it incredibly quiet.”3 But Eli, I hear you saying, aren’t polls themselves increasingly governed by modeling decisions? Indeed they are: pollsters’ choices on which sampling method to use, how to define their likely voter models, and how to weight their samples can and do lead to dramatic differences in the results they publish. Aaru even referenced these limitations in the methodology statement included with that maternal mortality “poll” — although I’m using the term “methodology statement” loosely here, because it doesn’t really explain how the model works at all. We can ignore the (frankly preposterous) implication that synthetic sampling isn’t subject to a separate set of biases. The important point is that there’s still a meaningful difference between using weighting and other statistical techniques on actual polling data and using a model to predict what a poll would say. The latter is far closer to election forecasts or techniques like MRP — potentially useful models, but not a replacement for polls.4 To be fair, other synthetic sampling companies are perfectly happy with the distinction between polls and models. Warner compared polling and synthetic sampling to different tools in a toolbox. “The mistake I think we make is we think that these new tools should either work in exactly the same way or somehow replace these old tools,” he said. “Rather than thinking of it as, okay, so we’ve always had the hammer, we’ve always had the screwdriver, now we’ve got a saw. But don’t use a saw to try [to] do the job of a hammer.” A quick comment from Nate Eli didn’t ask me for a comment — rather rude of him, don’t you think? But since I’m editing this story, I figured I’d add a few quick thoughts rather than putting words in his mouth. Beyond the frequently misleading marketing, what bothers me about the AI “poll” hype is that as AI tools make statistical inference cheaper and/or better (note that these are not synonyms) that actually increases the comparative value of collecting original data. You might be able to train a model to make a reasonable estimate of what some hard-to-reach poll respondent would say — say, a young Black man who voted for Trump. (Such a person checks a number of boxes for a voter who is usually hard to reach in surveys.) Indeed, this is closely related to what models like the Silver Bulletin forecast already do. They essentially smooth out the kinks in noisy survey data by making inferences based on past voting patterns or national polls or surveys of other states. But you don’t actually know what these voters think unless you’re reaching them directly. If there’s a shift in opinion among this subgroup, you’re not going to detect it. So if I were running a campaign, I’d invest more in going the extra mile to find a representative sample of those voters. And then I’d hire some smart quants — or Claude? — to figure out the implications for campaign strategy based on proprietary data that my competitors didn’t have access to. -Nate Silver Are these models any good? If synthetic surveys are just a new type of model, the next obvious question is whether the models are at least accurate. The answer very much depends on who you ask. On one end of the spectrum, you have the maximalist argument that synthetic sampling is more accurate than actual polls. “It’s an incredibly challenging problem to go to someone and say ‘hey, we’re going to be more accurate at predicting human behavior than you, even when you talk to your customers directly’,” Koh recently told CNBC. In his view, synthetic sampling isn’t a saw to polling’s hammer, it’s “magic.” There’s certainly evidence that synthetic samples can replicate certain survey toplines. But if Aaru does have any examples of their approach outperforming the polls, they’re keeping those to themselves.5 Aaru’s 2024 election model, for example, had Kamala Harris leading in Michigan, Nevada, Pennsylvania, and Wisconsin on November 4th. And although they’ve since taken down their forecast page, they gave Harris a 50.5 percent chance of winning the race on November 2nd.6 After the election, Fink told Semafor he was happy enough with those results because they were “within margin of error,” a term that is completely meaningless when applied to a “sample” of AI agents. And of course, Aaru says their models have improved since 2024, so supposedly now they’d be more accurate than the polls? Still, their stronger argument is on cost: “We are significantly faster and cheaper than traditional polling, and still more accurate,” said Fink. The first two claims are undeniably true, but the third brings us to the opposite end of the spectrum. Both Jackson and Hagner are skeptical that these models are reliable for anything beyond replicating common survey toplines. “I just […] don’t think the machines are what we want when we’re looking for nuanced views. My example on this is people in Arizona and Nevada in 2024 who voted for Trump and voted for expanding abortion in their states on ballot initiatives,” said Jackson. Hagner identified another issue. Maybe the synthetic respondents, like sycophantic LLMs, are inhuman in one important way: they’re too nice. “The reports that have come through at the meetings that I’ve been at are that the early experiments on this, they cannot get respondents to be as racist or sexist or, frankly, as negative as human respondents,” he said. Academic research mostly agrees on this point. While there are some papers that show promising results when using LLMs to replicate polling data, most show that LLMs suffer from various quirks like producing too few “don’t know” responses and can seriously overpredict the favorability of politicians like Donald Trump and Kamala Harris. They also seem to struggle with too little variation between demographic subgroups, so the difference in predicted opinion between Democrats and Republicans, for example, is too small. When I asked Warner about these studies, his response to these papers was that just because academics can’t get synthetic sampling to work doesn’t mean that the technique doesn’t work in general. “Actually, the argument is, okay, yours does not [work]. That does not mean […] for this complex set of machinery, which uses a lot of investment, a lot of time, a lot of