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生活真的有如此复杂吗?

发布者: 五毒 | 发布时间: 2022-8-3 00:30| 查看数: 99| 评论数: 0|



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?非常感谢。我是汉娜福莱,一个狠角色。今天,我想问大家一个问题:生活真的很复杂吗?我想用9分钟的时间给你们一个答案,我把答案分成了两部分。答案一:生活真的复杂,答案二:生活并不复杂。或者更准确地说:生活没那么复杂吧?

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,让我试着定义一下什么是“复杂”。我可以给你很多正式的定义,但是用最简单的说法,复杂问题就是爱因斯坦和他的同行都无法解决的。

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. 那么,让我们来想象——希望这个遥控器好用…好了。爱因斯坦正在玩斯诺克游戏。他是个聪明人,所以他知道当他击球时,他可以写出一个公式,精确地计算出红球将要击中的位置,红球的速度以及它将在何处停止。

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. 如果你将这些斯诺克球类推到太阳系。爱因斯坦的理论依然成立。当然,物理上发生了改变,但是如果你想知道地球绕太阳的轨迹,爱因斯坦可以写一个公式告诉你两者在任何时间的位置。

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.现在,加大难度。爱因斯坦可以把月球的引力考虑在内。但是随着你增加星球的数量,比如火星和木星,这个问题对爱因斯坦来说,只用笔纸来解决就太难了。奇怪的是,跟处理少量棘手的行星相比,当你有百万个甚至十数亿个星体时,问题实际上是变得更简单了,于是爱因斯坦的理论依然适用。让我来解释我想要表达什么,把这些对象缩小到分子水平。

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. 如果你想追踪单个空气分子的不稳定轨迹,这是绝对没戏的。但当你有百万个空气分子的集合时,它们开始以能够量化的、可预测的,以及规则的方式来行动。幸好空气的运动十分规律,如若不然,那么飞机就要飞进外太空了。

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. 现在,进一步扩大思考的范畴,全世界,对所有空气分子来说理论是完全一致的。的确,你不能拿一个单独的雨滴说它从哪里来或将到哪里去。但你可以很确定的说明天是否多云。

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,就是这样。在爱因斯坦的年代,这就是科学能达到的高度。我们可以通过少量对象和简单的互动来解决小问题,或者我们可以通过数以百万计的对象,简单的互动去解决大问题。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. 就在爱因斯坦去世的七年后,美国科学家沃伦 · 韦弗提出了这个观点。他说科学方法论从一个极端到另一个极端,留下了巨大的尚未触碰的中间地带。这一中间地带就是复杂科学所在的位置,这就是我说的复杂的意思。不幸的是,几乎你能想到的所有跟人类行为相关的简单问题,都在位于这个中间地带。 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. 爱因斯坦绝对不会知道如何模拟人群的移动。想要对个体进行单独观察,人数未免太多了想把人视为气体分子,这个数字又太少了。同样的,人们很容易厌烦像做决定这样的事情,并且对了解彼此没什么兴趣,这也使得问题变得更加复杂了。

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.爱因斯坦也没办法告诉你,下一次股市崩溃将是什么时候。爱因斯坦无法告诉你如何改善失业率,他甚至无法告诉你下一代苹果手机是一场失利还是翻牌。所以,得到结论一:我们完全搞砸了。我们没有解决的办法,生活太复杂了。

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. 但或许还是有希望的,因为在过去的几年里,我们开始看到一个使用数学来模拟社会体系的新的科学领域的兴起。我不只是在谈论统计学和计算机模拟。我要说的是写出关于我们社会的公式,帮助我们理解正在发生的事情,就像斯诺克球或者天气预报那样。

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.这个学科的出现是因为人们已经开始意识到,我们可以将类比方法应用于人类系统和周边的物理环境。

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. 现在,给你一个例子:欧洲移民这一难以置信的复杂问题。事实证明,当你把所有人放在一起观察时,总的来说,他们表现得就像在遵循万有引力。但不像行星彼此互相吸引,人们被吸引到的地区有更好的工作机会,更高的收入,更高质量的生活以及更低的失业率。

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.而且同样的,人们更有可能选择的机会是离他们所在的位置更近的地方,例如,从伦敦去肯特,要好过伦敦去墨尔本——远处行星的万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. 那么,给大家另外一个例子:2008年,加州大学洛杉矶分校的一个小组正在研究城市中盗窃事件频发的地点分布。关于盗窃的一个方面就是重复受害的概念。如果有一个团伙在某个地区成功地进行了一场盗窃,那么他们会更倾向于返回这个区域继续盗窃。他们摸清了房子的布局,逃跑路线,以及当地的安保状况。而且这将持续发生,直到当地居民和警察加强安保措施,盗窃者们才会转移到其他地方。

