Getting back into sketching this fall quarter by drawing friends old and new. :) First, notes from @lindseypowell.bsky.social's tenure talk. (Congrats Lindsey!!)
I'm very excited to share a new preprint with you all (5 years in the making).
"Making good decisions with counterfactuals" with Ricky Ma, Scott Mueller, and Thomas Icard.
We investigate how people combine experimental and observational data to make decisions.
π osf.io/preprints/ps...
We share some tips on how to develop better intuition for how observational and experimental data should be combined to make good decisions.
Counterfactual thinking is at the heart of it!
You can try out your own intuitions by playing around with data: cicl-stanford.github.io/good_decisio...
Side note: This project started with an email from Ricky in May 2021 who had just received his BSc in Cognitive Systems at UBC. It took over 5 years with lots of zoom sessions to complete it. Ricky and I still haven't met in person.
I'm very excited to share a new preprint with you all (5 years in the making).
"Making good decisions with counterfactuals" with Ricky Ma, Scott Mueller, and Thomas Icard.
We investigate how people combine experimental and observational data to make decisions.
π osf.io/preprints/ps...
People's decisions are well-explained by a simple decision model that uses a linear additive combination of the experimental and observational data.
But these decisions don't correlate well with the predictions of the normative model.
While both novices and experts make incorrect inferences about the counterfactual types from the data (e.g. believing people benefit from acting when they don't), their decisions systematically follow these (incorrect) inferences.
I'm very excited to share a new preprint with you all (5 years in the making).
"Making good decisions with counterfactuals" with Ricky Ma, Scott Mueller, and Thomas Icard.
We investigate how people combine experimental and observational data to make decisions.
π osf.io/preprints/ps...
Balke & Pearl (1994) developed a normative model of how to do this. How do people's decisions compare? Not well! People are better than chance but far from optimal. They have difficulty inferring the counterfactual types from the data, relying on a simple linear additive heuristic instead.
People leave a lot of money on the table! Getting feedback doesn't improve performance, but engaging with the data more closely helps. Experts at Stanford (postdocs & students in statistics, economics, or data science) performed better than novices but still far from optimally.
I'm very excited to share a new preprint with you all (5 years in the making).
"Making good decisions with counterfactuals" with Ricky Ma, Scott Mueller, and Thomas Icard.
We investigate how people combine experimental and observational data to make decisions.
π osf.io/preprints/ps...
One should use the data to infer whether someone will benefit from the treatment, be harmed by it, or be unaffected. These are counterfactual notions! Benefit = better because of action. By placing a value on each counterfactual type, one can compute the expected benefit of acting vs. not acting.
delighted to share my review article, out now in Trends in Cognitive Sciences!
i have been thinking a lot about dynamics lately. this article outlines three key principles - persistence, parallelism, and time-stamped encoding - that support human speech comprehension π§ β¨π
π The Social Tinkering paper with Nick Chater is now out in an issue of BBS. We highlight the importance of bottom-up and socially-oriented factors in cultural evolution 1/4
www.cambridge.org/core/journal...
We often say that humans struggle to produce random sequences⦠but what if that's not the whole story? In a new paper, @dorsaamir.bsky.social, @samiyousif.bsky.social & I show that context matters (a lot!). When playing strategic games, humans can produce near-random behavior osf.io/preprints/ps...
I am recruiting graduate students for UCI's PhD in Cognitive Sciences - www.cogsci.uci.edu/graduate/pro... The lab's focus is on how relational structure and combinatorial reasoning is implemented in human brains and large language models--and if they are similar.
I'm so grateful for the continued support from my lab, and for everyone who helped along the way, now as an associate professor with tenure at Stanford π§βπ«π₯π²
The Stanford Psychology Department is having a search for a tenure-track Assistant Professor with a research focus on developmental and/or social psychology.
Application deadline is 10/15.
More infos here: facultypositions.stanford.edu/jobs/assista...
(1/7) New paper in @cognitionjournal.bsky.social: "Manipulating Prior Causal Beliefs Affects the Formation of Apparent Causal Illusions"
Why do people sometimes "see" causal links in zero-contingency data? We tested if this is rational updating, not bias. π§΅
www.sciencedirect.com/science/arti...
Deciding when to jump in and help someoneβand when to hold back and let them work through itβis something humans navigate constantly. How do AI assistants handle this tradeoff?
We introduce Int-Bench, a framework for evaluating interventions during problem-solving tasks.
Wonderful keynote by @hyogweon.bsky.social at #cogsci2026 on "Distinctively human intelligence: Thinking, learning, and communicating about the self".
