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New OMB rule could break science in the United States
The drug that saved your mother. The treatment your doctor recommended. The clinical trial that bought someone you love more time. None of it was inevitable. It required a system built to operate outside politics and sustained over decades, because science doesn’t operate on the timeline of a politician. That system is now under direct threat. The Office of Management and Budget (OMB) has proposed a new rule to regulate all federal grants, not just science, but housing, education, defense, NASA and everything in between, that would fundamentally change how research is conducted in the United States. There have been a lot of fires in the past 16 months, and if everything is an emergency, nothing is an emergency. But this is a very big deal. These rules would strip away the independence that has kept science from becoming a political tool. The good news is there’s still something we can all do. How the grant system was designed to work When I was a new faculty member, I was full of millions of ideas, so I sat down and wrote an NIH proposal. I worked on it for months and thought it was so good. Then I sent it to my mentor. It came back covered in comments. Places where my reasoning wasn’t as airtight as I’d thought, methods that could be stronger, gaps in my thinking that I had been too close to the work to see. It stung, as honest feedback always does, but peer review almost always makes the work better. In fact, it’s the backbone of how American science has functioned for generations. At NIH, submitted proposals go to a panel of scientists who have experience in the field. These are the people who can read research methods and spot their weaknesses, who understand when an experiment is designed well and when it isn’t. Applications are scored rigorously, and often only the top 3-20% of proposals receive funding. The people making funding decisions are required to justify them based on these reviews. To be clear: this is not a perfect system, and good science still goes unfunded more often than any of us would like due to limited resources. There is also criticism that peer review may undervalue bold ideas that are risky but could have high payoffs. But the peer review system is nonetheless a meaningful part of the grant selection process. While thoughtful and careful changes could improve the system, the changes being proposed by OMB will not make things better. The rule that could change everything Through this OMB proposal, the system that helps decide what gets funded is being dismantled. There are many troubling elements buried in this proposal, but three provisions stand out in particular. Each would be damaging alone. Together, they would change what kind of science gets done in America, and who it serves. 1. Political appointees would decide which science gets funded, and peer review would be explicitly sidelined or ignored. The guidelines your doctor follows, the standards that determine what’s in your air and water, the drugs that get approved for your family: all of it starts with a funding decision. Right now, that decision is made by scientists who can evaluate whether the work is actually sound and whether it could move the needle forward. Under this proposal, funding decisions could be made by political appointees. The careful, expertise-driven review process that shapes grant funding would be effectively sidelined. That means that a poorly designed study could get funded simply because someone in a political office liked the sound of it, while rigorous, important work doesn’t get funded because it no longer aligns with the administration’s priorities. In other words, critical work that benefits all of us could now be missed just because it has become politically inconvenient. 2. Grants could be canceled at any point, without warning, in the middle of ongoing work. Say your tax dollars have been paying for a cancer study for two years. The grant was awarded for five years, so the team is mid-experiment. There are three additional years’ worth of answers that could change how the disease is treated for hundreds of thousands of people. With this new rule, the federal government could cancel the remaining funding tomorrow, walk away from the commitment it made with your money, and have no legal obligation to finish what it started. This is a huge waste of money. There are rarely other sources of funding for this work, which means the team, the graduate students, postdocs, and research staff who have dedicated years of their careers to this project could lose their jobs. Patients who have contributed their time to studies may not see it turn into useful learnings for others. Every hour of work already completed could result in nothing useful. Science can take decades to get to tangible outcomes. It needs a stable funding system to flourish. 