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." 这就是盗窃者和安保之间的平衡,这创造了城市的这类动态热点。事实证明,这跟豹子形成豹斑是同样的过程,只不过在豹子的例子中没有盗窃犯和安保,是化学过程创造了这些图案,该过程被称为“形态发生”。

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.事实上我们对豹斑的形态发生已经有了深入的了解。或许我们可以使用这个来试着寻找一些关于盗窃的警告信号,而且或许还能够创造更好的策略来阻止犯罪。在伦敦大学有一个团队,现在正在与西米德兰郡警方合作来解决这个问题。我还可以举出许多类似的例子,但是我想介绍一下我自己研究伦敦暴动的例子。

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. 你们可能已经听说了去年夏天的事件,伦敦和英国见证了过去的20年中最糟糕的持续性暴力抢劫和纵火事件。这是可以理解的,作为一个社会,我们总想尝试去理解到底是什么导致了这些暴动,而且同时,或许应该用更好的战略来武装我们的警察,拿出更好的解决方案来。

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.我不想在这里打击社会学家,所以我绝对不能讲出暴动者的个人动机,但当你把暴动者们放在一起看时,从数学的角度,你可以把它分为三个阶段,并相应地画出类比示意图。

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。他们中没有一个人参与到暴动,但其中一位路过一家正在被洗劫的Foot Locker鞋店,并走进去给自己包了一双新训练鞋。他给其中一个朋友发信息说,“快来加入暴动吧。”于是他的朋友加入了他,然后他们两个人会发信息告诉更多的朋友,加入他们的朋友也会发信息给更多的人,人数像滚雪球一样越来越多。

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.这个过程和病毒在人群中传播的过程是一样的。如果你还记得几年前的禽流感疫情,越多的人被感染,就会有更多的人受到感染,在当局设法采取行动前,病毒传染得就更快。暴动也经历了相同的过程。

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.那么让我们假设有一个暴动者,他已经决定要去参与暴动。下一件他必须做的事就是挑选暴动地点。关于暴动者你需要知道的是——看下这张图。关于暴动者你需要知道的是,他们通常并不打算去离他们住的远的地方,除非那真的是一个非常好的暴动地点。

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. 所以你可以从这张图中看出,绝大多数暴动者参与暴动的地点离家都不到1公里。这个模式也可以在零售消费的消费者模型中看到。比如,我们选择在哪里购物。当然,人们喜欢去本地商店,但你也并不介意去稍远一点的地方,如果那真的是一个很好的购物地点。

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.这个类比事实上已经被一些文章引用过了,一些小报记者把它称之为“暴力购物”,这可能或多或少总结了我们的研究成果。噢,不小心回到刚才的那页了。

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。最后,暴动者到达目的地了,他想要避免被警察逮捕。暴动者会随时躲着警察,但有些地方还是比较安全的。反过来,警察会利用他们有限的资源,试着尽可能地保护城市中更多的地方,在任何可能的地点逮捕暴动者,并产生威慑作用。

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.事实上,结果证明,这两种物种之间的机制,也就是说,暴徒和警察,和掠食者在野外捕食是一样的。所以如果你想象兔子和狐狸,兔子在不惜一切代价地试着躲狐狸,而狐狸在区域里巡逻来试着寻找兔子。实际上,我们非常了解捕食者和猎物的动态。我们也了解消费者支出流。而且关于病毒在人口中如何传播,我们也颇有研究。

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. 那么如果你把这三个类比放在一起来观察和分析,你就能对实际发生的事情 得出一个数学模型,能够复制暴动者他们自己的一般模式。一旦我们得到这个模型,几乎就可以用这个作为基础,并开始讨论城市的哪些区域比其他地区更可疑,以及当问题再次发生时,警察可以采取哪些手段。

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,人们对这类建模都还一无所知。但是我认为,这些类比方法 在追踪我们的社会问题时是非常重要的工具,或许最终还可以改善我们的社会环境。

So, to conclude: life is complex, but perhaps understanding it need not necessarily be that complicated. Thank you.那么总结一下:生活是复杂的,但或许要理解它,没有那么复杂。谢谢。


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