iiinova — where your digital self keeps evolving

Most notably, I think, we can study it using the Price equation! Check out the talk if you think that's an interesting or bold claim. I'll close with my favorite slide:

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But my favorite answer is that 'evolution' is not a metaphorical appeal, but rather a recognition that cultural change actually is a *kind* of evolutionary process, with both shared characteristics with genetic evolution and also its own unique characteristics.

Second, 'cultural evolution' has a set of core theoretical ideas which are unique and interesting in their own right, separate from behavioral ecology, evolutionary biology, etc.

Basically I think there are three reasons. First, 'cultural evolution' refers to a legitimate scholarly community now and growing field of study (e.g. we are facing an explosion of abstract submissions this year for @ces2026.bsky.social)

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I lead with the question, why do we like to refer to cultural change as 'evolution'? Does that do any work for us?

All in all, a classic that's stood the test of time. 5 stars.

Use your own notation and paraphrase the (sometimes old-timey) problems. Steamship coal consumption (ex10n10) is fundamentally about tradeoffs seen in a variety of applied situations.

The chapter on growth processes is very, very good, and informs my scientific work almost today. Knowing how to deploy a variety of growth models very useful for data analysis projects.

The book is 116 years old, but the exercises lend themselves to some very cool visuals that can be made with modern tools. www.desmos.com/calculator and digital tablets are a game-changer.

The problems are very, very good and extend naturally from the worked examples. Doing every one of them was a huge help for me. Especially so in the 1998 edition with Martin Gardner as co-author.

Bret Beheim @babeheim.bsky.social · 06/11/2025

A colleague at MPI asked how to get better at math. My vote is Thompson and Gardner's classic *Calculus Made Easy* (originally published in 1910!) I've uploaded my own (almost complete) worked problem sets from this classic book. A few thoughts.../

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welcome to the future, it sucks ass

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Consistent with other recent work in cultural evolution, there's also strong evidence of an inverse-U relationship between player community size and behavioral diversity. The most diverse era in the game was characterized by many small groups, versus the modern game.

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AI has introduced a lot of new moves into the game tree and defied a lot of conventional wisdom, but overall the families of strategies have only changed incrementally post-AlphaGo.

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Even though superhuman Go AI like AlphaGo have led to a measurable increase in innovation, player skill and move diversity, in the full context of historical time, the disruptiveness of AI has so far been pretty minor!

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Zooming in, it's clear the tempo of evolutionary change has increased since the arrival of the internet, with faster turnover and lower strategic diversity.

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The diversity of opening moves ebbs and flows with world events; industrialization, revolution and the arrival of the internet all have measurable impacts on the information ecology and strategic repertoires of high-level players

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Using sequence alignment algorithms on historical game records, we can identify families of opening strategies, and track how they rise and fall in popularity over the centuries. Here are the most common opening sequences as a decision tree, from the 1600s up until World War II.

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Bret Beheim @babeheim.bsky.social · 04/09/2025

How to quantify the impact of AI on long-run cultural evolution? Published today, I give it a go! 400+ years of strategic dynamics in the game of Go (Baduk/Weiqi), from feudalism to AlphaGo!

Miyagawa Shuntei's 1898 painting, "Playing Go (Japanese Chess)"

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last update: 48 years ago lol

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Bret Beheim @babeheim.bsky.social · 27/08/2025

Your restraint is a model for us all 😅 Incidentally, this paper largely wouldn't exist without your Current Biology paper on sequence alignment algorithms, which is a huge advance for cultural evolution. Getting to this MDS plot suddenly made a lot of stuff make sense in Go.

Bret Beheim @babeheim.bsky.social · 16/07/2025

Yes, that's right, this one:

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Bret Beheim @babeheim.bsky.social · 14/07/2025

I'm playing around with the decision tree for professional openings in the game of Go, and I've almost re-created the @culturalevolsoc.bsky.social logo

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I learned of this critique from David Freedman's excellent textbook "Statistical Models", where the above mortality table is also from, and think about it pretty much all the time.

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The difference was absolutely *massive*. Households getting dirty, cholera-filled wastewater from downriver of the city experienced like a 10-fold increase in mortality from cholera. The case was made that it was something in the water, with very clever reasoning and purely observational data.

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Basically, he noticed that in the 1850s, the Vauxhall and Lambeth water companies serviced the same London neighborhoods, even the same city blocks, but drew their water from different parts of the Thames (upriver and downriver of the city center). Can you see where this is going?

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Snow himself understood the flaws in the Soho study, and looked for more convincing evidence than a spatial correlation and dubious intervention. So what can we teach instead? I think Snow's second study of London water companies from his book, which had a huge contemporary impact on public health.

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