3. Researchers would have a harder time communicating their findings without pre-approval from the federal government. There is a saying from Sir Mark Walport: “Science isn’t finished until it’s communicated.” Science is no use to anyone if it is kept locked away in the labs that produced the data. The proposed rule could make communicating research findings harder in a number of ways: Make it harder for scientists to widely share their findings in scientific journals. Publication costs, including journal fees that allow for broad public access, could not be paid for by federal funds which is often how scientists pay these costs. Restrict researchers from engaging publicly about how their findings should inform policy or public health guidelines. This would restrict scientists from doing the work that transforms years of lab work into decisions that actually affect people’s lives. Make it harder for scientists to attend conferences. Conferences would now need to be approved by the federal agency at the time of grant award. This disadvantages conferences or publications that are not politically aligned. Conferences are a key way in which scientists learn about work happening in their field so they can collaborate and build on each other’s findings. What good is science with a muzzle? The long-term impact These changes could (and hopefully would) be reversed under the next administration. But by then, damage has been done. Once projects are halted or denied funding by political appointees, people leave their science careers for other paths or even leave the country to do their amazing science elsewhere. You cannot pause a scientific study the way you pause a subscription you decided isn’t useful anymore. You cannot freeze a research team that depends on salaries to feed their families, causing a scramble for replacement funding that, in most cases, simply does not exist. When the money stops, everything stops, and all the work in progress and its potential are lost. Despite all of the language about reducing waste, fraud, and abuse, this new proposed rule increases the administrative burden tremendously. Every researcher watching this unfold will make a rational decision: don’t start anything that will take a decade to finish. This includes not building a team around funding that could vanish, or asking the big questions that need patience and stability to answer. The most consequential science, the kind that produces the treatments and the breakthroughs that reach your doctor’s office twenty years from now, is exactly the science that would be abandoned first. This is still a proposal, so we can all do something Some worry this rule is already a done deal. But by law, OMB is required to open a public comment period. Those comments matter because they inform members of Congress, they can be used in litigation, and they create a public record. So here’s what you can do: Submit a public comment. The public comment period on this proposed change is open until July 13. Anyone can submit a comment, and OMB is required to respond to substantial ones. Each comment must be different to count as distinct; identical comments will be counted only once. Comment as an individual, not on behalf of your organization. Here’s a full resource to help you, with useful examples, but in general: Share a story about how science or federal funding has benefitted you or is involved in your work. Are you or someone you loved a cancer survivor? Do you know someone with Alzheimer’s? Have you received NIH/NSF or other federal funding? All of these can be stories you use to highlight why you care. Explain why you’re worried about these proposed changes. You can use the wording found here or in other resources to help you. Ask them to withdraw this proposed rule. Contact your elected representatives. Congress allocates money to federal agencies to spend, and it has oversight of how that process works. You can let your representatives know this proposed change concerns you and ask them to intervene. There are levers they can push that can help at this moment. Let others know why federal funding matters. This isn’t just about science, but ALL federal grants, including for education systems, defense projects, and more. The process, including the importance of federal funding, is invisible to many. We can all make it more visible by sharing how science benefits us and why we value it. You can also share this article, or any of the resources linked here, to help spread awareness! Bottom line We are quickly losing ground in scientific research in the U.S. More changes, like the proposed rule by OMB, would decimate our ability to conduct research here, leaving us all worse off: fewer treatments for pancreatic cancer, less research on pollution impacts, fewer answers for patients with rare disease, and more unaddressed health needs. The impact will be very real for all of us, regardless of where we stand politically. Using our voices for science is more important than ever. Love, LM Big thanks to Dr. Megan Ranney for reading this over and providing brilliant insights, as always. Dr. Liz Marnik, PhD, is Executive Director of The Evidence Collective at YLE and a science communicator and immunologist working at the intersection of public trust, science, and public health. You can find her on Substack, LinkedIn, Instagram and Threads. Your Local Epidemiologist (YLE) comprises a team of experts, ranging from physicians to immunologists to epidemiologists to nutritionists, working together with one goal: to “Translate” ever-evolving public health science so that people are well-equipped to make evidence-based decisions. The YLE suite of newsletters reaches over 475,000 people across more than 132 countries. This newsletter is free to everyone, thanks to the generous support of fellow YLE community members. To support the effort, subscribe or upgrade below: Subscribe
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Chartbook 449: Voldemort on Threadneedle street. The Bank of England and the "haunted house" of English politics.
