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UConn Business Students Claim ‘Double Victories’ at QuantumUP! Event
Transportation efficiency was the area tackled by both teams from the MSBAPM program
Only the champions might be happy with Minnesota’s student-athlete transfer system
Inside an imperfect system: Because the high school league is “not an investigative body,” athletic directors own the burden of enforcing Minnesota’s trust-based transfer process. Coaches are often caught in the middle, too.
How Dangerous Is Anthropic’s New AI Model? Its Chief Science Officer Explains.
Just how fast is the future coming at us, and how worried should we be? Last week, Anthropic announced Claude Mythos, the latest in what has become the leading family of AI models. In a very short time, AI models from Anthropic and other companies have become shockingly powerful at coding. But Mythos stands out because it is not just able to write code that can hack into critical systems, like those that run financial companies, but also to analyze systems and find and string together vulnerabilities in them, allowing Mythos to evade even sophisticated defenses. Anthropic chose to release Mythos to only about 40 leading corporations, so they could analyze the model’s capabilities and prepare countermeasures, in an effort it calls Project Glasswing. The release of Mythos—and the prospect of similarly powerful AIs to follow—has caused tremors at the top levels of Washington and corporate America. Jared Kaplan, co-founder and chief science officer at Anthropic, is at the center of this breakthrough. We sat down with Kaplan so he could walk us through just how powerful Mythos is, what the implications are for issues like our personal privacy, and what comes next. This conversation has been edited for length and clarity. Sean Fischer: For the layman, how is Claude Mythos different—more powerful, more dangerous—from previous models released by Anthropic? Jared Kaplan: I think most people have experienced the fact that our computers get faster and faster over time and over many decades. There’s this very smooth trend where every 18 months, maybe, computer processing power doubles. I think AI is on a trend in which it’s improving maybe 10 times faster than that. A lot of the earliest work that I did in AI was around identifying this scaling trend in AI. Claude Mythos is the latest model from Anthropic, but it’s not different because it’s qualitatively different. It’s really just kind of the culmination of the trend of AI models getting smarter and smarter at all kinds of general capabilities, from reasoning to software engineering to scientific research to knowledge work. For us, it was the first model to demonstrate very elite-level cybersecurity capabilities. It wasn’t because we trained Claude Mythos to focus on cybersecurity, but it was because, as a byproduct of its general intelligence and its general ability with software, it’s particularly good at identifying vulnerabilities in software and how to exploit them.
Indigenous Leadership for Health: Virtual Preparatory Webinar to UNPFII 2026
English - French - Portuguese - Spanish - Russian Indigenous Peoples have the right to the highest attainable standard of physical and mental health. WHO invites you to join Indigenous Leadership for Health, a virtual preparatory webinar to the 25th Session of the UN Permanent Forum on Indigenous Issues (UNPFII 2026), to be held on Thursday, 16 April 2026, from 13:30 to 16:00 CEST, via Zoom. Interpretation will be available in English, French, Portuguese, Russian, and Spanish.This event brings together Indigenous leaders working on health to help shape the forthcoming WHO Global Plan of Action on the Health of Indigenous Peoples (GPoA). It is co-organized by WHO, the Government of Brazil, the Government of the Philippines, and the Johns Hopkins Center for Indigenous Health.The webinar will be divided into two parts, each with a corresponding objective:Part I – Contents of the draft Global Plan of Action. Part I's objective is to provide an update on the process for development of the Global Plan of Action on the Health of Indigenous Peoples, to share important lessons learnt from previous work and inputs received thus far, and to invite participants to send written inputs to the Plan. The linkages to the health topics to be discussed at the forthcoming UNPFII will also be highlighted.Part II – Panel on Indigenous Leadership for Health. Part II's objective is to highlight Indigenous leadership, knowledge systems, and community-driven approaches that contribute to improving the health and well-being of Indigenous Peoples, through the sharing of select country and regional examples.Registration is free and open to all. Register hereWe encourage all Indigenous organizations, communities, partners, and individuals to join us and contribute to this important global process.
A negative side effect of ultra-processed foods you haven't thought about
Eating ultra-processed food is associated with negative health outcomes, but a new study is looking at an underexplored impact: muscle health.
When is LA28's next Olympics ticket drop, and where are $28 tickets?
The Times asked readers for their burning questions regarding the Olympics, and it’s the ticketing process that’s bringing the most heat.
