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Science diplomacy lessons from a North Korean volcano
Mount Paektu, a mythic, active volcano on the border between North Korea and China, is almost the epitome of a scientific challenge that crosses political lines. In 946 CE, it erupted in one of the five biggest volcanic events of the past 10,000 years, kicking up huge quantities of ash and sending destructive mud flows down river channels for hundreds of kilometres. Should this happen again, the entire region, including easternmost Russia, South Korea and even Japan could be hit. “It’s definitely got the potential to be big,” said James Hammond, a professor of geophysics at Birkbeck, University of London. An eruption on the scale of 946 would have “huge regional impact.” For the past 15 years, Hammond has helped lead a groundbreaking collaboration with North Korean scientists to study the volcano, navigating scientific sanctions, tough export controls on scientific equipment and a long, pandemic-enforced exodus from the country. Although he seems more at home on far-flung research expeditions – before speaking to Science|Business, Hammond was camping out on a Greenland ice sheet – he has also advised the European Commission on its changing science diplomacy strategy. His long experience with North Korea has made Hammond sceptical of blanket bans on science collaboration, no matter the country.This is a live question in Europe, where in the wake of Russia’s 2022 invasion of Ukraine, institutional ties with Russian universities were almost entirely severed, although some scientists fear this could undermine our understanding of climate change’s impact on the Arctic. Here, Hammond tells the story of the Mount Paektu mission and the policy lessons he takes from it. Ominous rumblingsThe genesis of Hammond’s collaboration came in 2002, when Mount Paektu began to rumble ominously. Earthquake activity picked up and the volcano began to emit unusual gases. North Korean scientists took notice. “People felt we need to know more about this volcano,” said Hammond. In 2011, North Korean vulcanologists put out a request for international expertise to help them learn more. At the time, Hammond and his collaborator, Clive Oppenheimer, were working on a vulcanology project in another sanctioned country, Eritrea, and so decided to answer the call. Within a month, they had flown into Pyongyang. “It was pretty incredible,” recalls Hammond (left). “We were made to feel like honoured guests, and invited to official celebrations.” The scientific opportunity was huge. Paektu is unusually positioned, a thousand kilometres from where tectonic plates rub against each other in the Pacific. “It was an incredibly interesting volcano, but not much research had been done, at least not in the international community,” he said. “There was so much we felt we could do. And we had these partners that were super keen to engage.”The mission received an unusual visitor in the form of volcano-obsessed filmmaker Werner Herzog, who accompanied Hammond and Oppenheimer while directing his 2016 film Into the Inferno about volcanos across the world. Four days into the trip, the German director delivered a long speech about reunification to his North Korean hosts, recalls Hammond. “He got to the heart of the Koreans and how they felt, and how they thought, in a way that I'm not sure I ever will,” he said. UN sanctionsHowever, Hammond realised he’d been “naïve” about how difficult it would be to collaborate with North Korea, which was sanctioned far more heavily than Eritrea. “We didn’t fully appreciate the all-encompassing nature of restrictions,” he said. In 2016, as tensions escalated over Pyongyang’s nuclear tests, a United Nations resolution banned all joint scientific work with North Korea. However, the UN sanctions did allow countries to request carve outs, and the UK successfully requested an exemption for Hammond’s work. Related articlesEU pushes for joint science diplomacy, but care needed to avoid gridlock, experts sayRussia severs its last ties with German scienceAnchor Greenlanders in Arctic climate research, experts tell EU ahead of policy updateExport controls have also delayed Hammond’s work. In one case, it took 18 months to get approval from the UK government to take seismometers, which measure earthquakes, to North Korea. “It was frustrating,” he said. “But they didn’t just say no.” However, one instrument, called an induction coil, used to measure how the earth conducts electricity, was blocked entirely because it can in theory be used to detect submarines. Karaoke bondingSince the collaboration started in 2011, Hammond has visited the country around 15 times, although the pandemic closed off North Korea for more than five years. A trip last November was Hammond’s first since the outbreak. Despite this lengthy interlude, Hammond has deep bonds in the country. The North Korean