we made tools to make our work easier. From sticks, to plows to tractors we’ve gone

傳統上，人類需要以打獵或聚居維生

from everyone needing to make food to, modern agriculture with almost no one needing to

但人類都是非常聰明(謎之音-懶惰)

make food — and yet we still have abundance.

這使我們發明了各種工具使生活更加便利

Of course, it’s not just farming, it’s everything. We’ve spent the last several

由棒子，到犁，到推土機 我們的社會由所有人都要耕作

thousand years building tools to reduce physical labor of all kinds. These are mechanical muscles

轉變成幾乎無人需要從事農業的現代社會

— stronger, more reliable, and more tireless than human muscles could ever be.

即便這樣，我們還是有豐富的食物

And that's a good thing. Replacing human labor with mechanical muscles frees people to specialize

這不單止是農業，而是各行各業

and that leaves everyone better off even though still doing physical labor. This is how economies

在過去幾千年，我們發明了無數的工具去減少人力勞動

grow and standards of living rise.

這些就是機械肌肉 更強壯、更可靠、能工作更持久

Some people have specialized to be programmers and engineers whose job is to build mechanical

是人類肌肉永遠無法追上的 而這是一件美好的事情

minds. Just as mechanical muscles made human labor less in demand so are mechanical minds

以機械肌肉替代人類勞動 使我們可以進行工作分工從而提升生產力

making human brain labor less in demand.

(即使我們還是有人專注於幹體力活)

This is an economic revolution. You may think we've been here before, but we haven't.

經濟和生活素質就是這樣提升

This time is different.

有些人專注於程序開發 而這些工程師的工作就是製造機械腦袋

## Physical Labor

如同機械肌肉能減低人類體力的需求一樣

When you think of automation, you probably think of this: giant, custom-built, expensive,

機械腦袋減低了人類腦力需求

efficient but really dumb robots blind to the world and their own work. There were a

這就是經濟革命 你可能以為我們已經經歷過

scary kind of automation but they haven't taken over the world because they're only

但這次將會不一樣

cost effective in narrow situations.

勞工

But they are the old kind of automation, this is the new kind.

如果我說「自動化」 在你腦海中想的很可能是以下的畫面:

Meet Baxter.

超誇張、特別訂製的、超貴的、超高效的 但同時是超笨的機械人

Unlike these things which require skilled operators and technicians and millions of

它們只活在自己的世界 只會幹被設計能做的事

dollars, Baxter has vision and can learn what you want him to do by watching you do it.

這的而且確是種很可怕的自動化 但世界還未被它們征服

And he costs less than the average annual salary of a human worker. Unlike his older

因為只有很少場合才能用得上它們

brothers he isn't pre-programmed for one specific job, he can do whatever work is within the

但這只是過去式的自動化

reach of his arms. Baxter is what might be thought of as a general purpose robot and

現在式的自動化是這樣的

general purpose is a big deal.

有請，Baxter

Think computers, they too started out as highly custom and highly expensive, but when cheap-ish

有别於過那些需要專業技術員 和數以百萬元去應用的機械人

general-purpose computers appeared they quickly became vital to everything.

Baxter擁有視覺系統 而且可以單靠觀看你怎樣去完成工作中自動學習

A general-purpose computer can just as easily calculate change or assign seats on an airplane

而它的價格比一般人年薪要更便宜

or play a game or do anything by just swapping its software. And this huge demand for computers

和它的前輩不一樣 它並不是預設計成只能做單一工作

of all kinds is what makes them both more powerful and cheaper every year.

而是只要手能觸及的，它都可以幹

Baxter today is the computer in the 1980s. He’s not the apex but the beginning. Even

Baxter可以說是一台「通用性」機械人

if Baxter is slow his hourly cost is pennies worth of electricity while his meat-based

而「通用性」是非常關鍵

competition costs minimum wage. A tenth the speed is still cost effective when it's a

以電腦做例子，一開始的時候都是價格高昂 且只能處理特定一種運算

hundred times cheaper. And while Baxtor isn't as smart as some of the other things we will

但當便宜又通用的電腦出現 一下子全世界都圍著它轉

talk about, he's smart enough to take over many low-skill jobs.

一台通用性電腦可以用來做找續計算

And we've already seen how dumber robots than Baxter can replace jobs. In new supermarkets

又或者飛機航班指定座位 又或者用來玩遊戲

what used to be 30 humans is now one human overseeing 30 cashier robots.

