生命的物理，第5集：人类历史如何塑造科学探究

现在，有人第一次听到这个说法，会说：哦，是的，这完全说得通。

Now, hears that for the first time and says, Oh yeah, that makes perfect sense.

我有点喜欢这个理论。

I kind of like that theory.

这简直是胡说八道。

This is crazy nonsense talk.

来自圣塔菲研究所，这里是复杂性研究。

From the Santa Fe Institute, this is Complexity.

我是克里斯·肯佩斯。

I'm Chris Kempes.

我是阿巴·伊莉·菲博。

And I'm Abha Eli Phoboo.

每次我们为这个节目采访嘉宾时，都喜欢先用几个轻松简单的问题来热身。

Every time we interview a guest for this show, we like to get them warmed up with a couple of light, easy questions.

几周前，我问了圣塔菲研究所的总裁大卫·克拉考尔一个我们认为很有趣的问题。

A few weeks ago, I asked David Krakauer, the president of the Santa Fe Institute, a question that we thought was fun.

他不同意。

He didn't agree.

那么，在你的研究过程中，你遇到的最有趣的事实是什么？就是你所有做过研究中的各种事实？

So what's the most interesting fact you've come across in the course of your research, like all kinds of research you've worked on?

我拒绝回答这个问题。

I refuse to answer that question.

你知道，事实太无趣了，对吧？

You know, facts are so uninteresting, right?

我的意思是，事实就像死掉的动物。

I mean, facts are like dead animals.

需要明确的是，大卫并不是说事实不重要。

To be clear, David's not saying that facts are unimportant.

它们只是不能让他早上起床的动力。

They're just not what gets him out of bed in the morning.

对他来说，事实并不是科学研究的全部和终极目标。

To him, they're not the be all, end all of scientific research.

这并不是因为圣塔菲研究所的人不喜欢了解事物。

And it's not because people at SFI don't like knowing stuff.

我们确实喜欢。

We do.

但我认为大卫觉得最有趣的东西，不是我们知道了什么，而是我们如何知道的。

But I think what David finds most interesting isn't what we know, but how we know it.

某些看待世界的方式为何会压倒其他方式，尤其是任何了解科学史的人都知道，我们很多认为是铁板钉钉的真理，最终却发现并非如此。

How certain ways of looking at the world become dominant over others, especially because anyone who knows the history of science knows that there's a lot we think is cold, hard truth until we find out it's not.

一个明显的例子是，在16世纪之前，许多人相信地球是宇宙的中心，所有事物都围绕着我们运转。

An obvious example is that up until the sixteenth century, many people believed that the Earth was the center of the universe and that everything revolved around us.

这是一种完全以人类为中心的视角，但如果缺乏全部信息，任何人都可能得出这样的结论，这也很合理。

Which is a totally human centered way of seeing things, but it makes sense that anyone could come to that conclusion if they didn't have all the information.

我们看到太阳、月亮和星星在天空中移动。

We watch the sun and the moon and the stars move around the sky.

我们感觉不到地球在我们脚下旋转。

We don't feel the earth rotating beneath our feet.

这种现实版本看起来很直观。

This version of reality seems intuitive.

但这是完全错误的。

But it's completely wrong.

确实如此。

It is.

在今天的节目中，我们将探讨人类历史和人类决策如何塑造了我们对科学现实的基本理解以及未来研究的方向。

And in today's episode, we'll look at how our basic understanding of scientific reality and the trajectory of future inquiry is shaped by both human history and human decision making.

首先，我让大卫来解释。

And to start, I'll let David explain.

我们的一位教员道格·欧文向我推荐了一本书，叫《争议的遗产》，这本书讲述了遗传学的历史。

One of our faculty, Doug Owen, suggested a book to me called Disputed Inheritance, and, it's about the history of genetics.

在二十世纪初，关于遗传因果性的本质曾爆发过激烈争论。

In the early twentieth century, there was a raging debate about the nature of genetic causality.

当时有两位人物针锋相对：剑桥的威廉·贝特森和牛津的拉斐尔·韦尔登。

And two figures were at war: William Bateson at Cambridge and Raphael Weldon at Oxford.

巴茨顿拥护孟德尔的定律，认为遗传是离散的原子单位。

And Bateson championed Mendel's laws, discrete atoms of inheritance.

巴茨顿利用孟德尔的遗传学观点论证说

Bateson used Mendel's ideas about genetics to argue that

某种意义上，少数基因就能解释个性、气质、疾病易感性、种族等等。

somehow a small number of genes can explain personality, you know, disposition, susceptibility to disease, race, and so forth.

这显然是错误的。

This is just patently wrong.

另一方面，韦尔登认为遗传确实有作用，但情况更复杂。

Weldon, on the other hand, argued that genetics do play a role, but it's more complicated.

他说，环境也具有强烈的影响。

He said that the environment also has a strong influence.

这是经典的人性与教养之争，巴茨顿和孟德尔站在‘人性’一方，而韦尔登则偏向‘教养’一方，或处于中间立场。

It's the classic nature versus nurture debate, with Bateson and Mendel being on the nature side and Weldon kind of being on the nurture side or somewhere in the middle.

在二十世纪之交，韦尔登正在撰写一本阐述他观点的书。

At the turn of the twentieth century, Weldon was writing a book that outlined his side of the debate.

而韦尔登对遗传学持一种更为复杂的态度。

And Weldon favored a much more complex attitude towards genetics.

但在韦尔登出版他的书之前，他去世了。

But just before Weldon published his book, he died.

因此，贝特森和孟德尔赢了。

And so Bateson and Mendel won.