scientists Hammond works with are somewhat isolated, as they struggle to access the latest research papers and travel to international conferences. That said, they are “excellent geophysicists” and are “very well trained in the field,” he said. Over karaoke and chats about their families, “we’ve made friendships, for sure,” he said. The authorities have to sign-off things like the placement of seismometers, for example, but Hammond said these requests have been approved. “Everything that we've asked for within a scientific context has been delivered.”Scientific backchannels? These kind of personal links between scientists across political lines are one purported benefit of science diplomacy. During the Cold War, some historians argue, scientific contact between the US and Soviet Union laid a groundwork of trust for other cooperation, such as on arms control. Hammond agrees that backchannel contacts to North Korean geophysicists are hardly likely to defuse a military crisis on the Korean peninsula, but the simple fact of the scientific collaboration makes contacts between diplomats that little bit easier. “It creates opportunities to understand each other a little bit better,” he said. “When maybe you have those more difficult discussions as diplomats, it's coming from a slightly better place.” Cutting tiesDrawing lessons from the Mount Paektu mission for today’s links with Russian science isn’t simple. The analogy is far from exact, Hammond said, “because one is essentially a Cold War, versus a pretty hot war in the case of Russia.” But Hammond’s broader argument is that the challenges we face, such as climate change, pandemics, biodiversity loss, pollution and so on, have globalised in an unprecedented way, making blanket shutdowns in collaboration with any country unwise.He’s somewhat critical of the UN scientific sanctions imposed on North Korea in 2016, even though they did allow for exceptions. “I think a blanket halt to some of these things, when we face big global challenges [. . .] that’s quite a risky thing to do,” he said.Institutional endorsement?European academics are still by and large free to work individually with Russian counterparts. However, official, institutional partnerships have largely ended. Shortly following the full-scale invasion of Ukraine in 2022, Russian university rectors wrote a public letter endorsing the war, meaning European universities fear official collaboration could also be seen as a kind of endorsement. Hammond acknowledges there is a risk of legitimising regimes, and state-controlled universities, through scientific cooperation. “That’s the trade off you have to make,” he said. Strategic projectsWith Russia, instead of giving a green light to restart all Arctic science, a middle ground might be firing up a few carefully selected “strategic” projects, said Hammond. After all, European countries are still collaborating with Russia on the International Thermonuclear Experimental Reactor, an experimental nuclear fusion plant in the south of France. However, even if Europe did try to revive Arctic science with Russia, there’s no guarantee Russian scientists would play ball. A series of high-profile arrests of physicists in Russia accused of sharing their findings with the outside world has made collaboration fraught. Even before the invasion of 2022, “the Russian regime made it increasingly difficult, and this sort of discouraged people,” Dag Rune Olsen, rector of the Arctic University of Norway, told Science|Business last year.
650 NASA Volunteers Have Co-Authored Scientific Papers
After a recent count, NASA Citizen Science is proud to report that more than 650 people who have volunteered to participate in NASA citizen science projects
iOS 26.5 adds beautiful wallpapers for your iPhone, here’s what’s new
iOS 26.5‘s new Pride wallpaper actually comes in 11 colorful variations, plus a custom option for creating your own. Here are the details.
Today’s Papers – Farewell Zanardi, the Superhero
La Gazzetta dello SportSuperheroFarewell to the man of impossible featsA driver living life always on the edge. The crash and his legs were amputated, then he won the gold medals at the Paralympic Gam...
New AI Trained Only on Pre-1930 Data Speaks Like the Most Old-Timey Guy Imaginable
Researchers have created an AI model trained exclusively on books, newspapers, and other text sources from before 1931.
Today’s Papers: Forza Calcio, Malagò progress, Gervasoni deposition
La Gazzetta dello SportOnly Milan Modric has decidedDoesn’t want to finish on an injury, another year in Rossonero to play in the Champions League with Allegri, or it’s goodbye to footballThe Scu...
Today’s Papers – Inzaghi speaks out, Spalletti calls Bernardo Silva
La Gazzetta dello SportPenalty Wednesday. Atletico-Arsenal ends in a drawInzaghi, I talkThe ex-Inter coach says it all for the first time‘No favours, we were affected instead. Well done, Chivu, I kn...
