>>> Most professors are unneeded given the size of the problem space. >most subjects are too deep for the professor to be knowledgable about more than just the

>>> Most professors are unneeded given the size of the problem space. >most subjects are too deep for the professor to be knowledgable about more than just their specialty >in many cases, the size of the problem space is much too big for a single group of researchers to have any effect on it. >most studies do not have the manpower available to do a completely formally-correct ideal study I agree that the size of the problem space requires a lot of researchers. This is probably why there's so much attention focused on machine learning and big data, since they seem to have the potential to address the problems you've listed here. Of course, there are many technical and ethical issues to be confronted in developing and deploying them. >If research were _truly_ a priority for humanity, and we really dumped all of our effort into scientific research as a society (i.e. governments and companies both prioritized R&D and gave the scientists enough resources to actually do the jobs properly) It's not, because the greatest problem for humanity is still subsistence, which requires solving a massive resource distribution problem. There are some governments and some companies that do prioritise R&D and provide enough resources, but they are too few and far between. >psychological, sociological, medical, and most other fields of research that aren't mathematical, are considered dubious. >then we might see these fields as "hard science" rather than "soft science". It seems to me that these fields are "soft" in part because the ethical issues surrounding the surveillance that's needed to collect the data to do a formally correct study are quite formidable.