How AI can bring on a second Industrial Revolution | Kevin Kelly

Translator: Leslie Gauthier Reviewer: Camille Martínez

翻译人员: Jiamin Zhao 校对人员: Hong Li

I'm going to talk a little bit about where technology's going.

我打算谈一谈技术的发展趋势。

And often technology comes to us,

当（新的）技术到来时，

we're surprised by what it brings.

常常会令我们感到惊讶。

But there's actually a large aspect of technology

但事实上，技术在很大程度上

that's much more predictable,

是能够被预见的。

and that's because technological systems of all sorts have leanings,

这是因为所有的技术 都有某种倾向性，

they have urgencies,

有某种冲动，

they have tendencies.

有某种趋势。

And those tendencies are derived from the very nature of the physics,

这些趋势是由电线、开关、以及电子的

chemistry of wires and switches and electrons,

物理和化学本质所决定的，

and they will make reoccurring patterns again and again.

并且呈现出不断重复的模式。

And so those patterns produce these tendencies, these leanings.

或者说，这些模式形成了 某种趋势、某种倾向。

You can almost think of it as sort of like gravity.

你可以把它看成类似于重力的东西。

Imagine raindrops falling into a valley.

想象雨点汇入山谷：

The actual path of a raindrop as it goes down the valley

一滴雨点流入山谷的实际路径

is unpredictable.

是无法预测的。

We cannot see where it's going,

我们并不知道它的具体走向，

but the general direction is very inevitable:

但大方向是很显然的：

it's downward.

它往下流。

And so these baked-in tendencies and urgencies

因此，这些内在趋势和冲动，

in technological systems

深深扎根于技术系统中，

give us a sense of where things are going at the large form.

使我们能够感知它们的大体方向。

So in a large sense,

具体点说，

I would say that telephones were inevitable,

电话是必然的，

but the iPhone was not.

但 iPhone 不是；

The Internet was inevitable,

因特网是必然的，

but Twitter was not.

但推特不是。

So we have many ongoing tendencies right now,

同样道理， 当下有许多正在发生的趋势，

and I think one of the chief among them

而我认为其中最重要的一个

is this tendency to make things smarter and smarter.

是让物体变得越来越聪明。

I call it cognifying -- cognification --

我称之为“知化”，

also known as artificial intelligence, or AI.

也就是人们常说的 人工智能，或者 AI。

And I think that's going to be one of the most influential developments

我认为在未来二十年中，

and trends and directions and drives in our society in the next 20 years.

这将是社会中最具影响力的 发展趋势和驱动力。

当然，它已经发生了。

So, of course, it's already here.

We already have AI,

我们已经有了 AI，

and often it works in the background,

它们通常都隐身在后台工作，

in the back offices of hospitals,

在医院里，

where it's used to diagnose X-rays better than a human doctor.

AI 分析 X 光片的水准 比人类医生还要棒。

It's in legal offices,

在律所里，

where it's used to go through legal evidence

AI 核查证物的本事

better than a human paralawyer.

比人类助理律师还要强。

It's used to fly the plane that you came here with.

我们乘坐的飞机是由 AI 在驾驶。

Human pilots only flew it seven to eight minutes,

人类驾驶员只飞个七、八分钟而已；

the rest of the time the AI was driving.

其他时间都是 AI 在操控。

And of course, in Netflix and Amazon,

当然，在 Netflix 和亚马逊网站，

it's in the background, making those recommendations.

是AI在后台进行推荐。

这些都是我们已经实现的。

That's what we have today.

And we have an example, of course, in a more front-facing aspect of it,

我们也有一些更前沿的例子，

with the win of the AlphaGo, who beat the world's greatest Go champion.

比如“阿尔法狗”战胜了 人类最强的围棋世界冠军。

But it's more than that.

但还不止于此。

If you play a video game, you're playing against an AI.

我们打电玩时，对手往往是 AI。

不过最近，谷歌教会了他们的 AI

But recently, Google taught their AI

to actually learn how to play video games.