Gazette newspapers win 51 awards at Top of the Rockies
The Gazette family of newspapers won more than 50 awards at the Society of Professional Journalists’ 2026 Top of the Rockies Excellence in Journalism contest. The Gazette family, which includes The Denver Gazette, The Colorado Springs Gazette and Colorado Politics, collectively won 51 awards at a ceremony Saturday. Colorado Politics won 12 awards, including three first-place […]
The Health Plan continues connection with Tough As Nails Urban Challenge
Jeff Knight, CEO of The Health Plan, said his company’s sponsorship of the Tough As Nails Urban Challenge – a highlight of the Ogden Newspapers Wellness Weekend presented by WVU Medicine – is an easy and fitting connection. “It has shared values with what The Health Plan stands for – a healthy lifestyle, wellness and […]
The Health Plan continues connection with Tough As Nails Urban Challenge
Jeff Knight, CEO of The Health Plan, said his company’s sponsorship of the Tough As Nails Urban Challenge – a highlight of the Ogden Newspapers Wellness Weekend presented by WVU Medicine – is an easy and fitting connection. “It has shared values with what The Health Plan stands for – a healthy lifestyle, wellness and […]
Today’s Papers – Italian football shocked again, a new Calciopoli?
La Gazzetta dello SportRocchi under investigation for sports fraud: ‘He picked referees wanted by Inter’Calcio, another shockThe designator accused by the Milan Prosecutor: ‘I’ll suspend mysel...
Google accidentally shares Pixel 11 Pro Fold wallpapers in Android 17 preview
Google seems to have accidentally included some Pixel 11 Pro Fold wallpaper thumbnails in a recent Android 17 preview build.
Here’s a preview of Pixel 11 Pro Fold’s wallpapers, hinting at colors [Gallery]
Google’s Pixel 11 series is in the pipeline and, in the latest Android 17 beta release, we spotted a quick...
Scene One Entertainment opens Market Arcade 8
Scene One Entertainment, alongside Benchmark Management Group, opened the Market Arcade 8 on Wednesday in downtown Buffalo - the latest for the Schenectady-based entertainment company, and its first foray in Western New York.
SCRC activism exhibit revisits protests, politics for America’s 250th
SCRC’s newest exhibit, “We Demand!: A Legacy of Activism in America” revisits newspapers, photographs, speeches of protests in the United States. The collection spans from the 1850s to the late 2010s.
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
Business Beyond the Beach Talk Show: Monica Matteo-Salinas
🎙 Welcome to the Business Beyond the Beach Talk Show! 🌴 The Miami Beach Chamber of Commerce is proud to present Business Beyond the Beach, the brand-new Chamber talk show created in partnership...
Scotland's papers: Starmer 'fights for his future' and child mental health crisis
A review of the front page stories from the daily newspapers in Scotland.
Scotland's papers: Edinburgh Uni student held in US and Scots declining health
A review of the front page stories from the daily newspapers in Scotland.
Inside the Supreme Court’s Risky New Way of Doing Business
Secret memos obtained by The New York Times illuminate the origins of the court’s now-routine “shadow docket” rulings on presidential power.
Can we trust the science shaping our lives?
Improved methods for social and behavioral sciences research could help enhance public trust in science, says a new study that investigated the robustness of data analysis to understand whether it reliably ...
Today’s Papers – Allegri’s frosty relationship with Milan, Yildiz’s knee problems
La Gazzetta dello SportRoma tension, Ranieri could even leaveGasp wants full trustInter, Bastoni takes a breakChivu changes; the defender is tired and will miss Cagliari.Devil of a nineJuve slow down,...
Scotland's papers: 'Catastrophic' A&E waits and unpaid business rates
A review of the front page stories from the daily newspapers in Scotland.
Today’s Papers: Two Italy duels, Inter strength, Juventus stars
La Gazzetta dello SportDuels of Italy Malago-Abete for the FIGCAzzurri CT: Allegri battles ConteSerie A in agreement (19 of 20) in favor of the former CONI President. The number one of the amateur le...
Today’s Papers – Shocking Milan, Juventus celebrate
La Gazzetta dello SportInter in Como for the Scudetto. Pio must do a LautaroNapoli in Parma with the comeback dream. Conte: ‘Let’s put pressure.’Great LadyWins in Bergamo and narrows the Champio...
“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.
