The findings confirm research that I conducted more than 20 years ago. Under the guise of the Comedy Research Project, Timandra Harkness and I performed a randomised clinical trial to assess whether or not science can be funny.
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.
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.
Minutes into teaching my business school class, I asked what seemed like an innocent question: What is one word that describes how you feel about AI right now? One word. That's it. My students looked up, looked down, looked anywhere to avoid eye contact. Silence. "I promise," I said, "this is a safe space." Something I'd repeat throughout the course-and I meant it. Then the answers came quickly, and the energy in the room shifted as they arrived. You could feel the sheen of performance
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.
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.
Fifty-four seconds. That's how long it took Raphael Wimmer to write up an experiment that he did not actually perform, using a new artificial-intelligence tool called Prism, released by OpenAI last month. "Writing a paper has never been easier. Clogging the scientific publishing pipeline has never been easier," wrote Wimmer, a researcher in human-computer action at the University of Regensburg in Germany, on Bluesky. Large language models (LLMs) can suggest hypotheses, write code and draft papers, and AI agents are automating parts of the research process.
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."
Ever since our ancestors first stood upright and squinted at the horizon, we've been wired to notice patterns. A rustle in the grass might have meant a stalking predator. Dark clouds often meant rain. Those who made these connections and guessed that one thing caused another tended to survive. Over time, this ability to link events became one of our most significant evolutionary advantages. It's how we built tools, tamed fire, and eventually invented Wi-Fi.