Imagine the scene: In some Harry Potter version of 21st-century London, a group of deathless UK Treasury officials gathered from across the last century huddle over warm pints and glasses of Chardonnay. Around the table there are officials from the 1920s, the 1930s, the 1970s, 2022 and today. Inevitably, in May 2026, the subject of conversation is the disintegration of the current Labour government. Despite its huge majority in parliament, it has been reduced to tatters by catastrophic local election result. These exposed the fact that rather than having a government with a clear popular majority, the UK is like most other modern societies divided into 5 segments each of which commands between 26 and 16 percent of the vote. Perhaps unsurprisingly, the leadership at Nos 10 and 11 Downing Street - where the Prime Minister and the Chancellor (Treasury Secretary) work - seem paralyzed. They are caught between mounting discontent over unfairness and the cost of living, and tough fiscal strictures that push them into making unpopular spending decisions. In the London pub, the Treasury officials from across the ages, can barely hide their satisfaction at the latest display of democratic politics caught in the vice-grip of financial logic. “Remember the mur d’argent and the banker’s ramp?” “Just like yesterday!” There are smirks around the table. Then the representative of 2026 pipes up: “One thing you have to say about the current lot (referring to the latest hapless Labour government), you don’t have to teach them about the bond market!” There is a murmur of ascent from the Treasury Mandarins. The trauma of the fiscal crisis of September-October 2022 sits deep. Back then, in the final stages of Tory decay, a ‘mini budget’ that challenged fiscal orthodoxy led to a brief but fierce panic in one of the oldest government bond markets in the world (aka gilt market). Now all you have to do is to mention the “bond market” to hush debate. [ Paul Mason@paulmasonnews In the name of public service, and as ex-economics editor of BBC Newsnight, I offer to do a zoom call, tonight, with any Labour MP who wants to understand why bond markets do not "fall into line" with governments. 1/ 3:57 PM · May 12, 2026 · 466K Views 224 Replies · 674 Reposts · 3.93K Likes ](https://x.com/paulmasonnews/status/2054229532404519082?s=20) “And the funny thing is”, the young man in the huddle continues, “they don’t even want to talk about … ”. There is a sudden hush. Significant looks are exchanged around the table. About? One of the senior figures puts down his glass with a decisive “clink”. He-Who-Must-Not-Be-Named has entered their thoughts. Meanwhile, a few miles away in a grubby pub in Bloomsbury, two conspirators from the camp of Critical Macrofinance huddle over cans of low-alcohol IPA. They look at each other and blurt out loud: “The Bank!” “Everyone in the bloody Labour party is talking about the bond market. But why aren’t they even mentioning … the Bank of England!?” “Why is no one talking about Voldemort?” In Paul Mason’s blogpost, after much chest-thumping about basic fiscal logic, the basic point about the Bank of England is buried in the fine print at #3 in his list of suggestions as to what a radical Labour government might actually be able to do! [ Conflict & Democracy Down with the bond market! Down with gravity! It may seem unfair to focus on Labour MP Paula Barker for her off-the-cuff assertion that the bond market would have to “fall in line” with Andy Burnham, should he replace Keir Starmer as prime minister. But Burnham himself told the New Statesman that Labour had to “get beyond this thing of being in hock to the bond markets… Read more 2 days ago · 100 likes · 3 comments · Paul Mason ](https://htsf.substack.com/p/down-with-the-bond-market-down-with?utm_source=substack&utm_campaign=post_embed&utm_medium=web) Back in Bloomsbury they shake their heads and ask: “Didn’t we learn anything from the Eurozone crisis?” Meanwhile, as if summoned to the conversation by some higher force, the “pink pages” announce: “The days of ultra-cheap government borrowing have come to an end” and Martin “Whizzard” Wolf publishes the graph of the season Look at the UK in 2026, perilously positioned on the upper edge of the pack. No wonder no one in London needs any lessons about the “bond market”. But, look again. Imagine how they feel in Rome. What is London’s nightmare in 2026? The nightmare is that you end up like Italy in the early 2010s during the Eurozone crisis. Once comfortably situated in the middle of the pack, watching with horror as your ten-year yields explode to 7 percent and “spreads” become a national nightmare. One of the largest economies in Europe, a founding member of the euro, stigmatized. But the message