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一個算法能預測下一次暴亂的地點嗎？在這篇無障礙的演講中，數學家漢娜·弗萊展示了如何通過與自然現象的類比來分析和預測複雜的社會行為，比如豹斑的模式，或者捕食者和獵物在野外的分布。演講題目：Is life really that complex?Thanks very much. I am Hannah Fry, the badass. And today I'm asking the question: Is life really that complex? Now, I've only got nine minutes to try and provide you with an answer, so what I've done is split this neatly into two parts: part one: yes; and later on, part two: no. Or, to be more accurate: no?非常感謝。我是漢娜福萊，一個狠角色。今天，我想問大家一個問題：生活真的很複雜嗎？我想用9分鐘的時間給你們一個答案，我把答案分成了兩部分。答案一：生活真的複雜，答案二：生活並不複雜。或者更準確地說：生活沒那麼複雜吧？So first of all, let me try and define what I mean by "complex." Now, I could give you a host of formal definitions, but in the simplest terms, any problem in complexity is something that Einstein and his peers can't do.首先，讓我試著定義一下什麼是「複雜」。我可以給你很多正式的定義，但是用最簡單的說法，複雜問題就是愛因斯坦和他的同行都無法解決的。So, let's imagine -- if the clicker works ... there we go. Einstein is playing a game of snooker. He's a clever chap, so he knows that when he hits the cue ball, he could write you an equation and tell you exactly where the red ball is going to hit the sides, how fast it's going and where it's going to end up.那麼，讓我們來想像——希望這個遙控器好用…好了。愛因斯坦正在玩斯諾克遊戲。他是個聰明人，所以他知道當他擊球時，他可以寫出一個公式，精確地計算出紅球將要擊中的位置，紅球的速度以及它將在何處停止。Now, if you scale these snooker balls up to the size of the solar system, Einstein can still help you. Sure, the physics changes, but if you wanted to know about the path of the Earth around the Sun, Einstein could write you an equation telling you where both objects are at any point in time.如果你將這些斯諾克球類推到太陽系。愛因斯坦的理論依然成立。當然，物理上發生了改變，但是如果你想知道地球繞太陽的軌跡，愛因斯坦可以寫一個公式告訴你兩者在任何時間的位置。Now, with a surprising increase in difficulty, Einstein could include the Moon in his calculations. But as you add more and more planets, Mars and Jupiter, say, the problem gets too tough for Einstein to solve with a pen and paper. Now, strangely, if instead of having a handful of planets, you had millions of objects or even billions, the problem actually becomes much simpler, and Einstein is back in the game. Let me explain what I mean by this, by scaling these objects back down to a molecular level.現在，加大難度。愛因斯坦可以把月球的引力考慮在內。但是隨著你增加星球的數量，比如火星和木星，這個問題對愛因斯坦來說，只用筆紙來解決就太難了。奇怪的是，跟處理少量棘手的行星相比，當你有百萬個甚至十數億個星體時，問題實際上是變得更簡單了，於是愛因斯坦的理論依然適用。讓我來解釋我想要表達什麼，把這些對象縮小到分子水平。If you wanted to trace the erratic path of an individual air molecule, you'd have absolutely no hope. But when you have millions of air molecules all together, they start to act in a way which is quantifiable, predictable and well-behaved. And thank goodness air is well-behaved, because if it wasn't, planes would fall out of the sky.如果你想追蹤單個空氣分子的不穩定軌跡，這是絕對沒戲的。但當你有百萬個空氣分子的集合時，它們開始以能夠量化的、可預測的，以及規則的方式來行動。幸好空氣的運動十分規律，如若不然，那麼飛機就要飛進外太空了。Now, on an even bigger scale, across the whole of the world, the idea is exactly the same with all of these air molecules. It's true that you can't take an individual rain droplet and say where it's come from or where it's going to end up. But you can say with pretty good certainty whether it will be cloudy tomorrow.現在，進一步擴大思考的範疇，全世界，對所有空氣分子來說理論是完全一致的。的確，你不能拿一個單獨的雨滴說它從哪裡來或將到哪裡去。但你可以很確定的說明天是否多雲。So that's it. In Einstein's time, this is how far science had got. We could do really small problems with a few objects with simple interactions, or we could do huge problems with millions of objects and simple interactions. But what about everything in the middle?所以，就是這樣。