甚至是任何的任務 只需要換個軟件就行了

Or the hundreds of thousand baristas employed world-wide? There’s a barista robot coming

就是這般強大的電腦需求 促使它們一年比一年便宜，且性能節節提升

for them. Sure maybe your guy makes your double-mocha-whatever just perfect and you’d never trust anyone

今天的Baxter就是1980年的電腦 它不是科技的尖端，而是開始

else -- but millions of people don’t care and just want a decent cup of coffee. Oh and

即使Baxter今天速度還是很慢 但他的工作成本就是幾毛錢的電費

by the way this robot is actually a giant network of robots that remembers who you are

而它的人肉版對手 - 還得付最低工資

and how you like your coffee no matter where you are. Pretty convenient.

即使速度慢十倍，但成本便宜一百倍 性價比還是非常的高

We think of technological change as the fancy new expensive stuff, but the real change comes

雖然Baxter還未至於聰明到 可以締代所有即將要提及的行業

from last decade's stuff getting cheaper and faster. That's what's happening to robots

但已經足夠聰明去替代很多低技術含量的行業

now. And because their mechanical minds are capable of decision making they are out-competing

在我們身邊已經有很多更笨的機械人 替代了大量工作崗位的例子

humans for jobs in a way no pure mechanical muscle ever could.

在新式大超市，從前需要三十個收銀員的地方 現在一個人管理三十台自助收銀機

## Luddite Horses

再看看世界各地顧用的幾十萬位咖啡烹調師

Imagine a pair of horses in the early 1900s talking about technology. One worries all

咖啡烹調機械人也即將普及

these new mechanical muscles will make horses unnecessary.

也許你們能烹調一杯完美的雙份摩卡加什麼的 而且永遠不會相信别人的手藝

The other reminds him that everything so far has made their lives easier -- remember all

但數以百萬計的消費者根本不關心 只要有杯靚咖啡喝就行

that farm work? Remember running coast-to-coast delivering mail? Remember riding into battle?

順帶一提，這台機械人是已經聯網的

All terrible. These city jobs are pretty cushy -- and with so many humans in the cities there

它能記住你是誰和你的口味 無論你身在何方。很方便吧？

are more jobs for horses than ever.

很多人以為科技改革都是指那些浮誇的東東

Even if this car thingy takes off you might say, there will be new jobs for horses we

但真正改變的在過去十數年間的 電腦變得又快又便宜

can't imagine.

機械人科技發展也是一樣的

But you, dear viewer, from beyond 2000 know what happened -- there are still working horses,

因為它們的機械腦袋已經發展到擁有決策的功能

but nothing like before. The horse population peaked in 1915 -- from that point on it was

這使它們能夠與人類爭長短 有别於之前看到的純機動機械人

nothing but down.

馬版盧德運動

There isn’t a rule of economics that says better technology makes more, better jobs

想像一下在20世紀初時 兩匹馬在討論科技改變

for horses. It sounds shockingly dumb to even say that out loud, but swap horses for humans

其中一匹擔心這些新發明的機械肌肉會使馬匹都要失業

and suddenly people think it sounds about right.

另一匹則說，到目前為止的改變都使牠生活更輕鬆

As mechanical muscles pushed horses out of the economy, mechanical minds will do the

還記得我們要耕田 要東西岸穿梭跑送快遞

same to humans. Not immediately, not everywhere, but in large enough numbers and soon enough

還要上戰場的日子嗎？多悲哀啊…

that it's going to be a huge problem if we are not prepared. And we are not prepared.

今天的城市新工作舒服多了

You, like the second horse, may look at the state of technology now and think it can’t

而且一個城市人口這麼多 想必需要更多新工作給馬匹幹

possibly replace your job. But technology gets better, cheaper, and faster at a rate

即使是你說的那個叫「汽車」的普及了

biology can’t match.

肯定也有其他新工作等著我們的

Just as the car was the beginning of the end for the horse so now does the car show us

但親愛的觀眾，來自21世紀的你 都知道故事的結局

the shape of things to come.

