TED2013
Rodney Brooks: Why we will rely on robots
羅德尼．布鲁克斯: 為什麼我們將依靠機器人
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Readability: 3.4
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危言聳聽者總說機器人將奪走人們的工作。事實上，它們將變成我們至關重要的合作伙伴。它們的出現使我們可以更多的去挑戰那些不刻板繁瑣的工作。羅德尼．布鲁克斯指出在這個工作年齡的成年人日趨減少，而退休人員日趨增加的時代，機器人對我們的重要性。他向我們介紹了 Baxter。它是一個眼睛可以活動，手臂可以對觸碰做出反應的機器人。Baxter 可以與老齡化人口一起合作，並學習在日常生活中幫助他們。
Rodney Brooks - Roboticist
Rodney Brooks builds robots based on biological principles of movement and reasoning. The goal: a robot who can figure things out. Full bio
Rodney Brooks builds robots based on biological principles of movement and reasoning. The goal: a robot who can figure things out. Full bio
Double-click the English transcript below to play the video.
00:13
Well, Arthur C. Clarke,
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亞瑟·查理斯·克拉克
00:14
a famous science fiction writer from the 1950s,
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上世紀50年代著名的科幻小說家
00:17
said that, "We overestimate technology in the short term,
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曾說過：“從短期看來，我們高估了科技；
00:21
and we underestimate it in the long term."
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但從長期而言，我們卻低估了它”
00:24
And I think that's some of the fear that we see
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隨著人工智能和機器人技術的發展
00:26
about jobs disappearing from artificial intelligence and robots.
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我們開始害怕某些工作將被取代
00:31
That we're overestimating the technology in the short term.
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正是我們高估科技短期影響的一種代表
00:33
But I am worried whether we're going to get the technology we need in the long term.
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但我擔心的是從長遠看，
我們能否達到所需要的科技水平
我們能否達到所需要的科技水平
00:39
Because the demographics are really going to leave us with lots of jobs that need doing
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人口的增長讓我們需要更多人手
00:45
and that we, our society, is going to have to be built on the shoulders of steel of robots in the future.
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我們的社會將不得不建立在這些鋼鐵機器的肩膀上。
00:50
So I'm scared we won't have enough robots.
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所以，我擔心的是我們沒有足夠的機器人
00:53
But fear of losing jobs to technology has been around for a long time.
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科技會導致失業的想法其實由來已久
00:57
Back in 1957, there was a Spencer Tracy, Katharine Hepburn movie.
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1975年，史賓塞·屈賽 和 凯瑟琳·赫本主演主演過一部電影
01:01
So you know how it ended up,
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你知道最後最後結局如何嗎？
01:03
Spencer Tracy brought a computer, a mainframe computer of 1957, in
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史賓塞·屈賽 弄來了一台電腦，一台1957年的大型機
01:07
to help the librarians.
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幫助那些圖書管理員
01:09
The librarians in the company would do things like answer for the executives,
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公司的圖書管理員需要負責回答高官們的問題。例如，
01:12
"What are the names of Santa's reindeer?"
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“聖誕老人的馴鹿叫什麼名字？”
01:16
And they would look that up.
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圖書管理員們就回去把答案找出來。
01:17
And this mainframe computer was going to help them with that job.
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這些大型計算機就會幫助他們
01:20
Well of course a mainframe computer in 1957 wasn't much use for that job.
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當然，一台1957年的大型機也不見得對這工作有多大幫助
01:24
The librarians were afraid their jobs were going to disappear.
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然而圖書管理員們依舊害怕他們會失業
01:27
But that's not what happened in fact.
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但事實上事情並非如此。
01:29
The number of jobs for librarians increased for a long time after 1957.
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在1957年之後很長的一段時間裡，
圖書管理員的數量反而增長了
圖書管理員的數量反而增長了
01:34
It wasn't until the Internet came into play,
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直到互聯網出現，
01:37
the web came into play and search engines came into play
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網絡出現，搜索引擎出現
01:40
that the need for librarians went down.
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對圖書管理員的需求才開始下降。
01:42
And I think everyone from 1957 totally underestimated
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同時，我認為在1957年所有人都完完全全低估了
01:46
the level of technology we would all carry around in our hands and in our pockets today.
