Mental Model: Second Order Thinking
models.substack.com
models.substack.com
"Even if you have cleverly identified a second-order effect in the opposite direction, it doesn't mean it actually outweighs the magnitude of the first-order effect – you still have to check."
In simple systems, first order effects tend to dominate.
In complex systems, higher order effects tend to dominate.
Let me give an analogy of trying to reason about physical properties from first principles. This is another popular exhortation - think from first principles just like Feynman or Fermi. I can think from first principles in one extremely narrow field where I happen to have half a decade of education and 20 years of experience. To reason from first principles like Fermi or Feynman in a broad domain like physics requires a world class mind, a world class education and a world of experience.
Most mental model writing is akin to consuming youtube fitness porn. It looks easy to do, you look cool doing it and the end results are just spectacular. However, like Arnold or David Goggins it requires an inhuman dedication, purpose, ability to withstand pain, bounce back from trauma and just keep sacrificing. Most of the time the only person benefiting is the video creator from the ad-roll.
I appreciate the posts but I now believe these mental models are incredibly hard to do and like most of the self-improvement/growth hacking genre is just good for entertainment and commerce 99.99% of the time.
I am trying very hard to integrate second order thinking into my decision making process.
I don't know how important this is for most line employees. As a code monkey, I rarely have some strong bias besides "Angular is my personal preference over React" which immediately leads to "Well, should we use React anyway because the team knows it better and blah blah."
With that said, I enjoy Mongo, for its specific use cases.
On the face of it, it might seem the answer is yes. Fewer cognitive biases means better decisions that correspond more closely to reality. The thrust is that the more rational we are, the more effective our actions are.
However, in my observation, the type of rationality that "works" isn't always the same as the type that is "logically correct" (they can be identical in some instances, but not in all). Successful organizations, it seems to me, tend to prize "instrumental rationality" over "value rationality" / "epistemic rationality" [1].
Just wondering what folks' thoughts are on that?
Folks like Gerd Gigerenzer advocate the use of heuristics, which while are often biased, actually lead to good outcomes on average -- especially in incomplete information scenarios (which is most scenarios in real life). [2, 3]
It has even been shown that heuristics or crude (or even slightly wrong) simple models can outperform complex rigorous models in complex environments – because they are usually more robust to assumption violations under changing conditions [4,5]. In real life, assumptions are violated to various degrees almost all the time.
[1] https://en.wikipedia.org/wiki/Instrumental_and_value_rationa...
[2] https://www.verywellmind.com/what-is-a-heuristic-2795235
[3] https://en.wikipedia.org/wiki/Heuristics_in_judgment_and_dec...
[4] https://www.johndcook.com/blog/2012/09/17/robustness-of-simp...
[5] https://sloanreview.mit.edu/article/why-forecasts-fail-what-...
[0] https://www.lesswrong.com/posts/RAh4fekdiRhZxb2Kw/the-ultima...
If the goal is recognition of bias, you cultivate social-norms which incentivize critique (both in yourself and others). Notice, however, that this begets perverse incentives. I.e. you can fool yourself, "recognize" a billion biases, then applaud yourself for your diligence. You can also invent new biases that don't actually make much difference.