@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.

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".

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.