A game-theoretic analysis of the ESP game

“Games with a Purpose” are interactive games that users play because they are fun, with the added benefit that the outcome of play is useful work. The ESP game, developed byy von Ahn and Dabbish [2004], is an example of such a game devised to label images on the web. Since labeling images is a hard problem for computer vision algorithms and can be tedious and time-consuming for humans, the ESP game provides humans with incentive to do useful work by being enjoyable to play. We present a simple game-theoretic model of the ESP game and characterize the equilibrium behavior in our model. Our equilibrium analysis supports the fact that users appear to coordinate on low effort words. We provide an alternate model of user preferences, modeling a change that could be induced through a different scoring method, and show that equilibrium behavior in this model coordinates on high-effort words. We also give sufficient conditions for coordinating on high-effort words to be a Bayesian-Nash equilibrium. Our results suggest the possibility of formal incentive design in achieving desirable system-wide outcomes for the purpose of human computation, complementing existing considerations of robustness against cheating and human factors.