于是，我们所接受的现实版本就是孟德尔和他的豌豆植物，以及我们在学校科学课上学到的那些庞尼特方格，它们表明基因以非常直接、简单的方式决定结果。

So this is the version of reality we're left with, Mendel and his pea plants, those Punnett squares that many of us learned in school science class, where genes shape the outcomes in very direct, simple ways.

这种对遗传学的理解方式塑造了过去一个世纪的大部分研究。

And this way of thinking about genetics has shaped much of the research done in the last century.

我对这一点很感兴趣，因为从某种意义上说，事实不过是历史的偶然。

I'm sort of interested in that, that facts are just sort of accidents of history in some sense.

那么，我们如何发现知识中的空白呢？

So then, how do we find the gaps in our knowledge?

对戴维而言，这意味着重新思考一些最基本的问题，比如生物体是什么？

For David, this means rethinking some of the most basic questions like what are organisms?

什么是生态系统？

What's an ecosystem?

什么是生命？

What does it mean to be alive?

我们倾向于将自己熟悉的极少数机制投射到整个现实中，并假定它们是普遍适用的。

We tend to project onto all of reality the very small number of mechanisms that we're familiar with and pretend that they're universal.

你知道的吧？

You know?

作为理论家，你可以玩一种反事实游戏，也就是假设这些并不成立会怎样？

And part of what you get to do when you're a theorist is play the counterfactual game, which is what if that were not true?

那会怎样？

What then?

这极其解放人心，也是一种数学上的共情，因为它让你看到那些我们从未遇见过的可能世界。

And it's extraordinarily liberating, and it's a kind of mathematical empathy because it allows you to see worlds that could exist that we've never encountered.

我认为，这些世界通常真正扩展了我们的同理心，因为你不必非得是这样。

And they generally, I think, extend genuinely extend our sympathies because you don't only have to be this way.

存在多种不同的生存方式。

There are lots of different ways of being.

在第一部分中，我们将探讨研究人员如何决定解决哪些问题以及追求何种类型的知识，并分析这些决策如何受到特定社群文化及其历史的影响。

In part one, we'll examine how researchers decide which problems to solve and what types of knowledge to pursue, and we'll look at how some of these decisions can come down to the culture of specific communities and the history that shaped them.

第一部分：哪些问题值得回答？

Part one, which questions are worth answering?

在这个节目中，我们避免将物理学视为传统上那种毫无生机的真空环境。

On this show, we've avoided looking at physics in the lifeless vacuum that it's traditionally viewed in.

相反，我们关注的是物理学的基本构成单元如何影响生物圈等更复杂的事物。

Instead, we've been interested in how the fundamental building blocks of physics can influence more complex things like the biosphere.

而这一交叉领域是一个广阔的未知疆域。

And this intersection is a huge area of uncharted territory.

但圣塔菲研究所的理论物理学家兼兼职教员肖恩·卡罗尔认为，即使在该学科最基础、最传统的部分，仍然存在一些深刻的谜题。

But Sean Carroll, theoretical physicist and fractal faculty at SFI, makes the case that even in the most basic, traditional parts of the discipline, there are still some deep mysteries.

所以，除了复杂性之外，我目前研究的另一个领域是量子力学的基础，你向任何人解释量子力学的问题时，他们都会说：这真的很重要。

So aside from complexity, the other thing that I do research on these days is the foundations of quantum mechanics, and you explain the problems with quantum mechanics to any person, and they're like, this is really important.

这应该是物理学内部一个地位非常高的子领域，对吧？

This should be a very high status sub specialty within physics, right?

我得解释一下，你知道的，如果你去思考这些问题，就会被物理学界排斥。

And I have to explain that, you know, no, you get kicked out of physics if you think about this.

对于非物理学家来说，量子力学是研究那些极其微小的物体的学科，这些物体在不同情况下会表现出波或粒子的特性。

Quantum Mechanics, for those of us who aren't physicists, is the study of extremely small objects that behave like waves or particles depending on the situation.

量子力学作为一种物理理论，其地位很特别，因为据我们所知，它就是自然界运作的方式。

Quantum Mechanics is an interesting position as a physical theory because it is the way nature works as far as we know.

它是我们对物理学基本定律如何运行、也就是驱动这些定律的‘引擎’的最佳理解。

It's our best idea of what the fundamental laws of physics, how they run, you know, the engine that gets them going.

但作为整体，物理学界已经决定，这并不重要，或者不值得投入精力。

But as a collective, the physics community has decided it's not important or perhaps not worth the effort.

但它有着一段奇特的历史。

But it has a weird history.

它最初是零散发展起来的，到20世纪20年代末大致成型，但仍留下了一些悬而未决的问题。

It came about sort of a patchwork, finally seemed to more or less coalesce in the late 1920s, but there were still some lingering questions.

在量子力学中，比如电子，并不是一个具有确定位置和速度的点状粒子。

In quantum mechanics, say the electron, for example, is not a point like particle with a position and a velocity.

我们用一种叫做波函数的东西来描述它，波函数在整个空间中都有取值。

We describe it using something called a wave function that has a value all throughout space.

但当你观测波函数时，你永远看不到它本身。

But then when you observe the wave function, you never see it.

你看到的只是一个点状的粒子。

You see a little point like particle.

于是我们决定一致告诉学生，这是因为当我们不观测时，波函数才是真实存在的。

And we decided to agree to teach our students that that's because the wave function is what's there when we're not looking at it.

但当我们进行测量时，看到的却是一个粒子。

But when we measure it, we see a particle.

