Björn Lindström

From information free-riding to information sharing: how have humans solved the cooperative dilemma at the heart of cumulative cultural evolution? Abstract. Cumulative cultural evolution, where populations accumulate ever-improving knowledge, technologies and social customs, is arguably a unique featu

New paper out in Phil Trans with Angel Jimenez, Keith Jensen and Lei Chang

From information free-riding to information sharing: how have humans solved the cooperative dilemma at the heart of cumulative cultural evolution?

royalsocietypublishing.org/rstb/article...

Very grateful that our paper was awarded ISCON’s Best 2024 Paper in Social Cognition!! Huge thanks to the fantastic team: Ben Stillerman, @bjornlindstrom.bsky.social , @leorhackel.bsky.social , Damaris Hagen, Nils Jostmann, and @davidamodio.bsky.social 🎊💐

Department of Social and Behavioral Sciences

🚨Two postdoc positions @tse-fr.eu @iast.fr 🚨

We are recruiting two postdocs as part of the ANR-funded project ENFORCE.

Join me, @giuliandr.bsky.social, & @zhgarfield.com, to study punitive systems across societies.

Full time, 2 years, no teaching.

Deadline: Jan 23

www.tse-fr.eu/groups/depar...

📣 Very happy to announce a new BBS target article with Nick Chater in which we propose a new theory of cultural evolution, highlighting the importance of bottom-up social interaction in explaining the emergence of cultural complexity
🧵 1/8

www.cambridge.org/core/journal...

A habit and working memory model as an alternative account of human reward-based learning Nature Human Behaviour - In this study, Collins proposes an alternative dual-process (working memory and habit) model of reinforcement learning in humans.

My paper is out!
Computational modeling of error patterns during reward-based learning show evidence that habit learning (value free!) supplements working memory in 7 human data sets.
rdcu.be/eQjLN

Come and do a PhD at Exeter with me and Chico Camargo (Computer Science) on human-genAI coevolution

"Leveraging Natural Language Processing for Data-Driven Agent-Based Modelling of Online Cultural Dynamics"

www.exeter.ac.uk/v8media/recr...

More details here:
www.exeter.ac.uk/study/fundin...

For this reason, we wrote this comment, published yesterday. royalsocietypublishing.org/doi/10.1098/...
We reason that 1) their data supports rather than rejects the sequence hypothesis, as monkeys and chimps did not perform with any precision in these sequential tasks. 7/n

Join us for this talk by @janhaaker.bsky.social on "A functional view on how we respond to others’ pain: Empathy, threat learning and neuropeptides"
11 November, 1pm CET

tu-dresden.de/mn/psycholog...

Just 1 week to apply! 4 year @erc.europa.eu funded PhD position working in an interdisciplinary team to study #culturalEvolution as a process of reuse, recombination, and creative re-engineering of past solutions. Details 👉 hmc-lab.com/ERCPhDCultur... 🙏Please share!

🚨 New preprint 🚨

Are reinforcement learning models complete accounts of decisions from experience if they ignore explicit memory?

In this new preprint, we show that people indeed form robust explicit memory representations that flexibly guide later decisions.

🔗 Preprint: doi.org/10.1101/2025...

Re-posting this because I really like it and I think we need to understand identity from a functionalist perspective more than ever.
osf.io/preprints/ps...

I'm excited to finally have a preprint of this paper up, a few years in the making.

In it we argue that industry-driven manipulation of social media research is well underway and that norms and institutions in the field are ill-prepared to resist tech's influence.

arxiv.org/abs/2510.19894

Fully-funded 4-year #PhD in Cultural Evolution! Join my @erc.europa.eu project exploring how compression & compositionality drive cultural innovation: hmc-lab.com/ERCPhDCultur...
Apply by Nov 12!
Maybe of interest to folks from #COSMOS2025 or @eslr.bsky.social? Please feel free to share! 🙏

Very thought-provoking post by @prakhargodara.bsky.social. Is confirmation bias/positivity bias a statistical "ghost" of model specification? Specifically not including temporally decaying learning rates? The evidence suggests this is not the case and here is why (1/n)

@culturalevolsoc.bsky.social

Note that we are making a distinction between semantic knowledge and causal understanding in the paper, which is about the former.

Of course, that seems likely! My hunch, after working on this project, is that semantic knowledge is so key for human cognition that it almost always will play an important role. If anything, the body of semantic knowledge co-evolves with technologies, and u couldn't have one without the other.

I agree, but as many such modeling conventions (eg fixed social learning strategies), it also seem to shape thinking. Influential people have been arguing that culture often evolves without knowledge (eg bow study in current bio), as in the models. Thanks for the preprint, interesting!

Might interest
@dominikdeffner.bsky.social
@watarutoyokawa.bsky.social
@thecharleywu.bsky.social
@lucasmolleman.bsky.social n.bsky.social
@maximederex.bsky.social y.social
@alexmesoudi.com oudi.com
@psmaldino.bsky.social ky.social
and hopefully many others.

Together, our results suggest that semantic knowledge is a key cognitive driver of cumulative culture.

It’s not just learning from others—knowledge of why things make sense may be key for culture to evolve.

Participants with access to semantic knowledge:
🔹 Explored fewer, more focused combinations
🔹 Showed lower entropy (less random search)
🔹 Used semantic generalization to build on prior success 🔹 Combined semantically dissimilar items to innovate

Using the same innovation task, we tested 1,243 participants combining items to make new inventions.

When items had meaning (semantic condition), people innovated far more—especially with social learning. Without meaning (non-semantic condition)? Performance was no better than random "bots".

Populations with both semantic knowledge and social learning produce far richer cultural repertoires.

Agents that with both semantic knowledge and social learning dominate over time, exploring efficiently—not randomly. Crucially, semantic knowledge and social learning act in synergy.

In our model, agents start without knowing how items combine. Through success, they build semantic knowledge. structured associations between items and functions, and pass this knowledge to their offspring.

Using an agent-based model (ABM) and a large-scale experiment (based on the innovation task from
@maximederex.bsky.social), we find that our capacity for semantic knowledge is crucial for directing exploration toward plausible innovations rather than random trial-and-error.

How do humans keep inventing tools and technologies that no single person could create alone?

Our new preprint, led by
@anilyaman.bsky.social & @ts-brain.bsky.social
shows that semantic knowledge guides innovation and drives cultural evolution. 🧠📘 arxiv.org/abs/2510.12837

Might interest @dominikdeffner.bsky.social @watarutoyokawa.bsky.social @thecharleywu.bsky.social @lucasmolleman.bsky.social @maximederex.bsky.social @alexmesoudi.com @psmaldino.bsky.social and hopefully many others.

Together, our results suggest that semantic knowledge is a key cognitive driver of cumulative culture.

It’s not just learning from others—knowledge of why things make sense may be key for culture to evolve.

Participants with access to semantic knowledge:
🔹 Explored fewer, more focused combinations
🔹 Showed lower entropy (less random search)
🔹 Used semantic generalization to build on prior success
🔹 Combined semantically dissimilar items to innovate

Using the same innovation task, we tested 1,243 participants combining items to make new inventions.

When items had meaning (semantic condition), people innovated far more—especially with social learning.
Without meaning (non-semantic condition)? Performance was no better than random "bots".