I'll add to this. When A and B are correlated, there are only three possibilities regarding causality (which may work in combination):
1. A causes B
2. B causes A
3. C causes both A and B
If we apply this where A is majoring in computer science and B is high earnings, which answers are true? #2 isn't, obviously. #1 is plausible, since perhaps employers are impressed by a computer science degree. But I think #3 is the most significant, where C is a strong desire to be a software professional. Very few people complete a degree in computer science unless they really want to work with software.
We all know English majors, psych majors, and history majors who became high-earning software engineers. Those are the people who had C (the desire to work with software) but not A (computer science degree). C is the thing that caused them to have B.
Assuming that you have a sufficiently large sample set. :)
The key here, of course, is that we don't know what C is. It could be that high IQ causes high wealth, regardless of degree. High IQ could also be a prerequisite of completing a CS degree, so necessarily the two correlate.
My point is that you know what A is, and you know what B is, but without measurement, you can't know what C is.
The original post has some quotes that say that, e.g.: "A degree in English is just as valuable as a degree in Biology — it teaches you critical thinking!"
Correlation ≠ Causality