Hyo argues that better understanding how people think about the self is a key ingredient for uncovering what makes us intelligent.
When you meet someone new, what kind of questions do you ask? Itβs tempting to think that *really* getting to know people is just a matter of asking the right questions. Excited to share the next chapter in ongoing work on what makes a *deep question* with amazing collaborators...
Very proud Doktorvater moment from a few weeks back. Pictured with Dr Sarah Wu and Dr David Rose (and with a large hat thanks to University College London's regalia).
Sarah will postdoc with @tomerullman.bsky.social. David with @shaunnichols.bsky.social and @davidpierce.xyz.
I will miss you!! β₯οΈ
I wrote a book! It's called WHY WE ASK WHY, and it's about the human drive to explain, combining psychology, philosophy, and stories. It will be released on October 6, but it's currently available for pre-order from Barnes & Noble at 25% off with code PREORDER25.
Most models of learning ask what you can represent. We think the real bottleneck is what you can afford to find, since searching for a good representation is itself expensive.
New preprint w/ @davidnagy.bsky.social, Peter Dayan & @thecharleywu.bsky.social π§΅π
Congratulations, Melissa Kibbe (@levelsof.bsky.social), on winning the Society for Philosophy and Psychologyβs 2026 Stanton Prize and, more generally, for your rich research program demonstrating the origins of abstract, generative thought in human infants.
ββ
Open Mind is MIT Pressβs Diamond Open Access Cognitive Science journal.
We now have our first Impact Factor: 2.9 as of June 2026
Submit your papers to Open Mind
direct.mit.edu/opmi
New paper in Cognitive Psychology on how people combine visual π, auditory π, and haptic information ποΈ to make causal judgments.
Led by Elyse Chase (www.elysechase.com), with Kevin Smith, and Sean Follmer.
π authors.elsevier.com/a/1nHnI2Hxok...
It was such an honor and so much fun to participate in Phil Johnson-Laird's 90th birthday conference. Thank you @ruthbyrne.bsky.social and Sunny Khemlani for organizing the event, and the folks at NYU for hosting it.
Here is Phil asking whether people are smarter than logic. Phil certainly is!
Thrilled to be sharing my latest work at #CogSci2026!
Many of the spaces we move through, from kitchens to airports, were designed with specific uses in mind. How do people create such environments, and how do users figure out what they were designed for?
π osf.io/preprints/ps...
The Unfolding World: Causal & Physical Cognition in Humans and Other Animals (April 24-25)
We're bringing together comparative, computational, developmental, vision science & philosophy for a workshop on causal reasoning + intuitive physics!
If you're in the Cambridge (UK) area, check it out! β¬οΈ
Some notes from the wonderful celebration of John Flavell's life and work at #CDS2026.
"Age early and get it over with." (John on his looks not having changed in many years.)
"Use the simplest word to get the idea across."
"If I could only step into a child's mind even if just for a moment."
From Susan Gelman's talk (who met John thrice πβοΈπ¨βπ«):
1) Don't be afraid to ask questions.
2) "Research is hard (and fun!)"
3) Appearances can be deceiving.
From Alison Gopnik's comments:
John showed us that it's possible to be a good man and a good scientist.
Excited (and cold) for my first ever #CDS2026!
I'll be presenting work by the 'Dropping Things' dream team in the workshop on "Counterfactual thinking: What is it good for?"
Paper sneak peek: cicl.stanford.edu/papers/rose2...
The Causality in Cognition Lab -- a supportive, bluesky-colored team -- is looking for a predoc to join us! Here are infos about the lab (cicl.stanford.edu) and the position (careersearch.stanford.edu/jobs/iriss-p...). The application deadline is May 1st.
Please share, thank you π
Thanks Arthur Le Pargneux (arthurlepargneux.wixsite.com/arthurleparg...) for your talk "Contractualist moral cognition: From fair divisions to the emergence of rules via implicit agreements". A novel take on morality backed by clever experiments + elegant models π
π psycnet.apa.org/fulltext/202...
π Postdoc Alert! Are you passionate about social learning & cultural evolution? @dominikdeffner.bsky.social & I have a 3-year position with freedom to develop your research and work on cutting-edge multiplayer and immersive experiments. Apply by March 30! hmc-lab.com/SocialLearni... Pls share π
Thank you Yoonseo Zoh (zohyos7.github.io) for sharing your work with us on "Intuitive Theories in Moral Cognition". Intuitive theories structure how people represent dilemmas, how they generalize to new contexts, and how they switch between representations based on resource-rational constraints.