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我們今天握在手中以及裝在口袋中的這些東西的科技含量
01:51
And we can just ask: "What are the names of Santa's reindeer?" and be told instantly --
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只需一瞬間，我們就可以知道聖誕老人的馴鹿的名字，
01:57
or anything else we want to ask.
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抑或是任何我們想問的
01:59
By the way, the wages for librarians went up faster
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順帶一提，圖書管理員的工資增速
02:04
than the wages for other jobs in the U.S. over that same time period,
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曾在一段時間內高過了全美其他崗位的工資水平，
02:07
because librarians became partners of computers.
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因為圖書管理員成為了電腦的同夥
02:11
Computers became tools, and they got more tools that they could use
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電腦成為了他們的工具，
同時他們也獲取了更多其他可用的工具
同時他們也獲取了更多其他可用的工具
02:14
and become more effective during that time.
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讓效率變得更高。
02:16
Same thing happened in offices.
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同樣的事情也發生在辦公室裡
02:18
Back in the old days, people used spreadsheets.
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以前，人們處理報表的方式是
02:20
Spreadsheets were spread sheets of paper,
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把數據寫在許多不同的紙張
02:22
and they calculated by hand.
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一一用手計算。
02:25
But here was an interesting thing that came along.
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但是有趣的事情發生了。
02:27
With the revolution around 1980 of P.C.'s,
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隨著1980年的電腦革命，
02:29
the spreadsheet programs were tuned for office workers,
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空白表格程式沒有取代辦公族，
02:34
not to replace office workers,
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反而受到他們的青睞
02:36
but it respected office workers as being capable of being programmers.
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辦公族變身成為程式設計師，
02:40
So office workers became programmers of spreadsheets.
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當他們成為空白表格的程式設計師
02:43
It increased their capabilities.
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他們的工作更有效率了。
02:45
They no longer had to do the mundane computations,
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他們不用再做那些繁瑣的計算，
02:48
but they could do something much more.
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他們可以做更多其他工作。
02:51
Now today, we're starting to see robots in our lives.
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今天，我們在日常生活中也能見到機器人的身影。
02:54
On the left there is the PackBot from iRobot.
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左邊是一台 iRobot 公司產的軍用機械人 PackBot
02:57
When soldiers came across roadside bombs in Iraq and Afghanistan,
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當士兵們穿越伊拉克和阿富汗戰場的雷區時，
03:00
instead of putting on a bomb suit and going out and poking with a stick,
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他們不再像 2002 年之前那樣，
03:04
as they used to do up until about 2002,
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穿著防彈背心拿著探棒到處戳，
03:06
they now send the robot out.
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現在他們派機器人去
03:08
So the robot takes over the dangerous jobs.
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讓機器人負責這些危險的工作
03:10
On the right are some TUGs from a company called Aethon in Pittsburgh.
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在右邊是匹玆堡的一家名為 Aethon 的公司
生產的 TUG 機器人。
生產的 TUG 機器人。
03:15
These are in hundreds of hospitals across the U.S.
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全美近百家醫院正在使用這些機器人
03:17
And they take the dirty sheets down to the laundry.
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它們把床單送去洗衣房。
03:20
They take the dirty dishes back to the kitchen.
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把髒盤子送回廚房
03:21
They bring the medicines up from the pharmacy.
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從藥房取藥送給病人
03:24
And it frees up the nurses and the nurse's aides
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這使得護士和他們的助手
03:26
from doing that mundane work of just mechanically pushing stuff around
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從那些到處搬東西的機械化勞動中解放，
03:30
to spend more time with patients.
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花更多的時間的陪患者。
03:32
In fact, robots have become sort of ubiquitous in our lives in many ways.
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事實上，機器人已經普及在我們生活的很多層次。
03:37
But I think when it comes to factory robots, people are sort of afraid,
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但是如果談及工業機器人，人們可能還是會有些害怕的，
03:42
because factory robots are dangerous to be around.
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因為工業機器人有可能會傷及周圍的人。
03:46
In order to program them, you have to understand six-dimensional vectors and quaternions.
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如果要為它們設計程序，你需要理解六維向量和四元空間。
03:51
And ordinary people can't interact with them.
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一般人無法和它們溝通。
03:54
And I think it's the sort of technology that's gone wrong.
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我認為一旦科技完全取代了原本的工人
03:57
It's displaced the worker from the technology.
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這樣的科技就有問題了
04:00
And I think we really have to look at technologies
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我們確實需要思考一下如何讓工人
04:04
that ordinary workers can interact with.
