alt Hacker NewsIt's because the models have different purposes in decision making, in ways which decision makers don't often appreciate.
Models are still great at helping us understand the world and are in many ways the best thing we have. The problem is that today we are overly relying on them to make real policy interventions on an ecology (e.g. what is a "healthy" amount of animals to cull or fish) based on an ecosystem, which is just a poor model.
If we could get rid of this idea of "stability" and "equilibrium" in economics and ecology, I would be a happy man.
> Ironically, the experts, the ones building the "wrong" models, tend to be the ones most aware of this
Exactly why I'm here :-)
Maybe the best way to illustrate our point is to use weather models, as it's pretty tangible for regular people.
Weather models are ridiculously advanced running on super computers crunching a massive global network of real time data. But they still aren't anywhere close to perfect.
That being said, just because it rains on your birthday when it was said to be sunny, doesn't mean you delete your weather app, call meteorology pseudoscience, and start a substack of "the forecast was wrong again" blog posts.
People intuitively grasp this foolishness because they constantly interact with weather models. But for things they have almost no contact with, it's easy to write it off on a single "bad forecast"
(I'll also admit the caveat that not every model is as good (or bad) as weather models, another dimension at play to throw a wrench in peoples gears)