Programmers accusing other fields of not being rigorous is like the pot calling the enamelware kettle black.
This is a field where favored practices in machine learning come and go at a furious pace, often based on the results of a single paper that didn't even attempt to isolate the new idea they're presenting as the primary cause of their result, as opposed to the 10 other variables they mention in the paper and that everyone knows can make a big difference, but that they didn't bother to control for. Other fields might not be uniformly meticulous about isolating confounding variables, but at least there's a common understanding that it's good to try.
This is a field where favored practices in machine learning come and go at a furious pace, often based on the results of a single paper that didn't even attempt to isolate the new idea they're presenting as the primary cause of their result, as opposed to the 10 other variables they mention in the paper and that everyone knows can make a big difference, but that they didn't bother to control for. Other fields might not be uniformly meticulous about isolating confounding variables, but at least there's a common understanding that it's good to try.