I think this here is the most interesting until now.
The first is basically politics/news/current affairs
Second is maths
Dealing with people
I'm wondering why the big prevalence of mathematical modelling tasks over programming if every models ends up as code. Maybe people qualify both as math modelling to avoid ticking the box listing programming together with such intellectually inferior professions as IT?
Actually, there's an ongoing debate in my field whether the code is the model. Journals turn to the policy of requiring the code to be revealed - a problem for guys like I, who build proprietary models (with their numerical implementations). I have to agree with that to some extent, though. I would even venture to say that in some fields, especially ML, the computer architecture becomes an integral part of the model - it's necessary to reproduce the result. As such omni-models grow - allowing to analyse more complex problems in more complex ways - it becomes increasingly harder to embrace all their elements. A simple example: dynamic execution (processor executes instructions in an random order) may affect insignificant digits in conventional modelling, but may change the result in reinforcement learning.
Even my, former physicist's mind starts to wonder whether the old Popperist method (i.e. falsification, which ruled the past century's science) is not obstructing the way of further scientific progress (a problem already encountered in cosmology, which struggles to test the theories of universe(s)). In many fields we are now capable of modelling phenomena at such a level of complexity and detail, that maybe we can no longer assume that the results, in which we are interested, are reproducible and "fundamental" - they are by the analysed problem's nature random and short-lived. Right as I hoped we were already past postmodernism.