Computers are getting smarter and smarter every day. A computer can tell you which exit to take off the highway or what kind of books to read. The one thing computers can’t do (yet) is to solve complex problems. And problem-solving is vital for business AND for building better computers! “When you play a game—if you learn to be good at it—you find what it is you should have been thinking about.” John Conway It is the ability of learning and “finding out” that makes humans much better than computers to learn how to solve complex problems. These days, getting people from diverse backgrounds to help us solve problems is on the rise. Several universities and private organizations around the world are tapping into the knowledge of people like you. Because this usually involves a large number of people (i.e. crowds) It is frequently referred to as crowdsourcing. This is unexpected since usually organizations rely on their internal experts to solve the problems. The key insight here is that non-expert humans can have vital input or to put it differently, they can think outside the box since they are not fixated by experience. However, we still know surprisingly little about the strategies that humans use, to learn how to solve a new problem. If we know the nature of the problem, obviously it is just about getting from A to B in a straight line. But how do people cope with not having (enough) information about where B, i.e. the goal, is? One of the most intuitive metaphors in problem-solving put forward by the pioneer of cognitive science and artificial intelligence, Simon Herbert, illuminates the issue: Simon likened problem-solving with a search through a landscape with a hidden treasure (Simon 1983). You don’t know where the treasure is but each move gives you a bit more information and allows you to make decisions about where to move next. If it is a very easy problem you can easily skip from location to location, quickly getting better and better and making your way towards the final goal (more or less following the A-B straight line, even if you don’t know where B is!). However, for more complex problems, this might not be the optimal strategy, because you will get ambiguous feedback. What do we mean by ambiguous feedback? There’s an old story of three blind men and an elephant. Each of them touches a different part of the elephant and reaches wildly different conclusions: it’s a brush, a pillar or a plow. Before you laugh, think about this: It’s not trivial when you touch something that resembles a brush to figure out that you are dealing with the tip of the tail of an elephant! Still, despite decades of research, we lack a proper understanding of how humans go about solving problems and we could use your help. In the end, by solving the complex Alien CODE, you can help us solve a complex problem!
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