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Navigating the social media minefield
Scientists and researchers seeking to announce promising findings, exchange ideas or contribute to policy discussions outside of academic circles may find social media an expedient tool.But increasingly, scientists and other professionals are discovering that online platforms can be a double-edged sword: while sharing their work and expertise is crucial for visibility and meeting funder expectations, it also exposes them to baseless criticism and even accusations of spreading false information."It is getting harder and harder for scientists, and researchers in general, to convey their findings without facing attacks on their legitimacy and accuracy of their research," says Valère Ndior, a professor of public law at the University of Western Brittany in Brest, France, who has spent more than a decade studying misinformation on social media. Researchers attempting to challenge deceptive online information may themselves be accused of political bias or not being objective in their research, he explains, adding that some scientists disengage because they feel overwhelmed and unable to sustain meaningful dialogue. "It is quite sad to see in some instances that researchers end up leaving social media altogether because they feel like the pressure is getting too intense or feel threatened," he says.Ndior, a past president of the Francophone Network of International Law, is also involved in European efforts to make science and research findings more accessible to the public. As an ambassador for the Science Comes to Town (SCTT) project, he has participated in recent discussions on public perceptions of science and online misinformation. The European Commission-funded initiative connects Brest and two other cities — Kiel in Germany and Split in Croatia — and aims to strengthen ties between communities, universities and research institutions to promote science awareness and cooperation across Europe.Coordinated campaigns around contentious topicsNdior draws a clear distinction between critical thinking and thoughtless criticism. Yet he sees online discussions being increasingly shaped by suspicious behaviour and coordinated information campaigns — including "raids" aimed at dominating discussions and "astroturfing," where small groups act as larger movements to sway debates. Tracking these patterns has become harder because some platforms have restricted data or charge for it, despite provisions of the European Union's Digital Securities Act aimed at ensuring researchers can have access to such data. According to Ndior, "platforms became more reluctant from the moment access to data became a legal requirement rather than a voluntary initiative."Unfounded claims and scepticism about science existed long before Internet chat groups. But the noticeable rise in online hostility has intensified around contentious topics, such as the coronavirus pandemic and climate change, alongside the weakening of gatekeepers to moderate content.For Ndior, dubious claims about pandemic countermeasures and vaccine safety highlighted the struggle between "balancing freedom of expression and the protection of public health and order." Efforts to remove social media content deemed false or risky for public health triggered accusations of censorship and the silencing of legitimate discussion, and in some cases, legal challenges.Concerns about attacks on the credibility of scientists and researchers have generated a flurry of academic papers in recent years and prompted professional communities to address ways to counter online attacks. Such unease extends to the generation that has grown up with digital media. Ndior points out that his students, some of whom research artificial intelligence regulation, hate speech, online surveillance and other controversial topics, hesitate to share their work or viewpoints online. "Many of them don't want to expose themselves too much because they don't feel ready to be faced with the backlash of other people criticising their research," he explains.Safer harbours for engagementLegal challenges against false or defamatory posts are not necessarily a solution — especially given the trans-jurisdictional nature of the Internet. Lawsuits also take time and money, and if they fail, can be counterproductive. Instead, Ndior advises scientists and researchers to be selective in how and where they communicate. Professional online platforms and moderated discussion spaces offer a better environment for engagement. He also highlights the value of more traditional formats, such as radio interviews and in-person discussions at schools, libraries and science fairs, which encourage dialogue with the public. "Personal contact makes a big difference," he says, while acknowledging that these approaches lack the global reach of social media.Ndior’s interest in digital law and online misinformation stems from his time as a doctoral student in international law in the early days of social media. He began analysing posts from governments and heads of state to determine if they could be considered official and thus used as evidence in litigation. His work attracted media attention and led to conference and speaking invitations. "This was not part of my plan," he says, "but this is what happens as a researcher — your interest is sparked by a certain event or phenomenon, and it suddenly becomes your focus."Ndior believes SCTT provides "a double benefit" for researchers, enabling them to connect with peers and interact with the public. "There is a wide community of people who are not in academia who are critical thinkers looking for opportunities to ask questions, to get information and contribute their ideas,” he says. "I really value that kind of feedback."Science|Business, which connects policymakers, academics and industry through its news reporting, analysis and events, is an SCTT partner.