现在，任何人第一次听到这个说法都不会说：哦，是的，这完全说得通。

Now, nobody hears that for the first time and says, Oh yeah, that makes perfect sense.

我某种程度上喜欢这个理论。

I kind of like that theory.

这简直是胡说八道，但我们至今还无法提出更好的解释。

This is crazy nonsense talk, but we have not yet been able to do better.

我们确实正是这样向学生传授这一范式的。

And we really do teach our students exactly this paradigm.

有一部分物理学家，从爱因斯坦时代起，就举手表示：这还不够好。

A certain subset of physicists, going back to Einstein, raise their hand and say, you know, that's not good enough.

我们希望更深入地探究，弄清楚究竟发生了什么。

We want to dig a little bit more deeply, figure out what is really going on.

出于种种原因——这些原因你甚至能谈上很久——物理学界最终决定说不。

And for whatever set of reasons, which you could talk about for a long time, the physics community decided to say no.

关于量子力学基础的问题——比如表象之下究竟发生了什么、现实的真实本质是什么——这些并不是我们物理学家感兴趣的方向。

Those questions about what we call the foundations of quantum mechanics, what's really going on beneath the hood, what is the actual stuff of reality and so forth, those are not what we physicists are interested in.

我们问了肖恩，这些原因具体有哪些。

We asked Sean what some of those reasons were.

最善意的解释是，物理学家们根本不知道如何在这一问题上取得进展。

The most charitable reason why is because physicists just don't see how to make progress on this problem.

即使他们说，嗯，这挺有意思的。

Like even if they said, Sure, it's interesting.

那你打算怎么做？

What are you going to do?

你能做什么样的实验？

What is the experiment you can do?

自然界并没有保证，我们对解决某个问题的兴趣程度会与这个问题的可解性成正比。

There's no guarantee in nature that how much we are interested in solving a problem tracks with how solvable the problem is.

这给科学研究提出了一个重大问题。

This poses a big question for scientific inquiry.

最好先摘取低垂的果实吗？

Is it best to grab the low hanging fruit first?

还是说，不顾目的地只摘低垂的果实，是一种错误的优先级排序方式？

Or is grabbing the low hanging fruit, with no regard to its purpose, the wrong way to prioritize?

这是否意味着一些重要的问题因为太难而被忽视了？

Does it mean some important questions get ignored because they are too difficult?

物理学家绝对有一些他们喜欢思考并给予尊重的问题，也有一些他们不感兴趣的。

Physicists absolutely have favorite problems to think about and attach respect to and so forth, and others they don't.

而这并不是因为这些问题仅仅根据其有趣程度来评级。

And it's not because the problems are just rated by their interest level.

物理学家真的很关心在回答这些问题上能取得多少进展。

Physicists really care about how much progress you could make in answering these questions.

结果发现，弄清楚电子的真实行为是非常困难的。

And it turns out trying to figure out what's really going on with an electron is very difficult to do.

另一件困难的事情是复杂系统。

And another thing that's difficult, complex systems.

我认为，在某种程度上，许多人对复杂性也有同样的看法，你知道，没错，确实存在复杂系统。

And I think many of them feel the same way about complexity in some sense that, you know, okay, yes, there are complex systems.

这些系统很难处理。

Those are hard to deal with.

我还是回到我熟悉的系统吧。

I'm going to go back to the systems I know how to deal with.

这种态度也有其可取之处。

And there's something to be said for that attitude.

但正如你我所知，如果你花足够的时间思考，实际上是可以在这类问题上取得进展的。

But I think as you and I know, if you spend enough time thinking about it, you actually can make progress on these.

我甚至可以说，你可以在量子力学的基础问题上取得进展。

Would I would even say you can make progress on the foundations of quantum mechanics.

所以，有时候这仅仅需要一点坚持。

So sometimes it just requires a little persistence.

在圣塔菲研究所，我们不会回到自己熟悉的系统。

At SFI, we don't go back to the systems we know how to deal with.

恰恰相反，我们不断提出新的系统。

If anything, we keep coming up with new ones.

随着我们发现新信息，我们会调整目标，跨越传统学科的界限。

And as we discover new information, we shift the goalposts and move across traditional disciplines.

我们认为这是值得的，但这并不容易，也不一定受欢迎。

We think it's worth it, but it's not easy or necessarily popular.

如今的学术界没有空间容纳年轻人，那些刚起步、刚刚获得博士学位的人，无法以有趣的方式突破学科界限。

We don't have space in academia right now for young people, for people who are just starting out, just getting a PhD and so forth, to step outside of the disciplinary boundaries in interesting ways.

我年纪够大了，所以能这么做，对吧？

I'm old enough that I can do it, right?

我知道，我已经稳定了，可以尝试去做，也有一些年轻人在努力，其中少数人奇迹般地成功了，但说实话，我们根本没给他们创造任何便利。

Know, I'm settled and I can try to do it and there are young people who try and some of them miraculously succeed, but man, we do not make it easy on them.

任何一位希望将来成为教授的年轻人，如果你的导师对你坦诚相待，他们会说：尽量在某个已知的学术领域内行事，因为这就是我们聘用人才的方式。

Anyone out there who's a young person who wants to become a professor someday, if your advisors are being honest with you, they will say, try to play within the boundaries of some known academic discipline because that's how we hire people.

物理系聘用物理学家，生物系聘用生物学家，等等。

Physics departments hire physicists, biology departments hire biologists, and so forth.

我不认为非得如此不可。

I don't think it has to be that way.

大卫，不出所料，表示赞同。

David, unsurprisingly, agrees.

