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不需要人类

Humans Need Not Apply

不需要人类
Humans need not apply
过去 人类需要打猎或收集资源以求生存
Every human used to have to hunt or gather to survive.
但人类都会耍小聪明偷懒
But humans are smart…ly lazy
所以 我们发明了工具让工作更简便
so we made tools to make our work easier.
从棍子到犁再到拖拉机
From sticks, to plows, to tractors
我们经历了 从所有人都需生产粮食
we’ve gone from everyone needing to make food
到几乎无人需要耕作的现代农业
to modern agriculture with almost no one needing to make food
并且 我们还有富余的食物
— and yet, we still have abundance.
当然 不单单是农业 而是所有方面
Of course, it’s not just farming, it’s everything.
为了减少各种身体上的劳动
We’ve spent the last several thousand years
过去的几千年我们都在创造工具
building tools to reduce physical labor of all kinds.
这是机械肌肉 比人类的肌肉
These are mechanical muscles. Stronger,more reliable,
要更强壮 更可靠 更加不易疲倦
and more tireless than human muscles ever could be.
这是件好事
And that’s a good thing.
用机械肌肉代替人工
Replacing human labor with mechanical muscles
解放人力 让工作更加精细
frees people to specialize
也让所有人富裕起来
and that leaves everyone better off –
即便是那些蓝领工人
even those still doing physical labor.
这就是经济增长以及生活质量提高的途径
This is how economies grow and standards of living rise.
一些人成为专职制造
Some people have specialized to be programmers and engineers
机械大脑的编程师与工程师
whose job is to build mechanical minds.
正如机械生产减少了对人力劳动的需求
Just as mechanical muscles made human labor less in demand
机械大脑也减少了对人类大脑的需求
so are mechanical minds making human brain labor less in demand.
这是一场经济意义上的革命
This is an economic revolution.
你可能觉得我们以前经历过这样的革命 但是没有
You may think we’ve been here before, but we haven’t.
这次不一样
This time is different.
体力劳动
Physical Labor
当你想到自动化时 想到的可能是这样的:
When you think of automation, you probably think of this:
一个巨大的 特别定制的 昂贵而高效的
giant, custom-built, expensive, efficient
但对世界和自己的工作一无所知的傻瓜式机器人
but really dumb robots blind to the world and their own work.
它们确实“自动化”得可怕
They were a scary kind of automation
但它们还没能掌控世界
but they haven’t taken over the world
因为它们只在
because they’re only
有限的情况下起到作用
cost effective in narrow situations.
但它们是老式的自动化仪器
But they’re the old kind of automation
来见见Baxter 它是新型的自动化机器人
this is the new kind.meet Baxter.
不像老式机器要求熟练的操作员
Unlike these things which require skilled operators
以及机师而且花费巨大
and technicians and millions of dollars,
Baxter有思想 并可以观看学习
Baxter has vision and can learn what you
你正在做且想让它学会的事
want him to do by watching you do it.
而且其开销比人类工人平均年薪要少
And he costs less than the average annual salary of a human worker.
和他的前辈们不同
Unlike his older brothers,
Baxter没有被预置具体的工作程序
he isn’t pre-programmed for one specific job,
他可以做所及范围内的任何工作
he can do whatever work is within the reach of his arms.
Baxter或许被看作是通用型机器人
Baxter is what might be thought of as a general purpose robot
这种机器人的目标很关键
and general purpose is a big deal.
想想电脑
Think computers,
它们刚出现时也极具个性 十分昂贵
they too started out as highly custom and highly expensive,
但当便宜通用的电脑出现之后
but when cheap-ish,general-purpose computers appeared
很快 电脑对所有的事物都至关重要了
they quickly became vital to everything.
一台通用型电脑可以
A general-purpose computer can just
轻易地计算 改变或指派飞机座位
as easily calculate change or assign seats on an airplane
或仅仅通过不同电脑软件 进行游戏或是做任何事
or play a game or do anything just by swapping its software.
这种对各类电脑的需求
And this huge demand for computers of all kinds
使其每年都更便宜 也更加强大
is what makes them both more powerful and cheaper every year.
现在的Baxter正如20世纪80年代的电脑
Baxter today is the computer of the 1980s.
它不是最顶尖的 而是最原始的
He’s not the apex but the beginning.
尽管Baxter很慢 但他每小时只消耗极少的电
Even if Baxter is slow, his hourly cost is pennies worth of electricity
而与他竞争的人类却仍需要最低工资
while his meat-based competition costs minimum wage.
