Recognition Heuristic

The recognition heuristic is a simple decision rule stating that if a person is choosing between two objects on some criterion and recognizes one but not the other, they should infer that the recognized object has the higher value on that criterion. Gerd Gigerenzer and Daniel Goldstein developed the heuristic as part of what they called an adaptive toolbox of fast and frugal decision-making shortcuts, and tested it with German and American university students comparing the populations of German and American cities. When a participant recognized one city but not the other, the recognition heuristic predicted their choice roughly eighty to ninety percent of the time. A striking further finding was that American students were sometimes more accurate judging the populations of German cities than German students were, and German students more accurate judging American cities than American students were, a pattern the researchers termed the less-is-more effect, since a degree of unfamiliarity that limits recognition to mainly the largest, most prominent places can make the heuristic more, rather than less, reliable.