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譯者: Lilian Chiu
審譯者: Yanyan Hong
00:12
I'm going to talk about
how AI and mankind can coexist,
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我將要談的是人類
和人工智慧要如何共存,
00:17
but first, we have to rethink
about our human values.
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但首先,我們先要
重新審視人類的價值觀。
00:21
So let me first make a confession
about my errors in my values.
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讓我先坦誠我在
我的價值觀中所犯的錯誤。
00:25
It was 11 o'clock, December 16, 1991.
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那是 1991 年 12 月 16 日 11 點。
00:30
I was about to become a father
for the first time.
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我就要成為一個新手爸爸了。
00:33
My wife, Shen-Ling,
lay in the hospital bed
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我的太太先玲躺在醫院的病床上,
00:36
going through a very difficult
12-hour labor.
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經歷著一段艱辛
並長達十二個小時的分娩。
00:40
I sat by her bedside
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我就坐在床邊,
00:42
but looked anxiously at my watch,
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但很焦慮地看著我的手錶,
00:45
and I knew something that she didn't.
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我知道一件她不知道的事。
00:47
I knew that if in one hour,
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我知道,如果一個小時內,
00:50
our child didn't come,
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我們的孩子還不出來,
00:52
I was going to leave her there
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我就得要把她丟在那裡,
00:54
and go back to work
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回去工作,
00:55
and make a presentation about AI
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去做一場關於人工智慧的簡報,
00:58
to my boss, Apple's CEO.
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對象是我的老闆,蘋果的執行長。
01:03
Fortunately, my daughter
was born at 11:30 --
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幸運的是,我女兒
在 11:30 出生了——
01:07
(Laughter)
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(笑聲)
01:09
(Applause)
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(掌聲)
01:11
sparing me from doing the unthinkable,
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讓我不用去做我無法想像的事,
01:15
and to this day, I am so sorry
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至今,我仍然很後悔
01:17
for letting my work ethic
take precedence over love for my family.
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我把工作擺在了我對家人的愛之前。
01:22
(Applause)
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(掌聲)
01:28
My AI talk, however, went off brilliantly.
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然而,我的人工智慧演說表現超好。
01:30
(Laughter)
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(笑聲)
01:33
Apple loved my work
and decided to announce it
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蘋果很愛我的作品,
01:36
at TED1992,
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決定在 TED 1992 宣佈它,
01:39
26 years ago on this very stage.
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26 年前,就在這個舞台上。
01:42
I thought I had made one of the biggest,
most important discoveries in AI,
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我認為我在人工智慧上
有了最大、最重要的發現,
01:47
and so did the "Wall Street Journal"
on the following day.
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隔天的《華爾街日報》也這麼認為。
01:51
But as far as discoveries went,
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但隨著越來越多的「發現」,
01:54
it turned out,
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結果是,
01:55
I didn't discover India, or America.
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我沒有發現印度,或美洲。
01:58
Perhaps I discovered
a little island off of Portugal.
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也許我發現的是
葡萄牙外海的一個小島。
02:02
But the AI era of discovery continued,
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但人工智慧發現的時代
仍然繼續走下去了,
02:06
and more scientists
poured their souls into it.
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更多的科學家
全心全意地投入其中。
02:09
About 10 years ago, the grand AI discovery
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大約十年前,三位北美科學家
02:11
was made by three
North American scientists,
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有了偉大的人工智慧發現,
02:15
and it's known as deep learning.
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即大家所知的深度學習。
02:17
Deep learning is a technology
that can take a huge amount of data
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深度學習這項技術,
是一個能利用海量數據
02:21
within one single domain
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在單一領域中
02:22
and learn to predict or decide
at superhuman accuracy.
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學會做超高精度的預測或判斷的技術。
02:27
For example, if we show
the deep learning network
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比如,如果我們給深度學習網路
02:30
a massive number of food photos,
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提供海量的食物照片,
02:33
it can recognize food
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它就能辨識出食物,
02:35
such as hot dog or no hot dog.
