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Technology Collective behavior Follow my leader
科技 集體行為 跟領導走
A group's “intelligence” depends in part on its members'ignorance
群體“智慧”部分依賴于群體成員的“愚昧”
HUMAN beings like to think of themselves asthe animal kingdom's smartest alecks.
人們總是喜歡將自己看作動物王國中最聰明的。
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，令一些人感到驚訝的是，普林斯頓大學的Iain Couzin相信人們能從更低等的、大群活動的動物中學到東西。
As he told the AAAS meeting in Washington, DC, groups of animals often make whatlook like wise decisions,
正如他在華盛頓AAAS（American Association forthe Advancement of Science，美國科學促進會）召開的會議上所說的，雖然群居動物中的大部分成員對接下來會發生什么一無所知，
even when most of the members of those groups areignorant of what is going on.
但整個群體卻常常做出看起來更明智的決定。
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.
得出這個結論并不容易。因為必須首先理解這些動物的行為，人們才能借鑒，而由于這些動物處于進化階梯的較低位置，（人們并不容易理解）。
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.
要做的這點，首先要用設備為他們打上標簽以便跟蹤——采用運動傳感器、無線電發射裝置和全球定位系統的探測器能精確描述它們活動。
Unfortunately, it is impossible to tag morethan a few individuals in a herd, flock or swarm.
不幸的是，能被標定的個體只是獸群、鳥群或蜂群中的少數。
Researchers have thereforetended to extrapolate from these few results by using various computer models.
研究者們因此將這些少量數據采用各種電腦模型進行推演。
Dr Couzin has done quite a bit of this himself.
Couzin博士已經完成了一部分工作。
Most recently, he has modelledthe behaviour of shoals of fish.
最近，他建立了魚群行為模型。
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.
他推測魚群游動的方式有賴于魚類個體傾向于截住對方，而又不真的靠近對方的競爭方式（因此它們總是同向游動）。
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.
基于這些傾向就歸納出模型，這些模擬的魚群可以自行轉圈巡游，就像真的一樣。
That is a start. But real shoals do not existto swim in circles.
那只是一個開始。不過真實的魚群并不只是轉圈游動。
Their purpose is to help their members eat and avoid beingeaten.
他們的目的是幫助成員覓食，同時防止被獵食。
At any one time, however, only some individuals know about—and can thusreact to—food and threats.
然而，無論什么時候，只有一些個體能對食物和威脅做出反應。
Dr Couzin therefore wanted to find out how suchtemporary leaders influence the behaviour of the rest.
因此，Couzin博士想找出這些臨時領導如何影響其余個體行為。
He discovered that leadership is extremelyefficient.
Couzin博士發現這種領導方式及其有效。
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.
魚群越大，需要知道接下來做什么才能有效覓食和避免危險的“領導”比例就越小。
Indeed, having too many leaders with conflicting opinions resultsin confusion.
的確，領導越多，矛盾觀點造成的混亂就越多。
At least, that is true in the model. He is now testing it inreality.
至少，模型上是這樣。他現在正在真實環境下測試模型。
Tracking individual fish in a shoal is hard.
跟蹤記錄魚群中的個體很困難。
Fortunately, advances in pattern-recognition software mean it is no longerimpossible.
幸運的是，模式識別軟件的進步讓這變成可能。
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.
為跟蹤人類設計的系統已經足夠智能，不僅能跟蹤人群中的某個人，而且能顯示這個人的頭轉向何方。
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，盡管魚類的身體是長條形，與這個軟件可以識別的人類橢圓形頭部不同，從原理上說，只要稍作修改使之適應魚類外形即可。
Robo fish
機器魚
Dr Couzin has been using a program developedby Colin Twomey, a graduate student at his laboratory, to track individual fishin a tank.
Couzin博士一直在使用他實驗室的研究生Colin Twomey開發的程序來記錄水池中魚類個體的行為。
The result is not just a model of shoaling fish, but a precisenumerical representation of their actual movements and fields of vision.
這個成果不僅是魚群的模型，更是魚群真實行動和視野的精確數值反應。
That means it is possible to investigate whether real-life fishy leaders have thesame effect on a group as their virtual kin.
這就意味著深入研究真實魚群中的領導們與他們的“模擬親戚”在魚群中是否有同樣影響變成可能。
Alas, merely observing a shoal does not makeit clear which individuals lead and which follow.
然而，僅僅只觀察一個魚群并不能清楚地區分哪個是領導，哪個是隨從。
Instead, Dr Couzin has builta biddable robot three-spined stickleback.
作為替代，Couzin博士制作了一條能發出命令的機器三棘刺魚。
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.
對一個有十條真實刺魚魚群的初步研究顯示，他們確實接納了那條機器魚，并且接受它的領導指示。
He is now making arobot predator to see how the shoal reacts to less benign intruders.
他現在正在制作一個機器獵食者，用來觀察魚群對兇猛入侵者的反應。
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，那么就可得出對群體來說最好的結果——不會被吃掉——這看起來有賴于大多數成員對魚群外部世界毫無知覺，僅僅只是接受其他魚指示的“傻魚傻福”。
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，這個現象符合所有的組織行為，從組織中的個體單位到民主過程中的選民（似乎更令人頭痛）。
His team has already begun probing thequestion of voting patterns.
他的研究團隊已經開始探索選舉模式的問題。
But is ignorance really political bliss?
然而，愚昧真是政治之福嗎？
DrCouzin's models do not yet capture what happens when the leaders themselvesturn out to be sharks.
Couzin博士的模型還沒有涉及領導們自己變成“鯊魚”會發生什么。
