Human Computation
A few days ago I attended a talk by Luis von Ahn from CMU. Luis von Ahn is one of the creators of the ESP Game and Peekaboom, both interactive, multiplayer online games that harness human computing power while also being entertaining. These games get people to help label images, generating data that will ultimately be used to make better image search engines and better computer vision image analysis and segmentation algorithms. Basically, Amazon Mechanical Turk got it wrong: fun is a better motivation than money.
Luis von Ahn opened his talk by saying that people spend many millions of human hours on solitaire each year, and that it would be useful if even a small fraction of that time could be harnessed to get people to play games that are also useful. If this is his goal, he has succeeded — some people spend over 40 hours a week on the ESP Game, which has been very successful.
Luis also presented a general approach for turning computationally hard pattern recognition problems into two player games and suggested that many problems can be solved in this way. He is currently thinking about such things as language translation and common-sense knowledge collection.
While it is cool that the ESP Game, if adopted by a major gaming site like Yahoo! Games, could label most of the web’s images in just a few months, the most exciting thing for me is the wealth of training data that this would generate for researchers to make better computer vision algorithms. This would also be true for things like language translation and common-sense knowledge collection — these would empower new algorithms.
Luis ended by pointing out that The Matrix got it all wrong: we’re useless as batteries, but we make great pattern recognition subroutines. That’s why the computers will need to keep us around, at least for the time being. They keep us entertained, and we compute for them. Oddly enough.