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GIA Hong Kong: Inviting the public to discover the science and wonder of natural diamonds
Behind the brilliant sparkle of every natural diamond lies a geological miracle formed deep within the earth over billions of years. To deepen public appreciation for these natural treasures, the Gemological Institute of America (GIA), the world’s leading authority on gemmology and creator of the 4Cs, is highlighting the scientific magic behind diamonds. GIA is helping enthusiasts, consumers, and industry professionals see natural diamonds in a whole new light while empowering the next generation of talent through its comprehensive educational programmes in Hong Kong.
China’s Nobel paradox reveals a deeper science challenge
China celebrates scientific gains, but can it become a place where top researchers freely choose to build their futures?
U.S. Department of Health and Human Services (HHS) Recommends Science-Based Thresholds to Target Dangerous Enhanced Kratom Products
Kratom products credit: CDPH DEA takes action based on updated recommendation from HHS October 11, 2026 - WASHINGTON - On Friday, the U.S. Department of Health and Human Services relesed the following: The U.S. Department of Health and Human Services (HHS) provided a new recommendation to the Drug Enforcement Administration (DEA) that establishes science-based thresholds for 7-hydroxymitragynine (7-OH) and mitragynine pseudoindoxyl (MGPI), potent opioid compounds associated with products marketed as kratom. The Department of Justice today announced that DEA issued new Notices of Intent reflecting HHS’ updated scientific analysis and recommendations, including a new Notice of Intent for 7-OH and MGPI incorporating HHS’ recommended concentration and ratio thresholds. Following a review of available scientific data and comments, HHS Assistant Secretary for Health Admiral Brian Christine, M.D., recommended that DEA use concentration or ratio-based thresholds to determine which products containing 7-OH and MGPI are subject to Schedule I control for purposes of temporary scheduling of these substances under the Controlled Substances Act. The recommendation is designed to target concentrated or chemically altered products while distinguishing them from natural botanical kratom products, which may contain trace amounts of 7-OH and MGPI. “We are drawing a clear line between natural kratom and dangerous, enhanced opioid products,” said HHS Secretary Robert F. Kennedy, Jr. “We listened to the public, followed the science, and developed a clear recommended threshold for temporary scheduling that targets concentrated 7-OH and MGPI without sweeping natural botanical kratom into Schedule I. The Trump Administration will continue taking decisive action against dangerous products that fuel addiction while making sure our policies are grounded in rigorous science.” Under the recommendation, 7-OH and MGPI would be controlled in Schedule I for purposes of temporary scheduling when either substance alone, or their combined amount when both are present: Exceeds 1 milligram per gram in solid powders, encapsulated material, or other solid forms, or exceeds 1 milligram per milliliter in liquid preparations; or When the mass of mitragynine present divided by the mass of 7-OH, or MGPI, or the combined amount of 7-OH and MGPI if both present, is less than 100. The ratio-based approach reflects the alkaloid composition of natural kratom products and provides a way to identify products intentionally enhanced or concentrated with 7-OH or MGPI. Available scientific data indicate that 7-OH occurs naturally in botanical kratom at relatively low or trace levels, while some evidence reviewed by FDA suggests MGPI may also occur at trace levels in some natural or kratom-derived products. FDA's scientific review found that 7-OH is substantially more potent than morphine in preclinical studies, with available data indicating approximately two to nine times greater potency depending on the study. FDA also identified evidence supporting a meaningful risk of opioid-like physical dependence and withdrawal from MGPI. “Our recommendation gives DEA a scientifically supportable framework to distinguish natural botanical kratom from products that have been concentrated or manipulated to deliver dangerous levels of potent opioid compounds,” said Assistant Secretary for Health Admiral Brian Christine, M.D. “This approach allows us to focus on the products that pose the greatest threat to public health.” In July 2025, following an FDA scientific and medical evaluation, HHS recommended that 7-OH above a specified threshold be placed in Schedule I of the Controlled Substances Act. In July 2026, DEA announced its intent to temporarily schedule 7-OH above a specified threshold, and HHS simultaneously sought public comment on the proposed threshold. DEA subsequently temporarily placed MGPI and two synthetic 7-OH derivatives, MGM-15 and MGM-16, in Schedule I. Since then, questions have emerged about how scheduling could affect natural botanical kratom products potentially containing trace amounts of MGPI. The new HHS recommendation responds to those concerns by providing DEA with a more precise threshold based on both the concentration of 7-OH and MGPI and their relationship to mitragynine, the predominant alkaloid in kratom. HHS and FDA will continue working with DEA to protect Americans from dangerous concentrated and synthetic opioid products while ensuring federal policy is grounded in the best available science. Source: HHS
Sweating the details: Sauna's potential health benefits draw scientists' interest
A group of international researchers is pushing to rigorously study the potential health benefits of sauna and other heat therapies. They hope to bring scientific legitimacy to the age-old practices.
Sweating the details: Sauna's potential health benefits draw scientists' interest
A group of international researchers is pushing to rigorously study the potential health benefits of sauna and other heat therapies. They hope to bring scientific legitimacy to the age-old practices.
The grave consequences of politicizing science
If political ideology determines which scientific questions receive support, science ceases to function as a check on power.
The Preliminary Lunar Science Report for Artemis II is Out!
Through photographs, spoken observations, drawings, and annotations, the Artemis II crew created a unique scientific record—one that is now available to the science community and the public for further study. Explore highlights here, and find the full suite of reports and select data resources at the bottom of the page.
NVIDIA CEO Jensen Huang receives National Medal of Science for turning gaming GPUs into AI powerhouses
NVIDIA CEO Jensen Huang received the National Medal of Science for advancing GPUs into general-purpose computing engines that power modern AI.
Ongoing lawsuits allege GLP-1s can cause serious harm. But we don't know how often
Scant data about serious adverse effects makes it harder to answer scientific and legal questions about how often the drugs might cause serious harm like blindness or pancreatitis.
One Law of Citation? Scientists Find Shared Rules Behind Science, Law and Patents
A new Nature Communications study shows that scientific papers, U.S. case law, and patents share similar statistical citation dynamics, which a community-centric model with three core mechanisms can reproduce, explain delayed recognition, and better predict future impact.
5 Ways Science Proves That Women's Bodies Are Amazing
The “weaker sex” myth has never been less true than it is today, when scientific evidence about the strength, intelligence, and resilience of a woman’s body just keeps piling up. Of course, there’s no...
EPA’s New Science Chief Defends Integrity After Trump’s Shakeup
The director of a new EPA science office says the agency is still committed to upholding scientific integrity, despite concerns from observers that the Trump administration has taken steps to undermine those efforts.
NIH Awards Boston University Clinical And Translational Science Institute $41 Million
The National Institutes of Health awarded $41 million to the Boston University Clinical & Translational Science Institute to support its work translating scientific research into new treatments and healthcare technologies.
Harvard Privately Weighs $500 Million Fundraising Push for Scientific Research
Harvard Privately Weighs $500 Million Fundraising Push for Scientific Research
NVIDIA's $1 Billion Plan Aims To Supercharge America's AI Science Race
Over the next five years, NVIDIA will invest $1B in US scientific research, embedding its hardware and software across top national laboratories.
Why We Must Invest in Scientists, Not Just Science
“It is through patient, painstaking work, driven by curiosity and pursued through personal dedication and sacrifice, that scientific advancement occurs,” writes Nicholas B. Dirks.
Why We Must Invest in Scientists, Not Just Science
“It is through patient, painstaking work, driven by curiosity and pursued through personal dedication and sacrifice, that scientific advancement occurs,” writes Nicholas B. Dirks.
Why Is the World’s Top Climate Science Body Struggling to Agree on Its Next Report?
The world’s leading climate science authority is facing an unprecedented deadlock over when to publish its next major assessment, raising concerns that governments could enter crucial United Nations climate negotiations in 2028 without an updated scientific assessment of global warming.
NASA Announces Bold Science Initiatives for America’s Golden Age Summit
NASA is launching two new science and technology initiatives to deepen scientific understanding and accelerate the innovation that will shape America’s future
DOE Announces Science Applications For Quantum Computing
The DoE released eight applications to guide the development and evaluation of fault-tolerant quantum computers for scientific use..
Scientists turn handheld car gadget into wildfire early-warning tool
Researchers at King's College London have converted an off-the-shelf product, usually used to determine whether car window tint is legal, into a scientific instrument that can measure leaf water content ...
NVIDIA Commits $1 Billion to U.S. Science and Quantum Computing
NVIDIA announces a $1 billion five-year commitment to U.S. scientific research, including quantum computing, energy and healthcare.
DOE Announces Science Applications for Quantum Computing
The U.S. Department of Energy (DOE) today announced the release of Quantum Genesis Priority Applications (QGPAs), a set of eight key scientific utility problems that will guide the Quantum Genesis’s goal of developing fault-tolerant scientifically relevant quantum computers. This effort directly supports the goals outlined in President Trump’s Executive Order Ushering in the Next Frontier of Quantum Innovation and builds on the recommendations made in the Blueprint for DOE Quantum Supercom
Nvidia Commits $1B To US Science As CEO Jensen Huang Backs Trump’s Genesis Mission
Nvidia commitment will be dispersed over five years with the aim of advancing U.S. scientific research and computing capabilities.
