SCROLL NEWS / DISCOVERY
Search headlines
Find the stories shaping the conversation.
Results for " tool " 2,136 found 🔀 AI-powered Shuffle
Homo erectus' tools include stunning geodes and fossils, possibly as a way to connect with the cosmos, study finds
Homo erectus may have deliberately selected rocks embedded with fossils and crystals to craft their hand axes — possibly to serve as mediators between humans and the cosmos.
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
7 ways AI is advancing healthcare and wellbeing around the world
AI-powered tools are being used to bring greater efficiency and security to healthcare around the world and increase access to medicines and care.
CMS Launches First Wave of Health Tech Ecosystem Health Information Sharing and Access Tools
The Department of Health and Human Services (HHS) Centers for Medicare and Medicaid Services (CMS) has launched the first wave of Health Tech Ecosystem The CMS has launched the first wave of Health Tech Ecosystem tools under its initiative to improve interoperability and patient access to their own health information.
AI usage limits are causing some people to restructure their workdays
Session limits on AI tools can frustrate users who are forced to rejigger their workdays. Others like a chance to hit the gym and see friends.
Barstool Sports returns to West Palm Beach for golf tournament
The Barstool Classic golf tournament returns to West Palm Beach's The Park for a two-day qualifying event in April.
Can AI Fix the Mental Health Crisis?
Demand is outpacing care. AI tools are already filling the gap. But are they safe, effective, and ready for clinical practice?
New Cold Case Task Force spotlights growing role of private forensic labs
The same DNA science being used to bring closure to families in long-unsolved cases is also increasingly being used as a frontline investigative tool.
Anthropic brings Claude into Microsoft Word, and legal contract review leads its use cases
Anthropic's Claude for Word beta is live in Microsoft Word for Team and Enterprise users, with legal contract review as the tool's first listed use case
“I stopped digging through folders”: How OmniSearch changed the way I find files on Windows 11
OmniSearch blends instant results, previews, and cleanup tools into one powerful search experience.
Democrats see gas prices as a potent political tool. Here’s the catch.
President Donald Trump’s attack on Iran sent gas prices surging, giving Democrats’ focus on affordability more traction if they can get voters to trust them.
How aggressive breast cancer turns off the immune system
Researchers are launching a new project to crack the mystery of aggressive breast cancer, where predicting disease progression remains a major hurdle. By studying how tumors interact with and suppress the immune system, scientists aim to identify new biomarkers that reveal how the cancer evolves. Using real patient samples, the team hopes to turn earlier discoveries into practical clinical tools. The goal: more precise, personalized treatments that can outsmart even the most dangerous tumors.
“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.
Microbial hockey: Scientists discover how bacteria rotate tiny pucks
At the Institute of Science and Technology Austria (ISTA), Jérémie Palacci's research group is venturing into metallurgy—albeit with a twist. Instead of traditional tools, the scientists use E. coli bacteria, ...
France Kicks Windows to the Curb, Pivots to Linux OS
David Amiel, France’s Minister of Public Action and Accounts, said his country must 'break free' and 'become less reliant on American tools.'
Rural Mental Health Hub Offers Tools, Training, and Support
A new program from Rural Minds gives farmers tools to recognize mental health struggles, start conversations, and offer support.
Are you a ‘HENRY’? Why 90% of financial advisers will waive their minimums to get your business.
Most advisory firms’ $500,000 or $1 million thresholds are actually just branding tools. Here’s how to tell if you’re actually a good fit for their services.
Science students find mentorship and pathways to career success
Batool Abdulruhman and Alyssa Rivera both grew up in rural Valley communities where doctors are scarce and medical care is difficult to access. Now they are on a path to become doctors practicing in the Valley because of the support and mentorship they received through the Center for Access to Science for All (CASA) in […]
Microsoft finally lets Windows 11 testers unlock experimental features without ViVeTool
The changes are part of the fix Windows 11 effort
Climate change is outpacing evolution. Scientists are using DNA to catch up
Coral reefs are among the first ecosystems where these tools are being put to use.
CMS highlights new digital health ecosystem tools
The Centers for Medicare & Medicaid Services April 9 held a demonstration showcasing the first series of products intended to push the health care industry toward a more connected ecosystem. The event highlighted tools and applications from more than 50 companies supporting the Medicare App Library that was initially announced in February.