New Willmar entertainment venue teaming up with Rendezvous Axe Throwing
(Willmar MN-) Shining Light Entertainment at The Uptown Willmar Mall is getting closer to opening. Co-Owner Jason Miller says in addition to laser tag and mini-golf, they will be teaming up with Rendezvous Axe Throwing......Victoria Hibma of Rendezvous Axe Throwing says their location on West Litchfield Avenue is now closed and the building, which also houses an operating laundry mat, is for sale. They are in the process of moving their throwing lanes and kitchen equipment to the Shining Light location, across from Golden Ticket Cinema, in the former Chen Garden Restaurant space. Shining Light had hoped to open this past winter, but Miller now hopes to be in operation in less than 2 months......
Scientists and the Fishing Industry Join Forces for Better Data and Management (Part 2)
Industry-Based Biological Sampling Fills Data Gaps to Improve Stock AssessmentsOur cooperative research team works with industry partners across New England and the Mid-Atlantic to collect fish and invertebrate samples to better understand age, growth, reproduction, and bioenergetics. These samples fill data gaps during times of year and areas without surveys or other ways of collecting fish samples.
Sunburn — The morning read of what’s hot in Florida politics
Politics, process, personalities — covered
Too much ultraprocessed foods can harm muscle health
You can order your own bloodwork now. Interpreting the results is another story
Firms like Function Health and Oura market regular blood tests to people wanting to take their health into their own hands. The process often raises more questions for patients than it can answer.
Q&A with chemist Max Delferro: Unlocking breakthroughs in catalytic science
In this Q&A, chemist Max Delferro explains how his team is combining catalysis, artificial intelligence and robotics to speed chemical discovery — cutting catalyst development from decades to years while advancing more efficient industrial processes.
Ultraprocessed foods are turning human thighs into well-marbled steaks
Diets high in ultraprocessed foods create streaks of fat in human muscles that may lead to osteoporosis, a new study found.
NASA’s Webb Redefines Dividing Line Between Planets, Stars
Planets, like those in our solar system, form in a bottom-up process where small bits of rock and ice clump together and grow larger over time. But the
The link between ultraprocessed foods and muscle health
People who ate diets that were high in ultraprocessed foods had more fat in between their muscles.
Q&A with chemist Max Delferro: Unlocking breakthroughs in catalytic science
In this Q&A, chemist Max Delferro explains how his team is combining catalysis, artificial intelligence and robotics to speed chemical discovery — cutting catalyst development from decades to years while advancing more efficient industrial processes.
Victoria Li's senior project: Exploring how AI processes information
Knowing how chatbots turn input into output will help with reliability and trust in AI agents
Asphalt/concrete plant proposed for former Bentley’s entertainment complex
ASHLEY — Ashley Borough Council will hold a public hearing on Tuesday on a proposed rezoning of the property where the former Bentley’s entertainment complex sits to allow for the development of an asphalt/concrete processing plant.
Scientists Uncover Brain Changes That Link Pain to Depression
A hidden process in the brain may quietly decide whether long-term pain results in resilience or depression.
Machine Learning As A Transformative Tool for (Exo-)Planetary Science
The exploration of planetary bodies in our Solar system and beyond relies on the processing
2026 All-Juice Team: One play from Fernando Mendoza earned him instant entry to this squad
On a team and in a process that has always sought QBs who could lead and elevate players around them, Mendoza's inclusion became a no-brainer. With that in mind, we give you the 12th installment of the All-Juice Team.
We Tested Every Ryzen 5 and 7 X3D CPU: From 5800X3D to 9800X3D
Nine X3D CPUs, two platforms, and 14 games tested. We compare every Ryzen 5 and 7 X3D processor to find out how much performance has improved since...
Politics made Alabama power bills high. It can lower them
The Alabama Legislature passed a law to cut the public out of the rate-making process. Here’s the flaw in it.
Trey McKenney discusses game-sealing shot in National Championship
At the national championship celebration, Michigan Basketball G Trey McKenney discussed his game-sealing shot vs UConn and how he “blacked out” in the process:
Scientists rethink DNA after discovering it can be built from scratch in a process they call 'doodling'
Scientists show DNA polymerases can build long, patterned DNA without a template called "doodling," opening new paths for synthetic biology.
“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.