NVIDIA Announces $1 Billion Commitment to Advance U.S. Science, Quantum Computing and Super Intelligence Research
NVIDIA commits $1 billion to enhance U.S. scientific research and leadership in super intelligence and quantum computing over five years.Quiver AI SummaryNVIDIA has announced a $1 billion commitment over the next five years to advance super intelligence research and development in the U.S., focusing on key areas like quantum computing, healthcare, and energy security. This announcement was made during the Science: A New Golden Age event in Washin
Open science is compatible with research security, says Canada’s chief science advisor
Open science is “not incompatible” with research security and science leaders and policymakers should “demystify” the false dichotomy between the two, according to Mona Nemer, Canada’s chief science advisor. More than a decade ago, EU policymakers were promoting open science, open innovation and open collaboration across the world. It was a political movement that aimed to make scientific research, data, software, publications and methodologies transparent, accessible and reusable for everyone.But that rhetoric has changed over the past few years. After Russia invaded Ukraine in 2022 and Donald Trump came back to power in 2025, international partnerships have become more pragmatic. Countries are trying to implement protectionist policies and governments are increasingly worried about technology espionage. According to Nemer, science can remain open if the sector can come up with improved security protocols that would protect research data from undue manipulation by foreign actors. “If anybody can fiddle with the with the data, then [open science] is actually quite dangerous and quite useless,” she told Science|Business. Universities and research institutions are increasingly vulnerable to attempted espionage and other types of foreign interference. In September, the UK’s domestic counter-intelligence service MI5 issued a security warning against collaborations with the China General Technology Research Institute. And earlier this year, Germany’s Helmholtz Center for Information Security was criticised by federal research minister Dorothee Bär, who told a parliamentary hearing that “existing rules and systems” at the institute “were not suitable” for preventing leaks to China. According to Nemer, universities and research institutions should perhaps follow the example of the private sector, as companies have been able to safeguard their research while still publishing results. “I think that there is a level of research security hygiene that researchers and institutions need to just adopt,” she said. “You don't have to tell Sanofi or IBM how to safeguard their research, which they end up publishing anyway.”While certain areas of research will not be open for collaboration with certain partners, in other areas cooperation is necessary even with researchers based in adversarial countries. “I stress this because politics change,” she said. “Science and politics don't make for good fellows, and whether we like it or not, politics will influence certain things.”Researchers will play an important role in “protecting the integrity of science,” said Nemer. “I think that it's time that there's a commitment to a certain scientific compact, so that citizens don't think that science is actually an open door for espionage and for anti-nationalism.”New partnershipsNemer spoke with Science|Business on the margins of the Hamburg Science Summit on September 17, the day when Canadian Prime Minister Mark Carney called for increased cooperation with the EU, including in science and technology. Canada is looking to strengthen ties with partners in other corners of the world, after the Trump administration threatened to put tariffs on Canadian goods and services and even openly suggested Canada could become the 51st state. In parallel, the US government has indicated it wants to retreat from international science projects, including US collaboration with Europe’s CERN particle accelerator and other big science labs.Related articlesThe stats we need to better understand R&DCanada looks to deepen research and education links with the EUCan researchers trust that AI models won’t leak their ideas?Nemer said the US is still a science “powerhouse,” but Canada and Europe will have to work closely together on global challenges. “It’s important for both [sides], but I think it's also important for the rest of the world, because the cut in funding for development, in health, in regions like Africa and other places, have dramatic effects.” The Trump administration is also planning a review of the Nelson memo, a Biden-era document that mandated that results of federally funded research would be openly available. With that idea being called into question, Nemer said it could be “very disruptive” to scientific collaborations and could jeopardise research on climate change, the Arctic and global health. “When your collaborator suddenly tells you I'm not going to share the data with you as a researcher, if this happens, I think it's very worrisome,” she said. “I'm certainly hoping that a lot of the Canadian institutions, funders, researchers, have started looking at joining forces on databases and using more European research infrastructures,” Nemer added.
Concern after Europeans endorse US science agenda
Germany’s biggest research funder has said it is “concerned” after Berlin, plus several other European countries, endorsed a controversial US-led science policy statement. On October 4, the White House announced that 16 countries, including Germany, the UK, Italy, Greece, Bulgaria, Cyprus, Poland, Japan and South Korea had backed the Kyoto Vision for a Golden Age of Science.The document, agreed on the margins of the annual Science and Technology in Society forum in Kyoto, which gathers science ministers from across the world, appears uncontroversial at first sight. It’s a one-page statement, without any concrete measures, that touches on reducing administrative burden on scientists, experimenting with new funding models and the use of “super intelligence” in science, the Trump administration’s preferred term for artificial intelligence. However, what’s controversial is that much of the language in the Kyoto Vision reflects Science: A New Golden Age, a major policy document released by the White House in July.That document attracted criticism for deriding universities as “legacy institutions” and suggesting money be diverted to new research labs. In a speech in Kyoto on October 4, Michael Kratsios, director of the White House Office for Science and Technology Policy and the report’s author, said that the US was seeking to “diversify the ways that we support research to meet our best scientists where and when they do their best work.” The worry is that the Trump administration may be using genuine dysfunctions in academia as a pretext to defund and disempower universities, which US vice president JD Vance has labelled “the enemy.” Many in Europe also want more experimentation and reform of how science is organised and funded, and agree with criticisms of academia made by Science: A New Golden Age. But some also fear that if the US pushes for reform partially in bad faith, it could politicise and undermine the whole agenda. Washington is currently trying to change federal funding rules so that political appointees can block and cancel scientific grants. It has cut grants mid-project on topics related to diversity and other politically forbidden areas. And last year, it threatened to cut Harvard University’s federal funding unless it admitted a “critical mass” of new faculty and students to create campus “viewpoint diversity.” “Particularly concerned”Because of this wider US political context, the Kyoto Vision’s otherwise innocuous sounding statement that “we encourage experimentation with new institutional models for science that provide varying levels of autonomy, resources and direction” has caused consternation in Europe, particularly from some of Germany’s biggest science organisations. A spokesperson for the German Research Foundation (DFG), the country’s biggest funder, said that it would “closely monitor whether the current US administration uses the Kyoto Vision to restructure research funding to the detriment of research institutions such as universities and their autonomy.” The DFG was “particularly concerned” with the statement’s references to Science: A New Golden Age, they continued. A spokesperson for the German Rectors’ Conference, which represents the country’s universities, said that the reference to “new institutional models” raises “questions on the underlying understanding of academic freedom and autonomy.” Research funding must “guided first and foremost by scientific not political principles,” they went on. Dampen criticismEuropean endorsement of the Kyoto Vision might dampen domestic criticism of the Trump administration’s science policy, some in the US fear, by suggesting international support. “What we saw from Germany, Japan, the UK and other countries, is an impulse that the administration has exploited with our own science reform movement, a belief they can use dialogue to make things better,” said Cole Donovan, director of science policy at the campaigning group Stand Up for Science. “In practice, the administration has done the opposite.” Not a binding statementThere’s been so much concern in Germany that the country’s federal Ministry of Research, Technology and Space put out a statement defending its endorsement of the Kyoto Vision, which it has posted on its website. Related articlesIs metascience being co-opted?European researchers sound the alarm that Trump rule changes will hit cooperationThe US ‘golden age’ science strategy: what Europeans need to know The ministry said that it “should be regarded as a basis for discussion and does not constitute a binding statement.” Backing the statement gives Germany the chance to raise “issues and concerns” with the US during upcoming talks on science and technology scheduled for November. “Although these intentions appear, in principle, to be worthy of support, they will be scrutinised and examined more closely as the process continues,” the statement continues. Super intelligence?A ministry spokesperson confirmed to Science|Business that Germany had broadly endorsed the Kyoto Vision.However, they said Berlin had not agreed to final changes in the statement to refer to AI as super intelligence. In September, facing protests against data centres and polling that suggests US citizens are far more concerned than excited by the technology, Trump issued an executive order that attempts to rebrand AI as super intelligence, following polling on social media.The name change is to “reflect the transformative capabilities of these technologies and the limitless opportunities they create for the American people,” the order says. EU askedThe UK and Italian science ministries did not respond to a request for comment on their endorsement of the Kyoto Vision. Although most EU countries did not endorse the statement, it’s not clear which states the US asked. The White House Office for Science and Technology Policy did not return a request for comment. A European Commission official, speaking under condition of anonymity, said that the US had approached the EU, but too late for the EU to quiz all its member states on whether Brussels should endorse the statement.
The Math Singularity Is Here, and Science May Be Next
OpenAI has released an extraordinary body of mathematical work produced by an unreleased frontier model: 722 manuscripts spanning 372 research families across fields including number theory, complexity theory, and mathematical physics. Each result required, on average, the equivalent of roughly three hours of ChatGPT Pro reasoning. A New Era of Discovery We may be witnessing the beginnings of a “math singularity”: a point at which machine-generated discovery accelerates beyond humanity’s ability to independently reproduce, verify, or fully absorb it. If frontier models can generate hundreds of meaningful results in the time it takes a human researcher to investigate one, the constraint will no longer be producing new mathematics. It will be our capacity to validate, interpret, and integrate it. This does not make mathematicians obsolete. It changes their role. They may increasingly serve as guides, critics, and meaning-makers. Increasingly, they will decide which questions matter, determining which results can be trusted, and explaining why they are important. Mathematical insight may become abundant, while human judgment becomes more valuable than ever. Mathematics May Be Only the Beginning Every scientific discipline could eventually experience a similar acceleration. AI systems could generate and test hypotheses, connect findings across specialized fields, and explore possibilities at a scale no human research community could match. In medicine, imagine models identifying overlooked disease mechanisms, designing drugs and clinical trials, personalizing treatments, or discovering cures in months rather than decades. In materials science, AI could help create better batteries and cleaner industrial processes. In climate science, it could accelerate advances in energy, forecasting, and carbon removal. In biology, it could uncover relationships hidden across enormous genomic and molecular datasets. The result would not simply be faster research. It could expand the frontier of what is scientifically possible. The New Bottleneck Scientific discovery, however, is not the same as scientific progress. A medical breakthrough must still survive laboratory testing, clinical trials, regulatory scrutiny, manufacturing constraints, and real-world deployment. As machine-generated ideas multiply, the bottleneck may shift from producing breakthroughs to validating them safely and translating them into practice. We may soon have more hypotheses than laboratories can test, more drugs than clinical trials can evaluate, and more mathematical results than experts can review. That imbalance will require better systems for automated verification, reproducible research, prioritization, peer review, and collaboration between AI and domain experts. The importance of OpenAI’s work is not merely the number of manuscripts produced. It offers a glimpse of a world in which intelligence can explore thousands of intellectual paths in parallel. If ideas cease to be scarce, humanity’s defining challenge will be deciding which are true, which matter, and how to turn them into progress. The math singularity is not the end of human inquiry. It is the beginning of a new kind—one in which machines expand the frontier of knowledge and humans decide where it should lead. Subscribe Share Leave a comment
Philips Oral Healthcare establishes Global Clinical Advisory Board to help shape the future of oral care through scientific and clinical insight
Philips Sonicare establishes a Global Clinical Advisory Board of dental experts to provide scientific, clinical and strategic guidance.
