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经济学人双语科技新闻在线试听:集体行为 跟领导走

Lily85 于2013-01-06发布 l 已有人浏览
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科技 集体行为 跟领导走 群体“智慧”部分依赖于群体成员的“愚昧”
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Technology Collective behavior Follow my leader
科技 集体行为 跟领导走

A group's “intelligence” depends in part on its members'ignorance
群体“智慧”部分依赖于群体成员的“愚昧”

HUMAN beings like to think of themselves asthe animal kingdom's smartest alecks.
人们总是喜欢将自己看作动物王国中最聪明的。

It may come as a surprise to some,therefore, that Iain Couzin of Princeton University believes they havesomething to learn from lesser creatures that move about in a large crowd.
然而,令一些人感到惊讶的是,普林斯顿大学的Iain Couzin相信人们能从更低等的、大群活动的动物中学到东西。

As he told the AAAS meeting in Washington, DC, groups of animals often make whatlook like wise decisions,
正如他在华盛顿AAAS(American Association forthe Advancement of Science,美国科学促进会)召开的会议上所说的,虽然群居动物中的大部分成员对接下来会发生什么一无所知,

even when most of the members of those groups areignorant of what is going on.
但整个群体却常常做出看起来更明智的决定。

Coming to that conclusion was not easy. Beforelessons can be drawn from critters perched on the lower rungs of theevolutionary ladder, their behaviour must first be understood.
得出这个结论并不容易。因为必须首先理解这些动物的行为,人们才能借鉴,而由于这些动物处于进化阶梯的较低位置,(人们并不容易理解)。

One way to dothis is to tag them with devices that follow them around—motion-capturesensors, radio transmitters or global-positioning-system detectors that can puta precise figure on their movements.
要做的这点,首先要用设备为他们打上标签以便跟踪——采用运动传感器、无线电发射装置和全球定位系统的探测器能精确描述它们活动。

Unfortunately, it is impossible to tag morethan a few individuals in a herd, flock or swarm.
不幸的是,能被标定的个体只是兽群、鸟群或蜂群中的少数。

Researchers have thereforetended to extrapolate from these few results by using various computer models.
研究者们因此将这些少量数据采用各种电脑模型进行推演。

Dr Couzin has done quite a bit of this himself.
Couzin博士已经完成了一部分工作。

Most recently, he has modelledthe behaviour of shoals of fish.
最近,他建立了鱼群行为模型。

He posited that how they swim will depend oneach individual's competing tendencies to stick close to the others (and thusmove in the same direction as them) while not actually getting too close to anyparticular other fish.
他推测鱼群游动的方式有赖于鱼类个体倾向于截住对方,而又不真的靠近对方的竞争方式(因此它们总是同向游动)。

It turns out that by fiddling with these tendencies, avirtual shoal can be made to swirl spontaneously in a circle, just like somereal species do.
基于这些倾向就归纳出模型,这些模拟的鱼群可以自行转圈巡游,就像真的一样。

That is a start. But real shoals do not existto swim in circles.
那只是一个开始。不过真实的鱼群并不只是转圈游动。

Their purpose is to help their members eat and avoid beingeaten.
他们的目的是帮助成员觅食,同时防止被猎食。

At any one time, however, only some individuals know about—and can thusreact to—food and threats.
然而,无论什么时候,只有一些个体能对食物和威胁做出反应。

Dr Couzin therefore wanted to find out how suchtemporary leaders influence the behaviour of the rest.
因此,Couzin博士想找出这些临时领导如何影响其余个体行为。

He discovered that leadership is extremelyefficient.
Couzin博士发现这种领导方式及其有效。

The larger a shoal is, the smaller is the proportion of it thatneeds to know what is actually going on for it to feed and avoid predationeffectively.
鱼群越大,需要知道接下来做什么才能有效觅食和避免危险的“领导”比例就越小。

Indeed, having too many leaders with conflicting opinions resultsin confusion.
的确,领导越多,矛盾观点造成的混乱就越多。

At least, that is true in the model. He is now testing it inreality.
至少,模型上是这样。他现在正在真实环境下测试模型。

Tracking individual fish in a shoal is hard.
跟踪记录鱼群中的个体很困难。

Fortunately, advances in pattern-recognition software mean it is no longerimpossible.
幸运的是,模式识别软件的进步让这变成可能。

Systems designed to follow people are now clever enough not only totrack a person in a crowd, but also to tell in which direction his head isturned.
为跟踪人类设计的系统已经足够智能,不仅能跟踪人群中的某个人,而且能显示这个人的头转向何方。

Since, from above, the oval shape of a human head is not unlike theoblong body of a fish, this software can, with a little tweaking, followpiscine antics, too.
因此,尽管鱼类的身体是长条形,与这个软件可以识别的人类椭圆形头部不同,从原理上说,只要稍作修改使之适应鱼类外形即可。

Robo fish
机器鱼

Dr Couzin has been using a program developedby Colin Twomey, a graduate student at his laboratory, to track individual fishin a tank.
Couzin博士一直在使用他实验室的研究生Colin Twomey开发的程序来记录水池中鱼类个体的行为。

The result is not just a model of shoaling fish, but a precisenumerical representation of their actual movements and fields of vision.
这个成果不仅是鱼群的模型,更是鱼群真实行动和视野的精确数值反应。

That means it is possible to investigate whether real-life fishy leaders have thesame effect on a group as their virtual kin.
这就意味着深入研究真实鱼群中的领导们与他们的“模拟亲戚”在鱼群中是否有同样影响变成可能。

Alas, merely observing a shoal does not makeit clear which individuals lead and which follow.
然而,仅仅只观察一个鱼群并不能清楚地区分哪个是领导,哪个是随从。

Instead, Dr Couzin has builta biddable robot three-spined stickleback.
作为替代,Couzin博士制作了一条能发出命令的机器三棘刺鱼。

A preliminary study of a shoal often flesh-and-blood sticklebacks shows that they do indeed mingle with therobot and that they follow its leadership cues as predicted.
对一个有十条真实刺鱼鱼群的初步研究显示,他们确实接纳了那条机器鱼,并且接受它的领导指示。

He is now making arobot predator to see how the shoal reacts to less benign intruders.
他现在正在制作一个机器猎食者,用来观察鱼群对凶猛入侵者的反应。

If the models are anything to go by, the bestoutcome for the group—in this case, not being eaten—seems to depend on mostmembers' being blissfully unaware of the world outside the shoal and simplytaking their cue from others.
如果模型一切正常,那么就可得出对群体来说最好的结果——不会被吃掉——这看起来有赖于大多数成员对鱼群外部世界毫无知觉,仅仅只是接受其他鱼指示的“傻鱼傻福”。

This phenomenon, Dr Couzin argues, applies to allmanner of organisms, from individual cells in a tissue to (rather worryingly)voters in the democratic process.
Couzin博士指出,这个现象符合所有的组织行为,从组织中的个体单位到民主过程中的选民(似乎更令人头痛)。

His team has already begun probing thequestion of voting patterns.
他的研究团队已经开始探索选举模式的问题。

But is ignorance really political bliss?
然而,愚昧真是政治之福吗?

DrCouzin's models do not yet capture what happens when the leaders themselvesturn out to be sharks.
Couzin博士的模型还没有涉及领导们自己变成“鲨鱼”会发生什么。

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