工作用的馬還是有的 但和上個世紀的情況完全拉不上邊

## The Shape Of Things to Come

世上馬匹數目在1915年到達高峰 但自此之後就一直滑坡

Self-driving cars aren't the future: they're here and they work. Self-driving cars have

經濟學並沒有「科技改進會為馬匹帶來更好的工作」這一規定

traveled hundreds of thousands of miles up and down the California coast and through

單單是說出口都覺得自己是個白痴

cities -- all without human intervention.

若將「馬」換成「人類」 突然有些人就覺得這句話很乎合邏輯

The question is not if they'll replaces cars, but how quickly. They don’t need to be perfect,

如同機械肌肉為馬匹帶來的經濟衝擊 機械腦袋也會為人類帶來同樣的影響

they just need to be better than us. Humans drivers, by the way, kill 40,000 people a

我不是說全球性立刻會出現這種現像

year with cars just in the United States. Given that self-driving cars don’t blink,

但如果我們毫無準備的話 這將會是個大問題

don’t text while driving, don’t get sleepy or stupid, it easy to see them being better

而我們的確是毫無準備

than humans because they already are.

你就像第二匹馬，根據觀察現今科技的情況 得出無可能取締自已的工作這一結論

Now to describe self-driving cars as cars at all is like calling the first cars mechanical

但科技改變一日千里 並以生物無可能追上的速度更新換代

horses. Cars in all their forms are so much more than horses that using the name limits

如同汽車發明是馬匹終結的開端

your thinking about what they can even do. Lets call self-driving cars what they really

今天的汽車預示了未來的日子

are:

汽車

Autos: the solution to the transport-objects-from-point-A-to-point-B problem. Traditional cars happen to be human

自動駕駛汽車(自駕車)並不是科幻電影情節 而是今天就存在的東西

sized to transport humans but tiny autos can work in wear houses and gigantic autos can

自駕車已經在加州開行了幾千萬公里

work in pit mines. Moving stuff around is who knows how many jobs but the transportation

攀山越嶺並經得起城市穿梭的考驗 當中完全不經人手

industry in the United States employs about three million people. Extrapolating world-wide

問題不是在於傳統汽車會否被取代 而是多快被取代

that’s something like 70 million jobs at a minimum.

自駕車技術不需要做到完美 只需要比人類駕駛汽車好就可以

These jobs are over.

順帶一提，單在美國 人類司機每年就因駕車殺死四萬人

The usual argument is that unions will prevent it. But history is filled with workers who

自駕車不會眨眼、不會滑手機 不會犯睏、不會犯傻

fought technology that would replace them and the workers always loose. Economics always

很顯現易見它們都比人類來駕駛汽車好 因為這個就是今天的事實

wins and there are huge incentives across wildly diverse industries to adopt autos.

我們將自駕車形容為「汽車」 就像將第一代汽車形容為「機械馬」一樣

For many transportation companies, the humans are about a third of their total costs. That's

現今各式汽車絕對不是馬能夠相比 用字不當會使我們無法突破思考空間

just the straight salary costs. Humans sleeping in their long haul trucks costs time and money.

我們必須更正自駕車這個用字

Accidents cost money. Carelessness costs money. If you think insurance companies will be against

自動交通工具(Autos): 一個能將物件由A移到B的解決方案

it, guess what? Their perfect driver is one who pays their small premium but never gets

傳統汽車都是依人類大小去設計 用來解決人類移動問題

into an accident.

但微型Autos能夠在倉庫裏工作 巨大Autos則能在礦場中作業

The autos are coming and they're the first place where most people will really see the

天曉得有多少人的工作就是將東西搬來搬去

robots changing society. But there are many other places in the economy where the same

而在美國運輸業顧用了約三百萬人

thing is happening, just less visibly.

將數字外推，全世界則 最起碼有七千萬人顧用於運輸業

So it goes with autos, so it goes for everything.

這些工作崗位即將成為過去式

## Intellectual Labor

一般反方的意見是，工會會阻止這樣的事情發生

### White Collar Work

但歷史告訴我們 工人與科技搞抗爭的結果只有一個

It's easy to look at Autos and Baxters and think: technology has always gotten rid of

工人必輸，經纃必勝

low-skill jobs we don't want people doing anyway. They'll get more skilled and do better

而全球各行各業都有很大的誘因去引入Autos

educated jobs -- like they've always done.

