Your ideas about the wisdom of crowds have been shred: Wissenschaftler haben herausgefunden, dass die gezielte, kollektive Aktion großer Gruppen an natürliche Grenzen stößt, desto komplexer die individuellen Teilnehmer dachten. In diesem Fall war eine mittelmäßige Gedächtnisleistung besser für das Ziel der Gruppe, als eine gute Gedächtnisleistung. Ebenso ist eine mittelgroße Gruppe besser für die Erreichung eines kollektiven Ziels, als eine große Gruppe.
Mit anderen Worten: Eine mittelgroße Gruppe von Systemen von nur mittelmäßigen Komplexitäten snychronisiert besser und schneller. Die Implikationen in unseren globalen, hypervernetzten, supersozialen Zeiten voller Superschlaumeier kann sich jeder selbst ausmalen.
Quantamag: Smarter Parts Make Collective Systems Too Stubborn
The researchers observed that when the agents could remember only one or two outcomes, fewer strategies were possible, so more agents responded in the same way. But because the agents’ actions were then too correlated, the collective movement in the model took it along a zigzagging route that involved many more steps than necessary to reach the target. Conversely, when the agents remembered seven or more past outcomes, they became too uncorrelated: They tended to stick with the same strategy for more rounds, treating a short string of recent negative outcomes as an exception rather than a trend. The model became less agile and more “stubborn,” according to Johnson.
The trajectories were most efficient when the length of the agents’ memory was somewhere in the middle: for about five past events. This number grew slightly as the number of agents increased, but no matter how many agents the model used, there was always a sweet spot — an upper limit on how good their memory could get before the system started to perform poorly.
“It’s counterintuitive,” said Pedro Manrique, a postdoctoral associate at the University of Miami and a co-author of the Science Advances paper. “You would think that improving the sophistication level of the parts, in this case the memory, would improve and improve and improve the performance of the organism as a whole.”
Kao sees a striking connection between Johnson’s and Manrique’s findings and his own work on the behavior of crowds. Over the past few years, he and others have found that medium-size groups of animals or humans are optimal for decision-making. That conclusion runs contrary to the standard beliefs about the “wisdom of crowds,” Kao said, “where the larger the group, the better the collective performance.” Success lies in achieving the right balance between coordination and independence among the system’s components.
“It’s like a second wave of this kind of research,” Kao said. “The first wave was naive enthusiasm for these collective systems. Now, it feels like … we’re questioning a lot of the assumptions we made initially and finding more complex behaviors.”