of the Italian experience is ambiguous. After all, the stigma didn’t last. In 2026, Italy borrows at rates lower not only than the UK but the US. The US, which, as everyone knows, enjoys the “exorbitant privilege” of being the issuer of reserve, safe asets. What kind of magic is this? How did Italy, in the space of fifteen years, go from being good, to bad and back again? Which brings us back to our dissident friends in their Bloombury boozer and their memories of the Eurozone crisis. Italy never was Britain - with its ongoing fiscal deficits. Without interest payments, on primary balance, from 2000 to 2020 Italy ran a tight fiscal ship. Even in 2008 it barely went into deficit and when it was being put on the rack in the early 20210s its primary surplus matched that of austere Germany. So, what happened? How did it end up stigmatized? Of course Italian politics didn’t help. Berlusconi was at the helm and he had legal issues. But amongst friends in the Bloomsbury pub, Berlusconi is a sideshow, the name we whisper to each other is “Trichet”. From 2004 to 2011 the ECB was headed by Jean-Claude Trichet, ex of the French Treasury, more German than the Germans. After 2009 as the news of the Greek fiscal disaster broke, the European bond markets wento into panic mode and Trichet began a brutal game of cat and mouse. Between 2009 and 2011, Trichet intervened in the bond market to help, only when he thought he had compliance with austerity. When he thought they were uncooperative, he withdrew. In the summer of 2011, he even made direct suggestions to his Italian counterparts in Rome, as to how Italy should be governed. It was this cat and mouse game that drove the bond markets crazy and exposed Italy to a violent squeeze. When Mario Draghi took over the ECB at the end of 2011 and declared “whatever it takes”, the pressure on Italy, gradually eased. It is that starring role that has made Draghi into the towering figure in European politics that he remains today. So now you see why voices in London hush when it comes to the Bank of England. “The bond market” isn’t an irresistible objective force like the weather or an avalanche. It can appear like that. But that depends on the way it is being handled, or not handled by the central bank. Which is why the silence about the Bank of England in London right now is so significant. If you think this all sounds a bit fishy, coming from a left-liberal Keynesian like myself, well, let me introduce you to Robin Brooks, who, to put it mildly, plays on a different quidditch team to me. Here, from the position of a fiscal hawk is Robin’s celebratory account of the Bank of England’s role since 2022; In October 2022, at the height of the bond market blow-up in the UK, something incredible happened. Governor Andrew Bailey told British pension funds the Bank of England would end its support program for the country’s fragile gilt market, drawing a line under how much help the central bank was willing to give to exposed pension funds and - implicitly - the government. By the end of that week, Kwasi Kwarteng - the finance minister - had resigned. Prime Minister Liz Truss would soon follow. This episode is so incredible because it contrasts with what happened in the Euro zone earlier that year. Bond markets in Spain and Italy were under pressure amid high inflation and rising interest rates. In the middle of this, Mario Draghi - Italy’s Prime Minister - resigned, compounding pressure on bond markets of high-debt countries on the Euro periphery. Unlike the Bank of England, the ECB caved. It bought Italian and Spanish government bonds in an effort to cap yields and introduced a new tool that signaled to markets it might do such caps more frequently going forward. Faced with pressure on bond markets, the ECB capitulated to political pressure from high-debt countries like Italy and Spain. The Bank of England stood its ground and toppled the Truss government. This kind of thing has long-lasting consequences. It means markets price a higher probability of yield caps in the Euro zone, which keeps Italian and Spanish yields artificially low, while markets feel free to push up UK yields without fear of central bank intervention. As I flagged in yesterday’s post, this means you really can’t compare UK yields to those of other high-debt countries. The UK looks worse, but only because its central bank isn’t interfering with markets. There’s more to this than just that 2022 episode. The Bank of England has also been much more aggressive in its quantitative tightening (QT) than other central banks. If one motivation for quantitative easing (QE) is to lower bond yields - especially longer-dated ones - then it stands to reason QT pushes yields up. The left chart above shows a