在一般運輸企業中，人力成本約佔三份一

Even ignoring the problem of pushing a hundred-million additional people through higher education,

而且這只是工資部份

white-collar work is no safe haven either. If your job is sitting in front of a screen

工人在長途貨車中睡覺既花時間又花錢

and typing and clicking -- like maybe you're supposed to be doing right now -- the bots

出意外又要花錢，一不小心又要花錢

are coming for you too, buddy.

如果你覺得保險公司一定會搞抗爭

Software bots are both intangible and way faster and cheaper than physical robots. Given

但「完美司機」是一位會付保費而又永不闖禍的顧客

that white collar workers are, from a companies perspective, both more expensive and more

Autos普及是勢不可擋

numerous -- the incentive to automate their work is greater than low skilled work.

這將是大眾最能直接感知的機械化轉變

And that's just what automation engineers are for. These are skilled programmers whose

經纃上的各個領域 都如同Autos的故事一樣悄悄展開

entire job is to replace your job with a software bot.

Autos的故事，到處都在發生

You may think even the world's smartest automation engineer could never make a bot to do your

未來轉變

job -- and you may be right -- but the cutting edge of programming isn't super-smart programmers

看著Autos和Baxter，我們會以為科技 只會帶走那些我們其實都不想幹的工作而已

writing bots it's super-smart programmers writing bots that teach themselves how to

而事實上，它們會演進並取代更高級的工作 如同過往的科技改革一樣

do things the programmer could never teach them to do.

我們暫且先跳過強逼了上億人進高等教育這個議題

How that works is well beyond the scope of this video, but the bottom line is there are

白領工種亦不能幸免於難

limited ways to show a bot a bunch of stuff to do, show the bot a bunch of correctly done

如果你的工作是在屏幕前打打字點點滑鼠

stuff, and it can figure out how to do the job to be done.

(如同可能你現在可能應該在幹的事)

Even with just a goal and no example of how to do it the bots can still learn. Take the

我告訴你，機械人已經盯上了你

stock market which, in many ways, is no longer a human endeavor. It's mostly bots that taught

軟件機械人遠遠比物理機械人無形、快速、便宜

themselves to trade stocks, trading stocks with other bots that taught themselves.

在公司角度中 白領工人更往往是最昂貴的開支

Again: it's not bots that are executing orders based on what their human controllers want,

相對於低技術工作 公司絕對會更希望把白領工作自動化

it's bots making the decisions of what to buy and sell on their own.

這就是自動化工程師的工作 他們都是編寫程序為生

As a result the floor of the New York Stock exchange isn't filled with traders doing their

工作就是製造各種軟件機械人 以取締你的工作為目標

day jobs anymore, it's largely a TV set.

你可能以為世界最聰明的自動化工程師 都絕不能夠發明出替代你的工作的機械人

So bots have learned the market and bots have learned to write. If you've picked up a newspaper

可能你是對的，但最尖端的編程科技並不限於此

lately you've probably already read a story written by a bot. There are companies that

而是由超聰明程序員編寫出 一套會自我學習的機械人

are teaching bots to write anything: Sports stories, TPS reports, even say, those quarterly

而且能習得無法由程序員直接傳授的智能

reports that you write at work.

詳細的說明並不是本片的重點

Paper work, decision making, writing -- a lot of human work falls into that category

基本來說，就是先為軟件編寫一堆特定算法

and the demand for human metal labor is these areas is on the way down. But surely the professions

然後向它展示哪些工作算是「完成」

are safe from bots? Yes?

之後軟件就能自行推算出 應該要怎樣做才能把工作完成

## Professions

即使只單單定義了目標而不教授方法 也不防礙軟件自行學習

When you think 'lawyer' it's easy to think of trials. But the bulk of lawyering is actually

看下股票市場交易，在各種義意上 都已經不算是人類的工作

drafting legal documents predicting the likely outcome and impact of lawsuits, and something

市場上都是交易軟件，自行學習如何做交易 並與其他同樣的軟件做交易

called 'discovery' which is where boxes of paperwork gets dumped on the lawyers and they

結果就是，紐約交易所裏 充斥的不再是交易員，而是大屏幕

need to find the pattern or the one out-of-place transaction among it all.

軟件已經看透交易市場 甚至能編寫文章

This can all be bot work. Discovery, in particular, is already not a human job in many firms.