Neuroscientist To Lead Engineering-Driven Brain Health Research
Dr. Matthew Walker joined UT Dallas in January to build the future of sleep science. His research spans fundamental neuroscience and the development of innovative engineering tools to improve the quality of life. Dr. Matthew Walker is helping to transform sleep research from an observational field into one in which engineered solutions can measure and […]
Neuroscientist To Lead Engineering-Driven Brain Health Research
Dr. Matthew Walker joined UT Dallas in January to build the future of sleep science. His research spans fundamental neuroscience and the development of innovative engineering tools to improve the quality of life. Dr. Matthew Walker is helping to transform sleep research from an observational field into one in which engineered solutions can measure and […]
CPUID site hijacked to serve malware instead of HWMonitor downloads
: Six-hour breach turned trusted links into a coin toss between legit tools and credential stealers
Microsoft Starts Removing Copilot from Notepad, Snipping Tool, and More in Windows 11
Microsoft's Copilot AI has generated significant negative sentiment among Windows 11 users, to the extent that even Microsoft has recognized the need to scale back some of the Copilot functionality it has long promoted. According to Windows Latest, Microsoft has updated core Windows applications suc...
Adyen tool speeds business payments
Financial operations at global enterprises remain “stubbornly complex,” as treasury teams juggle multiple banking and payment systems, the company said.
Google rolls out Gmail end-to-end encryption on mobile devices
Google says Gmail end-to-end encryption (E2EE) is now available on all Android and iOS devices, allowing enterprise users to read and compose emails without additional tools.
CPUID compromise: users report getting malware with HWMonitor and CPU-Z tools
Multiple users are reporting that the CPUID website has been compromised, leading to popular Windows utilities such as CPU-Z and HWMonitor delivering multi-stage, evasive malware.
Avec's Tinder-styled email app allows you to swipe through your inbox
Users can use the in-built voice transcription tool to reply to emails
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.
Using AI, solopreneurs can vibe-code custom business tools
5 solo business owners share how they are using AI and vibe coding
A more transparent, connected experience in Web of Science Research Assistant
The latest Web of Science Research Assistant update introduces a unified entry point, greater AI transparency, and new author and visualization tools that enhance the user experience.
Google bakes NotebookLM, its research tool, into Gemini
Google has fully integrated NotebookLM, its AI-powered research tool, into the Gemini app.
What is the quantum ‘Ghost Murmur’ purportedly used in Iran? Scientists question CIA’s claim of long-range heartbeat detection
Ghost Murmur was described as a futuristic CIA tool that could detect a heartbeat from vast distances. Physicists say the public story clashes with the basic limits of magnetic sensing
Tesla’s new Supercharger for Business tool reveals $940,000 all-in price
Tesla's new Supercharger for Business configurator pegs an 8-stall V4 site at $940,000 all-in, with 4–7 year payback depending on location.
Microsoft Mocked for Terms of Service That Admit Copilot Is for “Entertainment Purposes Only”
Microsoft admitting in its own Copilot terms of service that the tool should only be used for "entertainment purposes only."
Florida is not ready for Hurricane Season. Washington is making it worse
Florida's emergency managers are being asked to prepare for the worst with less money, fewer tools, and no certainty that help will arrive when it's needed.
Avalara to Deliver Fully Embedded, Automated Sales Tax Compliance Tool to Small Businesses Within the Clover Platform
New integration brings seamless access to daily tax set-aside, real-time tracking, and guaranteed filing and remittance DURHAM, N.C., April 8, 2026 /PRNewswire/ -- Avalara, Inc., the agentic tax...
April 8, 2026: Behavioral Science-Based Electronic Health Record Tools, in This Week's Rethinking Clinical Trials Grand Rounds
In this Friday’s Rethinking Clinical Trials Grand Rounds, Julie Lauffenburger of Harvard Medical School will present on the “Impact of Behavioral Science-Based Electronic Health Record Tools on Deprescribing for Older […]
Birding is more than a hobby. It’s a public health tool
Notifications, deadlines, and a steady stream of information compete for our attention all day long., Birding offers a simple interruption to that pattern.
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.
Bluesky users are mastering the fine art of blaming everything on "vibe coding"
Use of AI coding tools has become a convenient boogeyman for any tech issues.
AI 'mirages' mean tools used to analyze medical scans could fabricate their findings
Modern AI models can create convincing descriptions of images that were never given to them — a phenomenon researchers call a "mirage."
Google updates Gemini with crisis hotline tool, pledges $30M for mental health
The updates come after a Florida family sued Google, claiming Gemini coached a man through suicide
Adobe launches Acrobat Spaces, a free AI-powered study tool for students
Adobe Acrobat Spaces is a free tool for students to use AI and create different kind of study material from documents
Leading with Science and Evidence in a Time of Retreat
As global resources become more constrained, evidence-based tools that guide investments toward maximum impact are more important than ever. This World Health Day, the WHO urges the world to embrace evidence, support science-led solutions, and advance global cooperation to turn evidence into action.