Navigating the social media minefield
Scientists and researchers seeking to announce promising findings, exchange ideas or contribute to policy discussions outside of academic circles may find social media an expedient tool.But increasingly, scientists and other professionals are discovering that online platforms can be a double-edged sword: while sharing their work and expertise is crucial for visibility and meeting funder expectations, it also exposes them to baseless criticism and even accusations of spreading false information."It is getting harder and harder for scientists, and researchers in general, to convey their findings without facing attacks on their legitimacy and accuracy of their research," says Valère Ndior, a professor of public law at the University of Western Brittany in Brest, France, who has spent more than a decade studying misinformation on social media. Researchers attempting to challenge deceptive online information may themselves be accused of political bias or not being objective in their research, he explains, adding that some scientists disengage because they feel overwhelmed and unable to sustain meaningful dialogue. "It is quite sad to see in some instances that researchers end up leaving social media altogether because they feel like the pressure is getting too intense or feel threatened," he says.Ndior, a past president of the Francophone Network of International Law, is also involved in European efforts to make science and research findings more accessible to the public. As an ambassador for the Science Comes to Town (SCTT) project, he has participated in recent discussions on public perceptions of science and online misinformation. The European Commission-funded initiative connects Brest and two other cities — Kiel in Germany and Split in Croatia — and aims to strengthen ties between communities, universities and research institutions to promote science awareness and cooperation across Europe.Coordinated campaigns around contentious topicsNdior draws a clear distinction between critical thinking and thoughtless criticism. Yet he sees online discussions being increasingly shaped by suspicious behaviour and coordinated information campaigns — including "raids" aimed at dominating discussions and "astroturfing," where small groups act as larger movements to sway debates. Tracking these patterns has become harder because some platforms have restricted data or charge for it, despite provisions of the European Union's Digital Securities Act aimed at ensuring researchers can have access to such data. According to Ndior, "platforms became more reluctant from the moment access to data became a legal requirement rather than a voluntary initiative."Unfounded claims and scepticism about science existed long before Internet chat groups. But the noticeable rise in online hostility has intensified around contentious topics, such as the coronavirus pandemic and climate change, alongside the weakening of gatekeepers to moderate content.For Ndior, dubious claims about pandemic countermeasures and vaccine safety highlighted the struggle between "balancing freedom of expression and the protection of public health and order." Efforts to remove social media content deemed false or risky for public health triggered accusations of censorship and the silencing of legitimate discussion, and in some cases, legal challenges.Concerns about attacks on the credibility of scientists and researchers have generated a flurry of academic papers in recent years and prompted professional communities to address ways to counter online attacks. Such unease extends to the generation that has grown up with digital media. Ndior points out that his students, some of whom research artificial intelligence regulation, hate speech, online surveillance and other controversial topics, hesitate to share their work or viewpoints online. "Many of them don't want to expose themselves too much because they don't feel ready to be faced with the backlash of other people criticising their research," he explains.Safer harbours for engagementLegal challenges against false or defamatory posts are not necessarily a solution — especially given the trans-jurisdictional nature of the Internet. Lawsuits also take time and money, and if they fail, can be counterproductive. Instead, Ndior advises scientists and researchers to be selective in how and where they communicate. Professional online platforms and moderated discussion spaces offer a better environment for engagement. He also highlights the value of more traditional formats, such as radio interviews and in-person discussions at schools, libraries and science fairs, which encourage dialogue with the public. "Personal contact makes a big difference," he says, while acknowledging that these approaches lack the global reach of social media.Ndior’s interest in digital law and online misinformation stems from his time as a doctoral student in international law in the early days of social media. He began analysing posts from governments and heads of state to determine if they could be considered official and thus used as evidence in litigation. His work attracted media attention and led to conference and speaking invitations. "This was not part of my plan," he says, "but this is what happens as a researcher — your interest is sparked by a certain event or phenomenon, and it suddenly becomes your focus."Ndior believes SCTT provides "a double benefit" for researchers, enabling them to connect with peers and interact with the public. "There is a wide community of people who are not in academia who are critical thinkers looking for opportunities to ask questions, to get information and contribute their ideas,” he says. "I really value that kind of feedback."Science|Business, which connects policymakers, academics and industry through its news reporting, analysis and events, is an SCTT partner.
