If you have shown that a bias is small, you might not care about it, but often we don't know how bad a biased method might be, and therefore try to stay with unbiased methods as much as possible. There are lots of ways to create a bias large enough to worry about. With random sampling, many terms in the equation go to zero and simplify the math. No, there are lots of other ways to gather representative samples, and one of the best ones is a grid or systematic sample. That's not true.
Systematic samples have a long history of good results, and are used widely.
You can mess up of course. Random samples would avoid that, but so would a random orientation of the grid. . They sound a little better when written up in a scientific paper. Besides, they are almost never done correctly. Taking a random sample is something that has to be carefully done by someone who understands statistics.