Monkey First!
Computational Complexity 2018-03-12
The following story is not true nor has anyone claimed its true, but it has a point:
A company gets a contract to do the following: train a monkey to sit on a 10-foot pedestal and recite some passages of Shakespeare. After a week they announce they have made progress! They invite their investors to see what progress they have made! They unveil a curtain and there is... a 10-foot pedestal.
This story was in an article about how Google does moonshots-- that is, high-risk, high-reward, innovative work. The article is here. (How the Atlantic makes money when they have stuff online is a mystery to me. Perhaps they do in a very innovative way.) The point is that its BAD to have tangible results (like the pedestal) that are not getting at the heart of the problem. So Google has various incentives to do the important stuff. Their slogan is MONKEY FIRST.
This also applies to our research. The following sequence of events is common:
1) Prove some scattered results.
2) Pedastal or Monkey? You could write up what you have, polish it, write up some nice LaTeX macros to make the writing of the paper easier OR you could try to find the unifying principle that would be hard, and might not work, but if it works that would be, as the kids say, Jawesome (Jaw-dropping awesome). The sad answer is that which you do might depend on when the next conference deadline is.
More generally there is a tension between safe do-able research(Pedestal) and high-risk, high-reweard research (Monkey). Is our incentive structure set up to encourage high-risk high-reward? The Tenure system is supposed to do it and it DOES in some cases, but not as much as it could since there are other factors (salary, promotion to full prof, grants).
Does the system encourage high-risk high-reward? Should it? Could we do better? What are your experiences? I have no answers (especially to the question of what are your experiences) so I welcome your comments.