十分之一的速度在百分之一的价格面前
A tenth the speed is still cost effective when it’s a
仍然是划算的
hundredth the price.
虽然Baxter不如
And while Baxter isn’t as smart as
我们即将讨论的机器聪明
as some of the other things we will talk about,
但他已足够聪明去接手一些低技能的工作
he’s smart enough to take over many low-skill jobs.
而且我们也目睹了比Baxter迟钝的机器人如何取代人的工作
And we’ve already seen how dumber robots than Baxter can replace jobs.
在新型超市 以前会有30名收银员
In new supermarkets what used to be 30 humans
现在只有一个人照看30台收银机器
is now one human overseeing 30 cashier robots.
而那些全球数十万的咖啡师从业人员呢?
Or take the hundreds of thousand baristas employed world-wide?
咖啡机器人正在路上
There’s a barista robot coming for them.
或许你制作的双倍摩卡正合意
Sure maybe your guy makes the double-mocha-whateverjust perfect
你就不要别人帮你煮咖啡
and you’d never trust anyone else —
但更多的人并不在意 他们需要的仅仅是一杯咖啡而已
but millions of people don’t care and just want a decent cup of coffee.
顺便提一下 这是一个
Oh,and by the way this robot is actually a giant network of robots
不管你在哪儿 都能记住你是谁 喜欢怎样咖啡的联网机器人
that remembers who you are and how you like your coffee no matter where you are.
太方便了
Pretty convenient.
我们认为技术变化是华丽 昂贵的新玩意
We think of technological change as the fancy new expensive stuff,
但真正的变化是
but the real change comes
源于十年前的东西逐渐变得便宜和迅捷
from last decade’s stuff getting cheaper and faster.
这正在机器人身上发生
That’s what’s happening to robots now.
因为机器人的机械大脑有作决定的能力
And because their mechanical minds are capable of decision making
它们在工作上胜过人类 是纯机械肌肉无法做到的
they are out-competing humans for jobs in a way no pure mechanical muscle ever could.
勒德分子马
Luddite Horses
想象在20世纪初 两匹马在讨论科技
Imagine a pair of horses in the early 1900s talking about technology.
一只担心这些新机械肌肉会让马变得多余
One worries all these new mechanical muscles will make horses unnecessary.
另外一只提醒它
The other reminds him
至今为止所有的科技让它们的生活变得更轻松了
that everything so far has made their lives easier —
还记得那些农活吗
remember all that farm work?
还记得在东西海岸间飞奔送信吗
Remember running from coast-to-coast delivering mail?
还记得被骑着进入战场吗
Remember riding into battle?
太糟糕了 这些城里的工作多轻松
All terrible. These city jobs are pretty cushy,
随着城里有更多的人类
and with so many humans in the cities
马的工作会更多
there will be more jobs for horses than ever.
即使这辆车点火起步了
Even if this car thingy takes off –
它也会说 会有更多意想不到的工作等着我们的
he might say – there will be new jobs for horses we can’t imagine.
但是你 来自于千禧年后的观众知道发生了什么
But you, dear viewer, from beyond 2000 know what happened —
它们仍然是劳作马
there are still working horses,
但和以前不一样了
but nothing like before.
马的数量在1915年达到顶峰
The horse population peaked in 1915 —
从那以后就开始减少
from that point on it was nothing but down.
没有一条经济规则表示
There isn’t a rule of economics that
更发达的科技会分配给马更舒适的工作
says better technology makes more better jobs for horses.
这个想法说出来都感觉非常的傻
It sounds shockingly dumb to even say that out loud,
但是用“人类”代替“马”
but swap horses for humans
人们就觉得这听起来没什么问题
and suddenly people think it sounds about right.
机械肌肉能将马从经济运行中赶出去
As mechanical muscles pushed horses out of the economy,
机械意识也会使人类陷入相同的境地
mechanical minds will do the same to humans.
不会很快 不是在各个领域
Not immediately, not everywhere,
但如果我们不充分准备
but in large enough numbers and soon enough
只要它们数量够多 时间够久 就会是个大麻烦
that it’s going to be a huge problem if we are not prepared.
而我们并未准备好
And we are not prepared.
如同第二匹马 你可能还在衡量现在科技的水平
You,like the second horse, may look at the state of technology now
觉得它还无法代替你的工作
and think it can’t possibly replace your job.
但科技正以生物无法匹敌的速度 变得更好 更便宜 更迅捷
But technology gets better, cheaper, and faster at a rate biology can’t match.
如同汽车的出现
Just as the car was the beginning of the end
是马消逝的开始 也如同现在
for the horse so now does the car show us