Google Adds Mental Health Tools to Gemini Chatbot After Lawsuit
Alphabet Inc.’s Google plans to introduce new mental health support features for its Gemini chatbot as the company and rivals, like OpenAI, have faced several lawsuits accusing their artificial intelligence tools of leading to harm.
Google Adds Mental Health Tools to Gemini Chatbot After Lawsuit
Alphabet Inc.’s Google plans to introduce new mental health support features for its Gemini chatbot as the company and rivals, like OpenAI, have faced several lawsuits accusing their artificial intelligence tools of leading to harm.
AI in the mental health care workforce is met with fear, pushback
Artificial intelligence tools that help mental health therapists take notes and keep records are quickly entering the marketplace. But some question the safety of AI in mental health care delivery.
AI design platform Picsart launches a creator monetization program
The program invites creators to create original content with Picsart tools for a specific campaign, share it on their social channels, and earn revenue based on how their audience engages.
Earthquake science unites threatened scholar with Cornell researchers
A team of geophysicists from Cornell, Cameroon and South Africa is using machine learning tools to unearth new information from earthquake data collected by Cornell 15 years ago – providing a lifeline for a scholar whose career was upended by conflict.
Gene Editing Institute Receives $500K Federal Grant to Expand CRISPR Learning Lab
ChristianaCare’s Gene Editing Institute has received a $500,000 federal grant secured by Delaware’s congressional delegation to expand its Learning Lab, a hands-on program that introduces high school and college students to gene editing. The Learning Lab is powered by CRISPR in a Box™, a teaching toolkit developed by Institute scientists that lets students try gene […]
Scientists may finally detect hidden ripples in spacetime
Scientists have taken a major step toward probing one of physics’ biggest mysteries—how gravity and quantum mechanics fit together—by creating the first unified way to detect tiny “ripples” in spacetime itself. These subtle fluctuations, long predicted but poorly defined, are now organized into clear categories with specific signals that real-world instruments can search for. The breakthrough means powerful tools like LIGO and even small tabletop experiments could start testing competing theories of quantum gravity much sooner than expected.
Microsoft Labels Copilot “Entertainment Only” While Selling It as a Business Tool
Microsoft is currently facing criticism on social media over the wording in Copilot's terms of service. The company heavily markets its AI services to
Stop pasting this into AI — 7 things you should never share with a chatbot
AI tools aren’t designed to store sensitive information like private documents or bank details — so don’t treat them like a safe
No Time to Read, Plenty to Say
In an era where information is increasingly packaged as entertainment and consumed rapidly, the transmission of meaning has become more fragile. Writers, technologists, and institutions alike are realizing that communication is a complex interaction shaped by audience habits, digital tools, and shifting cultural norms. Each alteration not only affects what we know but also how we understand. The result is a growing tension between expression and interpretation. One that challenges our assumptions about knowledge, attention, and responsibility in the modern world.
Vibe coding is flooding Apple’s App Store, and Apple is fighting back
AI vibe coding tools drove an 84% quarterly surge in App Store submissions, straining review times to 30 days. Apple has started pulling apps that violate its self-containment rules.
Democrats rebounding without learning necessary lessons
“When we fight, we win!” That, reportedly, was the chant heard over and over again at the Colorado Democratic Assembly a week ago. It suggests that pugilism has been the piece missing from the Democratic toolkit. Perhaps it was just me, but I seem to recall Democrats exhibiting plenty of fight back in 2024. The […]
Microsoft Warns Copilot AI Is For 'Entertainment Purposes' Only: 'Use At Your Own Risk'
Microsoft updates Copilot terms and conditions, warning that the AI tool is for entertainment only and users assume all risks.
Beauty as strategy: Why K-beauty is also a political success
K-beauty is more than just a cosmetics trend. South Korea has combined popular culture, innovation and national strategy to create a business model where beauty products are an economic and political tool.
Anthropic cuts off OpenClaw support for Claude subscriptions
Anthropic said third-party tools like OpenClaw put an "outsized strain on our systems." OpenClaw's founder said cutting support would be "a loss."