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Your Thymus and Your Healthspan
Our thymus gland plays a central role in the development or our immune system, specifically for supporting T cell development (how these cells got their name, maturation and differentiation in the thymus) and discriminating between self and foreign, non-self antigen proteins with production of dendritic cells. As we age, our thymus gland shrinks—the process known as involution—with progressive change from spongy to fatty tissue, with loss of functionality. But this process, with respect to timeline and extent, markedly varies from one person to the next. And to make things even more complicated, our thymus gland anatomy and precise location in the chest also is highly variable. So the famous Frank Netter diagrams from the 1960s (such as at left below) don’t capture the remarkable heterogeneity that a random set of 12 chest CT scans (below at right). What I consider as 2 landmark papers in Nature this week (here and here) used AI to quantify health of the thymus in 2 large cohorts, and then correlate the metric to a broad array of health outcomes. In this edition of Ground Truths, I’m going to cover three questions: (1) How was thymus health determined by AI?; (2) How is thymus health linked to key clinical outcomes? and (3) Are there ways we can promote a healthy (aka rejuvenate) thymus gland in our later years? Subscribe 1. How was thymus health determined by AI? This was accomplished by extensive work developing and validating an AI pipeline for 2 stages, the first for localization and segmentation of the thymus bed, and the second to quantify a digital marker, termed the thymic health score. There’s a lot to this algorithmic development, so I won’t go into all the details, but just provide a rudimentary outline of what was done. The 1st stage used supervised learning with 2 radiologists reviewing 2,461 chest CT scans. That work trained a 3D U-Net model to automatically identify the thymic bed’s 3D cropped region using center of mass coordinates, which reached 99.8% accuracy. The 2nd stage used a foundation model that was pre-trained with SwAV (which stands for Swapping Assignment between multiple Views), a self-supervised model, that generated a high-dimensional thymus representation of 4,096 features. That compares to the radiology reductionist and subjective scoring of 0 to 3 where 0 means the thymus is fully degenerated and fatty, and 3 is considered dense, intact glandular soft tissue. Notably, the self-supervised learning (SSL) performance was superior to supervised (AUC ~0.75 vs 0.55, respectively) reflecting the shallowness of the 0-3 classifier vs SSL’s holistic, self-taught AI. The thymic health score ranged from 0 to 100, with the highest number indexed to fully preserved thymic health. The algorithmic work extended to explainability with both Shapely value distribution, meaning the model was holistic not relying on any “magic” pixel, and occlusion sensitivity, demonstrating the model’s performance was not affected by ribs, sternum, lung tissue, but rather focused on the thymic bed directly. Below are a few saliency maps from the occlusion sensitivity that indicate the thymic bed focus, not affected by neighboring structures, using the jet color scale. Now the AI was ready for processing ~25,000 CT scans, each over 30 MB files, from the 2 large participant cohorts to provide a thymic health score, it did so in less than 14 hours, which is less than 2 seconds per scan! Share 2. How is thymus health linked to key clinical outcomes? The two cohorts were the National Lung Screening Trial, NLST (N=25,031) and the Framingham Heart Study, FHS (N=2,581) each with baseline demographics and long term follow up of >12 years for health outcomes. From the NSLT, you can see below that increased age and body-mass index were correlated to reduced thymic health. And, overall, men had reduced thymic health scores compared with women. There are a lot of graphs in the paper for outcomes, for both the NLST and FHS cohorts. To simplify the major outcomes, below is a composite Figure with striking reduction of all-cause mortality and for the different causes of death. The results were consistent between the 2 cohorts. For example, the cardiovascular mortality hazard ratio average was 0.57 in NLST and 0.38 in FHS (weighted to be 0.53 for the aggregate). The reduction of mortality also extended to digestive diseases and pulmonary disease (data not shown below). Lung cancer incidence was reduced by 36% for high vs low thymic health (Figure below, with a panel -incidence and b panel-mortality, adjusted for age, sex, BMI, smoking status). Notably, there was a smoker’s paradox: lower incidence and improved survival for lung cancer in smokers who had a high thymus health score. Smoking was associated with lower thymic scores whereas alcohol was not. Higher thymic health was linked to higher HDL cholesterol, lower triglycerides, lower fasting blood glucose, and lower systolic and diastolic blood pressure. Inflammation biomarkers, such as C-reactive protein and interleukin-6, were elevated in the people with lower thymic health scores. In their second