汽车给我们展示了即将到来的事物
the shape of things to come.
关于汽车
Automobiles
自动驾驶汽车不是未来:它们已经存在并运行良好
Self-driving cars aren’t the future: they’re here and they work.
自动驾驶汽车
Self-driving cars have
不需要司机操作
travelled hundreds of thousands of miles up and
沿着加利福尼亚海岸 穿过城市
down the California coast and through cities
行驶了近千英里
— all without human intervention.
问题不在于它们是否会代替汽车 而在于多快会代替
The question is not if they’ll replaces cars, but how quickly.
它们不需要多完美
They don’t need to be perfect,
只需要比我们开的好
they just need to be better than us.
顺便说一下 仅在美国境内 人类司机
Humans drivers, by the way, kill 40,000 people a
每年就导致40000人的死亡
year with cars just in the United States.
鉴于自动驾驶汽车不会眨眼
Given that self-driving cars don’t blink,
不会在驾驶时发短信 打瞌睡或犯傻
don’t text while driving, don’t get sleepy or stupid,
很容易看出来 它们比人类出色
it’s easy to see them being better than humans
因为它们确实很出色
because they already are.
现在 把自动驾驶汽车叫做汽车
Now to describe self-driving cars as cars at all is
就像把第一辆汽车称为机械马一样
like calling the first cars mechanical horses.
所有形式的汽车都远远超过了马
Cars in all their forms are so much more than horses
使用这个名字会限制你思考它们可以做什么
that using the name limits your thinking about what they can even do.
我们还是叫自动驾驶汽车它的本名 乘具
Lets call self-driving cars what they really are: Autos:
从点a到点b的运输目标问题的解决方案
the solution to the transport-objects-from-point-A-to-point-B problem.
传统的汽车正好符合人类身材 来搭载人类
Traditional cars happen to be human sized to transport humans
较小的汽车可以在仓库里工作
but tiny autos can work in warehouses
而大型汽车可以在矿井中工作
and gigantic autos can work in pit mines.
没有人知道运送物体提供了多少工作
Moving stuff around is who knows how many jobs
但美国的运输系统
but the transportation in the United States
为近三百万人提供了就业
employs about three million people.
从全球范围来看
Extrapolating world-wide
这至少相当于7000万个工作岗位
that’s something like 70 million jobs at a minimum.
这些岗位要完蛋了
These jobs are over.
通常 工会都尽量避免发生这种事情
The usual argument is that unions will prevent it.
但历史中充斥着反对科技 怕被代替的工人
But history is filled with workers who fought technology that would replace them
而这些工人们常常会失败
and the workers always lose.
经济总是赢家
Economics always wins and
且各个行业都有足够理由使用汽车
there are huge incentives across wildly diverse industries to adopt autos.
对很多运输企业 人力占总花费的三分之一
For many transportation companies, humans are about a third their total costs.
这只是人力的直接支出
That’s just the straight salaries.
人类睡在长途卡车里要花费时间和金钱
Humans sleeping in their long haul trucks costs time and money.
交通事故要花钱
Accidents cost money.
粗心大意要花钱
Carelessness costs money.
如果你觉得保险公司会反对
If you think insurance companies will be against it,
猜猜怎么着
guess what?
对于他们 完美的司机就是
Their perfect driver is one who
需要支付很少的保险费
pays their small premiums
并且不会出事的司机
and never gets into an accident.
汽车正在发展
The autos are coming and they’re the
并且使大多数人第一次意识到
first place where most people will really see the
机器人正在改变社会
robots changing society.
但在经济的更多方面
But there are many other places in the economy
同样的事情正在发生 只是不够明显
where the same thing is happening, just less visibly.
汽车的发展如此 其他的事物也是如此
So it goes with autos, so it goes for everything.
未来事物的模样
The Shape of things to come
看到汽车与Baxter会很容易想到:
It’s easy to look at Autos and Baxters and think:
科技经常会淘汰掉
technology has always gotten rid of low-skill jobs
人类不愿亲自着手的低级工作
we don’t want people doing anyway.
他们会获得更多的技术 做更好的教育工作
They’ll get more skilled and do better educated jobs
像以往一直做的那样
— like they’ve always done.
即使忽视
Even ignoring the problem
让一亿人接受高等教育的问题
of pushing a hundred-million additional people through higher education,
白领工作也不是一个铁饭碗
white-collar work is no safe haven either.
如果你的工作是坐在屏幕前
If your job is sitting in front of a screen
打字敲键盘——