自己学习如何打电子游戏。

Again, teaching video games was already done,

教（AI）打游戏 已经不是什么新鲜事了，

but learning how to play a video game is another step.

但（AI）自己学习 打游戏则是另一个境界。

That's artificial smartness.

这就是人工智慧。

What we're doing is taking this artificial smartness

我们正在以此为起点，

and we're making it smarter and smarter.

让它变得越来越聪明。

There are three aspects to this general trend

在这个大趋势中，

我认为有三点尚未被充分认识；

that I think are underappreciated;

I think we would understand AI a lot better

如果我们能理解这三点，

if we understood these three things.

就能更好的理解 AI，

I think these things also would help us embrace AI,

并更加全身心的拥抱 AI。

because it's only by embracing it that we actually can steer it.

只有拥抱 AI，才能控制AI。

We can actually steer the specifics by embracing the larger trend.

我们可以通过拥抱 大趋势来控制细节。

So let me talk about those three different aspects.

所以，请允许我谈谈这三点。

The first one is: our own intelligence has a very poor understanding

第一点，我们自己尚未很好的理解

of what intelligence is.

什么是智能。

We tend to think of intelligence as a single dimension,

我们通常认为智能是单维度的，

that it's kind of like a note that gets louder and louder.

就像一个越来越响的音符。

It starts like with IQ measurement.

我们用智商来衡量它。

It starts with maybe a simple low IQ in a rat or mouse,

老鼠的智商较低，

and maybe there's more in a chimpanzee,

猩猩的智商较高，

and then maybe there's more in a stupid person,

接下来是比较笨的人，

然后是像我一样的普通人，

and then maybe an average person like myself,

再往上是天才。

and then maybe a genius.

And this single IQ intelligence is getting greater and greater.

智商越高，智能就越高。

That's completely wrong.

这种看法是完全错误的。

That's not what intelligence is -- not what human intelligence is, anyway.

这根本就不是智能， 人类智能也并非如此。

It's much more like a symphony of different notes,

智能更像由不同音符 组成的交响乐，

and each of these notes is played on a different instrument of cognition.

每个音符由不同的认知乐器来奏响。

There are many types of intelligences in our own minds.

人类的心智包含了多种智能。

We have deductive reasoning,

我们可以进行演绎推理，

we have emotional intelligence,

我们具备情绪智力，

we have spatial intelligence;

我们有空间智能。

we have maybe 100 different types that are all grouped together,

我们可能有一百种 不同的智能集合在一起，

and they vary in different strengths with different people.

它们在不同人的身上也 体现得强弱不一。

And of course, if we go to animals, they also have another basket --

而动物们则可能是另一套体系——

another symphony of different kinds of intelligences,

由其他智能组成的另一首交响乐，

and sometimes those same instruments are the same that we have.

当然，有些乐器与人类是相同的。

They can think in the same way, but they may have a different arrangement,

可能思考的方式相同但侧重点不同，

某些方面可能还强于人类，

and maybe they're higher in some cases than humans,

像松鼠的长期记忆就很了不得，

like long-term memory in a squirrel is actually phenomenal,

so it can remember where it buried its nuts.

能清楚记得坚果的埋藏之所。

But in other cases they may be lower.

但在另外一些方面可能不如人类。

When we go to make machines,

当我们制造机器时，

we're going to engineer them in the same way,

也会用同样的方式来设计它们，

它们在某些方面会比我们聪明得多，

where we'll make some of those types of smartness much greater than ours,

and many of them won't be anywhere near ours,

而在其他方面则远远不如我们，

because they're not needed.

因为根本没必要。

So we're going to take these things,

我们会用这些东西，

these artificial clusters,

这些人造的功能组合，

and we'll be adding more varieties of artificial cognition to our AIs.

为我们的 AI 添加 各种各样的人工认知。

We're going to make them very, very specific.

我们会让它们（的功能）非常具体。

So your calculator is smarter than you are in arithmetic already;

比方说，计算器在数学运算上 要比我们聪明得多；

your GPS is smarter than you are in spatial navigation;

GPS 的空间导航能力远胜过我们；

Google, Bing, are smarter than you are in long-term memory.