President Trump Remarks at Science and Technology Summit in Washington, D.C.
President Trump hosts a summit to highlight technology, artificial intelligence, scientific innovation, and his administration's updated science policy framework.
A Vital European Hub for Theistic Views on Science
Dr. Alistair McKitterick explains how intelligent design and natural theology provide a robust framework that challenges modern scientific materialism.
Should Diseases Be Renamed When Science Advances?
Changes in scientific understanding are prompting renewed scrutiny of disease names and their effects on how patients, clinicians, and researchers view conditions.
World leader in livestock fertility research closes out 58-year career
After 58 years, Fuller Bazer, Ph.D., University Distinguished Professor, Department of Animal Science, will close out his scientific career
Trump to give Musk top U.S. science medal
U.S. President Donald Trump will present close ally Elon Musk and other tech bosses with the top U.S. scientific award at a ceremony on Thursday, the White House said.
Trump to Give Musk Top US Science Medal
President Donald Trump will present close ally Elon Musk and other tech bosses with the top US scientific award at a ceremony on Thursday, the White House said. Google co-founder Sergei Brin, Nvidia CEO Jensen Huang and AMD chief Lisa Su will also receive the National Medal of Science at the "Science: A New Golden Age" summit. Computer mogul Michael Dell and Microsoft CEO Satya Nadella will get the National Medal of Technology and Innovation, the top award in its field.
Boston Scientific promotes Fitzgerald to COO, reorganizes business segments
Alongside Fitzgerald’s promotion, Boston Scientific will establish three reportable business segments.
Trump to appear at White House science event on Thursday
By Courtney Rozen WASHINGTON, Oct 7 (Reuters) - US President Donald Trump will speak at a White House event on scientific discovery on Thursday, according to a social media post from his tech adviser Michael Kratsios. The event will highlight the Tru...
NASA Releases Artemis II Lunar Science Data, Images
NASA’s Artemis II crew traveled around the Moon and back and, along the way, captured stunning imagery and scientific observations of our nearest neighbor.
DOE Science Committee Draws Concerns Over Limited Expertise
DOE’s smaller scientific advisory committee may not be equipped to plan the future of the physical sciences, scientists say.
Scientists in Vienna and Beijing create world's first nuclear clocks
Oct 7 (Reuters) - Scientific teams working separately in Vienna and Beijing have developed the world's first two operating nuclear clocks in what they are calling an important advance in timekeeping t...
Scientists in Vienna and Beijing create world's first nuclear clocks
Scientific teams working separately in Vienna and Beijing have developed the world's first two operating nuclear clocks in what they are calling an important advance in timekeeping that promises wide-ranging practical applications and offers a new tool to investigate fundamental physics.
Italy looks North: Science anchors Rome’s Arctic strategy
Italy is leveraging its long-standing scientific presence in the polar regions to shape its future Arctic policies. The National Polar Conference, attended by over 200 participants, aims to define shared priorities and perspectives for Italian research in the Arctic, Antarctica, and the Himalayas. This scientific tradition underpins Italy’s credibility and strategic approach to the Arctic, [...]
The 2026 Nobel Prize in Physiology Went to a Technique That Lets Scientists Control the Brain With Light
Neuroscientific advances follow a pattern of visualizing the brain, measuring its function and then controlling it. Optogenetics may lead to a new era of medical treatment.
Redoing Daubert: Are judges letting bad science back into the court room?
Daubert was meant to keep unreliable science out of the courtroom by making judges gatekeepers who ensure the reliability and relevance of expert testimony and the underlying research. A recent Second Circuit decision raises a harder question: how deeply may a judge examine the science when evaluating an expert’s methodology before determining the scientific dispute itself? The answer could reshape how courts translate epidemiological evidence into legal proof.
Science Literacy Week Open House at the Fisher Library - Events
For Science Literacy Week, the Fisher Rare Book Library is presenting a rare opportunity to view some of the most important scientific books ever...
Why Citizen Science Is On The Rise
As scientific and environmental budgets across the world shrink, citizen science could be a key way to bridge the current gaps in institutional data across ecosystems.
Why we need to talk about public health
At the Yale School of Public Health, a new course on public health communications helps advance a core priority for the school: providing communities with the scientific information they need.
Why we need to talk about public health
At the Yale School of Public Health, a new course on public health communications helps advance a core priority for the school: providing communities with the scientific information they need.
Ochsner uses AI to widen clinical trial screening
The health system reports 41% greater screening capacity, 3.6 times as many patients followed for future eligibility and approximately 75% less manual screening work. The vice chief scientific officer tells the tale.
Napo Pharmaceuticals, a Jaguar Health Family Company, Sponsoring Intestinal Failure Panel Discussion at Pediatric Gastroenterology Conference in Abu Dhabi
Participants in the panel discussion include Dr. Christos Tzivinikos, and Pravin Chaturvedi, PhD, Napo's and Jaguar's Chief Scientific Officer and Chair of the Scientific Advisory Board.
Going International: How Global South Journalists Can Elevate Local Science Stories
For journalists in the Global South, access to local science presents an opportunity to bring this knowledge to a wider audience via international outlets. Regional studies and perspectives can inform broader conversations about science, highlight multinational patterns, and elevate research conducted outside of traditional scientific centers. This story offers strategies to find stories, connect with international editors, and meet the needs of audiences that may know little about the place where a story is unfolding.
AIAS+ 2026 Brings Leading Scientists to San Francisco to Explore How AI Is Changing Scientific Discovery
The Tianqiao and Chrissy Chen Institute will bring leading scientists, AI researchers, engineers and innovators to San Francisco November 5–7 for AIAS+ 2026: AI Advancing Science & Society, a three-day symposium focused on one of the most consequential questions facing research today: How can artificial intelligence help scientists move beyond analyzing what is already known and accelerate new discovery?
The life-saving scientific knowledge hiding in plain sight
Humanity produces a staggering amount of new knowledge every day. The question is how to make sense of it all
Teaching students scientific-storytelling skills to inspire change
The senior capstone course ESCI 191 equips environmental-science majors with digital-storytelling skills to translate complex climate data into compelling narratives to immerse and engage the public.
Did New Science Board Just Shift BioCryst's (BCRX) Investment Narrative?
BioCryst Pharmaceuticals recently formed a seven-member Scientific Advisory Board made up of experienced rare disease and drug development leaders to guide its research, clinical plans and regulatory approach. The depth of this board, spanning big pharma R&D, AI driven drug discovery and rare disease commercialization, directly targets BioCryst’s execution risk as it builds a broader pipeline beyond its current portfolio. We will now examine how BioCryst Pharmaceuticals’ investment narrative...
Opportunities to advance precision kidney medicine for women: Vanderbilt Health-led scientific statement
The statement suggests improving women’s kidney care by recognizing how women’s unique biology and social factors affect kidney health.
Why the creative brain feeds on movement
Movement and creativity go hand in hand. Scientists are working to discover why
Should you be ‘poop maxxing,’ or ‘fiber maxxing’? Experts explain what’s healthy
Your feces can tell you a lot about your health
Yale School of Medicine On the Science of Childhood Anxiety, Say, Anxiety Disorders Are the Most Common Mental Health Challenges In Youth
Credit: Matt Bradbury October 5, 2026 - By Isabella Backman - Anxiety disorders are the most common mental health challenges in youth. Left untreated, they can disrupt the lives of both children and their families. The good news is that with intervention, most children will overcome these conditions. Across Yale School of Medicine, scientists are working to understand anxiety at every level, from common anxious behaviors to molecular biomarkers in the brain. They are using their findings to develop and disseminate new evidence-based treatments for childhood anxiety. Today, the go-to treatment for childhood anxiety disorders is cognitive behavioral therapy (CBT). This is a form of psychotherapy that teaches children skills for confronting anxious thoughts and helps them practice managing situations that cause anxiety. While it is the gold-standard treatment backed by considerable scientific evidence, up to 50% of children will not see sufficient benefit from CBT alone. Wendy Silverman, PhD, Alfred A. Messer Professor in the Child Study Center, co-directs the Anxiety and Mood Disorders Program alongside Eli Lebowitz, PhD, associate professor in the Child Study Center. One of their main interests is learning how to improve outcomes beyond CBT. “We’re developing cutting-edge, research-based knowledge that can reduce the suffering that anxiety causes children and their families,” says Silverman. Changing parent behavior YSM experts are investigating how to improve CBT outcomes for children by involving the parents. Silverman’s research has uncovered two main components of parent intervention that improve childhood anxiety: not enabling children to completely avoid the things that make them anxious and taking steps to enhance their autonomy. Parents may unintentionally reinforce their child’s anxiety by allowing them to avoid what makes them anxious. They also may unintentionally limit the children’s sense of autonomy by being overly intrusive. “One of the things that we take pride in is that we’ve focused on trying to understand what parents need to do, and to test our ideas and see if changing the parents’ behaviors is enhancing the effects of CBT,” Silverman says. “Our findings thus far suggest that they do." As much as CBT can be helpful, it can also be challenging to get one’s child to do the necessary steps for CBT to work. This is one important reason why Lebowitz created a novel intervention program for parents named Supportive Parenting for Anxious Childhood Emotions (SPACE). Existing intervention programs often teach parents to act as therapists for their child, such as training them on how to practice breathing exercises. “It makes sense, but this doesn’t work very well in practice,” says Lebowitz. “And part of the reason, I think, is that it’s not easy to get your kid to do things, especially if they’re not excited about doing it.” SPACE is unique because it focuses entirely on parent involvement and changing parental behavior—children are not involved in the sessions. For example, parents learn how to use supportive messages that convey confidence that their child can tolerate and manage distress. “It might sound like a parent saying to a child, ‘I get that this is really hard for you, but I know that you can handle it,’” Lebowitz says. The program also works with parents to identify the ways in which they are accommodating anxious behaviors. “We’ll pick one thing that parents are doing that is an accommodation and help them make a detailed plan for how they’re going to change that,” Lebowitz explains. Treating Anxiety in Children and Adolescents Much of the existing research on SPACE has focused on parents of children under age 14. Ongoing studies are now exploring its use with parents of older teens. “Both anxiety and accommodation can interfere with normative developmental shifts during the teen years, including increased autonomy and individuation from parents,” says Rebecca Etkin, PhD, associate research scientist in the Child Study Center. “In this sense, SPACE may be particularly well-suited for anxious teens and their parents. We want to see whether it is effective during this distinct developmental window.” Unfortunately, many families in need of CBT face barriers, including limited availability of services and geographic constraints. One way to improve access is digital interventions. Silverman and her team are developing an evidence-based digitized intervention program for parents that they can access directly from their computer or smart phone. “The work we’re doing will be one of the very few parent interventions that is digitized and importantly tested for effectiveness,” she says. Creating interventions