支持这种非常流动、非常自由探索的环境极其罕见。

The environment that supports that kind of inquiry, which is very, very fluid and very freewheeling, is super rare.

大卫又在谈圣塔菲研究所了，这种环境也有其弊端。

David's talking again about SFI here, and there are downsides to this type of environment too.

是的。

Yeah.

在这种环境中，最大的弱点是什么？

So in that environment, what's the biggest weakness?

有几个方面。

There are several.

其中一个是我们都经历过的，那就是缺乏足够的人才规模。

One is something we all experience, which is a lack of critical mass.

所以，当你对某个问题产生兴趣，想向专家请教时，他们却往往不在那里。

So there are oftentimes when you want to ask that question of an expert because you've become interested in the problem, and they're not they're not there.

而且，你知道的，你只能继续前进。

And, and, you know, you just have to move.

你只能去旅行。

You just have to travel.

去一所大学。

Go to a university.

去另一个机构去追求它，或者更好地把他们请过来。

Go to another institute and and pursue it, or bring them in even better.

所以用绿辣椒之类的东西吸引他们。

So lure them in with green chile or something.

这就是我们所做的。

So and that is what we do.

我的意思是，我们不断以新墨西哥北部的美景为承诺吸引人们来到研究所。

I mean, we're constantly luring people to the institute with the promise of the beauty of of Northern New Mexico.

这是一个显而易见的方面。

That's one obvious one.

另一个是与此相关的衍生问题，即重新发现别人早已知晓已久的事情。

Another one is a kinda corollary of that, which is rediscovering things that other people know and have known for a long time.

所以我们在吃午饭时，常常有人会说：‘我刚刚有了一个令人震惊的发现’，另一个人就会说：‘哦，那其实已经有两百年历史了。’

And so we'll often be at lunch and someone will say, I've just made this daunting discovery, and someone will say, well, that's actually 200 years old.

所以，如果你没有足够的核心群体，也就缺乏那种持续的学术监督作用，比如提醒你：‘你或许该读读这篇论文。’

And so if if you don't have critical mass, you don't also have that constant constructive aspect of academic policing, says, you know, you might want to read this paper.

因此，我们面临着一种天真的状态，而这恰恰极具力量，因为它让我们能够进入他人可能忽视或不敢探索的领域，但这也伴随着代价。

So we suffer from a kind of naivete, which is enormously powerful because it allows us to move into territories that others might either ignore or or be fearful of exploring, but it comes at a cost.

对吧？

Right?

我认为，圣塔菲研究所部分解决这个问题的方式，是让大量的人不断进出，以此来让我们保持清醒，这么说吧。

And the way that SFI, I think, has solved that problem to some extent is by bringing so many people through to sort of keep us honest, I guess, is is one way of saying it.

另一件让复杂性研究变得具有挑战性的事情是，它本身就很复杂，极其复杂。

Something else that makes it challenging to do complexity research is that it's complex, really complex.

为了说明这一点，我们先来看看传统物理学。

To illustrate, let's take a look at traditional physics first.

有一个规律：事物最初是简单的。

There's a trajectory where things start off as simple.

但当数量变大时，它们就会变得更加复杂。

Then in bigger numbers, they get more complicated.

但当你变得更大时，它又会变得简单起来。

But then as you get even bigger, it gets simple again.

你知道，如果你只有一个氢原子，那是一个相当简单的系统，你可以求解它。

You know, if you have one hydrogen atom, that's a pretty simple system and you can solve it.

如果你有一个由一千个原子组成的分子，那可能很难理解。

If you have a molecule made of a thousand atoms, that can be really hard to understand.

但一旦你拥有阿伏伽德罗常数数量的原子，它又会变得简单起来。

But once you have Avogadro's number of atoms, it becomes simple again.

现在它变成了流体。

Now it's a fluid.

流体和单个原子一样，行为是可预测的。

Fluids, like individual atoms, behave in predictable ways.

这种从简单到复杂再到简单的模式可能也适用于复杂系统，但远没有那么清晰。

This simple to hard to simple pattern might apply to complex systems, but it's not nearly as clear.

复杂性科学的大部分都处于难以理解的中间阶段，我们正试图找出一些规则，让事情再次变得简单。

Most of complexity science is in the middle category that's hard to understand, and we're trying to tease out some rules that might make things simple again.

但我们不知道，如果真的去应对的话，最终会得到什么结果。

But we don't know what we'll come out with all the way at the top, if we fight anything at all.

这就像在黑暗中摸索。

It's a lot like searching in the dark.

人类和其他生物并不会以固定、可预测的方式行为。

Humans and other organisms don't behave in fixed, predictable ways.

你完全正确，人类尤其复杂，途中很可能存在某些简化规律。

And you're absolutely right that human beings, especially complicated, there could very well be some simplifications along the way.

但人类和原子之间存在巨大差异：原子本身很简单，它们的相互作用也是线性的。

But there's a huge difference between human beings and atoms, which are atoms are themselves simple and their interactions are themselves simple, they're linear.

而人类本身就很复杂，他们的相互作用高度非线性，难以预测。

Whereas human beings are themselves complex and their interactions are highly nonlinear and difficult to predict.

因此，我不认为当我们聚集起十亿人，甚至阿伏伽德罗常数数量的人时，就能像流体动力学那样看到类似的简化现象。

So I don't think there's any guarantee or even a very strong reason to believe that once we get a billion or even Avogadro's number of people together that we will see simplifications like we do in fluid dynamics.

也许会有，我希望如此，我也完全支持去寻找，但我们要明白为什么它在最初有效，而不是盲目地将其推广到更复杂的情形中。

Might be, I hope that there are, I'm all in favor of looking for it, but let's realize why it worked in the first place and not just extrapolate it mindlessly to the more complex situations.

