Actually, you will find that computers can struggle with true randomization.

I know for instance, in programming, using a rand function to get a value actually needs to be seeded differently each time, otherwise you'll get the same number, despite trying to get a unique value

This is because most randomization is meant to only appear random -- really just a variable to a computer, but influenced enough to make it appear to the user as completely unique.

You can think of it like a big spinning wheel at a casino, except moving so fast you can't even read the numbers. You can press a button, and it will stop on a seemingly random number, but in reality, each number being turns "selected" and being "deselected", with the user making the indirect choice.

It's a weak example, but it illustrates how computer randomization can be different than ideal randomization

In this sense, one could argue ideal randomization is simply a descriptor for when the variables of an event occur in a way, maybe too fast, or too small a scale, which causes an individual to not perceive it's causational factors.

Basically saying all events have a distinct, measurable reasons/causes/factors for inception. When our cognition fails to understand the scope of these factors, or we don't have the technology/happenstance to measure them, is only something experienced as random.