I was thinking about research hyperboles. We have already worked on problems that impact “billions” of dollars. Next, papers will claim to solve problems that impact “trillions” of dollars (applications to US govt)?
My own reaction was: well, of course I’m working on trillion dollar problems, and so is Muthu and so are most researchers. Almost all theoretical work in most branches of science is doing so too. If you take a fundamental problem and try to estimate its worth in dollars, any reasonable measure will give you trillions of $’s. (One may certainly doubt that such a monetary quantification exercise is useful or tasteful, but that’s another question.) Now of course, I’m not “solving” any trillion dollar problems, only making small steps, but if even a single paper out of the 100 that I write during my whole career makes even a 0.01% step towards the “solution”, then that will give an average value of a million dollars per paper — certainly much more than society is paying for it.
For the skeptics who worry about the numbers rather than laugh at the whole notion of quantification in $’s, let me justify the trillion dollars, at least for “algorithmic game theory” at large. (It is probably not hard to undergo a similar exercise for many other branches and sub-branches of science , although likely but not all of them.)
World GDP is over 60 Trillion dollars per year and rising fast. Computing the present value of all of future humanity’s GDP requires an assumption on future growth as well as a heroic choice of an an interest rate, but the answer will certainly be in the quadrillions (quadrillion = 1000 trillion). Is it hard to imagine the Internet affecting 10% of that GDP, and algorithmic game theory deserving 1% of the credit for this future Internet? Is it hard to imagine better theoretical understanding of economics making a 10% change in that GDP, and algorithmic game theory contributing 1% of that understanding? I would say that each of these four numbers is actually an under-estimate.