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比如熱狗,或不是熱狗。
02:38
(Applause)
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(掌聲)
02:41
Or if we show it many pictures
and videos and sensor data
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或者,如果我讓它看很多
在公路上開車的照片、
02:46
from driving on the highway,
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影片,以及感測器資料,
02:49
it can actually drive a car
as well as a human being
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它就能夠在高速公路上
嫺熟地駕駛一台車,
絲毫不輸給人類。
02:53
on the highway.
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02:55
And what if we showed
this deep learning network
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如果我們向這個深度學習網路展示
02:57
all the speeches made by President Trump?
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川普總統做過的所有演說呢?
03:01
Then this artificially
intelligent President Trump,
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那麼,這位人工智慧的川普總統,
03:05
actually the network --
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其實就是這個網路——
03:07
(Laughter)
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(笑聲)
03:09
can --
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能夠——
03:10
(Applause)
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(掌聲)
03:14
You like double oxymorons, huh?
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你們喜歡一語雙關,是吧?
03:17
(Laughter)
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(笑聲)
(註:artificial 也是「虛假造作的」)
03:21
(Applause)
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(掌聲)
03:27
So this network, if given the request
to make a speech about AI,
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所以,如果要求這個網路
做出一段關於人工智慧的演說,
03:32
he, or it, might say --
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他,或它,可能會說——
03:36
(Recording) Donald Trump:
It's a great thing
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(錄音)川普:這是很棒的事,
03:38
to build a better world
with artificial intelligence.
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用人工智慧來建造一個更好的世界。
03:41
Kai-Fu Lee: And maybe in another language?
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講者:換個語言呢?
03:43
DT: (Speaking Chinese)
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川普:(說中文)
人工智能正在改變世界。
03:45
(Laughter)
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(笑聲)
03:46
KFL: You didn't know
he knew Chinese, did you?
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講者:你們不知道川普會說中文吧?
03:50
So deep learning has become the core
in the era of AI discovery,
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所以,深度學習已經成為
人工智慧發現時代的核心,
03:55
and that's led by the US.
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且是由美國來領導的。
03:57
But we're now in the era
of implementation,
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但現在,我們已經進入實踐的時代,
04:00
where what really matters is execution,
product quality, speed and data.
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在這個時代,重要的是執行、
產品品質、速度,和資料。
04:05
And that's where China comes in.
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這就是中國出場的時候了。
04:07
Chinese entrepreneurs,
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身為創業投資家,
04:09
who I fund as a venture capitalist,
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我投資的中國企業家
04:11
are incredible workers,
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是很棒的實幹家,
04:13
amazing work ethic.
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有很了不起的職業道德。
04:15
My example in the delivery room is nothing
compared to how hard people work in China.
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我在產房的那個例子,
完全不及中國人們賣力工作的程度。
04:20
As an example, one startup
tried to claim work-life balance:
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舉個例子,有間新興公司
提出「工作—生活」的平衡:
04:24
"Come work for us because we are 996."
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「來為我們工作,因為我們是 996。」
04:27
And what does that mean?
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那是什麼意思?
04:29
It means the work hours
of 9am to 9pm, six days a week.
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意思是,工作時間從早上 9 點
到晚上 9 點,一週工作 6 天。
04:34
That's contrasted
with other startups that do 997.
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相對的,其他新興公司都是 997。
04:39
And the Chinese product quality
has consistently gone up
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而中國的產品品質
在過去十年間持續不斷地提升,
04:42
in the past decade,
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04:44
and that's because of
a fiercely competitive environment.
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那是因為這個環境中的
競爭太激烈了。
04:48
In Silicon Valley, entrepreneurs
compete in a very gentlemanly fashion,
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在矽谷,企業家會
以很紳仕的方式競爭,
04:54
sort of like in old wars
in which each side took turns
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有點像是古老的戰爭,雙方會輪流
04:58
to fire at each other.
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向對方開火。
04:59
(Laughter)
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(笑聲)
05:00
But in the Chinese environment,
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但在中國的環境中,
05:03
it's truly a gladiatorial
fight to the death.
