Measure for Mismeasure
ISTANBUL – I recently used Uber (an online service for ordering a car and driver) and did not have the usual pleasant experience. The driver did not know the area, and, worse, he did not follow his navigator’s instructions, turning left instead of right. When Uber asked me, as usual, to rate the driver, I did not hesitate to give him two out of five. I was not being vindictive; I wanted to save other passengers from an unpleasant experience, and I hoped that maybe feedback would encourage him to improve or find another line of work.
But what does two out of five mean? It obviously means worse than average, which would be three. But, while I would always pick an average driver over a driver with a rating of two, given the choice between a two driver and a blind pick, I might pick the two, because the fear of someone even worse would keep me from taking a risk. This is a well-known phenomenon known as loss aversion: the risk of a one outweighs the hope of a five.
Just last week, I was engaged in ranking proposals for the Knight News Challenge; to simplify things, they had a three-point ranking: three for yes, two for consider, one for reject. The idea was to pick the easy winners, reject the losers, and focus on distinguishing among the maybes. That makes sense in the context of focusing attention where a decision is needed.