Teen Science Cafe/ AI in Everyday Life and Healthcare
We are excited to invite you to the Alexandria Teen Science Café on April 16, where we’ll explore how emerging technologies are reshaping the future of health. This month’s café will show you how the data behind everyday apps is being transformed into powerful tools that help solve medical challenges once considered impossible, even predicting
Gemma 4 and what makes an open model succeed
Having written a lot of model release blog posts, there’s something much harder about reviewing open models when they drop relative to closed models, especially in 2026. In recent years, there were so few open models, so when Llama 3 was released most people were still doing research on Llama 2 and super happy to get an update. When Qwen 3 was released, the Llama 4 fiasco had just gone down, and a whole research community was emerging to study RL on Qwen 2.5 — it was a no brainer to upgrade. Today, when an open model releases, it’s competing with Qwen 3.5, Kimi K2.5, GLM 5, MiniMax M2.5, GPT-OSS, Arcee Large, Nemotron 3, Olmo 3, and others. The space is populated, but still feels full of hidden opportunity. The potential of open models feels like a dark matter, a potential we know is huge, but few clear recipes and examples for how to unlock it are out there. Agentic AI, OpenClaw, and everything brewing in that space is going to spur mass experimentation in open models to complement the likes of Claude and Codex, not replace them. Especially with open models, the benchmarks at release are an extremely incomplete story. In some ways this is exciting, as new open models have a much higher variance and ability to surprise, but it also points at some structural reasons that make building businesses and great AI experiences around open models harder than the closed alternatives. When a new Claude Opus or GPT drops, spending a few hours with them in my agentic workflows is genuinely a good vibe test. For open models, putting them through this test is a category error. Something else to be said about open models in the era of agents is that they get out of the debate of integration, harnesses, and tools and let us see close to the ground on what exactly is the ability of just a model. Of course, we can’t test some things like search abilities without some tool, but being able to measure exactly the pace of progress of the model alone is a welcome simplification to a systematically opaque AI space. Share The list of factors I’d use to assess a new open-weight model I’m considering investing in includes: Model performance (and size) — how this model performs on benchmarks I care about and how it compares to other models of a similar size. Country of origin — some businesses care deeply about provenance, and if a model was built in China or not. Model license — if a model needs legal approval for use, uptake will be slower at mid-sized and large companies. Tooling at release — many models release with half-broken, or at least substantially slower, implementations in popular software like vLLM, Transformers, SGLANG, etc due to pushing the envelope of architectures or tools. Model fine-tunability — how easy or hard it is to modify the given model to your use-case when you actually try and use it. The core problem is that some of these are immediately available at release, e.g. general performance, license, origin, etc. but others such as tooling take day(s) to week(s) to stabilize, and others are open research questions — with no group systematically monitoring fine-tunability. In the early era of open models, the days of Llama 2 or 3 and Qwen pre v3.5, the architectures were fairly simple and the models tended to work out of the box. Some of this was due to the extremely hard work of the Llama, Qwen, Mistral, etc. developer teams. Some is due to the new models being genuinely harder to work with. When it comes to something like Qwen 3.5 or Nemotron 3, with hybrid models (either gated delta net or mamba layers), the tooling is very rough at release. Things you would expect to “just work” often don’t. I’ve been following this area closely since we released Olmo Hybrid with a similar architecture, and Qwen 3.5 is just starting to work well in the various open-source tools that need to all play nice together for RL research. That’s 1.5 months after the release date! This is just to start really investing more into understanding the behavior of the models. Of course, others started working on these models sooner by investing more engineering resources or relying on partially closed software. The fully open and distributed ecosystem takes a long time to get going on some new models. All of this is lead-in for the most important question for open models — how easy is it to adapt to specific use-cases? This is a different problem for different model sizes. Large MoE open-weight models may be used by entities like Cursor who need complex capabilities in their domain, e.g. Composer 2 trained on Kimi K2.5. Other applications can be built on much smaller models, such as Chroma’s Context-1 model for agentic search, built on GPT-OSS 20B. The question of “which models are fine-tunable” is largely background knowledge known by engineers across the industry. There should be a thriving research area here to support the open ecosystem model. The first step is to understand characteristics of different base and post-trained models to understand what they look like. The second step is to tune pretraining recipes for open models so they’re more flexible. Interconnects AI is a reader-supported publication. Consider becoming a subscriber. Subscribe For The ATOM Project and other Interconnects endeavors, we’ve put in substantial effort to measuring adoption trends in the open ecosystem. Everything takes a long time to unfold after a model is first publicly available — and adaptability is why. What we know for