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就像是羅馬競技場,
不死不休的戰鬥。
05:06
In such a brutal environment,
entrepreneurs learn to grow very rapidly,
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在這麼殘酷的環境中,
企業家學會要非常快速地成長,
05:13
they learn to make their products
better at lightning speed,
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他們學會要雷厲風行地
讓自己的產品變更好,
05:17
and they learn
to hone their business models
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他們學會要一直鍛鍊
他們的商業模型,
05:19
until they're impregnable.
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直到堅不可摧為止。
05:21
As a result, great Chinese products
like WeChat and Weibo
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結果就是,優秀的中國產品,
如微信和微博,
05:25
are arguably better
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可以說比美國
05:26
than the equivalent American products
from Facebook and Twitter.
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相對應產品,
如臉書和推特,還要好。
05:31
And the Chinese market
embraces this change
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且中國市場擁抱這樣的改變、
05:35
and accelerated change
and paradigm shifts.
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加速的改變,以及範式轉移。
05:38
As an example, if any of you go to China,
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舉個例,如果你去中國,
05:40
you will see it's almost cashless
and credit card-less,
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你會發現幾乎沒有
在用現金或是信用卡,
05:44
because that thing that we all
talk about, mobile payment,
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原因就是我們大家都在談的
那樣東西,移動支付,
05:47
has become the reality in China.
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在中國已經實現。
05:49
In the last year,
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去年,
05:50
18.8 trillion US dollars
were transacted on mobile internet,
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行動網路上的交易金額
達到 18.8 兆美元,
05:56
and that's because
of very robust technologies
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那是因為在行動支付背後的技術
05:59
built behind it.
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非常穩定健全。
06:00
It's even bigger than the China GDP.
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這個數字比中國的國內生產總值還高。
06:04
And this technology, you can say,
how can it be bigger than the GDP?
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你會問,這項技術怎麼可能
超越國內生產總值?
06:07
Because it includes all transactions:
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因為它包含所有的交易:
06:09
wholesale, channels,
retail, online, offline,
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批發、電視台、零售、線上、線下、
06:13
going into a shopping mall
or going into a farmers market like this.
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到購物中心去買,
或到像這樣的農民市場去買。
06:18
The technology is used
by 700 million people
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有 7 億人使用移動支付
06:22
to pay each other, not just merchants,
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來付錢給彼此,不只付錢給商人,
06:24
so it's peer to peer,
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所以,它是點對點的,
06:25
and it's almost transaction-fee-free.
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且幾乎不需要交易手續費。
06:29
And it's instantaneous,
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且是立即生效,
06:32
and it's used everywhere.
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到處都在使用。
06:34
And finally, the China market is enormous.
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最後一點,中國的市場很巨大。
06:37
This market is large,
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這個市場很大,
06:39
which helps give entrepreneurs
more users, more revenue,
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讓企業家能有更多的
使用者、更多的收益、
06:44
more investment, but most importantly,
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更多的投資,最重要的是,
06:46
it gives the entrepreneurs a chance
to collect a huge amount of data
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它讓企業家有機會
能收集到大量的數據資料,
06:51
which becomes rocket fuel
for the AI engine.
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這些資料就成了
人工智慧引擎的火箭燃料。
06:54
So as a result, the Chinese AI companies
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結果就是,中國的人工智慧公司
06:57
have leaped ahead
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已經大躍進,跳到前頭,
06:59
so that today, the most valuable companies
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所以,現今,最有價值的公司,
07:02
in computer vision, speech recognition,
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不論是在電腦視覺、語音識別、
07:05
speech synthesis,
machine translation and drones
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語音合成、機器翻譯,
及無人機的領域,
07:08
are all Chinese companies.
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都是中國公司稱霸。
07:11
So with the US leading
the era of discovery
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美國領導的是發現的時代,
07:14
and China leading
the era of implementation,
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而中國領導的是導入的時代,
07:17
we are now in an amazing age
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我們現在身處一個很了不起的時代,
07:20
where the dual engine
of the two superpowers
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這兩種超能力的雙重引擎
07:23
are working together
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在同心協力,
07:25
to drive the fastest
revolution in technology
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在科技領域中,
推動我們人類所見過
07:29
that we have ever seen as humans.