Not All “Plant-Based” Diets Are Equal for Brain Health
A large study suggests healthier plant-based diets may be linked to lower dementia risk, while processed plant foods may not. The findings show association, not proof.
Qualcomm's Snapdragon X2 Elite Extreme, Tested: Big 18-Core Energy for Laptops, Incoming!
Debuting in Asus’ exciting 16-inch Zenbook A16, Qualcomm's 2026 flagship processor looks like a benchmark bombshell ready to shake up the laptop CPU field. We have the receipts.
Blake Dowling: Delilah app aims to simplify legislation, boost civic engagement
People in The Process: Legislation? There is an app for that; meet Joseph Visconti and Delilah.
No refund top customer complaint BBB helps with process of complaints and reviews
For many shoppers in Washington, getting a refund is becoming a bigger headache than the original problem.New data from the Better Business Bureau shows complai
'Historic milestone': FSU now effectively owns TMH as city transfers hospital assets
'Historic milestone': FSU and the city of Tallahassee announced Friday evening that the legal transfer of the city-owned hospital assets are complete after a controversial process that divided the community.
How to Capture the Moments That Matter (in Life and in Business)
I'm a CEO and also the videographer for my son's football team. Here's what that experience has taught me about documenting processes and motivating teams.
Gov. Laura Kelly signs bills altering defendant competency process, child health care program
Gov. Laura Kelly announces the signing of more than 50 bills approved by the 2026 Kansas Legislature.
Investing with ‘the lordship of Christ’ in mind: Ecumenical business conference convenes in Denver
Remembering “the lordship of Christ” over all things, Catholic and Protestant leaders discussed ethical investing.
The Sonic Paradox: Do we, in fact, gotta go fast?
The human mind simply can't process super-speed, but the game Haste does it better than the famously fast Sonic The Hedgehog games.
How JD Vance went from well-known foreign war skeptic to the public face of peace talks with Iran
Vice President JD Vance will travel to Pakistan to helm talks aimed at solidifying the fragile truce between the US and Iran — and in the process, elevate himself as the key peacemaker within an administration that has devoted its last several weeks to war.
Washington, DC Small Business Opportunities: 2027 NFL Draft
Local DC businesses can join a procurement process with NFL Draft Source to provide services and gain national visibility.
Washington, DC Small Business Opportunities: 2027 NFL Draft
Local DC businesses can join a procurement process with NFL Draft Source to provide services and gain national visibility.
St. Petersburg Council advances $600M infrastructure bond proposal to Committee
Council took up the item without debate, reflecting desire to at least advance the conversation through the process despite likely debate.
White House budget puts 54 NASA science missions on the chopping block
Experts found that the White House budget request for the upcoming fiscal year could defund 54 NASA science missions, including a spacecraft currently studying Jupiter and two planned Venus missions
Inaugural Entertainment Acquires Green Day Inspired Comedy, And Announces New Title, “NIMRODS”
Today, Inaugural Entertainment announces the acquisition of a new Green Day inspired comedy from Live Nation Studios, as well as a new title, NIMRODS. The film, formerly titled “New Years Rev,” was developed by writer/director Lee Kirk with global rock superstars Green Day and produced by Tim Perell for Process. …
What to know about changes to US military draft registration
The US Selective Service registration process is changing to automatic enrollment. The agency says the move aims to streamline registration.