for anxiety-related challenges Silverman and Lebowitz recently received a generous gift to develop and test other interventions that help parents reduce other child anxiety-related behavioral and emotional difficulties, such as restrictive eating and unexplained somatic symptoms. One of these projects in particular focuses on understanding the risks of social media and its potential benefits, including offering a sense of connection. “A lot of research has focused on the idea that social media is harmful and the less of it the better,” says Lebowitz. “But we actually see is that this is not quite right—there are negatives, but there are also positives. So, we’re trying to get a little bit more nuanced of a picture.” The team is working with teens with social anxiety and their parents over an extended period to better understand their social media habits and how their anxiety levels affect engagement with different platforms. The teens will answer questions sent to an app on their phones about mood and social media usage in an effort to capture emotional responses as they unfold. “We hope to develop interventions that can help make the best of social media while protecting against the more problematic effects,” Lebowitz says. The brain’s role in anxiety Researchers are also testing therapies to address anxiety at the neurological and molecular levels. In collaboration with Dylan Gee, PhD, professor of psychology in Yale's Faculty of Arts and Sciences, and Hilary Blumberg, MD, John and Hope Furth Professor of Psychiatric Neuroscience at Yale School of Medicine, Lebowitz and Silverman are using brain imaging to identify changes in a child’s brain before and after parents enroll in SPACE. In one study, children viewed anxiety-inducing images while undergoing magnetic resonance imaging (MRI); the researchers conducted scans with and without the children’s parents nearby. Before SPACE, children’s brains were better able to activate the regulatory circuitry needed to turn off an anxious response when their parents were nearby. But after SPACE, children could activate this circuitry even without the parent around. “As parents work on gradually reducing some of their accommodations, you can see a child get better at regulating their own fear system in the brain,” Lebowitz says. “It’s remarkable.” Research into the molecular underpinnings of anxiety can also inform new childhood anxiety treatments. In a recent study, Lebowitz, Silverman, and Flora Vaccarino, MD, Harris Professor in the Child Study Center, discovered that a protein known as fibroblast growth factor 2 (FGF2) could be protective from the toxic effects of stress. FGF2 levels in children and their parents were linked to the children’s risk of developing anxiety and depression, the study showed. The findings could help explain why some children who are exposed to early life trauma such as poverty or abuse are more prone to developing mental health disorders. And FGF2 could be a target for treatment. “This is very novel because it starts to give a clue to what is the molecular chain that connects those lived experiences to the actual psychological outcomes,” Lebowitz says. New ways to study and treat childhood anxiety Michael Crowley, PhD, associate professor in the Child Study Center, collaborates with Silverman and Lebowitz to study the role that attention plays in development and maintenance of childhood anxiety. There is a large body of research that shows that anxious children, like anxious adults, are prone to focus on threatening stimuli such as angry faces compared with neutral faces. This has led to innovative interventions that involve attention retraining. The idea is that if experts train children to look away from threatening stimuli, it may reduce their anxiety—especially children with social anxiety who are most prone to attend to threats. The researchers have just completed a clinical trial for attention retraining with 10- to 14-year-olds with social anxiety disorders and are currently analyzing the findings. Besides this innovative attention retraining research, as Crowly notes, “I like to design tasks that are engaging to kids,” Crowley says. “My goal is to assess something without the kids knowing what we are assessing.” With this goal in mind, Crowley has created a virtual game, named Boom, to study threat processing in children with anxiety disorders. The game is similar to that of hot potato—the child and three digital players take turns virtually passing a ball to each other’s gloves. At some point, the ball turns into a bomb, and as the bomb lands in each player’s glove, the outline of the glove turns yellow. The goal is to avoid having the bomb go off in your glove. What isn’t obvious is that the game is designed to measure different types of threatening stimuli, both ambiguous and direct. In the game, the direct threat occurs as the bomb is traveling towards your glove. The ambiguous threat is the yellow outlined glove as it is unknown where the bomb will travel next. While children play the game, Crowley’s team measures their brain activity using electroencephalography (EEG). The researchers have discovered that in kids with anxiety, the brain reacts more strongly to ambiguous threats than it does in their peers, but less strongly to direct threats. They believe that the initial abnormally large brain response to not knowing where the bomb is going impairs the brain's ability to properly respond when the threat is actually traveling the child’s way. “The brains of children with anxiety are unable to differentiate between threats you need to do something about and those that are not your problem.” Michael Crowley, PhD, develops innovative games for studying anxiety in children and adolescents.Credit: Matt Bradbury Based on these insights, Crowley hopes to study whether interventions like attention training could restore appropriate threat processing. Crowley’s team is also working on a test called the Balloon Risk Avoidance Task, which evaluates risk-taking and avoidance behaviors. It features a digital balloon that is full of air and about to burst. Kids have six seconds to let air out of the balloon. The more air they let out, the less risk they face that the balloon will pop. But at the same time, the balloon becomes less valuable as it deflates. “The more air you keep in the balloon, the more points you get,” Crowley explains. So far, the researchers have found that when the balloons pop unexpectedly, teens with social anxiety show distinct brain responses. Studying these responses can help psychologists understand the underlying pathways driving the various manifestations of anxiety. The genetics of anxiety When Thomas Fernandez, MD, associate professor in the Child Study Center and of psychiatry, was still in training, there was a lot of excitement about understanding the genetics associated with autism spectrum disorder. Since then, scientists have identified around 250 genes associated with autism. The genetic contribution to anxiety disorders, on the other hand, has historically received less attention. Anxiety is less heritable than autism, but the genetic contribution for anxiety disorders that emerge in childhood may be higher than for anxiety disorders overall. While scientists estimate the heritability of anxiety disorders in general to be around 30% to 50%, some studies suggest higher heritability for certain childhood-onset anxiety presentations. “I saw firsthand how researchers in the field went about finding vulnerability genes for autism,” Fernandez says. “So, we’re using a very similar playbook for childhood anxiety.” “I saw firsthand how researchers in the field went about finding vulnerability genes for autism. So, we’re using a very similar playbook for childhood anxiety.” Thomas Fernandez, MD Associate Professor In the Child Study Center and in Psychiatry Now, Fernandez and Emily Olfson, MD, PhD, assistant professor in the Child Study Center, are studying children and their parents to identify genetic changes that are present in the child but not the parents, known as “de novo mutations.” “All of us have some de novo mutations—maybe about 50 to 100 sprinkled throughout the genome,” Olfson says. “But when they occur within the coding regions of genes, they can be really disruptive.” Previous research shows that people with autism have higher rates of damaging de novo mutations than the general population. In 2022, Olfson, Lebowitz, Silverman, and Fernandez published a study on 68 children and their families that found that children with anxiety had similarly high levels of these mutations. Studying de novo mutations can help point the researchers to where they should be looking for genes associated with anxiety. “The end game is using the genes to steer us toward the right part of biology that we can then target to come up with better treatments,” Fernandez says. Building on those findings, the team is now studying more families to better understand how these de novo mutations, along with other genetic and environmental factors, shape pediatric anxiety disorders. They recently received a National Institutes of Health grant to enroll 750 new families over the next five years. Olfson is the principal investigator, with co-investigators Lebowitz, Fernandez, Silverman, and Shuangge Steven Ma, PhD, department chair and professor of biostatistics at Yale School of Public Health. Neurodevelopment, Risk Genes, and Mental Health Conditions - The Olfson Lab Joel Gelernter, MD, Foundations Fund Professor of Psychiatry, is interested in how different anxiety disorders differ genomically. “We are studying social phobia, panic disorder, and generalized anxiety disorder, working to understand why people differ in their risk to these specific anxiety disorders and evaluating various risk factors,” he says. Gelernter was recently involved in one of the largest studies to date of the genomics underlying anxiety disorder. The study included around 122,000 people with anxiety disorders and around 730,000 without. It found that some genetic differences associated with anxiety were linked to signaling that helps reduce overactivity in the nervous system. Many anxiety medications available today work by targeting this process. “It’s nice when the biology that you get out of a large genome-wide study ratifies things that we already know because that can help increase confidence in further findings from the study,” Gelernter says. Uncovering the neurobiology of psychiatric disorders John Krystal, MD, Robert L. McNeil, Jr. Professor of Translational Research and chair of the Department of Psychiatry, is interested in the neurobiology of psychiatric disorders, including post-traumatic stress disorder (PTSD), of which anxiety is a major symptom. In the late 1980s, Krystal’s team discovered that the drug yohimbine activated symptoms in patients with PTSD. “This was the first time we could link a specific biological mechanism to the symptoms of PTSD,” Krystal says. At the time, he adds, this finding was highly controversial. “A lot of people felt that PTSD was a purely psychological syndrome that didn’t have an underlying biology.” Since then, Krystal has dived deep into understanding the neurobiology of PTSD to learn how to better treat it. His team is evaluating the use of ketamine and psychedelics. These would be among the first treatments to be developed specifically for PTSD. They may also be applicable for other disorders including anxiety disorders, Krystal adds. An important gap in PTSD treatment is the absence of biological tests that inform how to best help patients manage their PTSD symptoms. A doctor doesn’t diagnose cancer based on how they feel. Rather, they use tests of the biology of the cancer to determine the best course of treatment. “And we can’t do that in any psychiatric disorder other than Alzheimer’s disease,” Krystal says. “But now we are building a foundation for this approach to the treatment of anxiety disorders for the first time.” Source: Yale School of Medicine
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Studying Science in an Anti-Scientific Time