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最快速的革命。
07:32
And this will bring tremendous wealth,
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這會帶來驚人的財富,
07:35
unprecedented wealth:
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前所未有的財富:
07:36
16 trillion dollars, according to PwC,
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根據普華永道會計師事務所的資料,
07:40
in terms of added GDP
to the worldwide GDP by 2030.
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到 2030 年,全世界的國內生產總值
會增加 16 兆美元。
07:46
It will also bring immense challenges
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這也會帶來極大的挑戰:
07:48
in terms of potential job replacements.
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潛在的工作取代性問題。
07:52
Whereas in the Industrial Age
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在工業時代,
07:55
it created more jobs
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它創造了更多的工作,
07:57
because craftsman jobs were being
decomposed into jobs in the assembly line,
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因為技工的工作被重新
分解成為生產線的工作,
08:03
so more jobs were created.
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所以創造了更多的工作。
08:05
But AI completely replaces
the individual jobs
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但人工智慧完全取代了個人的工作,
08:10
in the assembly line with robots.
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在生產線上直接用機器人。
08:12
And it's not just in factories,
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且不只是在工廠,
08:14
but truckers, drivers
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還有貨車司機、一般司機,
08:16
and even jobs like telesales,
customer service
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甚至像電話銷售、客戶服務、
08:20
and hematologists as well as radiologists
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血液學學者,以及放射線研究者
08:23
over the next 15 years
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在未來十五年
08:25
are going to be gradually replaced
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都可能漸漸被
08:28
by artificial intelligence.
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人工智慧取代。
08:30
And only the creative jobs --
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只有有創意的工作——
08:32
(Laughter)
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(笑聲)
(表中講者被列在「安全」)
08:34
I have to make myself safe, right?
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我得讓我自己很安全,對吧?
08:38
Really, the creative jobs
are the ones that are protected,
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說真的,有創意的工作
是受到保護的工作,
08:41
because AI can optimize but not create.
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因為人工智慧能夠
做到最佳化,但不能創造。
08:45
But what's more serious
than the loss of jobs
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但比失去工作更嚴重的,
08:49
is the loss of meaning,
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是失去意義,
08:51
because the work ethic
in the Industrial Age
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因為在工業時代的工作倫理
08:54
has brainwashed us into thinking
that work is the reason we exist,
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已經將我們洗腦,
認為工作是我們存在的理由,
09:00
that work defined
the meaning of our lives.
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認為工作定義了我們人生的意義。
09:03
And I was a prime and willing victim
to that type of workaholic thinking.
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我就曾是那種工作狂思想的
主要受害者,也是自願受害者。
09:09
I worked incredibly hard.
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我工作非常努力。
09:11
That's why I almost left
my wife in the delivery room,
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那就是為什麼在產房時
我差一點就要丟下我太太,
09:14
that's why I worked 996
alongside my entrepreneurs.
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那就是為什麼我和我的
企業家們的工作時間是 996。
09:18
And that obsession that I had with work
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我先前對於工作的這種迷戀,
09:23
ended abruptly a few years ago
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在幾年前突然終止了,
09:26
when I was diagnosed
with fourth stage lymphoma.
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因為我被診斷出第四期的淋巴癌。
09:31
The PET scan here shows
over 20 malignant tumors
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這裡的正子掃描結果顯示
有超過 20 個惡性腫瘤
09:35
jumping out like fireballs,
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像火球一樣跳出來,
09:37
melting away my ambition.
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融化了我的野心。
09:40
But more importantly,
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但,更重要的是,
09:41
it helped me reexamine my life.
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它讓我重新檢視我的人生。
09:44
Knowing that I may only have
a few months to live
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知道我可能只剩下幾個月能活,
09:47
caused me to see how foolish it was
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讓我看清了我有多愚蠢,
09:50
for me to base my entire self-worth
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因為我把我的整個自我價值
09:54
on how hard I worked
and the accomplishments from hard work.
