Why do computer scientists on the whole work under the assumption that P ≠ NP? Coming from a math background, it seems interesting to me that on the whole computer scientists tend to work under the assumption that $P \neq NP$. While there is no proof either way, generally, unless something can be specifically unproven in both math and science it is taken with a fair amount of strength. I feel that in the years and years people have spent trying to disprove $P = NP$, the fact that no proof has been discovered yet would at least lead some computer scientists to work within the parameters of viewing $P = NP$ as possibly true. However, I often see people working within the framework of it not being true and I was wondering why? It seems more conservative to assume that $P = NP$ in many fields. I've read countless articles about how many computer science and CS-adjacent fields would have to change a lot of their current methodology if $P = NP$ was proven to be true, so why is this not assumed? While it is unlikely to be proven either way any time soon, it just seems somewhat odd to rely so heavily on the a conjecture like that. It almost seems paramount to assuming that Goldbach's conjecture is invalid as there is no proof for it either.
As a rule of thumb, for any unsolved problem people tend to conjecture the statement that starts with a universal quantifier - since if it started with an existential one, then one would expect to have a solution found.
Other than this, this topic has been discussed at several other places, see https://en.wikipedia.org/wiki/P_versus_NP_problem#Reasons_to_believe_P_.E2.89.A0_NP or https://rjlipton.wordpress.com/conventional-wisdom-and-pnp/.

Update: Or the very recent Chapter 3 here: http://www.scottaaronson.com/papers/pnp.pdf