This Chronicle Review Deep Cut was first published in 2025. By Julianne Werlin Thanks for reading The Chronicle Review! Subscribe for free to receive new posts and support my work. Subscribe The last two decades have not been kind to science studies. Already bruised and battered by the “science wars” of the 1990s, by the 2000s sociologists of science — who had long argued that science had to be understood in its human context — were encountering the funhouse-mirror version of their own views in right-wing critiques of climate scientists. It was enough to give some prominent scholars pause. “Was I wrong to participate in the invention of this field known as science studies?” asked Bruno Latour, the most famous sociologist of science in the world, in 2003. “Should we apologize for having been wrong all along? Or should we rather bring the sword of criticism to criticism itself and do a bit of soul-searching here: What were we really after when we were so intent on showing the social construction of scientific facts?” In response, Latour proposed a change of method and attitude. Science studies, now chastened and contrite, would no longer seek to strip facts of their authority, but to enrich and enhance them. What this meant in practice was never fully clear. But his diagnosis of problems resonated, even if his solutions did not. Latour’s exercise in public hand-wringing signaled a shift in mood. By 2016, with the first election of Donald Trump, the idea that skepticism of science was a right-wing position, not a left-wing one, had become a commonplace, discussed eagerly in The New York Times. For liberals, vaccine denial during the Covid era and Trump’s second-term attacks on the funding of scientific research, covered extensively in these pages, added a new urgency to the defense of science on both practical and principled grounds. There was little appetite for a sociology or philosophy of science that emphasized the messiness and missteps of the scientific process rather than its integrity and triumphs. The distinguished historian of science Peter Dear’s new book, The World as We Know It: From Natural Philosophy to Modern Science (Princeton University Press, 2025), which seeks to tell the story of 18th- and 19th-century science for a general public, may seem comfortably remote from these bitter contests. In its 16 short chapters, Dear draws swift, sure sketches of major discoveries from Newton to Einstein, ably guiding the reader through debates on stellar nebulae, animal taxonomy, atomic chemistry, evolution, and other flashpoints in the history of science. But though a work of history, Dear’s book must still negotiate our polarized present. In a blurb on its back cover, the historian of biology Lynn K. Nyhart alludes to the “present moment, when scientific knowledge is being swamped by misinformation and its institutions are under siege.” Dear himself, in his conclusion, refers to the “yard signs” and “bumper stickers” that proclaim “Science Is Real.” One antidote to both anti-science propaganda and to reductive slogans in science’s defense is a robust history and philosophy of science: exactly what Dear’s scholarship has long offered. But his new book illustrates how difficult such work has become. Dear, an emeritus professor of history at Cornell University, is best known as a creative and philosophically minded historian of the Scientific Revolution. His edited volume The Literary Structure of Scientific Argument (1991) analyzed the rhetoric of Galileo’s thought experiments to brilliant effect. Discipline and Experience: The Mathematical Way in the Scientific Revolution (1995) was a major contribution to the analysis of scientific experiments in early modern Europe and beyond, while Revolutionizing the Sciences: European Knowledge in Transition, 1500-1700 (2001), now in its third edition, remains one of the best overviews of the profound epistemological upheavals of 16th- and 17th-century science. But Dear has also ventured into later periods. Nearly two decades ago, in The Intelligibility of Nature: How Science Makes Sense of the World (2006), he turned to the 18th and 19th centuries to sketch a history and theory of scientific knowledge. Aimed at a generalist audience, Dear’s simple prose belied serious philosophical ambitions. Science, Dear argued, has two aspects: “natural philosophy,” the quest to understand the true nature of the universe, and “instrumentality,” the applied skills and technologies that allow us to manipulate the world for human advantage. Both strands are ancient, but the innovation of the phenomenon we call “science” was to yoke them together. As Francis Bacon wrote, “Human knowledge and human power meet in one; for where the cause is not known, the effect cannot be produced,” an insight typically abridged to “knowledge is power.” Or, in Bertrand Russell’s characteristically blunt phrase, science has two functions, “1. to enable us to know things, and 2., to enable us to do things.” So far, so conventional. But Dear took issue with this familiar story in one respect. Bacon’s formula implied that theory and practice could be fused in a single method. In fact, Dear argued, the quest to understand nature and the desire to manipulate it were coupled only loosely. They could come together, but they could also pull apart. Focusing on natural philosophy, the “knowing” half of the scientific circle, he used a series of case studies from cosmology, taxonomy, chemistry, electromagnetism, and quantum theory to show how theories changed over time, in dialogue with practice, but never reducible to it. Take the case of matter, the basic substrate of the physical world. In the 18th and 19th centuries, scientists not only disagreed about what it was, but also about how well it could be known. In 1789, the chemist Antoine Lavoisier dismissed speculation about the atomic composition of chemicals as “discussions entirely of a metaphysical nature,” as he sought to orient chemistry away from philosophical abstraction and toward laboratory results. But in the 19th century, atoms returned with a vengeance in the atomic chemistry of John Dalton, who wanted to explain the underlying structure of nature. It was not just that Dalton and Lavoisier had a different set of experimental results, or even a different theory, Dear showed. What counted as an explanation had changed. In arguing that scientific theories depended on their intelligibility to human beings with complex arrays of beliefs and commitments, Dear was in sympathy with science studies. Key figures such as the sociologist Steven Shapin emphasized the importance of psychological mechanisms like trust in the formation and acceptance of scientific ideas. But in focusing on the scientific pursuit of knowledge, not its politics or economics, Dear resisted the more cynical perspective of some of his colleagues. The Intelligibility of Nature strikes a very different note than Shapin’s collection of a few years later, Never Pure: Historical Studies of Science as If It Was Produced by People With Bodies, Situated in Time, Space, Culture, and Society, and Struggling for Credibility and Authority (2010), to name just one example. Walking a very fine line, Dear depicted science as driven at once by complex social dynamics and by the intellectual power of real discoveries. It was a testament not only to his own acumen but also to the vitality of the field that he was able to do so. Nearly two decades later, The World as We Know It returns to the questions broached in The Intelligibility of Nature. Like Dear’s earlier study, it begins with the Newtonian cosmos and ends with debates between Einstein and Bohr on quantum physics. Beyond its terminal figures, many of the same characters appear in both studies, including the naturalists John Ray and the Comte de Buffon; the chemists Étienne François Geoffroy, Antoine Lavoisier, and John Dalton; as well as Charles Darwin and Michael Faraday, among others. Its subject is nearly identical: As in The Intelligibility of Nature, The World as We Know It considers natural philosophy as opposed to instrumentality, here defined as the “desire to create a picture of what the world is really like — the world as God knows it — rather than simply having instrumental or operational control over it.” The two books also overlap in insights — and sometimes even in language. The reader who has learned in The Intelligibility of Nature that Buffon’s method of classifying animals “reflected his belief in the importance of the senses and empiricism in learning about nature (a doctrine associated with Newton and the philosopher John Locke)” will experience a sense of déjà vu on reading, in The World as We Know It, that the classification “reflects Buffon’s commitment to the epistemological stance of Newton and his philosophical underlaborer John Locke, who stressed the role of the senses in creating natural knowledge.” Later in the passage, we read that, “because of its stress on understanding the ways of life of animals in their environments, Buffon’s approach could almost be labeled (anachronistically) as ‘ecological.’” And again, “an anachronistic way of putting it would be to say that Buffon recommends an ecological mode of understanding.” Likewise, in The Intelligibility of Nature we read of Dalton that he was initially drawn to meteorology, and that: He did a bit of experimental work on these things, especially having to do with the water-holding capacity of gases, but his real interest lay in understanding what, at an underlying natural-philosophical level, was really going on physically.” Whereas, in The World as We Know It: He did experimental work on these things, especially concerning the water-holding capacity of gases — although not at a very refined level quantitatively — but he was continually trying to develop a theoretical conception of what was happening physically. The final full chapter of each book closes on the same resigned note. Intelligibility: These days, most serious work on the natural philosophical underpinnings and implications of quantum mechanics is performed not by physicists but by philosophers of science. Among scientific practitioners themselves, Bohr’s attempt to use instrumentality as sufficient grounds for a respectable science has met with a high degree of success. And again, in The World as We Know It: Bohr’s and Einstein’s concerns are now questions that are mostly discussed by philosophers of science rather than by physicists themselves. The marginalization of these sorts of questions amounts to the demise of natural philosophy, at least in physics, in the 20th century. Quantum mechanics “works,” and that’s good enough for most scientists who encounter it. Examples could be multiplied. When handling the same subject matter, some echoes are inevitable. Scholars should not feel that because they have written “Isaac Newton died in 1727” in one book, in the next they must describe him as perishing, expiring, or meeting his maker. But the repetitions of language and arguments (not to mention six reproduced images) threaded throughout The World as We Know It are more extensive than that. They should have been caught by Princeton University Press or its reviewers, and revised. Because the two books have so much in common, it is easy to see where they diverge. The World as We Know It is a less theoretical work than its predecessor. The sociology of knowledge that organized The Intelligibility of Nature has been reduced in scale and folded into readings and examples. The taut interplay between history and theory, which gave the earlier study so much interest, is there, but it is subtle. In the earlier book, the case studies demonstrated theoretical claims about the character and development of science. In the later work, each narrative of discovery is an end in itself. Insights emerge from the history, but they do not control the organization of the study. With the theory muted, it can be hard to understand the logic uniting Dear’s sprawling history of more than two centuries of scientific knowledge. The 16 brisk chapters cover an enormous amount of material. But the closer the volume edges to comprehensiveness, the more obvious the missing elements become. A chapter on “Institutions and Pedagogy,” describing the birth of the research university, illustrates the problem. Inserted roughly halfway through the book, the unnumbered chapter is designed as an “entr’acte,” in acknowledgement that it does not fit the study’s organization around scientific discoveries. Yet as Dear is well aware, no general history of the development of modern science can bracket its 19th-century institutionalization and professionalization. It was the 19th-century university, after all, that gave us the “scientist,” a term coined by the Cambridge philosopher William Whewell. Dear’s history of scientific discoveries implies a wider social and institutional history, but it remains largely subterranean, only occasionally extruded under the pressure of the narrative. It must be said that the balance is not all on the side of the earlier study. There are some advantages to the more historical, less theoretical organization of The World as We Know It. Dear’s accounts of paradigm shifts are remarkably lucid, no small accomplishment given that they span fields and centuries. He makes excellent use of the wealth of new scholarship on Darwin and his influences, to which he has himself contributed. It is satisfying to see puzzle pieces from Buffon’s natural history, Georges Cuvier’s animal taxonomy, Thomas Robert Malthus’s demography, and Charles Lyell’s geology recombined seamlessly in the Darwinian jigsaw. Likewise, Dear’s discussion of stellar nebulae, divided between chapters two and 15, shows vividly how Newton, Kant, Herschel, and Hubble reimagined insights and observations as they sought to discover whether the diffuse light that filtered through early telescopes was a glowing, gaseous substance or discrete but distant stars. Yet despite such pleasures, the book remains a more modest work than The Intelligibility of Nature. Dear has clearly not changed his views about the history of science. But in the two decades that have elapsed, the discipline and the world around it have changed, making it harder to write a sociologically and philosophically ambitious history of science for the general reader. That is a shame, because in the age of Silicon Valley and biotechnology, both the reciprocity and the tensions Dear identified between the epistemological and instrumental ambitions of science are more evident than ever. In recent years, some of the most exciting new books on the history of science in early modernity have focused precisely on this pressure point. Important studies such as Pamela H. Smith’s From Lived Experience to the Written Word (2022), James Poskett’s Horizons: The Global Origins of Modern Science (2022), and Vera Keller’s The Interlopers: Early Stuart Projects and the Undisciplining of Knowledge (2023) all shed new light on how early modern science negotiated the relationship between its instrumental and epistemological ambitions, or in Russell’s phrase, knowing and doing. There is every opportunity for a philosophically informed approach to draw new insights from this wealth of material. Dear, unfortunately, has not done so in The World as We Know It. But for future scholars of the history of science, his body of work over nearly four decades may provide just the model. Julianne Werlin is an associate professor of English at Duke University. Thanks for reading The Chronicle Review! Subscribe for free to receive new posts and support my work. Subscribe
