The collective intelligence of random small crowds: A partial replication of Kosinski et al. (2012)

• Main Authors: Ans Vercammen, Yan Ji, Mark Burgman
• Format: Article
• Language: English
• Published: Society for Judgment and Decision Making 2019-01-01
• Series: Judgment and Decision Making
• Subjects: crowdsourcing; wisdom of the crowd; intelligence testing; Raven’s Matrices; Mechanical TurkNAKeywords
• Online Access: http://journal.sjdm.org/18/18813/jdm18813.pdf

We examined the trade-off between the cost of response redundancy and the gain in output quality on the popular crowdsourcing platform Mechanical Turk, as a partial replication of Kosinski et al. (2012) who demonstrated a significant improvement in performance by aggregating multiple responses through majority vote. We submitted single items from a validated intelligence test as Human Intelligence Tasks (HITs) and aggregated the responses from “virtual groups” consisting of 1 to 24 workers. While the original study relied on resampling from a relatively small number of responses across a range of experimental conditions, we randomly and independently sampled from a large number of HITs, focusing only on the main effect of group size. We found that – on average – a group of six MTurkers has a collective IQ one standard deviation above the mean for the general population, thus demonstrating a “wisdom of the crowd” effect. The relationship between group size and collective IQ was characterised by diminishing returns, suggesting moderately sized groups provide the best return on investment. We also analysed performance of a smaller subset of workers who had each completed all 60 test items, allowing for a direct comparison between a group’s collective IQ and the individual IQ of its members. This demonstrated that randomly selected groups collectively equalled the performance of the best-performing individual within the group. Our findings support the idea that substantial intellectual capacity can be gained through crowdsourcing, contingent on moderate redundancy built into the task request.