有时，这些高层级的规律确实会从复杂系统中涌现出来，比如我们之前几期讨论过的标度律。

Sometimes these higher level laws do emerge from complex systems, like the scaling laws, which we've talked about in previous episodes.

当这些规律被发现时，那真是令人兴奋的一天。

And it's an exciting day when these things are discovered.

但我们需要指出，当我们谈论标度律或组装理论这类概念时，很容易简单地说：看啊。

But we should point out that when we're talking about something like the scaling laws or assembly theory, it's easy to just say, oh, look.

瞧，这又是一条新的物理定律，因为我们找到了一个将复杂事物简化为简单规则的方法。

Here's a new law of physics because we found a rule that distills something complicated into something simple.

但我们所使用的标签仍然存在争议。

But the labels we use are still up for debate.

如果你发现了新的涌现规律，并不意味着它们就是物理学。

If you discover new emergent laws, it doesn't mean they're physics.

复杂的真实世界会学习物理学，并学会利用物理学。

Complex reality learns physics, and it learns to exploit physics.

因此，当我们建造火箭时，这些技术在生命起源时并不存在。

So when we build rocket ships, those weren't present at the origin of life.

我们已经学会了如何利用引力进行引力弹弓效应。

We've learned how to use gravity to slingshot.

因此，物理定律与复杂系统定律之间存在着非常复杂的关系。

And so there's this really complicated relationship between the laws of physics and the laws of complex system.

有时，由于复杂系统对物理的运用如此高效，我们会误以为物理比实际上更重要。

And sometimes because complex systems use physics so well, we think physics is more important than it really is.

我们这一季讨论的很多内容，比如生物体中的尺度定律、生物多样性中的性状驱动理论，或城市中的创新路径，可能都存在于一个中间地带。

A lot of what we've talked about in the season, like scaling laws in organisms, trait driver theory in biodiversity, or the innovation pathway in cities, might exist, as we said, in a middle ground.

这个中间地带是像动物或人类社会这样的复杂系统与引力等事物相互作用的地方。

This is where complex systems like animals or human societies are interacting with things like gravity.

引力在宇宙的大部分历史中一直存在。

Gravity has existed for most of the history of the universe.

但植物和动物是随着时间演化而来的，那么当我们在这类因演化和时间而存在的系统中发现定律时，我们是否应该称它们为物理定律？

Plants and animals though have evolved over time So when we find laws in these systems, systems that exist because of evolution and time, do we call those laws physics?

而这个中间地带——我觉得特别有趣——在那里，物理被征用、改造、扭曲并加以扩展，以至于你很难分辨你看到的究竟是物理定律，还是新演化出的定律。

And then this middle ground which I find particularly fascinating where, you know, physics is recruited and morphed and distorted and built upon such that you don't quite know whether you're looking at a physical law or a new, evolved law.

这正是复杂性如此有趣的部分原因。

And that's partly what makes complexity so interesting.

我问肖恩，他认为在未来一个世纪里，物理学和复杂性科学会走向何方。

I asked Sean where he thinks we might be headed in the next century with physics and complexity science.

他或许明智地没有直接回答。

He perhaps wisely avoided answering directly.

你知道，之前我提到过，一个原子很简单，一千个原子就很难了，而阿伏伽德罗常数数量的原子又变得简单了。

You know, earlier I mentioned that one atom is simple, a thousand atoms is hard, Avogadro's number of atoms is simple again.

预测未来也是如此。

Same thing for predicting the future.

你问我关于一百年的事。

You asked me about a hundred years.

一年的时间我可以做到。

One year I can do.

一百年很难，但一千万亿年我又可以做到了，对吧？

Hundred years is hard, but a quadrillion years I can do again, right?

一百年很难预测，因为这是人类历史上那种有趣且不可预测的时间尺度。

So a hundred years is hard because that's the interesting, unpredictable kind of timescale that we have to deal with in human history.

一千万亿年对肖恩来说要容易得多，因为物理学家预测，最终熵的增加会导致宇宙的热寂，这意味着现在存在的所有事物都会耗尽能量、变冷并停止活动。

A quadrillion years is much easier for Sean because physicists predict that eventually increasing entropy will lead to the heat death of the universe, which means that everything that exists now will burn out, go cold, and stop.

而这种寒冷将永恒持续。

And that cold will last forever.

令人振奋。

Uplifting.

对吧？

Right?

但我们现在不会聚焦于热寂。

But we're not going to focus on heat death for the moment.

相反，我们将停留在生命这个有趣且不可预测的领域，这正是复杂性研究者所关注的。

Instead, we're going to stay here in this interesting, unpredictable space of life that Complexity researchers are working in.

在第二部分，我们将重新思考如何应对它。

And in part two, we'll rethink how to approach it.

如果我们彻底颠覆对‘活着’这一概念的理解，会发生什么？

What happens if we completely upend our understanding of what it means to be alive?

改变我们的思维框架，能否帮助我们更好地应对这些极其困难的问题？

Can shifting our frame of mind help us discover more with these really difficult questions?

第二部分：颠覆生命的定义 生命存在于宇宙时间线中这个混乱且不可预测的阶段。

Part two: Turning Life Upside Down Life exists in this messy, unpredictable part of the universe's timeline.

正如肖恩所说，人类和其他生物的行为不像原子那样。

Like Sean said, humans and other organisms don't behave like atoms.

但自从人类出现以来，我们一直在试图理解生命究竟是什么。

But as long as humans have been around, we've been trying to make sense of what life is anyway.