若你最近有讀報，很可能已經 閱讀過一些由軟件編成的稿件

Not because there isn't paperwork to go through, there's more of it than ever, but because

世上有專門的軟件公司 開發出能編寫任何文件的軟件

clever research bots sift through millions of emails and memos and accounts in hours

由運動新聞、到軟件測試報告

not weeks -- crushing human researchers in terms of not just cost and time but, most

到甚至乎你工作上要寫的季度報告

importantly, accuracy. Bots don't get sleeping reading through a million emails.

文書工作、決策工作、寫文章 很多行業都是屬於這一類的

But that's the simple stuff: IBM has a bot named Watson: you may have seen him on TV

而這方面的人力腦力需求正在下跌當中

destroy humans at Jeopardy — but that was just a fun side project for him.

當然，專業行業不會這樣就被自動化了吧。 你說呢？

Watson's day-job is to be the best doctor in the world: to understand what people say

專業機械人

in their own words and give back accurate diagnoses. And he's already doing that at

當提到律師這個字，多半馬上聯想到是上法庭

Slone-Kettering, giving guidance on lung cancer treatments.

但其實大部份的工作是在「發掘」階段:

Just as Auto don’t need to be perfect -- they just need to make fewer mistakes than humans,

只要文件處理得好，就能預視到訴訟結果

-- the same goes for doctor bots.

說白了就是律師埋頭在一箱箱的文件中

Human doctors are by no means perfect -- the frequency and severity of misdiagnosis are

試著找出某一犯案模式、又或 一筆不合常理的交易記錄

terrifying -- and human doctors are severely limited in dealing with a human's complicated

這統統都是軟件機械人可以幹的事

medical history. Understanding every drug and every drug's interaction with every other

尤其是這種「發掘」 在很多律師行中已經不是人工去做

drug is beyond the scope of human knowability.

不是因為要處理的文件少了 事實上是因為有更多的文件

Especially when there are research robots whose whole job it is to test 1,000s of new

而因為專門的分析機械人 能在以小時計(而不是以星期計)的時間內

drugs at a time.

分析數以百萬筆郵件、筆記和賬戶記錄

Human doctors can only improve through their own experiences. Doctor bots can learn from

不單止在時間或金錢上 都把人類分析員狠很地比下去

the experiences of every doctor bot. Can read the latest in medical research and keep track

更重要是軟件還有更高的準繩度

of everything that happens to all his patients world-wide and make correlations that would

軟件更不會因為處理幾百萬封郵件就犯睏

be impossible to find otherwise.

但以上所說的都是小兒科

Not all doctors will go away, but when doctor bots are comparable to humans and they're

IBM有一台叫Watson的電腦

only as far away as your phone -- the need for general doctors will be less.

你可能已經在電視上見過它

So professionals, white-collar workers and low-skill workers all have something to worry

(Jeopardy是一個美國電視問答比賽節目) 在Jeopardy中把人類參賽者重重擊敗

about.

但那只是它的兼職玩兒

But perhaps you're still not worried because you're a special creative snowflakes. Well

Watson正職是化身為一位全世界最一流的醫生:

guess what? You're not that special.

通過聆聴患者的說話 然後給出一個準確地診斷結果

## Creative Labor

(Sloan-Kettering是1884年在紐約建成的私家癌症專科醫院) 他已經在Sloan-Kettering投放使用 輔助肺癌治療過程

Creativity may feel like magic, but it isn't. The brain is a complicated machine -- perhaps

如同Autos一樣，醫生機械人並不需要十全十美

the most complicated machine in the whole universe -- but that hasn't stopped us from

只要比人類犯錯少就算是成功

trying to simulate it.

人肉醫生絕對不是十全十美

There is this notion that just as mechanical muscles allowed us to move into thinking jobs

事實上誤診的機率和嚴重性十分令人震驚

that mechanical minds will allow us all to move into creative work. But even if we assume

人肉醫生單在面對複雜的病歷就顯得抓襟見肘

the human mind is magically creative -- it's not, but just for the sake of argument -- artistic

要完全理解每隻藥 以及與每另一隻藥的互動

creativity isn't what the majority of jobs depend on. The number of writers and poets

絕對是人類能應付的范圍之外

and directors and actors and artist who actually make a living doing their work is a tiny,

和能同時測試千款藥物的 科研機械人一比，高下立見

tiny portion of the labor force. And given that these are professions that are dependent

人肉醫生只能透過自己的經驗去學習和改良

on popularity they will always be a small part of the population.