The "overlearning the game" problem
It's related to Goodhart's Law:<p><i>Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.</i><p>This is often the result of attempting to overoptimize a system. You can optimize a race car to a huge degree, because you know <i>exactly</i> what you want it to do.<p>You can't optimize a schooling system, because you <i>don't</i> know exactly what you want it to do. A little noise is a good thing, because the you want a little wiggle room for teachers to sidestep the dictums of education czars, and students to sidestep the dictums of teachers.<p>The Greeks solved this quite a few years ago, with sortition. Under sortition (injecting noise into elections - <a href="http://en.wikipedia.org/wiki/Sortition" rel="nofollow">http://en.wikipedia.org/wiki/Sortition</a>), Bush and Gore would have been forced to pay "paper, scissors, rock" for the presidency. Under the US's more pure democracy, they would have been tempted to make all kind of Faustian bargains with sordid players to nail down the last 0.01% of votes.<p>Randomization means that the last percent is just not worth chasing, so players in a competition won't be tempted to bend the rules for a tiny advantage.<p>The same process could be used for tests. If you allocate places in desirable courses (say medicine) randomly to anyone above a certain score, the top students won't bother drilling as hard just to get the top score.<p>Stocks are the same - quants wouldn't sweat timing as much if their placement in order books was randomized. It would be more efficient to pay attention to fundamental value than momentary fluctuations if they weren't guaranteed to make large profits on the momentary fluctuations. Some would still work on timing, but not as many.<p>Patents are just bad policy badly implemented at the moment, not over-optimized.