谷歌、必应在长期记忆上完胜我们。

And we're going to take, again, these kinds of different types of thinking

然后我们再把这些不同类型的智能

and we'll put them into, like, a car.

塞到……比如说汽车里， 实现自动行驶。

The reason why we want to put them in a car so the car drives,

我们之所以这么做， 正是因为它的驾驶方式

is because it's not driving like a human.

跟我们不一样。

It's not thinking like us.

它不像我们那样思考。

That's the whole feature of it.

这恰恰是它的特点。

It's not being distracted,

它不会分心，

it's not worrying about whether it left the stove on,

不会担心是否忘记了关炉子，

or whether it should have majored in finance.

不会纠结要不要选金融专业。

它只知道开车。

It's just driving.

(Laughter)

（笑声）

Just driving, OK?

它会专心开车，对吧？

And we actually might even come to advertise these

我们甚至可以把这个做为卖点，

as "consciousness-free."

叫做“无意识”。

They're without consciousness,

它们没有意识，

they're not concerned about those things,

不会东想西想，

they're not distracted.

不会分心。

So in general, what we're trying to do

所以，我们应该尽我们所能

is make as many different types of thinking as we can.

制造各种各样的思考（机器）。

We're going to populate the space

我们应该去尝试

of all the different possible types, or species, of thinking.

所有可能的思考方式。

And there actually may be some problems

在商业和科学上，

that are so difficult in business and science

我们会遇到一些难题，

that our own type of human thinking may not be able to solve them alone.

单凭人类自身的思考无法解决。

We may need a two-step program,

我们可能需要分两步走，

which is to invent new kinds of thinking

先发明出新的思考方式，

that we can work alongside of to solve these really large problems,

再与它们一起解决这些真正的难题，

say, like dark energy or quantum gravity.

比如暗能量和量子引力。

What we're doing is making alien intelligences.

我们实际上是在创造异形智能。

You might even think of this as, sort of, artificial aliens

某种意义上，甚至可以将它们看作

人造异形。

in some senses.

And they're going to help us think different,

它们将帮助我们用不同的方式思考，

because thinking different is the engine of creation

而换一种思考方式是创造的源泉，

and wealth and new economy.

是财富和新经济的引擎。

The second aspect of this is that we are going to use AI

第二点是，我们将用 AI

to basically make a second Industrial Revolution.

推动第二次工业革命。

The first Industrial Revolution was based on the fact

在第一次工业革命中，

that we invented something I would call artificial power.

人类发明了我称之为 “人造能源”的东西。

Previous to that,

在此之前，

during the Agricultural Revolution,

在农业革命时期，

everything that was made had to be made with human muscle

制造业靠人力驱动，

or animal power.

或者靠畜力。

That was the only way to get anything done.

除此之外别无他法。

The great innovation during the Industrial Revolution was,

工业革命时期的伟大发明就是

we harnessed steam power, fossil fuels,

人们利用化石燃料和蒸汽

to make this artificial power that we could use

所产生的“人造能源”来做

to do anything we wanted to do.

我们想做的任何事情。

So today when you drive down the highway,

今天，当我们开车行驶在高速上，

you are, with a flick of the switch, commanding 250 horses --

只需轻轻拨弄开关， 就能驾驭 250 匹马——

250 horsepower --

或者说，250 匹马的马力——

which we can use to build skyscrapers, to build cities, to build roads,

我们可以建造高楼大厦， 修建道路，建设城市，

to make factories that would churn out lines of chairs or refrigerators

开办工厂，源源不断地 生产桌椅或冰箱，

way beyond our own power.

这些都远远超出了人力所为。

And that artificial power can also be distributed on wires on a grid

这种“人造能源” 还可以通过电网和电线

to every home, factory, farmstead,

输送到家庭、工厂和农庄，

and anybody could buy that artificial power,

任何人都可以 购买这种“人造能源”，

just by plugging something in.