Bishop’s computer science chair says AI is eliminating ‘grunt work’ and reshaping digital jobs
Dr. Russell Butler, chair of Bishop’s University’s Department of Computer Science, says artificial intelligence is increasingly taking over routine digital “grunt work,” changing the skills students and workers may need in the years ahead. Photo courtesy of Bishop’s University. Click here to read our platform! Get local news like this every morning. Subscribe free below. Subscribe Pulse Newsroom Artificial intelligence is already taking over some of the routine digital work once performed by entry-level employees, according to Bishop’s University Computer Science chair Dr. Russell Butler — a shift he believes will make expertise, judgement and the ability to evaluate AI-generated work increasingly important. Butler described the change as automation reaching what he calls the “bottom of the cognitive pyramid” during an interview with The Pulse about AI, university education and the future of digital work. His argument is not that humans are disappearing from the workplace. Instead, he sees their role changing as AI becomes capable of handling more of the repetitive tasks involved in computer-based work. “Everything’s converging on just AI basically doing all the grunt work,” Butler said. The bottom of the cognitive pyramid Butler is from Lennoxville, completed his undergraduate studies at Bishop’s and later earned his PhD at the Université de Sherbrooke. He joined Bishop’s in 2019 and now chairs its Department of Computer Science. He uses AI in research, teaching and other creative work, and said the technology is increasingly capable of handling routine digital tasks that once required substantial human time. “You’ve got the grunt work, like moving things around in Excel, doing basic programming tasks,” Butler said. “That’s like the bottom grunt work that the entry-level worker would have done two or three years ago.” Butler went further, saying in his view that much of this type of work has already been absorbed by AI tools. He connected that change to a shift he sees taking place in computer science, where entry-level roles have declined while experienced workers can use AI to increase what they can produce. “A senior developer now has access to essentially an unlimited amount of junior developers on demand,” Butler said. He was describing AI systems metaphorically, not literal employees. His point was that one experienced developer can now ask AI tools to produce code or other technical work that might previously have been assigned to more junior workers. That raises a broader question for universities and employers. If some of the simpler work traditionally given to newcomers can now be done by machines, how do people gain the experience needed to become senior workers themselves? Students doing work that once required years of programming Butler said he is already seeing the change inside his classroom. He created a Bishop’s course called CS208, Coding in Plain English, to show students — including those without traditional programming backgrounds — what they can accomplish using AI. Some come from disciplines such as psychology or neuroscience with no previous programming experience. “What I’m finding is that students who have zero programming experience, they come in from another discipline like psychology or neuroscience or something, they are now able to get up and running with real data sets,” Butler said. Butler’s own doctoral work involved neuroimaging, and he said he has assigned students work he considers comparable to the kinds of analysis he performed during his PhD. He described giving students a real dataset, an expected result and instructions to use AI to complete the analysis. Butler said those students have been able to carry out work at a level he associates with tasks he once performed after years of programming experience. That does not mean a student using AI instantly acquires the same knowledge as an experienced computer scientist. But Butler sees it as evidence that AI can dramatically lower the technical barrier between having a problem to solve and producing a working result. The role of the person using the system then changes. They need to know what to ask for, understand enough about the subject to judge the answer and take responsibility for what is ultimately produced. What about AI hallucinations? One persistent concern surrounding generative AI is hallucination — when a system produces information that sounds convincing but is false or unsupported. Butler said that problem has improved substantially in newer systems and is not as severe as it was with earlier models. He pointed in particular to newer AI systems’ ability to search the web, consult scientific databases and return source links rather than simply generating a citation from their internal model. Butler nevertheless said users should verify what AI produces. “You should verify,” he said while discussing citations generated with AI. His position is that hallucinations have become less common in the systems he uses, not that incorrect AI output is impossible. Human checking remains part of the process. Hours of work compressed Butler offered another example from his administrative work at Bishop’s. The university has been comparing CEGEP courses with first-year Bishop’s courses to determine where students may qualify for advanced standing. Traditionally, Butler said, that means reviewing two sets of course descriptions and manually matching one institution’s courses with another’s. As department chair, that could require hours of reading and comparison. He said AI can now be given both sets of material and asked to generate an initial mapping automatically. “It saves me hours and hours of work,” Butler said. Butler said the AI-generated mapping can also produce a better result than he would produce himself. He sees similar opportunities in businesses. A company may receive specifications, drawings, emails or other digital material from customers and then have employees convert that information into an internal format before anything can be manufactured or delivered. AI can increasingly perform parts of that intermediate processing. In Butler’s view, the employee does not necessarily disappear. Instead, the job becomes more about checking the result. “The human is still there,” he said. Judgement could become more valuable That change is central to Butler’s view of where digital work may be headed. If AI can produce a first draft, write basic code, compare documents or process large amounts of information, he argues that knowledge and judgement become increasingly important. “The real scarce resource going forward is going to be domain knowledge, expertise, and… credentials, authority, the ability to work with other people,” Butler said. He is therefore encouraging students not only to learn AI tools but also to broaden their education. He mentioned acting, fine art and photography as examples of courses that can help develop what he described as taste and intuition — the ability to recognize what is good, what is not and what should be changed. “And that’s the skill that they need now because the grunt work has been automated and now it’s about evaluating what the AI produces and telling it how to improve or expand the output,” Butler said. That does not remove the need for technical knowledge. Butler’s argument is that the emphasis may shift away from manually completing every step of a task and toward directing, checking and improving work produced with AI assistance. He also stressed that humans remain responsible for final decisions. “At the end of the day, the human has to make the final call,” Butler said, pointing to the question of accountability. Physical work may be different Butler draws a distinction between digital work and jobs requiring people to manipulate the physical world. He expects AI to continue advancing quickly in tasks performed almost entirely on computers. He is more cautious about claims that humanoid robots will soon be able to replace workers such as plumbers or electricians. Butler said those trades would not be replaced “anytime soon” in his view and described some current robotics demonstrations as overhyped. He described the situation as counterintuitive. “It’s almost like we solved the highest level first,” he said, contrasting advances in digital AI with the harder problem of building robots capable of operating reliably in the physical world. Butler’s argument is that some digital occupations could face automation sooner than trades requiring complex physical work. The wider AI shift in the Townships Butler’s comments come as local institutions are increasingly grappling with how AI should be used. The federal government recently announced up to $162 million over five years for 10,000 AI-related placements through Mitacs. The Université de Sherbrooke told The Pulse that the number of its collaborative research and innovation projects supported through Mitacs has approximately doubled since 2018-19, while the number of placements has approximately tripled. UdeS also said it already has projects involving both AI adoption and the application of AI to other fields. At Bishop’s, Butler said part of his role involves building the Computer Science department’s local presence, connecting students with regional partners and strengthening relationships with the Sherbrooke technology ecosystem. Those developments put universities in a difficult position. They have to prepare students to use the tools employers increasingly have available while also making sure graduates understand enough to recognize when those tools are wrong, incomplete or being applied to the wrong problem. The risk of losing human skills Butler does not see AI as risk-free. Later in the interview, he raised a separate concern: as AI becomes better at reading, writing, programming and other cognitive tasks, people could lose some of the underlying skills that historically helped produce new ideas. “The other danger is that we’re going to lose the human skills,” Butler said. He specifically mentioned reading and writing and argued that people could lose some of the lower-level understanding that contributes to breakthroughs. Butler said AI systems are based on existing human knowledge and argued that they become much more powerful when paired with a capable person. That tension runs through his view of the technology. AI can remove hours of routine work. It can allow beginners to perform tasks that once required substantial technical training. It can give experienced workers significant leverage. But the more capable the technology becomes, the more important it may be for people to develop the judgement needed to decide what should be done in the first place. For Butler, that is where education may have to change. Students still need to understand their field. They still need to know when something is wrong. And they still need to be able to make the final decision. But if AI increasingly handles the bottom of the cognitive pyramid, the value of a worker may depend less on how quickly they can perform the grunt work and more on whether they understand what the work is supposed to accomplish. Don’t miss the next story that affects your community. Join thousands of readers getting The Pulse every morning—plus breaking news alerts when it matters most. If you value this kind of local journalism, consider supporting it. Subscribe, share and like! Subscribe Share