在科学界，尽管有人为此建立了整个职业生涯或播客系列，却没有人对生命的定义达成一致。

In the scientific community, no one seems to agree on how to define life, even though people have built entire careers or podcast seasons examining it.

在本季中，我们试图提炼出一些更高层次、更简单的生命特征，比如尺度定律、组装理论和性状驱动理论。

In this season, we've attempted to distill some higher level, simple characteristics of life, like the scaling laws, assembly theory, and trait driver theory.

但即便有了这些理论，目前仍没有达成共识。

But even with these theories, there's no consensus yet.

我们仍在探索肖恩所描述的从简单到复杂再回到简单的轨迹中的混乱中间阶段，试图理解物理学与生命起源之间的关系。

We're still wading through the messy middle part of that simple to hard to simple trajectory that Sean outlined, trying to understand the relationship between physics and the origin of life.

这里有一个大问题。

And there's a big problem here.

生命起源的问题在于，它看起来像一个单一事件。

And the problem with the origin of life is it looks like a singular event.

几年前，大卫和我发表了一篇题为《多重路径通往多重生命》的论文，刊登在《分子进化杂志》上，试图解决这个问题。

A couple of years ago, David and I published a paper titled Multiple Paths to Multiple Life in the Journal of Molecular Evolution, in which we tried to address just this problem.

因此，行星科学是一门比较科学。

So planetary science is a comparative science.

也就是说，存在多个行星，研究人员观察到的样本不止一个。

As in, there are multiple planets, more than one example of what researchers are observing.

而生命起源之所以成问题，是因为它只有一个样本。

And the origin of life has not been because it's a N of one.

因此，我们思考生命的方式，就像如果太阳系中只有地球，我们如何定义行星一样。

And so the way that we think about life is the way we define a planet if there was only the Earth in the solar system.

所以它是基于细胞的，含有DNA和RNA，具备这些代谢途径等等。

So it's cell based, it has DNA and RNA, it has these following metabolic pathways, and so on.

因此，生命的定义是基于有限的证据。

And so life is defined based on a sparsity of evidence.

我认为，克里斯，我们那篇论文试图探讨的是：如何将生命的起源变成一门比较科学？

And I think what we were trying to do, Chris, in that paper was say, how do we make the origin of life a comparative science?

为了找到更多数据、更多生命起源的案例，我们可能需要彻底重新思考什么是生命系统的定义。

In order to find more data, more origins of life, we might need to entirely rethink the definition of what a living system is.

我们得出的结论是一个非常明显的观点：生命系统是一种能够整合并存储过去，从而预测未来的系统或机制。

And what we came up with is the following very obvious statement, that a living system is a system, a mechanism, that is able to integrate and store a past so as to be able to predict a future.

但如果你从这个角度思考，就会开始扩展对个体性的理解，因为也许文化也具备这种特性。

But if you think about it in those terms, then you start to generalize your notion of individuality because maybe a culture has that property.

对吧？

Right?

当然，你在一生中会这样，你的谱系也会，物种也是如此。

And certainly you do during your lifespan, and and your lineage does too, species do.

所以我们只是试图摆脱我们所熟知的现实束缚，对其进行泛化，然后建立了一种数学形式体系，帮助我们在其他地方发现它。

So we were just trying to break out of the shackles of reality as we know it, generalize it, and then we built a kind of a mathematical formalism that would sort of help us find it somewhere else.

我认为，在那篇论文中，我们所做的最激进的事情之一，就是你和我都愿意说：也许我们已经拥有了其他形式的生命起源。

And I think it's really interesting that maybe the most radical thing we do in that paper is that you and I are then willing to say, maybe we already have other origins of life.

你知道，你和我会更愿意说，比如某些计算机程序或语言可能也算作生命起源。

You know, so you and I would be much more willing to say, for example, that certain computer programs or languages might count as an origin of life.

它们依赖于非常奇特的物质生存，但似乎遵循了我们希望生命具备的许多特性。

They live on really weird substances, but they seem like maybe they're obeying many of the things that we want life to have.

这个领域长期以来一直争论病毒是否属于生命。

There's a long debate in this field about whether viruses are alive.

你和我进行了一次非常有趣的对话。

And you and I had a really fun conversation.

我们坐下来深入讨论了这个问题。

We sat down and talked about this.

我们达成一致，都认为光合细菌是活着的，对此我们都感到非常满意。

And we said, well, both of us are really happy with a photosynthetic bacterium being alive.

它只是利用阳光，自己制造所有能量，看起来非常令人印象深刻。

It just uses sunlight, it makes all its own energy, it seems really impressive.

从这个角度来看，病毒的‘生命性’较弱，但也许我们也是如此。

And we said from that perspective, yeah, viruses are less alive, but maybe so are we.

作为人类，我们必须摄取许多其他物质，依赖体内整个微生物生态系统。

In terms of as humans, we have to eat all these other things, We rely on an entire microbial ecosystem inside of us.

我们不能直接从阳光中获取能量。

We don't make energy directly from the sun.

也许我们在其他维度，比如智能方面更具有生命性，但在依赖环境这个维度上，我们和病毒并没有太大区别。

And maybe we're more alive in some other dimension like intelligence, but for the dimension that's just dependence on the environment, us and viruses don't look so different.

我们都需要大量其他生物来维持生存。

We both require a lot of other organisms to make our living.

是的。

Yeah.

这里的问题部分在于术语本身。

And part of the problem here is the terms.

