Being a surgeon might require thinking about a few interacting systems, but mostly the number and nature of those systems involved stay the same. Talented programmers without even formal training in CS will eat and digest a dozen brand new systems before breakfast, and model interactions mentally with some degree of fidelity before lunch. And then, any formal training in CS kind of makes general systems just another type of object. This is not the same as how a surgeon is going to look at a heart, or even the body as a whole.
Not that this is the only way to acquire skills in systems thinking. But the other paths might require, IDK, a phd in history/geopolitics, or special studies or extensive work experience in physics or math. And not to rule out other kinds of science or engineering experts as systems thinkers, but a surprisingly large subset of them will specialize and so avoid it. By the numbers.. there are probably just more people in software/IT, therefore more of us to look stupid if/when we get stuff wrong.
Obviously general systems expertise can’t automatically make you an expert on particle physics. But honestly it’s a good piece of background for lots of the wicked problems[1], and the wicked problems are what everyone always wants to talk about.
A part of learning how to model things as systems is understanding your model doesn't include all the components that affect the system - but it also means learning how to quantify those effects, or at least to estimate upper bounds on their sizes. It's knowing which effects average out at scale (like e.g. free will mostly does, and quite quickly), and which effects can't possibly be strong enough to influence outcome and thus can be excluded, and then to keep track of those that could occasionally spike.
Mathematics and systems-related fields downstream of it provide us with plenty of tools to correctly handle and reason about uncertainty, errors, and even "unknown unknowns". Yes, you can (and should) model your own ignorance as part of the system model.
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[0] - In the most blatant example of this, around February 2020, i.e. in the early days of the COVID-19 pandemic going global, you could quite accurately predict the daily infection stats a week or two ahead by just drawing up an exponential function in Excel and lining it up with the already reported numbers. This relationship held pretty well until governments started messing with numbers and then lockdowns started. This was a simple case because at that stage, the exponential component was overwhelmingly stronger than any more nuanced factor - but identifying which parts of a phenomenon dominate and describing their dynamics is precisely the what learning about systems lets you do.
Doctors are actually known for this phenomenon. Flight schools particularly watch out for them because their overconfidence gets them in trouble.
And, though humans everywhere do this, Americans are particularly known for it. There are many compilation videos where Americans are asked their opinion on whether Elbonia needs to be bombed or not, followed by enthusiastic agreement. That's highly abnormal in most other countries, where "I don't know" is seen as an acceptable response.
> Anti-intellectualism has been a constant thread winding its way through our political and cultural life, nurtured by the false notion that democracy means that 'my ignorance is just as good as your knowledge. ― Isaac Asimov
You haven't meet many surgeons have you? When I was working in medical imaging, the technicians all said we (the programmers) were almost as bad as the surgeons.
You wouldn’t see this in other folks, for example, a successful medical surgeon won’t offer much assertion about NVIDIA.
And the general tendency among audience is to assume that expertise can be carried across domains.