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可以和這些高科技產物相互合作。
04:06
And so I want to tell you today about Baxter, which we've been talking about.
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所以今天我想聊聊我們曾經談到過的 Baxter 機器人。
04:09
And Baxter, I see, as a way -- a first wave of robot
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Baxter 在我看來是第一批
04:14
that ordinary people can interact with in an industrial setting.
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通過一些工業設定就可以和普通人互相溝通的機器人
04:18
So Baxter is up here.
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讓我們來看看 Baxter。
04:19
This is Chris Harbert from Rethink Robotics.
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這位是 Rethink Robotics 的克里斯·哈伯特
04:22
We've got a conveyor there.
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在這裡我們有一個輸送帶
04:24
And if the lighting isn't too extreme --
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如果亮度不是過高的話
04:27
Ah, ah! There it is. It's picked up the object off the conveyor.
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對了，對了。Baxter 從輸送帶上拿起了零件。
04:31
It's going to come bring it over here and put it down.
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接著它把零件拿過來放下。
04:34
And then it'll go back, reach for another object.
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然後再回去取下一個零件。
04:37
The interesting thing is Baxter has some basic common sense.
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有趣的是，Baxter 也具備一些基本的常識。
04:41
By the way, what's going on with the eyes?
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順帶一提，它的眼睛去哪兒了？
04:43
The eyes are on the screen there.
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眼睛在那邊的螢幕上。
04:44
The eyes look ahead where the robot's going to move.
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它會看著機器人要移動的方向。
04:47
So a person that's interacting with the robot
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因此和機器人一起工作的人
04:49
understands where it's going to reach and isn't surprised by its motions.
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可以明白機器人要移向哪裡
而不會被他的動向嚇到。
而不會被他的動向嚇到。
04:53
Here Chris took the object out of its hand,
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現在克里斯從它手裡拿走一個零件，
04:55
and Baxter didn't go and try to put it down;
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這時 Baxter 不會繼續嘗試將那零件移過去放下；
04:58
it went back and realized it had to get another one.
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它會返回原位，因為它意識到自己要去取下一個零件。
05:00
It's got a little bit of basic common sense, goes and picks the objects.
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在拿取和移動零件上Baxter已有了一些常識。
05:03
And Baxter's safe to interact with.
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同時與 Baxter 一起工作也是很安全的。
05:05
You wouldn't want to do this with a current industrial robot.
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你也許不會想和現在市面上的工業機器人一起工作。
05:08
But with Baxter it doesn't hurt.
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但是和Baxter一起是安全的
05:10
It feels the force, understands that Chris is there
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它能夠感覺阻力，從而明白克里斯在那裡。
05:14
and doesn't push through him and hurt him.
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它不會推他導致傷到他
05:17
But I think the most interesting thing about Baxter is the user interface.
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但是我認為 Baxter 最有意思的還是它的用戶界面。
05:20
And so Chris is going to come and grab the other arm now.
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現在克里斯要過去抓住它另一只手臂
05:23
And when he grabs an arm, it goes into zero-force gravity-compensated mode
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當他抓住一只手的時候，
Baxter 就進入了無動力重力補償模式，
Baxter 就進入了無動力重力補償模式，
05:29
and graphics come up on the screen.
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同時這樣的圖像出現在螢幕上
05:31
You can see some icons on the left of the screen there for what was about its right arm.
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你可以看到一些圖標出現在螢幕的右邊，
它們代表了 Baxter 的右臂。
它們代表了 Baxter 的右臂。
05:35
He's going to put something in its hand, he's going to bring it over here,
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他打算把那些東西放到這裡來，
05:38
press a button and let go of that thing in the hand.
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按下一個按鈕，然後讓它放下手裡的東西。
05:43
And the robot figures out, ah, he must mean I want to put stuff down.
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然後機器人明白了，“嗯，他一定是要我把這個東西放下”
05:48
It puts a little icon there.
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它在需要放零件的地方標了個圖標。
05:49
He comes over here, and he gets the fingers to grasp together,
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它把機器手移到這裡，併起它的手指，
05:55
and the robot infers, ah, you want an object for me to pick up.
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機器人明白克里斯要它撿起一個零件
05:59
That puts the green icon there.
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在那邊標一個綠色的圖標。
06:01
He's going to map out an area of where the robot should pick up the object from.