在愛因斯坦的年代，這就是科學能達到的高度。我們可以通過少量對象和簡單的互動來解決小問題，或者我們可以通過數以百萬計的對象，簡單的互動去解決大問題。但如果所有的事物都不大不小呢？Well, just seven years before Einstein's death, an American scientist called Warren Weaver made exactly this point. He said that scientific methodology has gone from one extreme to another, leaving out an untouched great middle region. Now, this middle region is where complexity science lies, and this is what I mean by complex. Now, unfortunately, almost every single problem you can think of to do with human behavior lies in this middle region.就在愛因斯坦去世的七年後，美國科學家沃倫 · 韋弗提出了這個觀點。他說科學方法論從一個極端到另一個極端，留下了巨大的尚未觸碰的中間地帶。這一中間地帶就是複雜科學所在的位置，這就是我說的複雜的意思。不幸的是，幾乎你能想到的所有跟人類行為相關的簡單問題，都在位於這個中間地帶。Einstein's got absolutely no idea how to model the movement of a crowd. There are too many people to look at them all individually and too few to treat them as a gas. Similarly, people are prone to annoying things like decisions and not wanting to walk into each other, which makes the problem all the more complicated.愛因斯坦絕對不會知道如何模擬人群的移動。想要對個體進行單獨觀察，人數未免太多了想把人視為氣體分子，這個數字又太少了。同樣的，人們很容易厭煩像做決定這樣的事情，並且對了解彼此沒什麼興趣，這也使得問題變得更加複雜了。Einstein also couldn't tell you when the next stock market crash is going to be. Einstein couldn't tell you how to improve unemployment. Einstein can't even tell you whether the next iPhone is going to be a hit or a flop. So to conclude part one: we're completely screwed. We've got no tools to deal with this, and life is way too complex.愛因斯坦也沒辦法告訴你，下一次股市崩潰將是什麼時候。愛因斯坦無法告訴你如何改善失業率，他甚至無法告訴你下一代蘋果手機是一場失利還是翻牌。所以，得到結論一：我們完全搞砸了。我們沒有解決的辦法，生活太複雜了。But maybe there's hope, because in the last few years, we've begun to see the beginnings of a new area of science using mathematics to model our social systems. And I'm not just talking here about statistics and computer simulations. I'm talking about writing down equations about our society that will help us understand what's going on in the same way as with the snooker balls or the weather prediction.但或許還是有希望的，因為在過去的幾年裡，我們開始看到一個使用數學來模擬社會體系的新的科學領域的興起。我不只是在談論統計學和計算機模擬。我要說的是寫出關於我們社會的公式，幫助我們理解正在發生的事情，就像斯諾克球或者天氣預報那樣。And this has come about because people have begun to realize that we can use and exploit analogies between our human systems and those of the physical world around us.這個學科的出現是因為人們已經開始意識到，我們可以將類比方法應用於人類系統和周邊的物理環境。Now, to give you an example: the incredibly complex problem of migration across Europe. Actually, as it turns out, when you view all of the people together, collectively, they behave as though they're following the laws of gravity. But instead of planets being attracted to one another, it's people who are attracted to areas with better job opportunities, higher pay, better quality of life and lower unemployment.現在，給你一個例子：歐洲移民這一難以置信的複雜問題。事實證明，當你把所有人放在一起觀察時，總的來說，他們表現得就像在遵循萬有引力。但不像行星彼此互相吸引，人們被吸引到的地區有更好的工作機會，更高的收入，更高質量的生活以及更低的失業率。And in the same way as people are more likely to go for opportunities close to where they live already -- London to Kent, for example, as opposed to London to Melbourne -- the gravitational effect of planets far away is felt much less.而且同樣的，人們更有可能選擇的機會是離他們所在的位置更近的地方，例如，從倫敦去肯特，要好過倫敦去墨爾本——遠處行星的萬有引力效力要小得多。So, to give you another example: in 2008, a group in UCLA were looking into the patterns of burglary hot spots in the city. Now, one thing about burglaries is this idea of repeat victimization. So if you have a group of burglars who manage to successfully rob an area, they'll tend to return to that area and carry on burgling it. So they learn the layout of the houses, the escape routes and the local security measures that are in place. And this will continue to happen until local residents and police ramp up the security, at which point, the burglars will move off elsewhere.