four-quarter moving average of UK government debt issuance (black line) in percent of GDP and which sectors absorb this issuance, including the Bank of England (blue bars). The right chart above compares the Bank of England’s accumulation or run-off of government bonds (blue line) with that of other central banks, where this blue line is the same as the blue bars in the left chart. The Bank of England was quicker and more aggressive than other central banks in downsizing its bond holdings, so UK yields will have risen more than elsewhere also for this reason, not just because of Governor Andrew Bailey’s remarks in October 2022. Back in October 2025, after a conversation in New York with friends in British politics, my sense of dysphoria was such that I raised the issue of the Bank of England openly in the FT Since 2008, the UK has slid into a deep economic and political predicament. Growth has stagnated to a degree far worse even than in the 1970s. The Tory leadership’s wager on the Brexit referendum spectacularly backfired, leaving the UK isolated from Europe and at the mercy of its special relationship with the US, many of whose political class regard the UK as a basket case. After years of austerity, the Labour party lurched to the left and then back to the centre. The Tory party has been eclipsed by the populist nationalism of Reform. Any British government should be worrying first and foremost about how to restart growth. Instead, Keir Starmer is beset by shades of the gilt market panic triggered by the Liz Truss government in 2022. The debt level is higher than in recent years, but there is no cause for panic. UK debt is at far from critical levels and of long duration. Whether you want to “take back control” or launch progressive economic policy, a democracy dogged by fear of bond market vigilantes is unhealthy. In a country that is a monetary sovereign, this climate points to one thing: a disconnect between the government and the central bank. Since 1997, the independence of the Bank of England has become a sacred cow. But independence is what you make of it. And in the wake of the gilt market crisis of September 2022, relations between the Bank of England and the UK government need a reset. In normal times, there is no doubt that an inflation-targeting independent central bank can serve a country well. But since 2008, the UK and other advanced economies have not had the luxury of such simple problems. To their credit, central bankers around the world have not stood on orthodoxy. After 2008, the US Federal Reserve rescued the global banking system and, through quantitative easing, it stabilised the Treasury market in the face of huge deficits. In Europe, things were trickier. Both the Bank of England under Mervyn King and Jean-Claude Trichet’s European Central Bank played cat and mouse with national governments. This was a high stakes wager that between 2010 and 2012 escalated bond market tension and triggered a disastrous turn to austerity. Shaken by the impact of those shocks, their successors, Mark Carney and Mario Draghi adopted a more protective stance (assuming you were not the government of Greece). Recall that Draghi’s legendary slogan, “Whatever it takes”, was uttered to face down the City of London’s bond vigilantes. In 2015, Draghi launched QE — financial repression by another name. In 2016, Carney used the authority of the Bank of England to stabilise markets following the vote for Brexit, an exemplary demonstration of how central banks can underpin democratic choice, even when those choices are wrong headed. All these were independent central bankers steeped in the best practice of the 1990s, who recognised that historic crises demanded radical action. It was the price surge of 2021-2023 that poisoned the atmosphere. Though the shock came mainly from the supply side, central banks ended up in the dock. Nowhere more so than in the UK. The Bank of England reacted with aggressive normalisation. Faced with a cost of living crisis, the governor called for workers to accept real wage cuts. In early 2022, as gas prices were at record levels and Russia’s army was poised to invade Ukraine, the Bank adopted a stringent programme of quantitative tightening, elevating interest rates. When the Truss government got itself in trouble, the Bank took almost a week to come to the rescue. Rather than enacting a charade of normality, it is time to recognise that in 2025 the UK faces a period of historic transition. To meet this challenge, what is needed is a new concordat with the Bank. This should not ignore inflationary pressures or the long-run trajectory of debt, but should affirm the priority of reviving investment-led growth. One could follow Donald Trump in demanding interest