and typing and clicking —
就像你现在或许正在做的那样
like maybe you’re supposed to be doing right now —
——机器人也会来找你 伙计
the bots are coming for you too, buddy.
软件机器人是无形的
Software bots are both intangible
比物理机器人更快 更便宜
and way faster and cheaper than physical robots.
从公司的发展前景来看
Given that white collar workers are,
雇佣白领工人的成本更高
from a company’s perspective,
并且雇佣人数太多
both more expensive and more numerous
自动化工作的效能
— the incentive to automate their work
比低技能工作更高
is greater than low skilled work.
这正是自动化工程师的职责所在
And that’s just what automation engineers are for.
这些老练的程序员的工作
These are skilled programmers whose
就是用软件机器人代替你的工作
entire job is to replace your job with a software bot.
你或许以为世上最聪明的自动化工程师
You may think even the world’s smartest automation engineer
都不会发明出一种会做你工作的机器人
could never make a bot to do your job —
你或许是对的
and you may be right —
但编程的前沿并不是
but the cutting edge of programming
超级聪明的程序员编写机器人
isn’t super-smart programmers writing bots, it’s super-smart
而是超级聪明的程序员编写出
programmers writing bots that teach themselves how to
能够自学程序员无法教会的那些事情 的机器人
do things the programmer could never teach them to do.
它的工作原理不属于本视频内容
How that works is well beyond the scope of this video,
但底线是
but the bottom line is there are
向机器人展示要做什么的方式是有限的
limited ways to show a bot a bunch of stuff to do,
向机器人展示一堆正确的事情
show the bot a bunch of correctly done stuff,
它就会知道怎么做
and it can figure out how to do the job to be done.
即使只有一个目标
Even with just a goal and no knowledge
没有做事的方法 机器人仍然可以学习
of how to do it the bots can still learn.
比如说股票市场
Take the stock market which,
很大程度上说已经不是人类的功劳了
in many ways, is no longer a human endeavor.
通常是教会自己股票交易的机器人
It’s mostly bots that taught themselves to trade stocks,
和其他教会自己股票交易的机器人进行股票交易
trading stocks with other bots that taught themselves.
结果是 纽约证交所的地板上
As a result, the floor of the New York Stock exchange
不是站满了正在忙碌的交易员
isn’t filled with traders doing their day jobs anymore,
而基本上是电视机
it’s largely a TV set.
机器人不但学会了买卖 还学会了写书
So bots have learned the market and bots have learned to write.
如果你拿起最近的报纸
If you’ve picked up a newspaper
你或许已经读过机器人写的故事了
lately you’ve probably already read a story written by a bot.
有些公司教机器人写任何东西:
There are companies that teach bots to write anything:
体育故事 TPS报告 甚至那些
sports stories, TPS reports, even say, those quarterly
每季度上班时你要写的报告
reports that you write at work.
文书 决策 撰写
Paper work, decision making, writing —
许多人们的工作都属于这一类
a lot of human work falls into that category
并且这方面的人力需求也
and the demand for human metal labor is these areas is
越来越少
on the way down.
但是专业的工作
But surely the professions
还是安全的 对吧?
are safe from bots? Yes?
专业机器人
Professional Bots
提及律师 最容易想到的是审判
When you think’lawyer’ it’s easy to think of trials.
但大部分律师实际上
But the bulk of lawyering is actually
是在起草法律文件
drafting legal documents,
预测诉讼可能产生的结果和影响
predicting the likely outcome and impact of lawsuits,
还有一种被称为“证据开示”的行为
and something called’discovery’ which is where boxes
就是一箱一箱的文件被扔给律师
of paperwork gets dumped on the lawyers and they
他们需要在里面找到
need to find the pattern or
问题或不正当交易
the one out-of-place transaction among it all
这可以变成机器人的工作 特别是证据开示
This can be bot work. Discovery, in particular,
在律师事务所里已经不是人类的工作了
is already not a human job in many law firms.
这不是因为没有文书工作要处理
Not because there isn’t paperwork to go through,
工作比以往更多 但是
there’s more of it than ever, but because
因为研究机器人在数小时 而不是数周内
clever research bots shift through millions
就能完成数百万封电子邮件 备忘录和账户的转换
of emails and memos and accounts in hours
这不仅在成本和时间方面优于人类研究员
not weeks — crushing human researchers in terms
更是在于准确性
of not just cost and time but,most importantly,accuracy