只需插上插头就可以使用。

So this was a source of innovation as well,

它也带来了很多创新，

because a farmer could take a manual hand pump,

农民可以为手动泵通上电，

and they could add this artificial power, this electricity,

加上这种“人造能源”，

and he'd have an electric pump.

就变成了电泵。

And you multiply that by thousands or tens of thousands of times,

类似的改造成千上万，

and that formula was what brought us the Industrial Revolution.

这个（人力器械+人造能源的） 公式造就了工业革命。

All the things that we see, all this progress that we now enjoy,

今天我们看到的所有事物， 享受的所有服务，

has come from the fact that we've done that.

几乎都来源于此。

We're going to do the same thing now with AI.

现在我们要用 AI 做同样的事情。

We're going to distribute that on a grid,

我们用网路传输 AI，

and now you can take that electric pump.

把 AI 加载到

You can add some artificial intelligence,

诸如电泵之类的东西上，

and now you have a smart pump.

就得到了聪明的电泵。

And that, multiplied by a million times,

类似的改造做上几百万次，

is going to be this second Industrial Revolution.

就会掀起第二次工业革命。

So now the car is going down the highway,

那么将来汽车行驶在高速上，

it's 250 horsepower, but in addition, it's 250 minds.

它不仅有 250倍马力， 还有 250倍的脑力。

这就是自动驾驶汽车。

That's the auto-driven car.

It's like a new commodity;

它是一种新的商品，

it's a new utility.

是一种新的基础设施。

The AI is going to flow across the grid -- the cloud --

AI 将会在网络、在云端传输，

in the same way electricity did.

就像电一样。

So everything that we had electrified,

所以凡是可以用电的地方，

we're now going to cognify.

都可以用 AI。

And I would suggest, then,

而我可以建议说，

that the formula for the next 10,000 start-ups

未来一万家创业公司的秘诀

is very, very simple,

其实非常非常简单：

which is to take x and add AI.

拿来某样东西，加上 AI。

That is the formula, that's what we're going to be doing.

这个公式就是我们将要不断践行的。

And that is the way in which we're going to make

我们将以这种方式

this second Industrial Revolution.

来掀起第二次工业革命。

And by the way -- right now, this minute,

顺便说一句，就在此时，

you can log on to Google

你可以登录谷歌，

and you can purchase AI for six cents, 100 hits.

购买 AI：用6美分 购买100次服务。

That's available right now.

这个服务现在就能用。

So the third aspect of this

第三点是，

is that when we take this AI and embody it,

我们将AI实体化，

we get robots.

就得到了机器人。

And robots are going to be bots,

机器人可以帮助我们，

they're going to be doing many of the tasks that we have already done.

完成许多曾经需要 我们亲力亲为的任务。

A job is just a bunch of tasks,

而工作就是一系列的任务，

so they're going to redefine our jobs

我们的工作将会被重新定义，

because they're going to do some of those tasks.

一部分任务将交给机器人来完成。

But they're also going to create whole new categories,

与此同时，也将产生一大批

a whole new slew of tasks

不同种类的新任务，

that we didn't know we wanted to do before.

一批以往我们没有意识到 要去做的任务。

They're going to actually engender new kinds of jobs,

它们甚至有可能催生出新的职业，

new kinds of tasks that we want done,

我们感兴趣的新工作，

just as automation made up a whole bunch of new things

就像自动化带来的许多新事物，

that we didn't know we needed before,

我们之前并不知道会需要它们，

and now we can't live without them.

但今天我们已经离不开它们了。

So they're going to produce even more jobs than they take away,

所以机器人带来的 工作机会比它们抢走的要多。

but it's important that a lot of the tasks that we're going to give them

更重要的是，我们交给它们的

are tasks that can be defined in terms of efficiency or productivity.

都是需要效率或生产率的任务。

If you can specify a task,

如果一个任务，

either manual or conceptual,

不管是体力的还是脑力的，

that can be specified in terms of efficiency or productivity,

可以用效率或生产率来衡量，

that goes to the bots.