paper, the same team looked at the relationship between thymic score and outcomes for 3,476 patients receiving cancer immunotherapy. The non-small cell lung cancer progression-free survival was reduced in patients with low thymic health score. A parallel relationship for survival was seen for other types of cancer including melanoma, breast, and kidney with a 44% lower risk among high thymic scores (Figure). A similar pattern was seen with different immune checkpoint inhibitors. The thymus health score outperformed programmed death ligand-1 (PD-L1)and tumor mutation burden (TMB) assay of the tumor and was an independent prognostic marker of progression-free survival. In this dataset, a direct connect with thymus score and adaptive immune function was noted with a correlation before cancer treatment for both T-cell diversity and thymus T-cell production (a metric known as T cell receptor excision circles). Thymus Removal Study There is a highly relevant citation about thymus function before moving onto ways to rejuvenate it. In 2023, a very important study of thymus removal during cardiothoracic surgery was published, with 1146 patients undergoing thymus removal vs 1146 matched controls (mean age 55 years). The adverse outcomes for thymus removal were striking, with a 2.9 higher risk of all-cause mortality and doubling of cancer incidence, 1.5 fold increase in cancer mortality, and 1.5-fold increase in autoimmune diseases. The immune function showed marked compromise after thymus removal, as reflected by CD4+ and CD8+ T cells (Figure below) Share Ground Truths 3. Are there ways we can promote a healthy (aka rejuvenate) thymus gland in our later years? In recent months we’ve learned a lot about the process of thymus involution and the pathways by which this may be modulated. Thymus involution is primarily due to loss to thymus epithelial cells (TECs) and there are 2 subtypes with different functions: the cortical, responsible for positive selection of T cells, and the medullary, for negative selection. When adipose tissue infiltrates the thymus, thymic adipocytes are pro-inflammatory, knocking out T-cell output. Likewise, systemic inflammation, or “inflammaging,” from smoking, obesity, and chronic stress promote thymic adipocytes. Now, from preclinical studies, we know about key pathways that account for these processes. Historically, back in 2014, FOXN1 was recognized as a single master transcription factor essential for TEC function, with studies in mice with forced FOXN1 upregulation leading to thymus regeneration. That laid the foundation for potential regrowth of quiescent thymus cells. It took awhile to find pathways to accomplish this goal and to even refute its role as the master regulator. The Liver-Thymus Axis Feng Zhang and his team recently showed that injection of an mRNA vaccine to the liver encoding DLL1, IL-7 and FLT3-L in combination, factors known to support thymopoiesis (Figure), successfully enhanced immune function in aged mice. However, the effect was transient. The FGF21 Story Two reports in 2025 addressed the thymus gland’s production of FGF21, a growth factor (fibroblast growth factor 21) and its control of thymus involution. This growth factor is also produced by the liver, but it doesn’t have impact on the thymus in aged rodent models. In contrast, The liver’s hepatocyte growth factor (HGF) has been shown to reverse senescent TEC structural changes. Growth hormone stimulates production of insulin growth factor-1 (IGF-1) in the liver and the thymus. Two small studies in human participants (TRIIM, for Thymus Regeneration, Immunorestoration, and Insulin Mitigation) of 6 and 50 people, respectively, treated with combined human growth hormone, metformin and DHEA, suggested the potential of slowing epigenetic aging and improving thymus mass and function. But the combination of drugs, small sample, and lack of controls make conclusions murky. Increased thymus FGF21 led to increased CD8 T cells in old mice and extended healthspan and improved physical performance. Building on the previous FOXN1 data, ablation of β-klotho, the obligatory co-receptor for FOXN1, accelerated thymic aging. The benefit to FGF21 was confirmed in a companion paper using an FGF21 knock-in mouse model showing thymus enlargement and increased TECs throughout the lifespan. (schematic Figure below). The accompanying editorial for these 2 papers speculated: “The proposed link between age-associated thymus involution and organismal aging is intriguing, and suggests we might seek to achieve systemic rejuvenation by counteracting thymic involution.” Other Factors Lessons from the Axolotl (Mexican Salamander) In an elegant set of experiments of the axolotl (Figure), known for its complete thymus regeneration after total surgical removal, mediators were identified. Surprisingly FOXN1 was dispensable. But midkine, a growth factor, appeared to be the driver, the initiator of thymus cell growth, survival, and repair. Other components that contributed were Postn+ (periostin-expressing mesenchymal niches) and Ccl19, a chemokine protein from the bloodstream. RANK and RANKL RANK (receptor activator of nuclear factor κB its ligand (RANKL) have been