rate cuts. The Bank could shadow the ECB in its commitment to capping Eurozone yields. But the top priority should be to lay the ghost of September 2022. The Bank’s slowing of QT last month was a concession. An immediate and complete end would send the right signal. Such a concordat will not by itself restore sanity to politics, solve the housing problem or rebuild the NHS. But it would help to lift the fear of bond market crisis, which is paralysing the effort by democratic politicians to answer the fundamental questions facing the nation. Now, that call for a new concordat between government and Bank of Englands seems more urgent than ever. The problem is that in October 2025, Starmer still had some authority. Today the government is in tatters. And when you are the “under the harrow” - to echo a phrase of Montagu Norman’s from the 1920s - it is the worst possible time to consider institutional change. To make general arguments at a time of crisis can only seem like special pleading rather than a general argument for long-term change. The same, unfortunately, is also true for the other basic institutional reform that Britain urgently needs i.e. the abolition of the out-dated first past the post electoral system and its replacement by a moderated form of proportional representation. And thirdly - whilst we are saying the quiet parts out loud - Britain needs to reopen the question of EU membership. What the local election results of 2026 show is that this remains a key issue. And what they also show is that there is a clear majority that would favor a return. Until these basic features of Britain’s political economy are addressed the country will carry on its politics as though in a haunted house, governed by governments that lack actual majorities, conjuring up false constraints whilst ignoring the real ones. This one is for DG and MI. I love writing the newsletter. If you enjoy it too and fancy buying me a coffee once a month, you know what to do. Click below! Subscribe
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Curing U.S. Health Care, Part II
On March 23, 2010 President Barack Obama signed the Patient Protection and Affordable Care Act — usually referred to either as the Affordable Care Act or as Obamacare — into law. Joe Biden, then the vice president, could be overheard whispering “This is a big fucking deal.” And it was. The ACA, which went into full effect in 2014, created a system of subsidies and regulations designed to make health insurance available to many Americans who had previously been left out. It worked: In 2010 there were 47 million uninsured people in America, but by 2016 this number had dropped to 27 million. This still fell short of the universal health insurance that every other advanced nation has, but it was real progress. In 2017, during his first term, Donald Trump tried to destroy the ACA, replacing it with the American Health Care Act — legislation that would have eliminated most of the provisions that expanded health insurance under Obama. At the time the Congressional Budget Office projected that the G.O.P.’s replacement bill would nearly double the number of Americans without health insurance, increasing the total uninsured population by 23 million and undoing all of the progress achieved under the ACA. However, the attack on Obamacare failed by one vote in the Senate, and the ensuing public backlash against the G.O.P. delivered a large victory in the 2018 midterms to the Democrats. After these developments many observers assumed that the ACA had become a more or less permanent feature of American life. Such assessments, however, failed to take into account the deep hostility of the U.S. right toward policies that expand access to healthcare. As we’ll see, this hostility goes back generations. And the second Trump administration has taken actions that the CBO projects will add 16 million people to the rolls of the uninsured by 2034. How did we get here? And now what? Today’s primer will analyze the political economy of U.S. healthcare since the 1940s and the combination of danger and opportunity created by the current crisis. Beyond the paywall I will discuss the following: US health care on the eve of Trump II 80 years of US health politics The Obamacare story The new assault on healthcare
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“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.
SGMC Health Enhances Hip Replacement Surgery with IntelliJoint® HIP Technology
SGMC Health is advancing orthopedic surgical care in South Georgia with the utilization of IntelliJoint® HIP, an advanced technology used during hip replacement surgery by orthopedic surgeon Anthony D’Abarno, DO. Hip […]
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