那麼，給大家另外一個例子：2008年，加州大學洛杉磯分校的一個小組正在研究城市中盜竊事件頻發的地點分布。關於盜竊的一個方面就是重複受害的概念。如果有一個團夥在某個地區成功地進行了一場盜竊，那麼他們會更傾向於返回這個區域繼續盜竊。他們摸清了房子的布局，逃跑路線，以及當地的安保狀況。而且這將持續發生，直到當地居民和警察加強安保措施，盜竊者們才會轉移到其他地方。And it's that balance between burglars and security which creates these dynamic hot spots of the city. As it turns out, this is exactly the same process as how a leopard gets its spots, except in the leopard example, it's not burglars and security, it's the chemical process that creates these patterns and something called "morphogenesis."這就是盜竊者和安保之間的平衡，這創造了城市的這類動態熱點。事實證明，這跟豹子形成豹斑是同樣的過程，只不過在豹子的例子中沒有盜竊犯和安保，是化學過程創造了這些圖案，該過程被稱為「形態發生」。We actually know an awful lot about the morphogenesis of leopard spots. Maybe we can use this to try and spot some of the warning signs with burglaries and perhaps, also to create better crime strategies to prevent crime. There's a group here at UCL who are working with the West Midlands police right now on this very question. I could give you plenty of examples like this, but I wanted to leave you with one from my own research on the London riots.事實上我們對豹斑的形態發生已經有了深入的了解。或許我們可以使用這個來試著尋找一些關於盜竊的警告信號，而且或許還能夠創造更好的策略來阻止犯罪。在倫敦大學有一個團隊，現在正在與西米德蘭郡警方合作來解決這個問題。我還可以舉出許多類似的例子，但是我想介紹一下我自己研究倫敦暴動的例子。Now, you probably don't need me to tell you about the events of last summer, where London and the UK saw the worst sustained period of violent looting and arson for over twenty years. It's understandable that, as a society, we want to try and understand exactly what caused these riots, but also, perhaps, to equip our police with better strategies to lead to a swifter resolution in the future.你們可能已經聽說了去年夏天的事件，倫敦和英國見證了過去的20年中最糟糕的持續性暴力搶劫和縱火事件。這是可以理解的，作為一個社會，我們總想嘗試去理解到底是什麼導致了這些暴動，而且同時，或許應該用更好的戰略來武裝我們的警察，拿出更好的解決方案來。Now, I don't want to upset the sociologists here, so I absolutely cannot talk about the individual motivations for a rioter, but when you look at the rioters all together, mathematically, you can separate it into a three-stage process and draw analogies accordingly.我不想在這裡打擊社會學家，所以我絕對不能講出暴動者的個人動機，但當你把暴動者們放在一起看時，從數學的角度，你可以把它分為三個階段，並相應地畫出類比示意圖。So, step one: let's say you've got a group of friends. None of them are involved in the riots, but one of them walks past a Foot Locker which is being raided, and goes in and bags himself a new pair of trainers. He texts one of his friends and says, "Come on down to the riots." So his friend joins him, and then the two of them text more of their friends, who join them, and text more of their friends and more and more, and so it continues.第一步：假如你有了一群朋友。他們中沒有一個人參與到暴動，但其中一位路過一家正在被洗劫的Foot Locker鞋店，並走進去給自己包了一雙新訓練鞋。他給其中一個朋友發信息說，「快來加入暴動吧。」於是他的朋友加入了他，然後他們兩個人會發信息告訴更多的朋友，加入他們的朋友也會發信息給更多的人，人數像滾雪球一樣越來越多。This process is identical to the way that a virus spreads through a population. If you think about the bird flu epidemic of a couple of years ago, the more people that were infected, the more people that got infected, and the faster the virus spread before the authorities managed to get a handle on events. And it's exactly the same process here.這個過程和病毒在人群中傳播的過程是一樣的。如果你還記得幾年前的禽流感疫情，越多的人被感染，就會有更多的人受到感染，在當局設法採取行動前，病毒傳染得就更快。暴動也經歷了相同的過程。