So thrilled to be joining the Psychology Department at @columbiauniversity.bsky.social as an assistant prof next summer! I'll be recruiting for PhD/postdoc to start in Autumn 2027, so if you're interested in using computational approaches to studying human cognition please get in touch!

Are you on academic job market for #Postdoc or #TT Assistant/Assoc. Prof/Lecturer/ #AP /Research Scholar/ #fellowship jobs for 2026-2027 in #CS/ #SocSci/ #InfoSci/ Management Science/ #Psych & similar? Like last year, I am maintaining a list (so far ~200 positions) docs.google.com/spreadsheets...

2026-2027 Postdoc/TT/Research Scientist Positions in Information/CS/Social Science + Related Fields

docs.google.com

The Neuroscience Department at UC Berkeley is hiring an Asst Professor in Computational Neuro. All areas of computational/theoretical neuro are welcome. Deadline Oct 30. Join our neuroscience community! aprecruit.berkeley.edu/JPF05446 #AcademicJobs #Neuroscience #NeuroJobs

Assistant Professor - Computational Neuroscience - Department of Neuroscience

University of California, Berkeley is hiring. Apply now!

aprecruit.berkeley.edu

1st book review! “Lombrozo unpacks the psychology of explanations in rich detail and sharply analyzes how explaining can help and hinder…The result is a fresh, engrossing take on an important aspect of human behavior.” 😀 www.publishersweekly.com/9780063395008

Why We Ask Why: The Science of Explanation and the Human Drive to Understand by Tania Lombrozo

People explain what they experience, feel, and encounter in order to understand the present and anticipate the future, according...

publishersweekly.com

Twelve quick tips for AI-assisted coding in science journals.plos.org/ploscompbiol... - our latest by @ericwbridgeford.bsky.social with @thisisadax.bsky.social , Zijiao Chen, Zhicheng Lin, @hritz.bsky.social and @joachim.cidlab.com

Twelve quick tips for AI-assisted coding in science

While AI coding tools have demonstrated potential to accelerate software development, their use in scientific computing raises critical questions about code quality and scientific validity. In this pa...

journals.plos.org

What do rubber ducks have to do with learning and AI? You can find out in my TEDx talk, released today as an Editor’s Pick at the YouTube TED Channel! www.youtube.com/watch?v=cbiy...

How you can learn in a world of information overload | Tania Lombrozo | TEDxNewEngland

YouTube video by TEDx Talks

youtube.com

I'm recruiting two postdocs (or potentially PhD students) to work on projects at the intersection of cognition, neuroscience, and AI (with a particular emphasis on mechanistic interpretability). Apply here: docs.google.com/forms/d/e/1F... and please share!

At Brown, I'm privileged to organize an AI policy summer school where we bring grad students from across the nation together to learn about policymaking. We travel down to DC as a group and learn about policy implementation and careers, and the students conduct meetings with Congressional offices.

We appreciate the love ❤️ But limited engagement and few followers on Bsky makes some (not us!) question whether it's worth it Be sure to follow (and share with your ML friends!) if you want to see more updates from ICML!

Marc Lanctot@sharky6000.bsky.social · 4w ago

Wow, awesome! Massive thank you to the comms & PR team @icmlconf.bsky.social 🤩 ✅️ Multiple update posts per day ✅️ Posts with photos!! 📷 ✅️ Great use of hash tags #icml2026 ✅️ Schedule and QR links at the local mall ✅️ Setting the gold standard for academic Bluesky 👍 🙏

New paper! w/ @cocoscilab.bsky.social🧵Can large language models reason flexibly, or have they learned what reasoning looks like? We introduce a new paradigm to test this question—the riddle riddle—and find that humans and LLMs show opposite patterns of performance. 📜

More evidence, from a large-scale study in China, that using AI hurts learning if it undermines mental effort. When homework time drops due to AI use, so do test scores. Across studies, there is a clear theme: AI tutoring in support of classes is good, using AI to "help" with homework is bad.

Very excited to share that my lab will be moving to Princeton (Neuroscience & Psychology) this fall. I'll be recruiting at all levels (more info to come soon), please share / get in touch if you're interested in joining!

