The Netflix optimization challenge exemplifies a situation for which there should be a solution, but which I’ve not seen a good answer. Namely: for-profit but initially ad-hoc cooperation. For instance, let’s just say that I made the case that a Pandora-like “Movie Genome Project” was the key to winning the prize. And let’s say that you are sitting on top of a data-mining algorithm that you think will work great in conjunction with such a database. And let’s say that there are 5 people who, reading this, think “Well, I might not be able to contribute an algorithm, but for a piece of $1M, I’d be willing to ‘genotype’ some movies.”
The problem is: how do we go about working with each other? In the Open Source world, one can prototype a project by throwing it against the wall and seeing if it sticks: if people contribute or show interest, one can make a judgment about continuing or discontinuing the project. This works because all work, whether prototype or production, is given the same (free) value. However, if there’s money at stake, one cannot begin prototyping until “what if we win?” is sorted out. Even more importantly, the payoff percentages seem to necessarily be predetermined even though the relative contributions of all parties to the task won’t be known until after-the-fact.
I wonder if some derivative of a fairness-ensuring “cake cutting” algorithm can be applied to the problem.