3L Rachel Sadler Charts Path in Brain Health, Technology, and Policy Through UC Law SF’s Health Law Concentration - UC Law San Francisco (Formerly UC Hastings)
3L Rachel Sadler studies health law and policy at UC Law SF while researching the legal implications of neurotechnology and other emerging tools that may affect human cognition. 3L student Rachel Sadler shares how UC Law SF’s Health Law Concentration prepared her for a career focused on the intersection of brain health, government policy, and technology. Gained a detailed understanding of how U.S. health care is regulated and where policy reform is needed through coursework and research. Interned with state and federal agencies that regulate health care services and worked with a major health care provider’s bioethics department. Plans to pursue a career focused on protecting cognitive liberty and mental privacy as new technologies reshape healthcare. 3L Rachel Sadler: The Health Law Concentration has given me fluency in one of the most complex regulated industries and the tools to become an effective advocate for better health policy. Before coming to law school, I spent a decade teaching and working with teachers and administrators on high school programming for multilingual learners. Healthcare kept emerging as the most powerful driver of student outcomes. I wanted to understand how to make effective policy change in this area and how to use existing law to defend people’s health rights in California. Through the concentration’s coursework, I gained a sophisticated understanding of how U.S. healthcare is regulated. I also learned where the pressure points for reform exist. The courses gave me space to develop what became my central research interest: how law and policy can be built to protect human cognition and healthy brain development, particularly regarding new technologies such as generative AI and neurotechnology. The health law faculty were instrumental in that process, genuinely invested in helping me and other students define and pursue our own intellectual vision. During law school, I interned at the General Counsel’s Office for Region IX of the U.S. Department of Health and Human Services. I also externed at the California Department of Justice’s Health, Education and Welfare Division. Additionally, I externed at Kaiser Permanente Northern California’s Bioethics Department. Alongside those placements, I conducted extensive independent research on mental privacy and emerging neurotechnology, working closely with Professors Emily Murphy and George Horvath. That research became the throughline of my law school experience and the foundation of my current policy focus. I must also credit Nicole Ozer of the Center for Constitutional Democracy (CCD), whose deep knowledge of California privacy law and the public-interest privacy landscape deeply informed my work. I currently serve a research assistant with the CCD, where I spearhead the development of K-12 educational resources in partnership with law faculty and students. I’ve found UC Law SF to be an ideal place for second-career, nontraditional students. There is a tremendous diversity of life and career experience here, and I felt fully welcomed into the community, despite returning as a student at a different stage of life. I came to law school wanting to promote equity in California’s healthcare system. I am leaving with a sharper and more specific ambition: to build a policy career focused on protecting cognitive liberty and mental privacy from technological intrusion. This is both an urgent and underserved area of law, and I want to be part of defining this landscape going forward. Whether as a practicing attorney or a policy advisor, I plan to work on these issues after law school. I strongly recommend UC Law SF and the Health Law Concentration. When I arrived in law school, I worried the concentration would be narrow and that my non-clinical background would be a disadvantage. The opposite was true. The health law faculty thinks about health expansively, encompassing social determinants of health, structural inequity, and emerging technologies alongside the regulatory mechanics of the industry. The faculty are accessible, intellectually generous, and genuinely invested in students’ development. I found my research vision here, and I deeply appreciate the concentration’s role in this. The Evidence of Success series highlights UC Law SF students as they share how the College’s opportunities equip them with the experience, skills, and confidence to excel in the legal profession.
UC Berkeley students express transparency concerns in computer science comprehensive review process
UC Berkeley students attempting to add the computer science major have been navigating an uncertain comprehensive review process this year.
Accenture acquires Spain-based Keepler to boost AI and data business
The IT service provider says it aims to expand its capabilities to help clients reinvent core business processes.
Amazon says annual revenue run rate for chips business now over $20 billion
Amazon.com's annual revenue run rate for its chips business, which produces its Graviton and Trainium processors, is now over $20 billion, CEO Andy Jassy said in a letter to shareholders on Thursday.
Pakistan’s Last-Minute Diplomacy Secures Iran War Ceasefire
Pakistan warned U.S. officials that ongoing Israeli operations risked collapsing the entire diplomatic process.
Data & Business Process Services Stocks Q4 Teardown: Verisk (NASDAQ:VRSK) Vs The Rest
Earnings results often indicate what direction a company will take in the months ahead. With Q4 behind us, let’s have a look at Verisk (NASDAQ:VRSK) and its ...
Your DNA has a secret “second code” that decides which genes get silenced
Not all parts of our genetic code are equal, even when they appear to say the same thing. Scientists have discovered that cells can detect less efficient genetic instructions and selectively silence them. A protein called DHX29 plays a key role in this process by identifying and suppressing weaker messages. This finding reveals a hidden layer of control in how genes are used.