sure now, when Qwen has been going from strength to strength with its releases, is that technical staff across the industry has gotten comfortable working with Qwen models. Countless research methods and datasets were made to work with Qwen. It’ll take patience for any other model family to get to this point — a patience I’m not sure many open model builders have. This takes us to Gemma 4, Google’s latest open models. Gemma 3 was released more than a year ago, in March of 2025, and is a bit underrated. Gemma 4 comes in 4 sizes for now, with a bigger, MoE model of over 100B total parameters rumored but not released yet. The models we have today come in sizes of ~5B dense, 8B dense, 26B total 4B active MoE, and 31B dense. I’m most excited that they’re finally adopting a standard Apache 2.0 open source license. This’ll massively boost adoption. The standard of better licenses for strong open-weight LLMs was set by mostly Chinese open model labs in the last 1-2 years, and now U.S. companies are following suit. I will personally be so happy if the horrible Llama licenses and Gemma terms of service were an ~18-month transient dynamic of the industry being nervous about releasing strong open models. The Gemma 4 scores look very solid, the small models have incredible benchmark scores (especially in general domains like LMArena) and the 31B model rivals the recent Qwen 3.5 27B, which is the leading member of that class. The ~30B size range is an important one, as it’s accessible both to researchers and to enterprises looking to deploy the model in real use-cases. Where the 7B model scale is the default for tinkering and research, a 30B model is the default for seeing if an open model can unlock substantial value in your specific workflow — a good mix of intelligence, low price, tractability for downstream training, etc. This takes us back to the above adoption criteria I mentioned for open models and the bigger question — do I think Gemma 4 will be an overwhelming success? Previous Gemma models have been plagued by tooling issues and poorer performance when being finetuned. Gemma 4’s success is going to be entirely determined by ease of use, to a point where a 5-10% swing on benchmarks wouldn’t matter at all. It’s strong enough, small enough, with the right license, and from the U.S., so many companies are going to slot it in. I’m cautiously optimistic that Gemma 4 is going to work better here. Winds are shifting for open models built in America. We saw GPT-OSS go through a bumpy launch to become an overwhelming success. There’s a collective energy around the likes of Reflection, Arcee, Nemotron, Gemma, Olmo, and peers that show substantial demand for building new stacks around open models. There’s capital to be spent on AI stacks across the economy by those who want more ownership of everything, including the model. After launching The ATOM Project 240 days ago, the conversation is shifting into the next stage. Summer of 2025 was a crisis moment where the U.S. AI scene realized it can’t wait and figure out open models after building AGI. The two markets will capture different areas and proceed in parallel. Now that more companies in the U.S. are releasing strong models, we need to improve the ecosystem so that these models are easy to use, understand, and build value around. It’s the hard work to build another inflection point in these adoption plots I’ve been updating consistently, but that’s the work to be done. Join me in it. More data coming soon! Here’s a sneak peek:
Cosmic Baseball lights up Oklahoma City this weekend with unique sports twist
Fans can experience a glowing, high-energy baseball show as Cosmic Baseball transforms Chickasaw Bricktown Ballpark into a neon-lit spectacle this weekend.
Cal Poly student Parker Jones calls out professors' slowness on AI
This Cal Poly computer science student says professors lag on AI as students already use tools like ChatGPT for learning, not cheating, in class.
Guardianship is not a homelessness policy
By Amelia McKeon The federal government’s proposal to expand guardianship for homeless veterans is being framed as compassionate. It is anything but. It is a dangerous shift toward using one of the most restrictive legal tools we have as a substitute for real solutions — and it risks turning guardianship into a mechanism for forced […]
Top 5: Fighters on the Rise at UFC Vegas 115
Abdul-Rakhman Yakhyaev seems to possess all the tools necessary to blossom into a full-bloom star in the Ultimate Fighting Championship light heavyweight division.
Innovative UC Health tool leads to better blood pressure control
‘These are real Californians who didn’t end up in an emergency room, didn’t have a disability, didn’t lose time with their families.’
Public Preview: Your business apps, now part of every conversation - Microsoft Power Platform Blog
Bring your Power Apps into Microsoft 365 Copilot. In public preview, makers can enable conversational access to model-driven app data with Grids and Forms, with Custom Tools coming soon
SoFi Deepens Blockchain Efforts With Business Banking Offering
SoFi is expanding its blockchain efforts with the debut of its Big Business Banking tool. The new offering is designed to let businesses manage fiat and
KPMG trains tax professionals to build software in six-week pilot
In a six-week pilot program, KPMG US tax staffers used vibe coding to create software tools the firm said it now uses with clients.
Saving biodiversity: Can innovation stop extinction?
Nearly a third of all species are at risk. New tools—from biodiversity credits to AI like BirdNET and measures against the Asian tiger mosquito—aim to protect ecosystems and human health.
Apple releases security fix for older iPhones and iPads to protect against DarkSword attacks
The security update protects a raft of older iPhones and iPads from attacks linked to leaked hacking tools called DarkSword.