money, you can’t get it to work.” Cards on the table, I’m somewhat sympathetic to this argument because academics aren’t exactly great at making election forecasts. Usually, the people with skin in the game are the most accurate. Warner’s argument is that the approach Electric Twin takes — which includes, for example, making multiple predictions for each synthetic respondent using different models and prompts and subsequently averaging those to get a final prediction in a sort of ensemble forecast — produces better results than the simpler academic models. Warner shared a comparison between his method and the method from a recent academic paper with me, and Electric Twin was indeed able to get more accurate replication. But even still, he acknowledged that synthetic sampling “is not a crystal ball.” “If you asked me, do I think using other data sources will be more accurate than asking somebody who they will vote for, I would probably say no. But if you asked me ‘would your system be useful for our turnout modeling today?’ I would say yes.” For better or worse, it looks like the method is already getting more popular in the market research world. Most of the clients Aaru touts these days are businesses like EY and McDonald’s. And AI will probably begin to pop up in other parts of the political polling process. Pollsters are already using it to code open-ended survey responses, and some firms, like YouGov, are testing using LLMs to ask survey respondents questions. More worryingly, one danger to actual polls is that AI agents can be used to infiltrate online surveys. Most online polls use various checks to prevent that from happening, but there’s conflicting evidence on how effective those filters are and how prevalent AI agents currently are in online panels. If those agents ever become impossible to detect, it might spell the end of online polling, but the solution isn’t to replace all of your respondents with ChatGPT. Silver Bulletin is a reader-supported publication. To receive new posts and support our work, consider becoming a subscriber. Subscribe 1 That particular poll obviously doesn’t meet Silver Bulletin standards for aggregation. But we exclude all Public Sentiment Institute polls from our averages because we classify them as an amateur polling firm. 2 You could argue that Fink meant the next presidential election, but (a) I’m also confident we’ll still have real polls in 2028 and (b) in that case he should have asked an LLM to define “general election.” 3 Quick caveat: that’s reporting from a Democratic pollster. It’s possible that Republicans are more willing to use AI in political campaigns. 4 Indeed, Silver Bulletin does not include “polls” produced by MRP in our forecasts or averages, and we think it’s extremely misleading when their practitioners describe them in a way that suggests original data had been collected among a large number of states or Congressional districts. 5 A recent report from Aaru and EY did show two examples of a synthetic estimate being closer than a survey to a real-world benchmark — but I’d take those findings with a grain of salt because the report reads more like an ad and didn’t involve any sort of prediction being made ahead of time. 6 For comparison, our odds for Harris on the same day were 48.2 percent.
IT’S SCIENCE. IT’S SURREAL. IT’S THE SIBILANCE OF KIM SALMON
KIM SALMON APPEARS on my screen intact, in motion, but not, I assure him, infected by any filters adding bunny ears, cat whiskers or fish scales. Dignity is appropriate for the man who emerged from the most isolated punk scene of all in late ‘70s Perth to become a force of nature, and whose early swamp-rock take on life after punk was to spawn a decade and a half later – for better and worse – the more earnest, less thrilling grunge movement.Yes, somehow that mega selling, decade-defining scene
The Super Mario Galaxy Movie is a black hole of entertainment
Somehow, the Super Mario Galaxy Movie is even less of a film than the first.
The Super Mario Galaxy Movie is a black hole of entertainment
Somehow, the Super Mario Galaxy Movie is even less of a film than the first.
We all need to become better science storytellers. Here’s why and how.
Last week, in a lovely New Haven bar, six people gathered in front of a crowd to tell stories that were somehow related to science and public health. It was magical. One person talked about learning how social determinants of health helped them forgive their mother’s alcoholism. Another shared what it’s been like navigating a dementia diagnosis. Another described their last dinner with their mother before they left Nigeria to come to the U.S. and how that moment, plus the diagnosis that followed, shapes their career goals today. As the Executive Director of The Evidence Collective at Your Local Epidemiologist, I was ecstatic to bring this event, “Science and Storytelling,” to the community surrounding the Yale School of Public Health. Stories are not the default way most people communicate about science and public health. In fact, we are taught to take all the emotion out of data, but that makes it pretty darn boring to everyone else. And if people can’t see themselves in it, feel themselves in it, or influence it, how can we ask them to support it? Why do stories stick? How can we all—from community members to public health scientists—do better? And what are some examples?
Kemi the attention-seeker somehow always makes two plus two equal five
The looming oil crisis caused by the Iran war gives the Conservative leader a platform from which to jump to the wrong conclusions
79 Brilliant Memes That Brought Science And Humor Together
Let’s be honest—complex physics theories and mind-bending math problems can leave most of us staring blankly, wondering what just happened. But one thing most of us can understand is a good meme about them. Somehow, even the most complicated subjects become instantly relatable when they’re turned into a clever joke. And that’s exactly what we’ve got for you today, pandas. We’ve rounded up a bunch of science and math memes that take these “serious” subjects and give them a fun twist. You might no
Microsoft Promises Slew of Windows 11 Changes in Response to "Microslop" Criticisms
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