You can certainly dig up more information. For me, and this is just my opinion based on 35 years of software and hardware engineering, recursion is a neat academic idea but in the real world it is useless and dangerous.
I'm seeing stack overflows (not a problem with tail-call optimization) as the biggest problem here. There are equally dangerous problems, though. Buffer overflows are a very real concern, especially in embedded software; but that doesn't mean that people don't ever use pointers. Everything about software has risks. Yes, they probably shouldn't have used recursion there in that car; but honestly, it's just a stack. Enough calls and some state could have been frozen. They should have put mitigations in place to stop the potential for a stack overflow to have actual, detrimental results. Do you refuse to ever make a function call for fear that you might be at the top of the stack somehow? After all, how can you know that you haven't accidentally created a state machine with function calls and are at the peak of it now, and end up causing the same problem. Recursion may have been the final manifestation, but it's certainly not the only place that failed.
I argue against your thought that recursion is useless, as well. It's a natural and intuitive solution for a lot of problems. The very concept of a dynamic programming solution starts with a recurrence relationship. It starts with recursion. Sorting algorithms are intutively recursive in many cases, Quicksort and Mergesort are just two examples.
And, 'dangerous' is an interesting term. I understand you've worked in embedded systems and hardware, and so those things are often critical systems that have to be super secure and completely bug free. Not every system is like that, though.
I want to understand why you believe that recursion is both useless and dangerous. Could you give some broad examples of the dangers of recursion from your years of experience?
Both, the obvious example is the fibinatchi sequence f(x) = f(x-1) + f(x-2). There are lots of efficient ways of coding it but the most obvious O(n^2) approch is n depth and it can't be tail-call optimized.
Granted, you can write much more efficient code that can be tail call optimized, but there complex and less obvious. There are also languages which cache previous results so the native approch becomes O(n) with fairly elegant code that's still depth n.
PS: Anyway, tail call optimization only works when you can rewrite the code as a loop for more complex structures it's less useful.