我认为我就是那种有点疯狂的人，你可能也是，认为文化是活的，思想是活的，尤其是计算机病毒是活的。

And I think that I am one of those slightly crazy people, and and you might be too, who thinks that culture is alive or ideas are alive or certainly computer viruses are alive.

它们非常简单，但却是活的。

They're very simple, but they're alive.

在这篇论文中，大卫和我提出了三个类别，用来尝试定义生命。

In this paper, David and I landed on three categories for the way we might try to define life.

第一类定义是直接观察物质本身。

The first level of definitions is just looking at literal material.

它是由DNA、RNA和蛋白质构成的，还是由完全不同的东西构成的？

Is it made from DNA, RNA, and proteins, or something totally different?

第二类关注生命的限制条件，比如规模定律，或不同物种间某些特征的趋同，比如视觉的物理原理。

The second looks at constraints on life, like the scaling laws, or convergence of certain characteristics across different species, like the physics of eyes that see.

我们将这些称为L1（有机物质本身）和L2（塑造进化的限制条件）。

We refer to these as L1, the organic material itself, and L2, the constraints that shape evolution.

但第三层L3则更加抽象，涉及生物在任何世界中——无论是真实还是虚拟——如何优化其功能。

But the third level, L3, is even more abstract and has to do with how organisms optimize functions in any world, real or virtual.

戴夫和我还将L3称为《电子世界争霸战》理论，源自上世纪八十年代的科幻电影。

Dave and I also call l three the Tron theories based on the sci fi movie from the eighties.

因此，我们把一类理论称为《电子世界争霸战》理论，指的是在硅基模拟环境中完全虚拟化的生命体验。

And so one set of theories we call Tron theories, which is a fully virtualized living experience in silico in simulation.

这些概念来源于上世纪八十年代的电影《电子世界争霸战》。

And and these are from the film Tron from the eighties.

在那个世界里，如果你仔细想想，人们放弃了有机化学，转而生活在无机的、基于硅的晶体管构成的物质中，但他们依然是他们自己。

And there, if you think about it, you have people, they've given up their organic chemistry, and they live on inorganic, you know, condensed matter, silicon based transistors, but they're still themselves.

在我们的世界里，这就是人工生命领域，致力于将L3——即那些通用原理——迁移到不同的L1（物质基础）上，并适应不同的L2（约束条件）。

And that's the world, in our world, of artificial life and the effort to move l three, you know, the general principles, across to a different l one and, with different l twos, different constraints.

对吧？

Right?

所以，再次强调，转移生命的原理和身份，但使用完全不同的底层载体。

So, again, move the principle of life, the identities, but with a completely different underlying substrate.

让我们想想，如果我们只关注记忆——即存储和传递信息的能力——这会是什么样子。

Let's think about what this might look like if we just focused on memory, the ability to store information and pass it on.

你知道吗，我认为每个听这个节目的人都会熟悉这种观点，即文化记忆存在于图书馆中。

You know, I think everyone who listens to this show will be familiar with the idea of saying there's a memory of culture in a library.

对吧？

Right?

或者维基百科里有记忆，但蠕虫和狗里也有记忆。

Or there's a memory in Wikipedia, but there's also a memory in a worm and a memory in a dog.

在每种情况下，有些东西保持不变，但很多东西也在变化。

And in each of those cases, something's staying the same, but a lot of things are also changing.

所以，原理是不变的，但物质是可变的。

So the principle's invariant, but the matter is variable.

智能这一概念为我们将生命视为什么增添了另一层含义。

The concept of intelligence adds another layer to what we think of as life.

在科学中，生命是我们所说的下限。

Life is what we would call in science a lower bound.

只要你具备某些必要的条件，你就算是活着的。

As long as you have a certain number of things in place, you're alive.

拥有更多这些并不意味着你更活着。

And you're not more alive by having more of them.

这是一个下限。

It's a lower bound.

对吧？

Right?

所以，只要你能将信息从过去传递到未来，你就活着。

So as long as you can propagate information from the past into the future, you're alive.

你就完成了。

You're done.

但如果你能将更多信息从过去传递到未来，你可能就更智能。

But if you can propagate more information from the past into the future, you could be more intelligent.

因此，生命可能是任何智能系统的下限。

So it could be that life is the lower bound on any intelligent system.

因此，有办法以有原则的方式将这些概念联系起来。

So there are ways of trying to connect these concepts in principled ways.

只是因为这非常困难。

It's just that it's very difficult to do.

还有一个最棘手的例子，那就是我们都会同意其具有智能但可能并不具备生命特征的系统，大型语言模型就是这样的例子。

And there's also the trickiest example, which is a system that we would all agree is intelligent that might not be alive, And that's where things like large language models come in.

我认为说它们不智能是愚蠢的。

I think it would be foolish to say that they're not intelligent.

它们显然具有智能。

They clearly are.

它们不是人类那样的智能，但确实是智能的。

They're not human intelligent, but they're intelligent.

它们显然无法自我复制。

They they just certainly don't replicate.

它们在出现错误时显然也无法自我修复。

They certainly don't repair errors when they occur.

它们似乎缺乏太多的自主性。

They don't seem to have much autonomy.

它们不断地被输入海量数据。

They're fed with huge amounts of data constantly.

它们由人类进行维护。

They're tendered by humans.

因此，在自然界中有一些现象，我不知道如何将智能与生命联系起来，但在某些情况下，我认为我可以。

So there are categories of phenomena in the natural world where I don't know how to connect intelligence to life, but in some cases, I think I do.

所以这是一个非常开放的问题。

And so it's a very open question.

对一些人来说，尤其是那些不属于圣塔菲研究所圈子的人，这听起来可能非常离奇。

To some people, especially for those outside the SFI world, this might seem pretty outlandish.