机器人在阅读百万封电子邮件时不会犯困
Bots don’t get sleepy reading through a million emails.
但这些都是小事 IBM有一台名为华生的机器人
But that’s the simple stuff: IBM has a bot named Watson:
你可能在电视上看过他在《危险》中碾压人类
you may have seen him on TV destroy humans at Jeopardy
但这对他只是小菜一碟
— but that was just a fun side project for him.
华生的日常工作是作为世界上最好的医生
Watson’s day-job is to be the best doctor in the world:
弄明白人类所想表达的
to understand what people say in their own words
并且给他们准确的诊断
and give back accurate diagnoses.
华生已经在Slone-Kettering医院开始
And he’s already doing that at Slone-Kettering,
给予肺癌引导治疗
giving guidance on lung cancer treatments.
就像乘具不需要完美一样
Just as Auto don’t need to be perfect —
它们只需要犯的错误比人类少
they just need to make fewer mistakes than humans —
医疗机器人也同样如此
the same goes for doctor bots.
人类医生并不完美
Human doctors are by no means perfect —
误诊的频率与数量让人震惊
the frequency and severity of misdiagnoses are terrifying
且人类医生在处理人类复杂的病史方面
— and human doctors are severely limited
有非常严重的局限
in dealing with a human’s complicated medical history.
了解每一种药物
Understanding every drug
和每种药物与其他药物之间的相互作用
and every drug’s interaction with every other drug
超出了人类的认知范围
is beyond the scope of human knowability.
特别是当存在 同时测试近千种新药的
Especially when there are research robots whose whole
研究机器人存在时
job it is to test thousands of new drugs at a time.
然而人类医生只能通过实践来提升能力
And human doctors can only improve through their own experiences.
医疗机器人可以从
Doctor bots can learn from
任一医疗机器人的经验中学习
the experiences of every doctor bot.
并且可以读取最新的医疗研究
Can read the latest in medical research and keep track
跟踪它们全球病人的动态
of everything that happens to all their patients world-wide
进行别人根本无法完成的数据统计
and make correlations that would be impossible to find otherwise.
不是所有的医生都会离开
Not all doctors will go away,
但当人类医生与你手机中的
but when the doctor bots are comparable to humans and they’re
医疗机器人相比时
only as far away as your phone —
常规的人类医生需求就会减少
the need for general doctors will be less.
所以专家 白领和
So professionals, white-collar workers and
低技能工人都需要担心自动化的威胁
low-skill workers all have things to worry about from automation.
但或许你并不苦恼
But perhaps you are unfazed
因为你就像朵创意满满的特别的雪花
because you’re a special creative snowflake.
你猜怎么着 你没那么特别
Well guess what? You’re not that special.
创意机器人
Creative Bots
创造力感觉像是魔法 但不是的
Creativity may feel like magic, but it isn’t.
大脑是一台复杂的机器
The brain is a complicated machine — perhaps
也许是整个宇宙中最复杂的
the most complicated machine in the whole universe —
但那也阻止不了我们试着仿造它
but that hasn’t stopped us from trying to simulate it.
有一种概念是
There is this notion that just
机械肌肉允许我们进行思考性的工作
as mechanical muscles allowed us to move into thinking jobs
机械意识允许我们进行创造性的工作
that mechanical minds will allow us to move into creative work.
但即使我们假设人类大脑有魔法般的创造力
But even if we assume the human mind is magically creative —
其实不是的 只是为了论证
it’s not, but just for the sake of argument —
大部分工作并不依靠于艺术创造力
artistic creativity isn’t what the majority of jobs depend on.
真正以创作为生的
The number of writers and poets
作家 诗人 导演
and directors and actors and artists who actually
演员和艺术家
make a living doing their work is a tiny,
只占劳动力的很小一部分
tiny portion of the labor force.
考虑到这些职业依赖于受欢迎的程度
And given that these are professions dependent
做这些工作的人只占了一小部分
on popularity they’ll always be a very small portion of the population.
不存在 需要以诗歌和绘画为基础的经济
There can’t be such a thing as a poem and painting based economy.
哦对了
Oh,by the way,
你正在听的这首背景音乐
this music in the background that you’re listening to?
是机器人写的
It was written by a bot.
她叫艾米丽·豪威尔
Her name is Emily Howell and she can
她能整天尽情的编写音乐 而且不产生花费
write an infinite amount of new music all day for free.