So let's say you've got a rioter, he's decided he's going to riot. The next thing he has to do is pick a riot site. Now, what you should know about rioters is that, um ... Oops, clicker's gone. There we go. What you should know about rioters is, they're not prepared to travel that far from where they live, unless it's a really juicy riot site.那麼讓我們假設有一個暴動者，他已經決定要去參與暴動。下一件他必須做的事就是挑選暴動地點。關於暴動者你需要知道的是——看下這張圖。關於暴動者你需要知道的是，他們通常並不打算去離他們住的遠的地方，除非那真的是一個非常好的暴動地點。So you can see that here from this graph, with an awful lot of rioters having traveled less than a kilometer to the site that they went to. Now, this pattern is seen in consumer models of retail spending, i.e., where we choose to go shopping. So, of course, people like to go to local shops, but you'd be prepared to go a little bit further if it was a really good retail site.所以你可以從這張圖中看出，絕大多數暴動者參與暴動的地點離家都不到1公裡。這個模式也可以在零售消費的消費者模型中看到。比如，我們選擇在哪裡購物。當然，人們喜歡去本地商店，但你也並不介意去稍遠一點的地方，如果那真的是一個很好的購物地點。And this analogy, actually, was already picked up by some of the papers, with some tabloid press calling the events "Shopping with violence," which probably sums it up in terms of our research. Oh! -- we're going backwards.這個類比事實上已經被一些文章引用過了，一些小報記者把它稱之為「暴力購物」，這可能或多或少總結了我們的研究成果。噢，不小心回到剛才的那頁了。OK, step three. Finally, the rioter is at his site, and he wants to avoid getting caught by the police. The rioters will avoid the police at all times, but there is some safety in numbers. And on the flip side, the police, with their limited resources, are trying to protect as much of the city as possible, arrest rioters wherever possible and to create a deterrent effect.好了，第三步。最後，暴動者到達目的地了，他想要避免被警察逮捕。暴動者會隨時躲著警察，但有些地方還是比較安全的。反過來，警察會利用他們有限的資源，試著儘可能地保護城市中更多的地方，在任何可能的地點逮捕暴動者，並產生威懾作用。And actually, as it turns out, this mechanism between the two species, so to speak, of rioters and police, is identical to predators and prey in the wild. So if you can imagine rabbits and foxes, rabbits are trying to avoid foxes at all costs, while foxes are patrolling the space, trying to look for rabbits. We actually know an awful lot about the dynamics of predators and prey. We also know a lot about consumer spending flows. And we know a lot about how viruses spread through a population.事實上，結果證明，這兩種物種之間的機制，也就是說，暴徒和警察，和掠食者在野外捕食是一樣的。所以如果你想像兔子和狐狸，兔子在不惜一切代價地試著躲狐狸，而狐狸在區域裡巡邏來試著尋找兔子。實際上，我們非常了解捕食者和獵物的動態。我們也了解消費者支出流。而且關於病毒在人口中如何傳播，我們也頗有研究。So if you take these three analogies together and exploit them, you can come up with a mathematical model of what actually happened, that's capable of replicating the general patterns of the riots themselves. Now, once we've got this, we can almost use this as a petri dish and start having conversations about which areas of the city were more susceptible than others and what police tactics could be used if this were ever to happen again in the future.那麼如果你把這三個類比放在一起來觀察和分析，你就能對實際發生的事情 得出一個數學模型，能夠複製暴動者他們自己的一般模式。一旦我們得到這個模型，幾乎就可以用這個作為基礎，並開始討論城市的哪些區域比其他地區更可疑，以及當問題再次發生時，警察可以採取哪些手段。Even twenty years ago, modeling of this sort was completely unheard of. But I think that these analogies are an incredibly important tool in tackling problems with our society, and perhaps, ultimately improving our society overall.就在二十年前，人們對這類建模都還一無所知。但是我認為，這些類比方法 在追蹤我們的社會問題時是非常重要的工具，或許最終還可以改善我們的社會環境。So, to conclude: life is complex, but perhaps understanding it need not necessarily be that complicated. Thank you.那麼總結一下：生活是複雜的，但或許要理解它，沒有那麼複雜。謝謝。版權歸原作者所有，如有侵權請告知我們儘快刪除，謝謝！
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