Agentic Science Toolkit for Exoplanet Research
The expansion of exoplanet observations has created a need for flexible, accessible, and user-friendly workflows
Your Windows 11 PC is slower than it should be. Here's what to check
Everything running on your PC uses system resources, so why tax it with unnecessary processes and programs you no longer need? There are tools available to help you tidy up your Windows system.
Apple Will Push Out Rare ‘Backported’ Patches to Protect iOS 18 Users From DarkSword Hacking Tool
As a DarkSword takeover technique spreads, Apple tells WIRED it will release fixes for millions of iPhone owners who remain on iOS 18 rather than force them to update to iOS 26 simply to be protected.
Should the Twins extend Walker Jenkins before he debuts?
The Twins’ talented prospect has all the tools to succeed and early extensions are all the rage.
Using advanced statistics and AI to improve health | Harvard T.H. Chan School of Public Health
Matlin Gilman, PhD ‘26, studies the real-world health effects of policy decisions and builds artificial intelligence tools to advance health care.
Using advanced statistics and AI to improve health | Harvard T.H. Chan School of Public Health
Matlin Gilman, PhD ‘26, studies the real-world health effects of policy decisions and builds artificial intelligence tools to advance health care.
UNC Health tool helps families talk about cancer
WRAL Health Reporter Grace Hayba introduces us to the new tool by UNC Health, helping parents like her navigate the hardest conversations.
‘I’m not done’: Jon Maples launches new HD 87 bid, will retool strategy for November race
Maples promised a top-to-bottom campaign review, saying no question is off the table in fine-tuning his General Election strategy.
Quilty Launches as the Entertainment's Intelligence Platform
Today, Quilty launches as the first unified intelligence platform for the entertainment industry, a new tool set that consolidates creative analysis, writer development, packaging, market forecasting, production planning, industry introductions and legal intelligence. Founded by Simon Horsman, a technology and entertainment lawyer and film, television, and theatre producer, alongside technology entrepreneur and film producer, Daniel Wood, Quilty was created to address the global entertainment in
How to embed AI into business processes without breaking the business
Studies show that many AI projects fail because AI tools are introduced without aligning them with the operational workflows employees rely on every day. Using no-code tools to embed AI into everyday business processes offers a solution.
Bluesky's new AI tool Attie is already the most blocked account other than J.D. Vance
More than 125,000 Bluesky users have blocked Attie in just a few days, sending a strong message from the user base.
When a parent has cancer, this UNC Health tool helps guide conversations with kids
A North Carolina mom diagnosed with breast cancer at age 38 shares how she navigated telling her children. Now, a new UNC Health tool is helping more families have those difficult conversations.
Science in the age of AI
The transformative potential of new tools was the emphasis of Virginia Tech's Leaders+ discussion in Alexandria with OpenAI Vice President for Science Kevin Weil. The event was attended by more than 150 researchers, graduate students, and other members of the scientific and industry communities.
2 men facing charges after business trailer, tools stolen in Dundee
The Villainization of Business: Corporate Tyrants and Government Sycophants
Across political eras, corporations have been recast as either predatory villains or tools of the state—distorting their proper role in a free economy.
Navigating the social media minefield
Scientists and researchers seeking to announce promising findings, exchange ideas or contribute to policy discussions outside of academic circles may find social media an expedient tool.But increasingly, scientists and other professionals are discovering that online platforms can be a double-edged sword: while sharing their work and expertise is crucial for visibility and meeting funder expectations, it also exposes them to baseless criticism and even accusations of spreading false information."It is getting harder and harder for scientists, and researchers in general, to convey their findings without facing attacks on their legitimacy and accuracy of their research," says Valère Ndior, a professor of public law at the University of Western Brittany in Brest, France, who has spent more than a decade studying misinformation on social media. Researchers attempting to challenge deceptive online information may themselves be accused of political bias or not being objective in their research, he explains, adding that some scientists disengage because they feel overwhelmed and unable to sustain meaningful dialogue. "It is quite sad to see in some instances that researchers end up leaving social media altogether because they feel like the pressure is getting too intense or feel threatened," he says.Ndior, a past president of the Francophone Network of International Law, is also involved in European efforts to make science and research findings more accessible to the public. As an ambassador for the Science Comes to Town (SCTT) project, he has participated in recent discussions on public perceptions of science and online misinformation. The European Commission-funded initiative connects Brest and two other cities — Kiel in Germany and Split in Croatia — and aims to strengthen ties between communities, universities and research institutions to promote science awareness and cooperation across Europe.Coordinated campaigns around contentious topicsNdior draws a clear distinction between critical thinking and thoughtless criticism. Yet he sees online discussions being increasingly shaped by suspicious behaviour and coordinated information campaigns — including "raids" aimed at dominating discussions and "astroturfing," where small groups act as larger movements to sway