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克里斯現在要劃出一塊區域，
讓機器人從這塊區域裡取零件。
讓機器人從這塊區域裡取零件。
06:06
It just moves it around, and the robot figures out that was an area search.
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他只是把機械手臂到處移動，
機器人就明白這是一塊搜索區域。
機器人就明白這是一塊搜索區域。
06:11
He didn't have to select that from a menu.
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他不用在選單中選擇。
06:13
And now he's going to go off and train the visual appearance of that object
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他現在要離開一會兒，去教會機器人識別零件。
06:16
while we continue talking.
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現在我們繼續聊。
06:18
So as we continue here,
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說到這裡，
06:20
I want to tell you about what this is like in factories.
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我先要告訴你們這些機器人在工廠裡是怎麼工作的。
06:22
These robots we're shipping every day.
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這些每天運出的這些機器人，
06:23
They go to factories around the country.
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被送往遍佈全美的工廠。
06:25
This is Mildred.
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這位是米爾德里德。
06:26
Mildred's a factory worker in Connecticut.
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米爾德里德是康涅狄格的一名工人。
06:28
She's worked on the line for over 20 years.
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她在生產線上工作了20多年。
06:30
One hour after she saw her first industrial robot,
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就在她見到她生平的第一個工業機器人的一個小時以後，
06:33
she had programmed it to do some tasks in the factory.
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她就已經教會了這台機器人一些工廠裡的工作。
06:37
She decided she really liked robots.
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她確實非常喜歡機器人。
06:39
And it was doing the simple repetitive tasks that she had had to do beforehand.
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機器人正在做那些她之前不得不做的重複性工作。
06:44
Now she's got the robot doing it.
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現在機器人代替她做這些。
06:45
When we first went out to talk to people in factories
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在我們最開始走到工廠裡與那裡的人們談論
06:48
about how we could get robots to interact with them better,
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我們如何更好的讓機器人和他們合作時，
06:51
one of the questions we asked them was,
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我們問的其中一個問題是，
06:52
"Do you want your children to work in a factory?"
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“你想讓你的孩子在工廠工作嗎？”
06:55
The universal answer was "No, I want a better job than that for my children."
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所有答案都是，“不，我想我孩子有個更好的工作。”
06:59
And as a result of that, Mildred is very typical
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其結果是，米爾德里德就是現在美國一個很典型的
07:03
of today's factory workers in the U.S.
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工廠工人。
07:04
They're older, and they're getting older and older.
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他們都比較年長，並在不斷走向衰老。
07:07
There aren't many young people coming into factory work.
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很少有年輕人願意在工廠工作。
07:09
And as their tasks become more onerous on them,
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隨著他們肩負的工作變得日益繁重，
07:13
we need to give them tools that they can collaborate with,
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我們需要提供他們一些可以幫助他們的工具，
07:16
so that they can be part of the solution,
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使他們可以成為解決方案的一部分，
07:17
so that they can continue to work and we can continue to produce in the U.S.
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使他們可以繼續留在工作崗位上，
也是美國的製造業得以持續。
也是美國的製造業得以持續。
07:22
And so our vision is that Mildred who's the line worker
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所以我們期望米爾德里德可以從一個流水線工人
07:26
becomes Mildred the robot trainer.
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轉變為一個機器人教練。
07:29
She lifts her game,
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她改變了她的工作性質，
07:30
like the office workers of the 1980s lifted their game of what they could do.
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就如同上世紀 80 年代的辦公室一族一樣
07:35
We're not giving them tools that they have to go and study for years and years in order to use.
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我們不會提供他們那些需要花好幾年才能學會使用的工具。
07:39
They're tools that they can just learn how to operate in a few minutes.
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我們提供的工具只需幾分鐘就可以學會操作。
07:43
There's two great forces that are both volitional but inevitable.
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這世界上有兩種必須出現、無法避免的力量
07:47
That's climate change and demographics.
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那就是氣候變遷和人口變化
07:50
Demographics is really going to change our world.
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人口的轉變將確確實實的改變我們的世界。
07:52
This is the percentage of adults who are working age.
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這是處於工作年齡的成年人佔整體成年人數的百分比。
07:56
And it's gone down slightly over the last 40 years.
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在過去的40年中輕微的下跌
07:58
But over the next 40 years, it's going to change dramatically, even in China.
