Selection pressure [https://en.wikipedia.org/wiki/Evolutionary_pressure] is one of those important ideas that human intuition isn't designed for. The idea helps visualize how selection (natural or otherwise) works. I usually picture it as a force pushing the evolution of a species

Martin Sustrik has a 3-part series [https://250bpm.com/blog:161/] that helps understand how the Swiss direct democracy system works. My takeaways: * The system depends a lot on decentralization. A lot of power is in the hands of municipalities and cantons (equivalent to

The Long Now foundation on the longest living institutions [https://blog.longnow.org/02020/10/21/the-data-of-long-lived-institutions/]. Here's an interesting bit on the bristlecone pine, a tree with an incredibly long lifespan: > The bristlecone exemplifies how an existential crisis gives you practice in terms

I learnt about a useful way to visualize progress of new technologies: The Gartner Hype Cycle. The key idea is that a technology has five phases in its life cycle: The trigger, the peak of inflated expectations, the trough of disillusionment, the slope of

Categorizing Variants of Goodhart’s Law [https://arxiv.org/abs/1803.04585] gives us a deeper look at the now well known Goodhart's law. The definition of Goodhart's Law from the paper: > a Goodhart effect is when optimization causes a collapse of the statistical

There are probably lots of complex tools for modelling systems, but Loopy [https://ncase.me/loopy/] is a really simple and easy to use one. Given how simple it is, it's probably more suitable as a way of explaining your intuitions about how a

I was introduced to the idea of breaking up learning environments into 'kind' and 'wicked' by David Epstein's book Range [https://www.amazon.co.uk/Range-Generalists-Triumph-Specialized-World/dp/1509843493] . I think this is a powerful idea with broad implications. Kind learning environments have quick feedback,

John Salvatier's essay [http://johnsalvatier.org/blog/2017/reality-has-a-surprising-amount-of-detail] articulates something I've been trying to wrap my head around for a while. Reality is surprisingly complicated. Almost every field of science and engineering has an immense amount of detail and nuance involved in it,

This [https://ncase.me/ballot/] interactive essay covers common types of voting systems and the tradeoffs associated with each. The simulations are great fun to play with. My takeaway was that it is very difficult to design a voting system that is fair to

I've started a lot of online courses but finished very few of them. One of the few I've finished and enjoyed was Scott Page's Model Thinking [https://www.coursera.org/learn/model-thinking] course on Coursera. This is a very practical introduction to modelling systems

This cool, short video is an illustration how changes to systems can have unintended (and in this case, positive) consequences. The introduction of wolves to Yellowstone National Park literally changed the paths of rivers in the park.