Excited to announce that I'll be starting my own lab in Tübingen this October! Hiring at all levels: Postdoc, PhD & RA. Want to work on computational cognitive science at scale? Apply: core-cognition.github.io Reposts and shares much appreciated 🙏

Pointing out that “everyone else is already doing it!” is a classic way to motivate prosocial behavior. But how can we encourage actions which aren't popular yet? In a new paper in @jexpsocpsych.bsky.social, Mike Norton and I had a lot of fun testing a method using "collective streaks." (1/5)

Do LLMs *understand* language? Do educational AI agents *understand* the material they teach (or their students)? Claims about what AI systems do or don't understand are pervasive, but assessing them requires an account of MACHINE UNDERSTANDING

Excited to share I will be joining UC Davis as an assistant professor starting July 2027! Thank you dearly to all mentors and friends who have supported me over the years ❤️ and Cal Poly friends, I'll miss you!

💬 Getting the ick with chatbots? Our research in Nature shows that models trained to adopt a warm and friendly tone are more likely to make mistakes when answering your questions. Small changes in tone can undermine accuracy across architectures, particularly when users express vulnerability.

New paper w/ UK AISI: Millions of people now use AI to help them write and communicate. In three experiments (14k participants, 3m+ human ratings) we show that AI writing assistance systematically distorts writer personas – their perceived beliefs, personality, and identity. 🧵

A computational theory of Aha! moments! New paper explaining why Aha! moments occur & why they feel so good. TLDR: They are a form of meta-cognitive prediction errors i.e. they occur when we surprise ourselves about our own abilities! @rachitdubey.bsky.social www.sciencedirect.com/science/arti...

🚨New preprint and our results are rather concerning.. We find the "boiling frog" equivalent of AI use. Using large-scale RCTs, we provide *casual* evidence that AI assistance reduces persistence and hurts independent performance. And these effects emerge after just 10–15 minutes of AI use! 1/

Excited that my paper on metacontrol in humans and neural networks with @summerfieldlab.bsky.social and @lhuntneuro.bsky.social is out in PNAS! We examine the way that predictive representations of control enable behavioral adaptation across settings, and pathologies: www.pnas.org/doi/10.1073/...

Honored to be in such esteemed company! Many thanks and super grateful to my great mentors and collaborators over the years.

Association for Psychological Science@psychscience.bsky.social · 5mo ago

⭐️ Congratulations to the newest class of APS Rising Stars ⭐️ www.psychologicalscience.org/members/awar...

DeepMind's RL team is hiring a research scientist: if you're passionate about RL, come work with us! And if you know people who might be interested, please share: job-boards.greenhouse.io/deepmind/job...

In his new book, “The Laws of Thought,” Tom Griffiths @cocoscilab.bsky.social shows how symbolic logic, probability theory and neural networks, when used together, are enough to explain how mind and brain work via “laws of thought.” #neuroskyence www.thetransmitter.org/brain-inspir...

Tom Griffiths describes how neural networks, logic and probability theory together explain cognition

In his new book, “The Laws of Thought,” Griffiths shows how these three pillars of study complement one another and together form a solid foundation to eventually explain all of our cognition…

thetransmitter.org

🚨New preprint! LLM teams are being deployed at scale, yet we lack the tools to predict when they’ll succeed, fail, or how to design them. Distributed computing faced the exact same questions and figured out how to answer them. We show those insights apply directly to LLMs 🧵👇

New preprint shows how ideas from distributed computing can be used to understand the performance of teams of language model agents on different kinds of tasks

Elizabeth Mieczkowski@emiecz.bsky.social · 5mo ago

🚨New preprint! LLM teams are being deployed at scale, yet we lack the tools to predict when they’ll succeed, fail, or how to design them. Distributed computing faced the exact same questions and figured out how to answer them. We show those insights apply directly to LLMs 🧵👇

Sharing “Neural Thickets”. We find: In large models, the neighborhood around pretrained weights can become dense with task-improving solutions. In this regime, post-training can be easy; even random guessing works Paper: arxiv.org/abs/2603.12228 Web: thickets.mit.edu 1/

Both "A" words; 1 conference. RSVP now to join us on April 3 for a symposium all about merging affordability and climate policy. We just announced the speakers and the panels. It's free to attend but you must register and we do expect the event to fill up! docs.google.com/forms/d/e/1F...

New paper! The Linear Representation Hypothesis is a powerful intuition for how language models work, but lacks formalization. We give a mathematical framework in which we can ask and answer a basic question: how many features can be stored under the hypothesis? 🧵 arxiv.org/abs/2602.11246

Psychophysics is a human-facing science with interventions arguably more robust than medicine.

1000 Hurts

Psychophysics is a human-facing science with interventions arguably more robust than medicine.

argmin.net