debates. Tracking these patterns has become harder because some platforms have restricted data or charge for it, despite provisions of the European Union's Digital Securities Act aimed at ensuring researchers can have access to such data. According to Ndior, "platforms became more reluctant from the moment access to data became a legal requirement rather than a voluntary initiative."Unfounded claims and scepticism about science existed long before Internet chat groups. But the noticeable rise in online hostility has intensified around contentious topics, such as the coronavirus pandemic and climate change, alongside the weakening of gatekeepers to moderate content.For Ndior, dubious claims about pandemic countermeasures and vaccine safety highlighted the struggle between "balancing freedom of expression and the protection of public health and order." Efforts to remove social media content deemed false or risky for public health triggered accusations of censorship and the silencing of legitimate discussion, and in some cases, legal challenges.Concerns about attacks on the credibility of scientists and researchers have generated a flurry of academic papers in recent years and prompted professional communities to address ways to counter online attacks. Such unease extends to the generation that has grown up with digital media. Ndior points out that his students, some of whom research artificial intelligence regulation, hate speech, online surveillance and other controversial topics, hesitate to share their work or viewpoints online. "Many of them don't want to expose themselves too much because they don't feel ready to be faced with the backlash of other people criticising their research," he explains.Safer harbours for engagementLegal challenges against false or defamatory posts are not necessarily a solution — especially given the trans-jurisdictional nature of the Internet. Lawsuits also take time and money, and if they fail, can be counterproductive. Instead, Ndior advises scientists and researchers to be selective in how and where they communicate. Professional online platforms and moderated discussion spaces offer a better environment for engagement. He also highlights the value of more traditional formats, such as radio interviews and in-person discussions at schools, libraries and science fairs, which encourage dialogue with the public. "Personal contact makes a big difference," he says, while acknowledging that these approaches lack the global reach of social media.Ndior’s interest in digital law and online misinformation stems from his time as a doctoral student in international law in the early days of social media. He began analysing posts from governments and heads of state to determine if they could be considered official and thus used as evidence in litigation. His work attracted media attention and led to conference and speaking invitations. "This was not part of my plan," he says, "but this is what happens as a researcher — your interest is sparked by a certain event or phenomenon, and it suddenly becomes your focus."Ndior believes SCTT provides "a double benefit" for researchers, enabling them to connect with peers and interact with the public. "There is a wide community of people who are not in academia who are critical thinkers looking for opportunities to ask questions, to get information and contribute their ideas,” he says. "I really value that kind of feedback."Science|Business, which connects policymakers, academics and industry through its news reporting, analysis and events, is an SCTT partner.
Navigating the social media minefield
Scientists and researchers seeking to announce promising findings, exchange ideas or contribute to policy discussions outside of academic circles may find social media an expedient tool.But increasingly, scientists and other professionals are discovering that online platforms can be a double-edged sword: while sharing their work and expertise is crucial for visibility and meeting funder expectations, it also exposes them to baseless criticism and even accusations of spreading false information."It is getting harder and harder for scientists, and researchers in general, to convey their findings without facing attacks on their legitimacy and accuracy of their research," says Valère Ndior, a professor of public law at the University of Western Brittany in Brest, France, who has spent more than a decade studying misinformation on social media. Researchers attempting to challenge deceptive online information may themselves be accused of political bias or not being objective in their research, he explains, adding that some scientists disengage because they feel overwhelmed and unable to sustain meaningful dialogue. "It is quite sad to see in some instances that researchers end up leaving social media altogether because they feel like the pressure is getting too intense or feel threatened," he says.Ndior, a past president of the Francophone Network of International Law, is also involved in European efforts to make science and research findings more accessible to the public. As an ambassador for the Science Comes to Town (SCTT) project, he has participated in recent discussions on public perceptions of science and online misinformation. The European Commission-funded initiative connects Brest and two other cities — Kiel in Germany and Split in Croatia — and aims to strengthen ties between communities, universities and research institutions to promote science awareness and cooperation across Europe.Coordinated campaigns around contentious topicsNdior draws a clear distinction between critical thinking and thoughtless criticism. Yet he sees online discussions being increasingly shaped by suspicious behaviour and coordinated information campaigns — including "raids" aimed at dominating discussions and "astroturfing," where small groups act as larger movements to sway debates. Tracking these patterns has become harder because some platforms have restricted data or charge for it, despite provisions of the European