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建立在工作努力程度上,
以及努力帶來的成就上。
09:59
My priorities were
completely out of order.
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我的優先順序完全錯亂。
10:02
I neglected my family.
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我忽視了我的家庭。
10:05
My father had passed away,
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我父親已經過世,
10:06
and I never had a chance
to tell him I loved him.
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我從來沒有機會告訴他我愛他。
10:10
My mother had dementia
and no longer recognized me,
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我母親有失智症,已經不認得我,
10:13
and my children had grown up.
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我的孩子已經長大。
10:16
During my chemotherapy,
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在我做化療期間,
10:18
I read a book by Bronnie Ware
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我讀了一本布羅妮韋爾寫的書,
10:20
who talked about dying wishes and regrets
of the people in the deathbed.
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談到臨終的人的死前願望和悔恨。
10:26
She found that facing death,
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她發現,面對死亡時,
10:28
nobody regretted that they didn't
work hard enough in this life.
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沒有人後悔這一生的
工作不夠努力。
10:32
They only regretted that they didn't
spend enough time with their loved ones
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他們只會後悔沒有花
足夠時間陪他們愛的人,
10:38
and that they didn't spread their love.
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沒有把他們的愛散播出去。
10:42
So I am fortunately today in remission.
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現在,我很幸運處於緩解期。
10:46
(Applause)
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(掌聲)
10:53
So I can be back at TED again
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所以我能再次回到 TED,
10:55
to share with you
that I have changed my ways.
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和各位分享,
我已經改變了我的方式。
10:59
I now only work 965 --
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我現在的工作方式是 965 ——
11:03
occasionally 996, but usually 965.
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偶爾是 996,但通常是 965。
11:07
I moved closer to my mother,
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我搬到離我母親比較近的地方,
11:09
my wife usually travels with me,
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我太太通常與我一同旅行,
11:11
and when my kids have vacation,
if they don't come home, I go to them.
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當我的孩子有假期時,
若他們不回家,我會去找他們。
11:15
So it's a new form of life
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這是一種新的生活形式,
11:17
that helped me recognize
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協助我了解到
11:19
how important it is that love is for me,
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愛對我而言有多重要,
11:22
and facing death
helped me change my life,
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面對死亡,協助我改變了我的生活,
11:26
but it also helped me see a new way
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也協助我找到了一種新的方式,
11:28
of how AI should impact mankind
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看待人工智慧對於人類的衝擊,
11:32
and work and coexist with mankind,
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以及如何和人類合作與共存,
11:36
that really, AI is taking away
a lot of routine jobs,
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確實,人工智慧會奪走
很多例行性的工作,
11:41
but routine jobs are not what we're about.
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但我們並不只會做例行性的工作。
11:44
Why we exist is love.
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我們存在的目的是愛。
11:47
When we hold our newborn baby,
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當我們抱著新生的嬰兒,
11:49
love at first sight,
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第一眼就產生了愛,
11:50
or when we help someone in need,
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當我們協助了需要幫忙的人,
11:52
humans are uniquely able
to give and receive love,
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人類能給予愛和接收愛,
這是獨一無二的,
11:56
and that's what differentiates us from AI.
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這就是我們和人工智慧的差別。
12:00
Despite what science fiction may portray,
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不論科幻小說怎麼寫,
12:03
I can responsibly tell you
that AI has no love.
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我可以很確定地告訴各位,
人工智慧沒有愛。
12:07
When AlphaGo defeated
the world champion Ke Jie,
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當 AlphaGo 打敗世界冠軍柯潔,
12:10
while Ke Jie was crying
and loving the game of go,
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當柯潔在哭泣,他很愛圍棋比賽,
12:13
AlphaGo felt no happiness from winning
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AlphaGo 卻不會感到勝利的喜悅,
12:17
and certainly no desire
to hug a loved one.
