Modern scientific societies are increasingly vulnerable due to their dependence on membership fees and journal subscriptions, which are being challenged by the rise of virtual networking and open-access publishing.
"We hope that by taking strong action against violations of agreed-upon policy we will remind the community that as our field changes rapidly the thing we must protect most actively is our trust in each other."
Computer programs that check mathematical arguments have existed for decades, but translating a human-written proof into the strict programming language of a computer is extremely time-consuming, often taking months or even years.
Social foraging strategies illustrate the balance between competition and cooperation, where individuals either produce resources or exploit the efforts of others, navigating ecological and social constraints.
Many colleges and universities have made cuts in these programs, often bolstering STEM programs at their expense. It's a situation that has sparked no small amount of impassioned editorials. The headline of a recent article at The Guardian by Alice Speri referenced an 'existential crisis at U.S. universities,' and Speri's reporting features numerous examples of undergraduate and graduate programs facing cuts or outright elimination.
I'm less interested in topics than in questions, and I'm less interested in publishing than I am in curation. When I've testified before Congress or dealt with an appropriations bill or a budget negotiation, this question, of what is the return on investments when you're doing R&D, comes up quite often. It's been asked by economists in very formal ways since at least the 1950s, but the data and the methods that were available were really not very strong.
As it turns out, neuroscience might be able to explain why. In a new study whose findings will surprise absolutely no one who's endured a fiery holiday dinner debate, researchers discovered that conservative and liberal brains don't just arrive at fundamentally different conclusions, but take strikingly different paths to get there. It's a fascinating piece of research which just might explain something about the yawning political divides currently tearing society apart.
Some clinicians have an uncanny quality. A colleague describes herself and others with this instinct as "witchy"-a capacity to know things about patients they haven't said yet, to follow a stray association to a song lyric or a half-remembered cultural reference and arrive, reliably, at something the patient urgently needed to say but couldn't reach on their own. We see with artificial intelligence these intriguing possibilities for discovery, especially as connections that human beings never would see pop out of apparently unrelated data.
In 2023, Australia abandoned its expensive and bureaucratic scholar-led research-assessment programme. New Zealand followed suit soon after. The hope, according to a transition plan unveiled by the Australian federal government's Department of Education and the research sector, was to find a "more modern, data-driven approach". In the United Kingdom, where financial pressures on universities are especially acute, there are similar calls to reform the Research Excellence Framework (REF), the country's performance-based research-funding system.
A professional philosopher outside the academy walls can act as a popularizer (the goal here is to make philosophy more accessible to the general public), an applied ethicist (the major task is to offer an analysis of various specific moral issues that arise within a society), and a public intellectual (I limit this role to questions that have political connotation). Of course, there are overlaps between these roles and they certainly do not exhaust all possible forms of public engagement of a professional philosopher.
Consistent with the general trend of incorporating artificial intelligence into nearly every field, researchers and politicians are increasingly using AI models trained on scientific data to infer answers to scientific questions. But can AI ultimately replace scientists? The Trump administration signed an executive order on Nov. 24, 2025, that announced the Genesis Mission, an initiative to build and train a series of AI agents on federal scientific datasets "to test new hypotheses, automate research workflows, and accelerate scientific breakthroughs."
Recent integrative approaches suggest that physics cannot be adequately characterized by magnitude-based distinctions alone, such as those implied by Big-P, little-p, and mini-p physics. While these categories capture differences in scope and historical impact, they fail to address the heterogeneity of physical activity itself. To remedy this, I propose the Five Fs of physics: force, friction, flux, formulation, and foundational structure.