如果进行盲测 人们也分不出
And people can’t tell the difference between her
她与人类作曲者的区别
and human composers when put to a blind test.
现在人工创造不可思议地快
Talking about artificial creativity gets weird fast —
这到底是什么意思?
what does that even mean?
这仍然是一个发展中的领域
But it’s nonetheless a developing field.
在机器人击败最好的棋手之前
People used to think that playing chess
人们以前觉得下棋是一个机器人
was a uniquely creative human skill that machines
无法立即学会独特的人类创造技能
could never do right up until they beat the best of us.
所有的人类才能都是如此
And so it will go for all human talents.
结论
Conclusion
对 接受这现实或许得一段时间
Right this may have been a lot to take in,
你可能不愿接受
and you might want to reject it — it’s
人们容易对没完没了的愚蠢预测嗤之以鼻
easy to be cynical of the endless and idiotic predictions
而这些预测从来都不是
of futures that never are.
这就是再强调一遍的重要性
So that’s why it’s important to emphasize again
这东西不是科幻小说
that this stuff isn’t science fiction.
机器人现在就在这里
The robots are here right now.
世界上的实验室和仓库中
There is a terrifying amount
有相当大数量的自动化机器
of working automation in labs and warehouses
在工作着
around the world.
我们已经经历过经济革命
We have been through economic revolutions before,
但机器革命完全不同
but the robot revolution is different.
现在 马不是因为懒惰而没在工作
Horses aren’t unemployed now because they got lazy
而是因为无法给它们安排工作
as a species, they’re unemployable.
马能做的工作很少
There’s little work a horse can do
马舍与干草的价值不及这些工作
that do to pay for its housing and hay.
许多聪明 完全有能力的人会发现
And many bright, perfectly capable humans will find themselves
自己成了一匹新马 无业并不是他们的错
the new horse: unemployable through no fault of their own.
如果你仍觉得新工作可以拯救我们
But if you still think new jobs will save us:
你还要考虑最后一点
here is one final point to consider.
1776年的美国人口普查只查到了几种工作
The US census in 1776 tracked only a few kinds of jobs.
现在有着数百种工作
Now there are hundreds of kinds of jobs,
但新工作在劳动力中占的比重并不大
but the new ones are not a significant part of the labor force.
以下是根据从事这些工作的人数
Here’s the list of jobs ranked by the number of people
排名的工作列表 令人警醒
who perform them — it’s a sobering
交通行业位居榜首
list with the transportation industry at the top.
继续向下看 所有这些工作
Continuing downward, all of this work existed
一百年前都以某种形式存在
in some form a hundred years ago
几乎所有这些工作都易成为自动化的目标
and almost all of them are eazy targets for automation.
当我们看到名单上第33名时
Only when we get to number 33 on the list
终于有点新东西了
is there finally something new.
不要认为每一个咖啡师或白领
Don’t think that every barista or white collar worker need
都需要在问题出现之前失业
lose their job before things are a problem.
大萧条时期失业率为25%
The unemployment rate during the great depression was 25%.
这张列表占大约45%的劳动力
This list above is 45% of the workforce.
就像我们现在所谈论的 这些已经在发生了
Just what we’ve talked about today, the stuff that
这会让我们的失业人数很快超过这个数字
already works, can push us over that number pretty soon.
考虑到
And given that even in our modern
即使在现代科技的仙境里
technological wonderland new kinds of work
新型工作也不是经济的重要组成部分
aren’t a significant portion of the economy,
这是个大问题
this is a big problem.
这条视频不是讲自动化的坏处
This video isn’t about how automation is bad —
而是自动化的必然性
rather that automation is inevitable.
它是种投入少 收获多的工具
It’s a tool to produce abundance for little effort.
我们现在该考虑
We need to start thinking now about what to
当大部分人不是因为自己的错而失业时
do when large sections of the population are unemployable —
应该怎么办
through no fault of their own.
在未来的工作中 大多数工作都不需要人类时
What to do in a future where, for most jobs,
应该怎么办
humans need not apply.

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译制信息
视频概述

自动化职业会大量取代人类职业,但这不全是坏事,并且这是必然的趋势。

听录译者

收集自网络

翻译译者

YT

审核员

审核员_XY

视频来源

https://www.youtube.com/watch?v=7Pq-S557XQU

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