Union's Digital Securities Act aimed at ensuring researchers can have access to such data. According to Ndior, "platforms became more reluctant from the moment access to data became a legal requirement rather than a voluntary initiative."Unfounded claims and scepticism about science existed long before Internet chat groups. But the noticeable rise in online hostility has intensified around contentious topics, such as the coronavirus pandemic and climate change, alongside the weakening of gatekeepers to moderate content.For Ndior, dubious claims about pandemic countermeasures and vaccine safety highlighted the struggle between "balancing freedom of expression and the protection of public health and order." Efforts to remove social media content deemed false or risky for public health triggered accusations of censorship and the silencing of legitimate discussion, and in some cases, legal challenges.Concerns about attacks on the credibility of scientists and researchers have generated a flurry of academic papers in recent years and prompted professional communities to address ways to counter online attacks. Such unease extends to the generation that has grown up with digital media. Ndior points out that his students, some of whom research artificial intelligence regulation, hate speech, online surveillance and other controversial topics, hesitate to share their work or viewpoints online. "Many of them don't want to expose themselves too much because they don't feel ready to be faced with the backlash of other people criticising their research," he explains.Safer harbours for engagementLegal challenges against false or defamatory posts are not necessarily a solution — especially given the trans-jurisdictional nature of the Internet. Lawsuits also take time and money, and if they fail, can be counterproductive. Instead, Ndior advises scientists and researchers to be selective in how and where they communicate. Professional online platforms and moderated discussion spaces offer a better environment for engagement. He also highlights the value of more traditional formats, such as radio interviews and in-person discussions at schools, libraries and science fairs, which encourage dialogue with the public. "Personal contact makes a big difference," he says, while acknowledging that these approaches lack the global reach of social media.Ndior’s interest in digital law and online misinformation stems from his time as a doctoral student in international law in the early days of social media. He began analysing posts from governments and heads of state to determine if they could be considered official and thus used as evidence in litigation. His work attracted media attention and led to conference and speaking invitations. "This was not part of my plan," he says, "but this is what happens as a researcher — your interest is sparked by a certain event or phenomenon, and it suddenly becomes your focus."Ndior believes SCTT provides "a double benefit" for researchers, enabling them to connect with peers and interact with the public. "There is a wide community of people who are not in academia who are critical thinkers looking for opportunities to ask questions, to get information and contribute their ideas,” he says. "I really value that kind of feedback."Science|Business, which connects policymakers, academics and industry through its news reporting, analysis and events, is an SCTT partner.
Turkey Mountain cleanup event focuses on improving mental health
Volunteers gathered Sunday to clean trails at Turkey Mountain, while promoting mental wellness and community connection.
How Are Health Systems Assessing ROI for AI Tools?
Michael Meucci, CEO of health data platform Arcadia, thinks health systems are changing their thinking about ROI when it comes to AI projects. As providers face tighter budgets, he said they’re broadening how they measure AI’s ROI, including benefits like reducing clinician burnout.
Partner with the Business Fights Poverty Institute to Drive Action
Discover how the Business Fights Poverty Institute helps companies turn sustainability insight into action through collaboration, research and practical tools.
Businesses' renewal emails might be a scam
Scammers are reaching out about renewing subscriptions, and you can spot the fakes using these tools.
Oliver Bearman health update after monster 50G Japanese GP crash
Oliver Bearman was taken to the medical centre following a huge crash in the Japanese Grand Prix.
Release Engineer Completes Data Science Online Courses
This spring a release engineer completed three Coursera Data Science courses from Johns Hopkins and the Software Carpentry instructor training, each roughly four weeks long. The courses covered The Data Scientist's Toolbox, R Programming, and Getting and Cleaning Data, and required substantial external reading to finish programming assignments. The training emphasized R, GitHub, reproducible research, and evidence-based teaching methods applicable to managing distributed systems.
Scientists say the evidence is clear: E-cigarettes beat patches and gum in helping smokers quit
Nicotine e-cigarettes may be one of the most effective tools yet for quitting smoking, according to a sweeping review of global research. By analyzing findings from 14 major reviews spanning nearly a decade, researchers found consistent, high-quality evidence showing that nicotine vapes outperform traditional methods like patches, gum, and even behavioral support. While some lower-quality studies produced mixed results, the strongest data clearly favored nicotine e-cigarettes.
New Google tool allow users to scrub more personal data to keep safe from online thieves
Google is rolling out a new feature called "Results about you" to help users scrub more sensitive information such as social security and driver's license numbers from internet search results, on top...
How one business owner is using AI during tax season
Small business owner Kyle Ray uses a handful of AI and software tools. For tax questions, though, he turns to ChatGPT.