A 2006 study by Matthew Salganik and his co-researchers at Princeton suggests that a huge amount of effort is wasted in many different areas of human endeavor, and the resulting outcomes are far less than optimal — but that there is a simple algorithm that could fix both problems.

In Salganik’s experiment, users of a music-rating site were divided at random into eight artificial “worlds”. All of the users in all eight worlds had access to the same library of songs, which they could download or recommend to their peers, but they could only recommend songs to other users in the same world. Also, each user could view the number of times that a song had been downloaded, but only by other users in the same world.

The goal was to see whether certain songs could become popular in some worlds while languishing in others, despite the fact that all groups consisted of randomly assigned populations that all had equal access to the same songs. The experiment also attempted to measure the “merit” of individual songs by assigning some users to an “independent” group, where they could listen to songs and choose whether to download them, but without seeing the number of times the song had been downloaded by anyone else; the merit of the song was defined as the number of times that users in the independent group decided to download the song after listening to it. Experimenters looked at whether the merit of the song had any effect on the popularity levels it achieved in the eight other “worlds”.

Continue reading ‘An Algorithm For An Automated Meritocracy’