我们许多人直觉上都清楚‘活着’意味着什么，无论我们是否是研究人员。

Many of us feel we know intuitively what it means to be alive, whether or not we're researchers.

但拓展我们对生命的理解方式，不仅仅是一个有趣的思维练习。

But expanding the way we think about life isn't just a fun thought exercise.

它实际上能为我们提供更多的数据来研究。

It can actually give us more data to work with.

无论大家是否对生命的确切定义达成一致，或许都不如能否从中获得关于生命或类生命系统的全新洞见来得重要。

And whether or not everyone agrees on an exact definition may be less important than the ability to find new insights about life or lifelike systems.

一旦你意识到你可以识别生命——L1物质、L2受约束的结构、L3功能——你就可以寻找这三者中的任意一种或全部，而这些定义都是基于原则层面的。

Once you realize that you can recognize life, L1 matter, L2 constrained, L3 function, You can look for all three or any one of them, and they and these are defined at the level of principles.

事实上，如果我们坦诚相待，这正是我们试图表达的：你总是从原则出发。

And in fact, if we're brutally honest, and that's what we try to say, right, is that you always start with principles.

因此，当你前往另一颗星球时，你会问的问题是：哪种物质支持复制？

So as you go to another planet, the question you will ask is, what matter supports replication?

那么，哪种L1物质支持哪种L3功能？

So what l one supports what l three?

因此，在试图判断一个系统是否具有生命时，我们本质上总是调动这三者。

So we always, in some sense, mobilize all three of these when we try to understand whether a system is living.

只是我们长期以来被对物质演化历史的痴迷所主导，而圣塔菲研究所的方法或许更侧重于原则。

It's just that we've been extraordinarily dominated by an obsession with the evolutionary history of matter, and SFI's approach has perhaps been a bit more principle based.

顺便说一句，这也是我们经常发生激烈争论的领域之一，因为很多人并不喜欢这种观点。

And that's, by the way, one of the areas where we get into big arguments because, you know, a lot of people don't like that.

他们说这太数学化了。

They it's too mathematical.

不过，大家似乎都同意一点：无论你如何定义生命，它都不会永恒存在。

One thing that everyone does seem to agree on, though, is that whatever you think life is, it won't last forever.

这或许正是生命对我们而言如此有意义的原因。

And that might be why it feels so meaningful to us.

无论你认为生命的意义是什么，它都必须与物理学定律以及更广泛的科学原理相容。

Whatever you think the meaning of life is, it had better be compatible with the laws of physics and with science more generally.

这些定律明确告诉我们，我们的生命是有限的。

And those laws are telling us very strongly that our lives are finite.

人类的平均寿命大约是30亿次心跳。

The average human lifespan is about 3,000,000,000 heartbeats.

我强调一下，这只是一个平均值。

I emphasize that's just an average.

你不可能通过从不让心跳加速来延长寿命。

You're not going to live longer by you know never getting your heartbeat up.

好的。

Okay.

但30亿是一个非常有感染力的数字，因为它是一个很大的数字。

But 3,000,000,000 is a very evocative number because it's a large number.

这是很多次心跳，但并不是大得离谱，对吧？

It's a lot of heartbeats, but it's not wildly large, right?

并不是像联邦赤字那种规模的大。

It's not like federal deficit kind of large.

心跳是一种具体的计时单位。

And a heartbeat is a tangible unit of time.

你能感受到心跳的流逝。

You can feel the heartbeats going by.

随着生命不断演化和变化，宇宙中的熵也在增加。

As life continues to evolve and change, the entropy in the universe increases too.

熵。

Entropy.

我讨厌人们把熵的增加视为敌人。

I hate it when people think about increasing entropy as the enemy.

我们试图对抗熵的增加。

We're trying to fight increasing entropy.

不，我们需要熵的增加。

No, we need increasing entropy.

如果熵没有增加，那就意味着你处于热力学平衡状态，而那里没有生命。

If entropy is not increasing, that means you're at thermodynamic equilibrium and there's no life.

没有有趣的东西。

There's no interesting stuff.

没有互动。

There's no interaction.

没有任何复杂或重要的东西。

There's nothing complex or important.

熵的增加是我们前进的动力，但它不会永远持续。

Entropy increasing is the fuel that makes us go and it won't last forever.

在个体层面上，这也不会永远持续。

It won't last forever on the individual level.

即使在宇宙层面上，它也不会永远持续。

It won't last forever even on the universal level.

因此，我们在地球上的渺小、短暂和临时性，我认为是人类如果想让生命有意义，就必须正视的重要事实。

So our smallness, our fleetingness, our temporary nature here on this earth is something that I think is absolutely an important thing for human beings to stand up to if they want to make their lives meaningful.

宇宙的演化轨迹始于简单，变得复杂，然后最终——在遥远的未来——又会回归简单。

The trajectory of the universe starts off simple, gets complex, and then eventually, far, far in the future, it will get simple again.

所有的恒星都会熄灭，对吧？

All the stars will die out, right?

恒星依赖于自由能。

Stars rely on free energy.

它们依赖于宇宙最初处于低熵状态，从而拥有燃料，能够燃烧；而所有这些燃料将在大约10的15次方年后耗尽。

They rely on the universe starting with low entropy so they have fuel and they can burn and all that fuel will eventually be burnt out in about ten to the fifteen years from now.

大多数星系中心都有巨大的黑洞，所有这些恒星将非常缓慢地坠入这些黑洞。

And most galaxies have large black holes in the middle of them and all those stars will very gradually fall into those black holes.