那么就应该交给机器人来完成。

Productivity is for robots.

需要效率的事情交给机器人好了。

What we're really good at is basically wasting time.

我们真正擅长的是浪费时间。

(Laughter)

（笑声）

我们最擅长做那些没有效率的事情。

We're really good at things that are inefficient.

Science is inherently inefficient.

科学从本质上来说是低效的。

It runs on that fact that you have one failure after another.

我们一次又一次的失败，

It runs on the fact that you make tests and experiments that don't work,

很多试验和尝试都徒劳无功，

否则我们也学不到什么东西。

otherwise you're not learning.

It runs on the fact

事实就是，

that there is not a lot of efficiency in it.

科学研究没有什么效率。

Innovation by definition is inefficient,

创新从定义上来说就是低效的。

because you make prototypes,

毕竟我们需要制作原型，

because you try stuff that fails, that doesn't work.

需要做各种尝试，经历各种失败。

Exploration is inherently inefficiency.

探索是低效的。

Art is not efficient.

艺术是低效的。

Human relationships are not efficient.

人际关系也是低效的。

These are all the kinds of things we're going to gravitate to,

这些都是我们喜欢做的事情，

because they're not efficient.

因为它们都是低效的。

Efficiency is for robots.

高效是机器人的使命。

We're also going to learn that we're going to work with these AIs

还要认识到，我们将和 AI 一起工作，

because they think differently than us.

因为它们的思维方式与我们不同。

When Deep Blue beat the world's best chess champion,

在“深蓝”战胜国际象棋的世界冠军后，

people thought it was the end of chess.

人们以为国际象棋没什么玩头了。

但事实上，目前世界上 最厉害的国际象棋冠军

But actually, it turns out that today, the best chess champion in the world

is not an AI.

并不是 AI，

And it's not a human.

也不是人类，

It's the team of a human and an AI.

而是由人类和 AI 组成的团队。

The best medical diagnostician is not a doctor, it's not an AI,

最棒的医学诊疗师 既不是医生，也不是 AI，

it's the team.

而是他们组成的团队。

也就是说我们将和 AI 一起工作，

We're going to be working with these AIs,

and I think you'll be paid in the future

你将来的薪酬，

by how well you work with these bots.

很可能取决于 你跟机器人合作得如何。

So that's the third thing, is that they're different,

这就是我想说的第三点： AI 是不同于我们的，

they're utility

它们是技术设备，

and they are going to be something we work with rather than against.

我们将与它们合作，

We're working with these rather than against them.

而非竞争。

So, the future:

那么，

未来会如何？

Where does that take us?

I think that 25 years from now, they'll look back

我想，25年后我们回头再看

and look at our understanding of AI and say,

今天对 AI 的理解，我们会说：

"You didn't have AI. In fact, you didn't even have the Internet yet,

“你们那都不叫 AI。 你们甚至都还没有真正的因特网，

25年后的因特网才能叫因特网呢。“

compared to what we're going to have 25 years from now."

There are no AI experts right now.

我们也还没有真正的 AI 专家。

There's a lot of money going to it,

而大量的资本正涌向这个领域，

there are billions of dollars being spent on it;

动辄数十亿美金，

it's a huge business,

这是一个巨大的产业。

but there are no experts, compared to what we'll know 20 years from now.

但我们尚未拥有真正的 AI 专家—— 如果跟20年后相比的话。

So we are just at the beginning of the beginning,

我们还处在最初的起步阶段，

we're in the first hour of all this.

所有一切才刚刚开始。

We're in the first hour of the Internet.

因特网的历史才刚刚开始。

美好的未来才刚刚开始。

We're in the first hour of what's coming.

未来20年最受欢迎的 AI 产品，

The most popular AI product in 20 years from now,

that everybody uses,

最普及的 AI 产品，

has not been invented yet.

还没有被发明呢。

That means that you're not late.

也就是说，你们还有机会。

Thank you.

谢谢！

(Laughter)

（笑声）

(Applause)

（掌声）