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Over the last half-decade, the National Science Foundation (NSF) has spent hundreds of millions of dollars on projects designed to influence academic policies, both in the sciences and other disciplines. The aim was to foster a progressive conception of social justice in these fields. In pursuit of this end, the foundation earmarked nearly a million dollars for a project titled “Creating Inclusive Scientific Societies through Policies and Practices,” over a million for a project on “Faculty Online Learning Communities for Gender Equity,” and over $2 million to foster “racial equity focused departmental change.” Through a public records request, I’ve obtained the proposals and progress reports for dozens of NSF grants designed to promote social justice. Although funding for these grants was eventually halted by the Trump administration, the projects illustrate an important facet of recent higher-education policy. Many of the university policies that promised “social transformation” didn’t arise in a vacuum. They were actively encouraged by outside funders—often by the federal government itself. Subscribe Accreditation—the peer-review process which enables universities to receive federal grants and student loans—has recently become a policy battleground, with accreditors wielding significant power over both universities and academic disciplines. In 2020, when Oregon Health and Science University’s medical school issued an extensive diversity action plan—which promised “consequences” for employees who failed to support “DEI, anti-racism and social justice”—it specifically pointed to the Liaison Committee on Medical Education (LCME), the medical-school accrediting body, to justify the overhaul. The NSF actively promoted DEI-focused accreditation policies. The proposal for a $1.2 million program on promoting “community engagement” in STEM, which I obtained through a records request, notes that the Accreditation Board for Engineering and Technology was exploring changes to its criteria “that would incorporate JEDI [justice, equity, diversity, and inclusion].” The proposal promised to “support broader JEDI efforts in the general criteria for engineering.” Another grant funded a conference designed to “identify and share best practices and strategies to integrate IDEA principles in accreditation criteria”—referring to an acronym that stands for “inclusion, diversity, equity, and accessibility.” Scholarly societies have become another flashpoint in debates over higher education. Critics argue that many of these societies, which have the power to shape entire disciplines, have become increasingly politicized. Again, through its giving, the NSF played a role in promoting this politicization. In one million-dollar grant that received funding in 2024, a group of psychologists proposed a series of social-justice reforms to the Society for the Psychological Study of Social Issues. The proposal, which I obtained via a records request, asserts that “[r]edistributing resources (such as moving different people into leadership roles) is not enough” and that the society’s “governance structures do not yet reflect its stated values of diversity, equity, and inclusion.” Its solution: review and rework the society’s criteria for leadership development, academic awards, conferences, and publications. Adjusting review criteria informed by “intersectionality” designed to fight “epistemic exclusion” is an easy way to introduce de facto ideological litmus tests into the peer-review process. For many of the grants I obtained, such litmus tests seem to be the point. “Academic departments are racialized social systems that produce and sustain the byproducts of systemic racism,” a proposal for a $2.7 million project funded in 2024 asserts, promising to develop “departmentally-focused change efforts that cultivate values, assumptions, and behaviors that advance racial equity.” The University of Illinois Urbana Champaign’s million-dollar “I-ADVANCE” project, which effectively created a small DEI bureaucracy on campus, promised to Embed 28 ADVANCE faculty fellows in STEM departments” to amplify its equity goals. Another $1.2 million project promised to create “faculty online learning communities,” made up of scientists at universities around the country, that would eventually build department-level diversity action plans. “Ultimately,” the proposal asserts, perhaps more perceptively than its authors realized, “both organizational change and intersectionality frameworks deal with power.” Indeed, such grants confer a great deal of power to administrators and scholar-activists, who can even use the mere availability of funding as a tool to advance their causes. That history is worth remembering amid today’s debate over federal involvement in higher education: Washington has been shaping university priorities for years, including by financing efforts to instill progressive ideas about race, gender, and equity into academic institutions—and many of the policies those grants encouraged remain embedded within universities long after the federal money has stopped flowing. John D. Sailer is the director of higher education policy and a senior fellow at Manhattan Institute. Share
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Good science requires much more than evidence
Empiricists believe that scientific theories are true only if they make correct empirical predictions: if we can't verify these predictions, then there is no reason to expect that they tell us anything about reality. However, Professor of Philosophy at King's College David Kyle Johnson argues that this is mistaken. In response to Bas van Fraassen, who has written on this subject for the IAI, he argues that we have many reasons for believing a theory to be true, such as it being parsimonious and having large scope — qualities which have been used throughout the history of science as criteria for judging theories. In 2024, Princeton philosopher Bas van Fraassen wrote a short article for IAI News entitled “Science Does not Describe Reality: The Limits and Benefits of Explanation.” At the time, I was working on two projects (a science book and a Great Course) that, when completed, would (among other things) defend science’s ability to describe reality. I wanted to write a response to van Fraassen, but the projects demanded too much of my attention. But now that those projects are complete, I am in a position to explain the objections to van Fraassen’s thesis. Summarizing van Fraassen’s argumentIn a nutshell, his argument is this: What scientists do is make predictions based on theories and then invite others to test to see whether those predictions are borne out. “If theory T is right, result R should happen in experimental condition C.” Many think that running an experiment that shows that R happens in condition C is proof that theory T is true (and should be believed). But, van Fraassen argues, that R happened in condition C is only a reason to think that R happens in condition C. That’s the only observable, or empirical, result we can actually see, so that is all that we are really justified in believing. (The underlying theory that made that prediction still may or may not be true.) That is why he calls those who accept his position “empiricists.”Before I explain what is wrong with this position, let me explain what it gets right. What van Fraassen Gets RightFirst, a theory correctly predicting the results of an experiment is not, strictly speaking, “proof” that the theory is correct. The basic line of reasoning is this:If the theory T is true, result R should happen. Result R did happen. Thus, theory T is true.In other words:“If T then R. R. Thus, T.”This is a deductively invalid, fallacious mode of reasoning, called “affirming the consequent.” Those premises do not guarantee that the conclusion follows. “If I am in Pennsylvania, then I am in the USA. I am in the USA. Thus, I am in Pennsylvania.” Clearly that argument doesn’t guarantee its conclusion; neither does the above argument.However, science is not a deductive method of reasoning; it is an inductive one. And inductive arguments merely try to raise the probability of their conclusion, not “prove” them for certain. Thus, the fact that an experimental result doesn’t prove a theory is true is irrelevant; it’s not supposed to. That is not what scientific reasoning is about.___If the hypothesis that something exists clearly provides the best explanation for what we can observe, then the belief that it exists is what is rational.___Second, it’s also true that a single experimental result doesn’t provide enough justification to believe that a theory is true. Scientists do not come to a consensus about whether a theory is true by looking at a single experiment; they look at all the evidence to determine where the preponderance of evidence points. The mere fact that I am in the USA raises the probability that I am in Pennsylvania, but not nearly enough to conclude that I am in Pennsylvania. However, if I am also regularly encountering people wearing Eagles and Phillies hats and seeing advertisements for Founding Father tours, I probably am. In the same way, a theory successfully predicting the outcome of one experiment is not enough to conclude that it is true; but if a theory makes a wide variety of predictions that are all vindicated by multiple experiments, performed by many different groups and people, all actively trying to prove the theory false (which is what good scientific experiments are designed to do)—that is a good reason to conclude that the theory is true. In other words, if you repeatedly try to prove something false but can’t, that is a very good indication that it isn’t. The problem of underdeterminationIn reply, those whom van Fraassen calls “empiricists” often point to the “problem of underdetermination.” For any given theory that makes successful predictions about what happens in experimental conditions, there are countless other possible theories that make exactly the same predictions—and since they do, the experimental evidence in question is just as much reason to accept any of those theories as it is to accept our original one. Thus, the argument goes, we have no way of knowing whether our original theory is true, or one of the other “predictively equivalent” theories is true. SUGGESTED VIEWING How Occam's Razor changed the world With Johnjoe McFadden As an example of underdetermination, philosophers often offer this example. The evidence of fossils seems to provide reason to conclude that the universe is quite old; ancient fossils are what the “ancient universe” hypothesis predicts. But it’s also possible that God created an ancient-looking universe 200 years ago, complete with a “fake” fossil record for us to find, to make it look old. The existence of fossils is what that theory predicts too. So, the argument goes, the fossil record can’t be used as evidence that the universe is ancient; the fossil record supports the “200-year-old ancient-looking universe” theory just as much. The problem of underdetermination points out that, for any theory with supporting evidence, we could invent another completely different theory that predicts exactly the same evidence, and thus undermine that evidence’s ability to support the original theory.But this “argument from underdetermination” betrays a fundamental misunderstanding of what scientific reasoning is and how it works. To explain, let me use another rather strange (but very real and commonly discussed) philosophical thought experiment called “The Grue Problem.” The “Grue” ProblemSuppose I want to know what color emeralds are, so I observe a few, see that they all appear green, and form the theory that “all emeralds are green.” I thus predict that the next 100 emeralds I find will also appear to be green. And let’s say that happens, and so I thus conclude that my theory that all emeralds are green is true. Now, one might rightly point out that I don’t know for sure that all emeralds are green—I have not seen them all. Maybe some I haven’t found yet are blue. Fair enough. After all, we used to think that all swans were white, until we found some black ones. But let’s say that I go on a quest and collect every emerald in the universe—and, for the sake of the argument, let’s say I can do this, and can even know that I have every one of them. So, I collect them all, look at them all, and verify that they all appear green. Can’t I now rightly conclude that all emeralds are green?Inspired by the problem of underdetermination, a friend might argue that I cannot.Sure, they all appear green now—but there could be another kind of color called “grue.” Something is grue if it is green up to a certain point in time, but then spontaneously turns blue. And there could be an infinite number of “shades” of grue. Something that is one shade of grue will turn blue at noon today, but something that is another shade of grue will turn blue at noon tomorrow, etc. So yes, the emeralds appear green now; and since they haven’t turned blue yet, they are not some “past” shade of grue. But they might be some “future” shade of grue (e.g., they may turn blue at noon tomorrow). And since all future shades of grue are consistent with “being green up to this point in time,” the evidence you have is completely consistent with the notion that all emeralds are some future shade of grue, rather than green. Indeed, that they would appear green until now is what the “some future shade of grue” hypothesis predicts. So, we have just as much reason to conclude that all emeralds are some shade of grue as we do to conclude that they are green.You’re probably thinking “It’s not equally possible that the emeralds are grue; they are obviously green.” You