HUMAN beings like to think of themselves as the animal kingdom's smartest alecks. It may come as a surprise to some, therefore, that Iain Couzin of Princeton University believes they have something to learn from lesser creatures that move about in a large crowd. As he told the AAAS meeting in Washington, DC, groups of animals often make what look like wise decisions, even when most of the members of those groups are ignorant of what is going on.
Coming to that conclusion was not easy. Before lessons can be drawn from critters perched on the lower rungs of the evolutionary ladder, their behaviour must first be understood. One way to do this is to tag them with devices that follow them around—motion-capture sensors, radio transmitters or global-positioning-system detectors that can put a precise figure on their movements.
Unfortunately, it is impossible to tag more than a few individuals in a herd, flock or swarm. Researchers have therefore tended to extrapolate from these few results by using various computer models. Dr Couzin has done quite a bit of this himself. Most recently, he has modelled the behaviour of shoals of fish. He posited that how they swim will depend on each individual's competing tendencies to stick close to the others (and thus move in the same direction as them) while not actually getting too close to any particular other fish. It turns out that by fiddling with these tendencies, a virtual shoal can be made to swirl spontaneously in a circle, just like some real species do.
That is a start. But real shoals do not exist to swim in circles. Their purpose is to help their members eat and avoid being eaten. At any one time, however, only some individuals know about—and can thus react to—food and threats. Dr Couzin therefore wanted to find out how such temporary leaders influence the behaviour of the rest.
He discovered that leadership is extremely efficient. The larger a shoal is, the smaller is the proportion of it that needs to know what is actually going on for it to feed and avoid predation effectively. Indeed, having too many leaders with conflicting opinions results in confusion. At least, that is true in the model. He is now testing it in reality.
Tracking individual fish in a shoal is hard. Fortunately, advances in pattern-recognition software mean it is no longer impossible. Systems designed to follow people are now clever enough not only to track a person in a crowd, but also to tell in which direction his head is turned. Since, from above, the oval shape of a human head is not unlike the oblong body of a fish, this software can, with a little tweaking, follow piscine antics, too.
Dr Couzin has been using a program developed by Colin Twomey, a graduate student at his laboratory, to track individual fish in a tank. The result is not just a model of shoaling fish, but a precise numerical representation of their actual movements and fields of vision. That means it is possible to investigate whether real-life fishy leaders have the same effect on a group as their virtual kin.
Alas, merely observing a shoal does not make it clear which individuals lead and which follow. Instead, Dr Couzin has built a biddable robot three-spined stickleback. A preliminary study of a shoal of ten flesh-and-blood sticklebacks shows that they do indeed mingle with the robot and that they follow its leadership cues as predicted. He is now making a robot predator to see how the shoal reacts to less benign intruders.
If the models are anything to go by, the best outcome for the group—in this case, not being eaten—seems to depend on most members' being blissfully unaware of the world outside the shoal and simply taking their cue from others. This phenomenon, Dr Couzin argues, applies to all manner of organisms, from individual cells in a tissue to (rather worryingly) voters in the democratic process. His team has already begun probing the question of voting patterns. But is ignorance really political bliss? Dr Couzin's models do not yet capture what happens when the leaders themselves turn out to be sharks.