The Secret of Our Success argues that cultural traditions have had a lot of time to evolve. So seemingly arbitrary cultural practices may actually encode important information, even if the practitioners can't tell you why.
If the thesis in Unlocking the Emotional Brain is even half-right, it may be one of the most important books that I have read. It claims to offer a neuroscience-grounded, comprehensive model of how effective therapy works. In so doing, it also happens to formulate its theory in terms of belief updating, helping explain how the brain models the world and what kinds of techniques allow us to actually change our minds.
There are at least three ways in which incentives affect behaviour: Consciously motivating agents, unconsciously reinforcing certain behaviors, and selection effects.
Jacob argues that #2 and probably #3 are more important, but much less talked about.
A tour de force, this posts combines a review of Unlocking The Emotional Brain, Kaj Sotala's review of the book, and connections to predictive coding theory.
It's a deep dive into models of how human cognition is driven by emotional learning, and this learning is what drives many beliefs and behaviors. If that's the case, on big question is how people emotionally learn and unlearn things.
Elizabeth summarizes the literature on distributed teams. She provides recommendations for when remote teams are preferable, and gives tips to mitigate the costs of distribution, such as site visits, over-communication, and hiring people suited to remote work.
Divination seems obviously worthless to most modern educated people. But Xunzi, an ancient Chinese philosopher, argued there was value in practices like divination beyond just predicting the future. This post explores how randomized access to different perspectives or principles could be useful for decision-making and self-reflection, even if you don't believe in supernatural forces.
Evolution doesn't optimize for biological systems to be understandable. But, because only a small subset of possible biological designs can robustly certain common goals (i.e. robust recognition of molecules, robust signal-passing, robust fold-change detection, etc) the requirement to work robustly limits evolution to use a handful of understandable structures.
Kaj Sotala gives a step-by-step rationalist argument for why Internal Family Systems therapy might work. He begins by talking about how you might build an AI, only to stumble into the same failure modes that IFS purports to treat. Then, explores how IFS might actually be solving these problems.
Fun fact: biological systems are highly modular, at multiple different scales. This can be quantified and verified statistically. On the other hand, systems designed by genetic algorithms (aka simulated evolution) are decidedly not modular. They're a mess. This can also be verified statistically (as well as just by qualitatively eyeballing them)
What's up with that?
While the scientific method developed in pieces over many centuries and places, Joseph Ben-David argues that in 17th century Europe there was a rapid accumulation of knowledge, restricted to a small area for about 200 years. Ruby explores whether this is true and why it might be, aiming to understand "what causes intellectual progress, generally?"