How Sisters in Public Health is changing who gets to lead
Angela Frazier had a vision. As a master’s student in public health, she looked around at the women in her program and saw something that troubled her. Talented, committed women were navigating a demanding field largely on their own, without mentors who looked like them, without spaces to process the weight of the work, and … Continue reading How Sisters in Public Health is changing who gets to lead
AMD Ryzen 9 9950X3D2 To Be Priced At $899 USD
At the end of March AMD announced the Ryzen 9 9950X3D2 processor with both dies having 3D V-Cache
Viewpoint: FP10 should remain open, excellent and secure
Europe is right to worry about research security. Foreign interference is real. So is the misuse of sensitive knowledge. Universities working in sensitive areas such as AI, quantum, semiconductors and advanced materials cannot afford to ignore the geopolitical environment around them.But Europe is in danger of drawing the wrong conclusion, one that would increase, not reduce, its strategic vulnerabilities.If the EU applies an “EU preference” logic to the next Framework Programme for research and innovation (FP10), it will weaken one of its greatest strategic assets: a research system built on openness, excellence and international collaboration. In the name of security, Europe could end up advancing science more slowly, innovating less effectively and making itself less attractive to global talent and partners in advanced science and technology.That would be a serious mistake.The EU preference included in Article 10 of the proposed European Competitiveness Fund may make sense in some industrial or deployment contexts, but is far harder to justify when applied to collaborative research in advanced science and technology, where excellence and global connectivity are crucial. Research is not procurement. It does not thrive when isolated. It advances through access to the best ideas, the best people, the best facilities and the best data, wherever they are found. This is why FP10 should not simply absorb industrial policy logic by default. Doing so would risk importing instruments that are ill-suited to research and that ultimately increase vulnerability rather than resilience.For universities of science and technology, the issue is especially acute. These institutions sit at the frontier of knowledge and technology creation in the very fields Europe sees as critical for its future competitiveness and resilience. They know better than most that security risks are real. But they also know that openness and security are not opposites. In practice, they have to be made to work together. Research security is not about closing doors. It is about building resilience through collective responsibility, trust, proportionate safeguards and better governance. That is a fundamentally different approach from default restriction.The risks of non-collaborationThe real danger in the current debate is that Europe talks too much about the risks of collaboration and not enough about the risks of non-collaboration. Those risks are strategic too. Cut researchers off from international networks and Europe loses access to knowledge, data, infrastructures and talent. Slow down global collaboration in critical technologies and Europe slows down its own progress on cutting-edge science. Make participation rules unpredictable and Europe weakens its attractiveness to researchers and investors alike.In other words, over-restricting collaboration will create strategic vulnerabilities, particularly in advanced science and technologies.This point is often underestimated in policy discussions that frame openness mainly as a value to be defended. Europe’s scientific strength, technological development and long-term competitiveness depend on remaining connected to the best research ecosystems in the world. For a continent that wants to accelerate deep tech, strengthen industrial capacity and reduce strategic dependencies, weakening the excellence base would be self-defeating. That does not mean ignoring risk. Quite the opposite. Universities are already strengthening due diligence, internal governance, awareness-raising, screening procedures and compliance support. Across Europe, institutions are working to manage risks linked to foreign interference, sanctions, export controls and the misuse of research. The right response is not complacency. It is better risk management. But that means targeted, evidence-based and proportionate measures, not blunt top-down restrictions with wide spillover effects. In the daily reality of universities, openness and restriction often coexist. The real challenge is how to apply safeguards without sliding into securitisation that damages academic freedom, open science and international cooperation. Restrict partners, not nationsMore restrictive treatment of collaborators from European Economic Area members Iceland, Liechtenstein and Norway, or from Switzerland and the UK, is strategically very difficult to justify. These are deeply embedded partners in Europe’s research and innovation ecosystem. Beyond that, Europe should still resist default exclusion and instead rely on case-by-case assessment. The relevant question is not nationality in the abstract. It is the actual risk profile of a collaboration: the institution, the affiliations, the field, the knowledge involved, the intended use and the safeguards available. Screening should focus on institutions and affiliations rather than nationality alone. Related articlesParliament ‘misreads’ link between Horizon Europe and ECF, Commission official saysFrustration grows at governance gap in next Horizon EuropeIf EU preference logic is imported into research without careful calibration, the likely result is a chilling effect. Researchers may step back from legitimate and beneficial collaboration, even where risks are manageable. International partners may see Europe as less predictable. And Europe may end up undermining the very excellence base it needs to compete, scale up and lead in strategic technologies, thereby increasing its dependence on others.FP10 should do the opposite. It should remain open by default, with restrictions used only exceptionally, and then on the basis of clear evidence. It should integrate research security into open science and research integrity frameworks, not set them against each other. And it should recognise that academic freedom, scientific excellence and responsible international collaboration are not obstacles to Europe’s security, they are part of it. Europe needs stronger tools to protect itself. But it also needs the discipline to avoid measures that would weaken it and increase its strategic vulnerabilities in the process. In FP10, that means staying open, excellent and secure.Louise Drogoul is senior advisor for innovation and sustainability at the Cesaer university association.