considered key regulators of medullary TECs. In a study of both aged mice and human thymus cell cultures, their key role was confirmed, with multiple benefits of resorting TEC function, recruitment of progenitor cells, and T cell development. Subscribe Summing Up This body of work strongly supports the health of the thymus gland as a critical regulator of human healthspan, not just a correlate or link. The new landmark studies are reinforced by the regenerative biology experimental models that have shown, via an array of mediators, that healthspan of aged mice is at least in part dependent on thymus gland function and its critical role for maintaining adaptive immunity. It sure seems that we’d be better off having an immune reservoir of naive T cells instead of a profile in older adults of exhausted, low quality, memory T cells, with a senescent phenotype. It is striking that we ignored the importance of the thymus gland for many decades. A wake-up call was the results of the thymectomy matched control study reviewed here, with the opposite of high thymic health score improved health outcomes. The convergence of AI and healthspan here is notable. The exceptional and laborious work for developing and validating (no less explaining) the AI to quantify thymus health set the foundation for probing the connect the major health outcomes in two cohorts with extensive follow-up. We’ve never had a way to meaningfully quantify the thymus gland before, so this represents important leverage of supervised, self-supervised, and transformer models. The study wouldn’t have been possible without AI. And it begs the question as to whether there are ways we can maintain our thymus at a high health score. But it’s not so simple to rejuvenate our thymus. There are multiple risks including the induction of autoimmunity, increasing the risk of cancer, and inducing a pro-inflammatory state. For example, factors that increase TEC proliferation could compromise the medulllary negative selection process and leak out auto-reactive (self-attacking) T cells. Thymic cells could be induced to proliferate, but we know, for example, that growth hormone and IGF-1 are associated with an increase risk of cancer. If thymus rejuvenation doesn’t clear out the accumulated senescent cells in older adults, then inflammation within the gland could block the production of TECs. Keeping these risks in mind, we now have identified many ways to keep our thymus healthy as we age that undoubtedly will be tested in clinical trials going forward. Ultimately, the benefit-to-risk tradeoffs will be defined. In the meantime, we have desperately needed an immunome. As I’ve stressed in multiple prior Ground Truths, we have no test in the clinic to assess a patient’s immune status! It was very encouraging for me to get an email from Hugo Aerts, the senior author of the landmark papers in the days after they were published: “I also wanted to say that your Substack on “Why We Need an Immunome” was inspiring for this work. We found it a very compelling perspective and greatly enjoyed reading it.” Just having an assessment of a person’s immune status via a chest CT scan, with millions of these performed per year, might help in guiding the right immunotherapy for cancer (e.g. more intensive, combinations for those with low thymic health scores) and help define people who are increased risk for age-related diseases of cancer, cardiovascular, and neurodegenerative. The main theme of Super Agers is that we now have many layers of data (genetics, proteins, biomarkers, organ clocks that can be integrated via multimodal AI) for us to define a person’s specific risk decades before one of these age-related diseases leads to symptoms, enabling prevention. From the new studies this week, we can add thymus health score as yet another way to understand a person’s risk, a window into their adaptive immune system and healthspan. And perhaps someday we will be able to safely rejuvenate the thymus, or maintain its health through one’s life, and use the thymus health score to monitor. NB: I wrote this post (No A.I.) A Quick Poll Loading... ********************************************************************* Thanks to Ground Truths subscribers (now > 200,000) from every US state and 212 countries. Your subscription to these free essays and podcasts makes my work in putting them together worthwhile. Please join! If you found this interesting PLEASE share it! Share Ground Truths Paid subscriptions are voluntary and all proceeds from them go to support Scripps Research. They do allow for posting comments and questions, which I do my best to respond to. Please don’t hesitate to post comments and give me feedback. Let me know topics that you would like to see covered. Leave a comment Many thanks to those who have contributed—they have greatly helped fund our summer internship programs for the past two years. It enabled us to accept and support 47 summer interns in 2025! We aim to accept even more of the several thousand who will apply for summer 2026.
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OpenAI’s latest product let’s you vibe code science
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