are right! But explaining why your instinctive reaction to my friend’s argument is correct will help inform why van Fraassen’s “empiricist” is wrong and science actually does describe reality.The main mistake my friend makes is in thinking that the “empirical evidence” (of all the emeralds appearing green) is (or even should be) all I am using to draw the conclusion that all emeralds are green. It is not. I am also considering known facts about how colors typically work; things don’t usually change color, and when they do, they don’t do so suddenly, without cause, and all at once. So, even though the simple evidence of the emeralds all appearing green up to this point is consistent with them being some future shade of grue—that is even what the grue hypothesis “predicts”—it is still exceedingly unlikely that they are. The hypothesis that they are green is much more likely. Understanding science refutes the problem of underdetermination The misunderstanding about science that the “empiricist” pointing to “the problem of underdetermination” makes is similar to the one that my friend made. Science is not just about considering experimental evidence; in fact, it’s not even just about considering empirical evidence. As Ernan McMullin and many other philosophers of science have pointed out, the inference that makes science is “inference to the best explanation” (sometimes called “abduction” or “retroduction” by McMullin). While, depending on the circumstances, scientists use many different kinds of reasoning, science as a whole is, simply put, the process of considering multiple competing explanations and comparing them to certain criteria—explanatory criteria (the kinds of things explanations must be and do, by definition, to be a good explanation)—to see which explanation is the best.And these criteria do not deal only with empirical results. Yes, successful predictions raise the probability of a hypothesis, but it’s also the case that the more new assumptions a theory makes, the less likely it is to be true; every new assumption presents an opportunity for the theory to be false. (The fewer assumptions a theory makes, the simpler or “more parsimonious” it is said to be.) Likewise, the more existing evidence a theory contradicts, the less likely it is, because in order for a theory to be true, every piece of evidence it contradicts has to be somehow faulty. (The fewer established theories a new theory contradicts, the more “conservative” it is said to be.) And, obviously, the more something explains, the better explanation it is. (This is called having “scope.”) If a theory raises unanswerable questions, it’s not expanding our understanding, and thus is not wide-scoping. Scientists consider all these things when deciding which theory to accept, because the theory that adheres best to these explanatory criteria is most likely to be true.___the mere fact that a theory’s predictive success is why it “sticks around” or “becomes accepted” in the scientific community is not a reason to be skeptical about its truth.___The reason the grue hypothesis is no good is because it invents an entirely new kind of color—not just a new shade, but an entirely different category of color (a different way colors work)—and thus is not parsimonious. It raises unanswerable questions about how and why emeralds would just spontaneously change from green to blue (and thus does not have wide scope). And it contradicts what is already well established about how color works (and thus is unconservative).The theories that the problem of underdetermination points to do the same thing. Yes, the theory that God created an “ancient-looking universe” (complete with an ancient-looking fossil record) two hundred years ago is also consistent with the empirical evidence (of a fossil record) that presently exists; but that theory is monumentally unparsimonious (it requires many extra assumptions about infinite entities) and not wide-scoping (it raises unanswerable questions about why God would do such a thing). So, I can rationally conclude that it is false.Indeed, the history of science includes many examples of theories that were rejected because they lacked parsimony and/or scope, even before their falsity (and the truth of their competing theory) was confirmed by observation. As I point out in my book, geocentrism was rejected by the scientific community because it lacked parsimony, almost 200 years before the observation of parallax confirmed that the Earth moves around the sun. And the continuum theory of matter was completely rejected by 1860, because it couldn’t explain chemical reactions or organize matter into a periodic table, even though the experiments that eventually confirmed atomic theory weren’t even proposed until the 1870s. Solving the best of a bad lot problemIn response, the “empiricists” are likely to object, this time pointing to the “best of a bad lot” problem. “We have no reason to conclude that an explanation that has been shown to be better than others is true because we have no guarantee that the true theory was among those that we were considering.” If you have a “lot” (a collection) of poor explanations, even the best one is not true.The responses to this problem, however, are numerous. Peter Lipton argues that the set of hypotheses that scientists consider are not just randomly selected and thus unlikely to contain a theory that is true; they use existing knowledge to home in on what is most likely to be true. A doctor trying to explain abdominal pain is not going to bother wondering whether demons are causing it; they are going to stick with things like appendicitis and kidney stones, because they are most likely. Further, despite its name, inference to the best explanation is not just the process of comparing hypotheses and accepting the best one; we also want one that is a good explanation in its own right. If it’s not, we are going to keep looking until we find an explanation that is. And while that process does not guarantee that we will come across the exact truth, it’s very likely that the theory that emerges as the best will be at least approximately true, and thus we will be justified in believing it. And lastly, as I point out in my book, although many theories not based in scientific evidence (like geocentrism and continuum theory) have been completely overturned, science almost always progresses by the refinement of scientifically established theories—not their replacement. (Although our sun is not the center of the universe, heliocentrism was our first step in understanding the Earth’s true place in the universe.) So even if a theory we accept today may not be completely right, accepting it is a step on the journey toward the complete truth. The example of atomic theoryNow, it’s worth pointing out that most empiricists are not skeptical of all scientific theories; they are only skeptical of the ones that hypothesize the existence of “unobservables.” It’s not like they think that round Earth, heliocentrism, and germ theory are just useful (but untrue) “instruments” for making predictions about how to most efficiently navigate the seas, predict planetary motion, and treat diseases. They admit that the Earth actually is round, that the planets revolve around the sun, and that germs exist and cause disease. These facts and entities can be observed; the theories that suggest they exist are true. It’s only when theories start hypothesizing the existence of unobservables—like electrons, or quantum fields—that can’t be observed directly, that we should start doubting the theories’ truth. And to be fair to van Fraassen, in this published work, he doesn’t really say that we should doubt the truth of such theories. Only that scientific reasoning does not rationally force us to accept them as true. Skepticism, or agnosticism, he argues, is warranted. SUGGESTED READING Science is based in metaphor By Andrew Reynolds But the history of atomic theory throws a monkey wrench into that argument. Atoms used to be unobservable; again, scientists first accepted the theory that they exist because it had such grandiose explanatory power. But then atoms were seen with electron microscopes. They thus moved into the category of the observable. But this didn’t substantially change anything about what scientists were justified in believing; it certainly didn’t change any “atomic skeptics’” minds. It just confirmed what everyone already knew! If the hypothesis that something exists clearly provides the best explanation for what we can observe, then the belief that it exists is what is rational. The fact that the thing itself is not technically observable does not make doubting its existence rational.What’s more, the atoms were seen with an electron microscope. But electrons are themselves unobservable. How can an electron microscope reveal an atom if electrons are not real? This leads us to what is famously known as Hilary Putnam’s “miracle argument.” It’s (not) a miraclePhilosopher Hilary Putnam’s miracle argument is somewhat famous. Basically, he argued that a scientific theory being able to repeatedly make successful predictions—even about unobservables—without being at least approximately true would require a “miracle.” In other words, it would be such an improbable occurrence that it could not rationally be believed—the better explanation for why scientific theories about unobservables make the right predictions is because the unobservable entities and structures they hypothesize exist.Van Fraassen has addressed this argument. Indeed, in his original article, where he references Alison Gopnik’s point about orgasms not being “necessary for procreation” even though the desire for orgasm “drives the creation of progeny,” he is pointing to his own argument about how organisms are not naturally selected by evolution to get true beliefs; to the extent that belief-forming processes are selected for, the ones that are selected are the ones that are useful for survival—not the ones that produce true beliefs. In the same way, van Fraassen argues, scientific theories are accepted, not because they are true, but because they aren’t falsified; they make successful predictions; that’s what makes them “stick around.” So, the fact that they make successful predictions (and thus became accepted) is not a reason to think they are true.This argument is similar to C. S. Lewis’s “argument from reason,” which he used to argue against evolution: “The truth of evolution undercuts our ability to know that it is true.” Lewis’ argument famously failed; Elizabeth Anscombe, by Lewis’s own admission, demolished Lewis in a debate on the topic, and I have explained elsewhere why modified versions of the argument fail as well. In short, it’s because it fails to recognize that a belief-forming process can make an organism more likely to survive because it reliably produces true beliefs. It is therefore not the case that beliefs generated by naturally selected belief-forming processes are automatically false or unjustified.In the same way, the reason a theory “sticks around” could be because it’s not falsified, because it “makes correct predictions.” But the reason it makes correct predictions is most likely because it is true. (In pointing this out, I am echoing the arguments of Musgrave, Lipton, Psillos, and Kitcher, who refuted van Fraassen’s argument and analogy long before his 2024 article.) It would be a huge coincidence that it could do so without being true. And that is the point of Putnam’s miracle argument. Thus, contrary to van Fraassen’s suggestion, the mere fact that a theory’s predictive success is why it “sticks around” or “becomes accepted” in the scientific community is not a reason to be skeptical about its truth. ConclusionLet me close by saying something about the fact that empiricists don’t doubt the truth of all scientific theories, just the ones that hypothesize unobservables. In today’s society, this theory is dangerous to espouse publicly. The nuance between being skeptical about all of science, and just the highly technical theories about unobservables, is guaranteed to be lost to the average reader. And there is so much unjustified skepticism and doubt about the findings of science and experts that a headline like “Science Does Not Describe Reality” could easily fuel the anti-science movement, worsen climate change denial and cause the next pandemic.This is why I believe it was important to still respond to van Fraassen’s article, a full two years after he wrote it. Not only, as I have argued, does it represent a philosophically inaccurate view of how scientific reasoning works and what scientific reasoning can do, but it is a dangerous view to boot. It should thus be rejected.
Democratic Michigan Senate hopeful Abdul El-Sayed explains how science influences his politics
Scientific American spoke to the Michigan Senate candidate about how his background in medicine has shaped his outlook
Democratic Michigan Senate hopeful Abdul El-Sayed explains how science influences his politics
Scientific American spoke to the Michigan Senate candidate about how his background in medicine has shaped his outlook
PLOS and Chinese Academy of Sciences join forces on open science programme
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