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MAGA Is Winning Its War Against U.S. Science
Source: NBER With all the other terrible news right now, you may not have noticed that Donald Trump is in the process of killing American science. OK, that’s an exaggeration — but not that much of an exaggeration. The Trump administration’s latest budget proposal calls for a gigantic increase in military spending combined with severe cuts to social programs. But as the chart above shows, it also calls for debilitating reductions in research funding. Furthermore, Trump appointees have already been strangling science by sharply reducing the rate at which research grants are approved. Here, for example, is the number of new grants approved by the National Science Foundation: Source: Nature Large numbers of existing grants have also been frozen or terminated, especially in the study of infectious diseases. Add to this a sharp drop in visas issued to foreign students, who often play a direct role in research and who help support academic departments that do research: Put all of this together, and much U.S. scientific research is set to come to a screeching halt — not a few years from now, but over the course of the next year or two. This new assault on U.S. science is taking place at a time when the role of American science in the world has already been greatly eroded. The chart below, based on research recently reported by the National Bureau of Economic Research, measures national strength in science by the share of publications in highly ranked journals. In the 1990s the United States had more such publications than the rest of the world combined. Since then we’ve dropped into third place — well behind China and slightly below the European Union. And this was before the Trump administration’s attack on science had time to take its full effect. Source Some erosion in U.S. scientific preeminence was inevitable given China’s growing sophistication and wealth. But we’ve also fallen behind Europe, even though everyone says that Europe is lagging economically and technologically. Claims about Europe’s underperformance are, in fact, dubious if one looks hard at the data. But it’s still striking to see America lagging. What’s going on? There are presumably multiple factors behind America’s scientific lag. But even before Trump II the growing hostility of the U.S. right to science surely had some negative effect. And since the rise of MAGA G.O.P. attitudes toward science in general have become overwhelmingly hostile. This is true even for the Republican rank and file: And while I haven’t been able to find good survey data, it’s obvious that the anti-science turn has been even more pronounced — and began earlier — among the Republican political elite. Chris Mooney published The Republican War on Science in 2005, and even then was describing a longstanding trend. Why have Republicans turned so anti-science? Part of the answer is that they believe that scientists don’t support them. And they’re right! A study of who scientists give money to shows that only a small percentage gave money to Republicans even 20 years ago, and that almost none of them donate to Republicans now: Social scientists have always been strongly pro-Democratic, while there used to be a significant number of physical, “hard” scientists supporting the GOP. But these days physicists are almost as uniformly Democratic, or at least non-Republican, as sociologists. Why are there almost no Republican scientists? It’s not a mystery. GOP political orthodoxy includes positions that are at odds with the scientific consensus on multiple issues, ranging from the validity of the theory of evolution, to the reality of climate change, to the efficacy and safety of vaccines. In each case the scientific consensus is solidly grounded in evidence. But even before the rise of MAGA the U.S. right was increasingly hostile to evidence-based policymaking — especially, of course, where the evidence is unfavorable to fossil fuel interests or quack medicine, both financial mainstays of right-wing politics. So scientists don’t support Republicans, and the feeling is mutual. Today’s Republican Party doesn’t like science or scientists. It doesn’t like having its preconceived views challenged by appeals to evidence. It knows that very few scientists are on its side electorally. In general, it sees scientific research as a threat to its grasp on political power. Add in MAGA’s combination of rabid anti-intellectualism and allergy to any hint of criticism, and one has the makings of a drastic anti-science turn in policy. “Ignorance is strength” might was well be an official MAGA motto. And as I said, we aren’t talking about something that will happen over the course of multiple years: The U.S. scientific enterprise is threatened with severe damage, even collapse, over just the next year. There are many reasons to find this prospect horrifying: Think of all the beneficial advances, affecting almost every part of life, that won’t happen because U.S. science — still crucial to the world — has been eviscerated. But think, also, of America’s international standing. Can a nation that has forfeited its role as a leader, or even a contender, in global science, still be a Great Power? No. MUSICAL CODA
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