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但是在未來的40年，它將有顯著的變化，即便是在中國。
08:02
The percentage of adults who are working age drops dramatically.
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處於工作年齡的成年人比例將顯著下降。
08:08
And turned up the other way, the people who are retirement age goes up very, very fast,
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另一方面，隨著嬰兒潮一代逐步步入退休年齡，
08:13
as the baby boomers get to retirement age.
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處於退休年齡的人將越來越多。
08:17
That means there will be more people with fewer social security dollars
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那意味著將有更多的人需要服務
08:20
competing for services.
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社會福利的資金卻會減少
08:23
But more than that, as we get older we get more frail
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不止如此，隨著年齡的增長，我們將變得更加脆弱
08:27
and we can't do all the tasks we used to do.
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以至於我們沒辦法完成那些我們曾經可以做到的事情。
08:29
If we look at the statistics on the ages of caregivers,
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如果我們看一下社工的年齡統計數據，
08:33
before our eyes those caregivers are getting older and older.
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我們所看到的是這些社工正變得越來越年長。
08:38
That's happening statistically right now.
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而統計結果也正表明了這一點。
08:40
And as the number of people who are older, above retirement age and getting older, as they increase,
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隨著那些越發年邁的退休者的數量的增加，
08:46
there will be less people to take care of them.
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能夠照顧他們的人缺日趨減少。
08:48
And I think we're really going to have to have robots to help us.
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所以我們真切的感受到
我們不得不讓機器人去幫助他們。
我們不得不讓機器人去幫助他們。
08:50
And I don't mean robots in terms of companions.
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我並不是在說機器人伴侶。
08:53
I mean robots doing the things that we normally do for ourselves
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我指的是有機器人來做一些
一般我們可以自己完成
一般我們可以自己完成
08:57
but get harder as we get older.
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但隨著年齡增長變得艱難的日常瑣事。
08:58
Getting the groceries in from the car, up the stairs, into the kitchen.
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例如將食物從車裡搬出來，上樓搬進廚房。
09:01
Or even, as we get very much older,
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或者，等我們再老一點，
09:04
driving our cars to go visit people.
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開著車去見朋友。
09:07
And I think robotics gives people a chance to have dignity as they get older
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我認為通過控制機器人解決問題
09:13
by having control of the robotic solution.
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那些年邁的人將獲得更多尊嚴。
09:17
So they don't have to rely on people that are getting scarcer to help them.
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因此他們不用在依靠那些日漸稀缺的人們去幫助他們。
09:20
And so I really think that we're going to be spending more time
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我相信我們將與 Baxter 這樣的機器人
09:27
with robots like Baxter
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一起度過更多的時間
09:29
and working with robots like Baxter in our daily lives. And that we will --
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並在日常生活中與像 Baxter 這樣的機器人合作。
09:36
Here, Baxter, it's good.
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看，Baxter，它很不錯。
09:38
And that we will all come to rely on robots over the next 40 years
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在接下來的40年中
我們都會需要依賴機器人
我們都會需要依賴機器人
09:43
as part of our everyday lives.
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它將成為我們日常生活的一部分
09:45
Thanks very much.
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謝謝各位
09:46
(Applause)
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（掌聲）
ABOUT THE SPEAKER
Rodney Brooks - RoboticistRodney Brooks builds robots based on biological principles of movement and reasoning. The goal: a robot who can figure things out.
Why you should listen
Former MIT professor Rodney Brooks studies and engineers robot intelligence, looking for the holy grail of robotics: the AGI, or artificial general intelligence. For decades, we've been building robots to do highly specific tasks -- welding, riveting, delivering interoffice mail -- but what we all want, really, is a robot that can figure things out on its own, the way we humans do.
Brooks realized that a top-down approach -- just building the biggest brain possible and teaching it everything we could think of -- would never work. What would work is a robot who learns like we do, by trial and error, and with many separate parts that learn separate jobs. The thesis of his work which was captured in Fast, Cheap and Out of Control,went on to become the title of the great Errol Morris documentary.
A founder of iRobot, makers of the Roomba vacuum, Brooks is now founder and CTO of Rethink Robotics, whose mission is to apply advanced robotic intelligence to manufacturing and physical labor. Its first robots: the versatile two-armed Baxter and one-armed Sawyer. Brooks is the former director of CSAIL, MIT's Computers Science and Artificial Intelligence Laboratory.
Rodney Brooks | Speaker | TED.com