Computers are awesome. They crunch numbers at mind-boggling speeds. Had the automotive industry kept pace with the computer industry for the last 40-50 years, the average car would cost $15 and fit in your pocket.

That said, there are limitations. Computer vision and artificial intelligence still have a long way to go. Even if we do get those things sorted out, there are still a large number of important problems that don’t have quick solutions in all likelihood. This is where people step back into the picture.

Luis van Ahn has done a lot of work in the field. Most notably, the Google Image Labeler, where two players work together to label photos with relevant tags. Traditionally, image search engines had to rely on the name of the image, as well as words orthographically near it to guess at the contents. A human can do this much more reliably by simply looking at the image.

So, people are good at some things, and computers are good at others. And so it’s very possible that computing in the near future will be more of a team effort for certain projects. Computers doing the heavy lifting in terms of cataloging, aggregating, recording, crunching, and humans doing the interpretive stuff. Lifehacker had an article recently about a tool called Foldit that turns manipulating virtual proteins into a game. People can do certain really complicated tasks easier than a computer could, and untangling proteins is apparently one of them.

To give you an idea of how many “human clock cycles” are wasted, in 2003, 9 billion hours were spent playing computer solitaire. If you have 50 minutes to yourself and would like to hear a really good lecture, van Ahn gives a great presentation.