Using statistical tests, we show that combining all available participants is unnecessary to achieve minimum classification error rate. This error could be significantly reduced upon combining the individual decisions using group aggregation rules. Further, the classification error rates from individual judgement were found to increase with increasing task difficulty. We demonstrate that the weighted average of individual decision confidence/neural decision variables produces significantly better performance than the frequently used majority pooling algorithm. A separate behavioural experiment was performed by different subjects (20 subjects, 11 female) on the same set of images to categorize the tasks according to their difficulty levels. Concurrently the neural activities (EEG signals) were recorded. Our study consisted of a random target detection task in natural scenes, where human subjects (18 subjects, 7 female) detected the presence or absence of a random target as indicated by the cue word displayed prior to stimulus display. A longstanding problem in this regard has been to determine how decisions of individuals can be combined to form intelligent group decisions. These results demonstrate for the first time Wisdom of the Crowd in the realm of motor control, opening the door to further studies of human and also animal behavioural trajectories and their mechanistic underpinnings.ĭecades of research on collective decision making has claimed that aggregated judgment of multiple individuals is more accurate than expert individual judgement. Fourth, while older individuals outperform younger ones, a crowd of young individuals outperforms the average older one. Third, the aggregate trajectory outperforms more than 99% of individual trajectories. Second, this great improvement requires aggregating trajectories from different individuals (rather than trials from the same individual). First, the aggregate trajectory can be up to 5 times more accurate than the individual ones. Our results show the characteristics of the strongest examples of Wisdom of the Crowd. We asked more than 700 school students to trace five patterns shown on a touchscreen and then aggregated their individual trajectories to improve the match with the original pattern. Here we tested this effect in the context of drawing geometrical shapes, which still enacts cognitive processes but mainly involves visuomotor control.
Because of its enormous social potential, this effect has been thoroughly investigated, but predominantly on tasks that involve rational thinking (such as estimating a number). Wisdom of the Crowd is the aggregation of many individual estimates to obtain a better collective one.
0 kommentar(er)
