Crowdsourcing a solution works best if some don’t help

Sarah Scoles at the New Scientist: “There are those who edit Wikipedia entries for accuracy – and those who use the online encyclopaedia daily without ever contributing. A new mathematical model says that’s probably as it should be: crowdsourcing a problem works best when a certain subset of the population chooses not to participate.

“In most social undertakings, there is a group that actually joins forces and works,” says Zoran Levnajic at the University of Ljubljana, Slovenia. “And there is a group of free-riders that typically benefits from work being done, without contributing much.”

Levnajic and his colleagues simulated this scenario. Digital people in a virtual population each had a randomly assigned tendency to collaborate on a problem or “freeload” – working alone and not sharing their findings. The team ran simulations to see whether there was an optimum crowdsource size for problem-solving.

It turned out there was – and surprisingly, the most effective crowd was not the largest possible. In fact, the simulated society was at its problem-solving best when just half the population worked together.

Smaller crowds contained too few willing collaborators with contrasting but complementary perspectives to effectively solve a problem. But if the researchers ran simulations with larger crowds, the freeloaders it contained naturally “defected” to working alone – knowing that they could benefit from any solutions the crowd reached, while also potentially reaping huge benefits if they could solve the problem without sharing the result (….(More)”