【文章內(nèi)容簡介】 you do that?If you can, you have good, strong attentional filters. But some people really struggle with that. Some of Carsonamp。39。s undergraduate subjects struggled with that. They had weak filters, they had porous filters let a lot of external information in. And so what that meant is they were constantly being interruptedby the sights and the sounds of the world around them. If there was a television on while they were doing their essays, they couldnamp。39。t screen it out.
　　你能做到嗎?如果你可以的話，你就有很好、很強的注意力過濾能力。但是有些人確實不容易做到。一些卡爾森實驗的畢業(yè)生也或多或少地缺乏這種能力。他們的過濾能力不強，容易把很多關(guān)鍵信息漏掉。但卻會引入很多外部信息。意思就是說他們會不斷地被他們周圍世界中的聲色所干擾。如果當他們寫作的時候旁邊有一臺開著的電視， 他們排除不了電視的干擾。
　　Now, you would think that that was a disadvantage ... but no. When Carson looked at what these students had achieved, the ones with the weak filters were vastly more likely to have some real creative milestone in their lives, to have published their first novel, to have released their first distractions were actually grists to their creative mill. They were able to think outside the box because their box was full of holes.
　　現(xiàn)在，你可能會覺得這是個缺點。 但并不是。當卡爾森觀察這些學生的表現(xiàn)時，那些過濾能力較弱的學生極有可能在他們的一生中建立真正的創(chuàng)造性的里程碑，更可能出版他們的第一部小說，或者發(fā)行第一張唱片。這些外部的干擾實際上激發(fā)了他們的創(chuàng)意機能。他們可以跳出固有的思維模式，因為他們的思維模式中全是”。小孔”。
　　Letamp。39。s talk about plexity science. So how do you solve a really plex the worldamp。39。s full of plicated problems how do you solve a really plicated problem?
　　讓我們聊一聊復(fù)雜性科學。那么你們是怎么解決一個真正復(fù)雜的。這個世界充滿了復(fù)雜的問題。你們是怎么解決一個 確實復(fù)雜的問題的呢?
　　For example, you try to make a jet engine. There are lots and lots of different variables, the operating temperature, the materials, all the different dimensions, the shape. You canamp。39。t solve that kind of problem all in one go, itamp。39。s too hard. So what do you do? Well, one thing you can do is try to solve it stepbystep. So you have some kind of prototype and you tweak it, you test it, you improve it. You tweak it, you test it, you improve it.
　　比如，你試著去制造一臺噴氣式發(fā)動機。這工作存在著很多不同的可變因素，工作溫度、材料、所有不同的維度、形狀。你不能一次性解決全部這些問題，那太難了。那你會怎么做呢?你所能做的就是試著一步一步地解決。你做出了幾種原型出來，然后你會做出一些改變，做一下測試之后再改進。再做出一些改變，做一下測試之后再改進。
　　Now, this idea of marginal gains will eventually get you a good jet engine. And itamp。39。s been quite widely implemented in the world. So youamp。39。ll hear about it, for example, in high performance cycling, web designers will talk about trying to optimize their web pages, theyamp。39。re looking for these stepbystep gains.
　　這種邊際增益的理念最終可以讓你做出一個很好的噴氣式發(fā)動機。這種方法在全世界 都廣泛應(yīng)用。你可能會聽說，比如在高性能循環(huán)領(lǐng)域，網(wǎng)頁設(shè)計師會討論試圖優(yōu)化他們的網(wǎng)站，他們會尋找這些逐步收益。
　　Thatamp。39。s a good way to solve a plicated problem. But you know what would make it a better way? A dash of mess. You add randomness, early on in the process, you make crazy moves, you try stupid things that shouldnamp。39。t work, and that will tend to make the problemsolving work better. And the reason for that is the trouble with the stepbystep process, the marginal gains, is they can walk you gradually down a dead end. And if you start with the randomness, that bees less likely, and your problemsolving bees more robust.
　　這是一個解決復(fù)雜困難問題的好方法。但你知道更好的方法是什么嗎?針對一系列的麻煩。你可以隨意一點，在工作的初期階段，你可以做一些瘋狂的事，你可以試著做一些并不管用的傻事情，而這可能會使解決問題的效果更好。原因就是一步一步地解決問題，所謂的邊際增益，會逐漸帶你走進死胡同。但如果你一開始就隨意一些，那結(jié)果就會不太一樣了，你解決問題會變得更加高效。
　　Letamp。39。s talk about social psychology. So the psychologist Katherine Phillips, with some colleagues,recently gave murder mystery problems to some students, and these students were collected in groups of four and they were given dossiers with information about a crime alibis and evidence, witness statements and three suspects.
　　我們來談一談社會心理學。心理學家凱瑟琳。菲利普斯和幾個同事最近把神秘謀殺案 交給了一些學生解決，這些學生編為四人