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肯定也不會想要去擁抱愛人。
12:23
So how do we differentiate ourselves
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所以,在人工智慧的時代,
12:26
as humans in the age of AI?
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我們要如何讓人類有所不同?
12:28
We talked about the axis of creativity,
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我們剛有談到「創意」這個軸,
12:31
and certainly that is one possibility,
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那肯定是其中一種可能性,
12:34
and now we introduce a new axis
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現在,我們要再介紹一個新的軸,
12:37
that we can call compassion,
love, or empathy.
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我們可以稱之為
同情心、愛,或是同理心。
12:40
Those are things that AI cannot do.
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那些是人工智慧做不到的。
12:43
So as AI takes away the routine jobs,
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所以,當人工智慧奪走
例行性的工作時,
12:46
I like to think we can, we should
and we must create jobs of compassion.
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我會認為 ,我們能夠、應該而且必須
創造出同情心相關的工作。
12:51
You might ask how many of those there are,
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你可能會問,這類工作有多少個?
12:54
but I would ask you:
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但我會反問你:
12:55
Do you not think that we are going
to need a lot of social workers
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你不認為我們會需要很多社工
12:59
to help us make this transition?
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來協助我們做這項轉變嗎?
13:01
Do you not think we need
a lot of compassionate caregivers
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你不認為我們會需要
很多有同情心的照護者
13:05
to give more medical care to more people?
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來給予更多人醫療照護嗎?
13:07
Do you not think we're going to need
10 times more teachers
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你不認為我們會需要十倍的老師
13:11
to help our children find their way
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來協助我們的孩子找到他們的路,
13:14
to survive and thrive
in this brave new world?
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在這個勇敢的新世界中
存活並茁壯嗎?
13:17
And with all the newfound wealth,
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且當有這麼多新的財富產生時,
13:19
should we not also make
labors of love into careers
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我們不應該創造以人性為本的職業,
13:24
and let elderly accompaniment
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把陪伴老人,
13:27
or homeschooling become careers also?
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或是居家教育也變成職業嗎?
13:30
(Applause)
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(掌聲)
13:36
This graph is surely not perfect,
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這張圖的確不完美,
13:39
but it points at four ways
that we can work with AI.
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但它能展示出我們
和人工智慧合作的四種方式。
13:42
AI will come and take away
the routine jobs
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人工智慧會到來,
也會奪走例行性的工作,
13:46
and in due time, we will be thankful.
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到時,我們會很感激。
13:49
AI will become great tools
for the creatives
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對有創意的人,
人工智慧會變成很棒的工具,
13:52
so that scientists, artists,
musicians and writers
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讓科學家、藝術家、音樂家及作家
13:55
can be even more creative.
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都更有創意。
13:58
AI will work with humans
as analytical tools
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人工智慧也會扮演
分析工具的角色來和人類合作,
14:03
that humans can wrap their warmth around
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對於高同情心的工作,
14:06
for the high-compassion jobs.
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人類可以將溫暖傾注其中。
14:08
And we can always differentiate ourselves
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我們還有方式讓我們自己不同,
14:10
with the uniquely capable jobs
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就是通過參與需要獨特能力的工作,
14:12
that are both compassionate and creative,
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要有同情心又要有創意,
14:16
using and leveraging
our irreplaceable brains and hearts.
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充分利用和發揮
我們無可替代的頭腦和内心,
14:21
So there you have it:
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所以,這就是:
14:22
a blueprint of coexistence
for humans and AI.
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人類和人工智慧共存的藍圖。
14:27
AI is serendipity.
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人工智慧的發展是種機緣。
14:29
It is here to liberate us
from routine jobs,
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它的出現將我們
從例行性的工作中解放出來,
14:32
and it is here to remind us
what it is that makes us human.
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它也是來提醒我們,人因何為人。
14:36
So let us choose to embrace AI
and to love one another.
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所以,讓我們選擇
擁抱人工智慧,並去關愛彼此吧。
14:40
Thank you.
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謝謝。
14:41
(Applause)
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(掌聲)
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