TED2017
Martin Ford: How we'll earn money in a future without jobs
馬丁福德: 在沒有工作的未來，我們要如何賺錢？
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能思考、學習、適應的機器要來了－那可能意味著，會有大量人類失業。我們要怎麼辦？未來學家馬丁福德在這場關於一個爭議想法的坦率演說中，說明了將收入和傳統工作分離開，並制定全體基本收入的好處。
Martin Ford - Futurist
Martin Ford imagines what the accelerating progress in robotics and artificial intelligence may mean for the economy, job market and society of the future. Full bio
Martin Ford imagines what the accelerating progress in robotics and artificial intelligence may mean for the economy, job market and society of the future. Full bio
Double-click the English transcript below to play the video.
00:12
I'm going to begin with a scary question:
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一開始，我想先
提出一個駭人的問題：
提出一個駭人的問題：
00:15
Are we headed toward
a future without jobs?
a future without jobs?
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我們是否正在邁向
一個沒有工作的未來？
一個沒有工作的未來？
00:18
The remarkable progress that we're seeing
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我們看到科技的驚人進展，
00:21
in technologies like self-driving cars
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比如自動駕駛的汽車，
00:22
has led to an explosion
of interest in this question,
of interest in this question,
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讓很多人注意到我剛問的問題，
00:26
but because it's something
that's been asked
that's been asked
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但因為在過去這個問題
已經被問過太多次了，
00:28
so many times in the past,
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00:29
maybe what we should really be asking
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也許我們真正該問的是，
00:31
is whether this time is really different.
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這次是否真的會有所不同？
00:35
The fear that automation
might displace workers
might displace workers
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恐懼自動化會取代工人，
00:38
and potentially lead
to lots of unemployment
to lots of unemployment
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並可能會導致許多人失業，
00:40
goes back at a minimum 200 years
to the Luddite revolts in England.
to the Luddite revolts in England.
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可追溯回至少兩百年前的
盧德（勒德）份子運動。
盧德（勒德）份子運動。
00:44
And since then, this concern
has come up again and again.
has come up again and again.
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從那之後，這種擔憂就
一而再再而三地出現。
一而再再而三地出現。
00:47
I'm going to guess
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我猜測，
00:48
that most of you have probably never
heard of the Triple Revolution report,
heard of the Triple Revolution report,
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在座大部份人可能從來沒有
聽過「三重革命」報告，
聽過「三重革命」報告，
00:53
but this was a very prominent report.
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但它是份非常重要的報告。
00:55
It was put together
by a brilliant group of people --
by a brilliant group of people --
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它是由一群聰明人集思廣義出來的，
00:58
it actually included
two Nobel laureates --
two Nobel laureates --
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實際上還包括兩名諾貝爾得主，
01:01
and this report was presented
to the President of the United States,
to the President of the United States,
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這份報告被呈交給美國總統，
01:04
and it argued that the US was on the brink
of economic and social upheaval
of economic and social upheaval
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報告指出，美國正處在
經濟和社會動亂的邊緣，
經濟和社會動亂的邊緣，
01:09
because industrial automation
was going to put millions of people
was going to put millions of people
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因為工業自動化
將會讓數百萬人失去工作。
01:13
out of work.
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01:14
Now, that report was delivered
to President Lyndon Johnson
to President Lyndon Johnson
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那份報告被呈交給詹森總統，
01:17
in March of 1964.
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當時是 1964 年三月。
01:19
So that's now over 50 years,
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那是至少五十年以前的事，
01:21
and, of course, that
hasn't really happened.
hasn't really happened.
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當然，報告說的狀況沒有發生。
01:24
And that's been the story again and again.
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那故事從此不斷重覆上演。
01:26
This alarm has been raised repeatedly,
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警報不斷重覆被發出，
01:28
but it's always been a false alarm.
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但每次都是假警報。
01:30
And because it's been a false alarm,
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因為一直都是假警報，
01:32
it's led to a very conventional way
of thinking about this.
of thinking about this.
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就導致對這狀況的慣性思維。
01:35
And that says essentially that yes,
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基本上，那思維是：
01:37
technology may devastate
entire industries.
entire industries.
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對啊，科技可能會破壞所有產業，
01:40
It may wipe out whole occupations
and types of work.
and types of work.
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它有可能會徹底消滅
所有職業和各種工作；
所有職業和各種工作；
01:43
But at the same time, of course,
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但同時，當然，
01:45
progress is going to lead
to entirely new things.
to entirely new things.
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進步也會引來全新的事物。
01:47
So there will be new industries
that will arise in the future,
that will arise in the future,
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所以將來會有新的產業出現，
01:50
and those industries, of course,
will have to hire people.
will have to hire people.
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而那些產業，當然，一定會僱用人。
01:53
There'll be new kinds of work
that will appear,
that will appear,
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將來會出現新類型的工作會，
01:56
and those might be things that today
we can't really even imagine.
we can't really even imagine.
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可能是我們現今無法想像的。
01:59
And that has been the story so far,
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目前為止，故事一直是如此，
02:01
and it's been a positive story.
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且一直是很正面的。
02:03
It turns out that the new jobs
that have been created
that have been created
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結果，新創造出來的工作，
02:06
have generally been
a lot better than the old ones.
a lot better than the old ones.
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一般來說，比舊的工作好很多。
02:08
They have, for example,
been more engaging.
been more engaging.
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比如，新的工作比較吸引人。
02:11
They've been in safer,
more comfortable work environments,
more comfortable work environments,
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工作環境比較安全、比較舒適，
02:15
and, of course, they've paid more.
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當然，薪水也比較高。
02:16
So it has been a positive story.
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所以這個故事一直很正面。
02:18
That's the way things
have played out so far.
have played out so far.
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目前為止的發展也的確是這樣。
02:21
But there is one particular
class of worker
class of worker
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但特別有一類的工作者，
02:24
for whom the story
has been quite different.
has been quite different.
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對他們來說，故事相當不同。
02:27
For these workers,
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對這些工作者而言，
02:29
technology has completely
decimated their work,
decimated their work,
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科技可說是大舉毀滅了他們的工作，
02:32
and it really hasn't created
any new opportunities at all.
any new opportunities at all.
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且完全沒有再創造出
新的機會給他們。
新的機會給他們。
02:35
And these workers, of course,
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當然，這些工作者
02:37
are horses.
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是馬。
02:38
(Laughter)
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（笑聲）
02:40
So I can ask a very provocative question:
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我問一個會引發爭議的問題：
02:43
Is it possible that at some
point in the future,
point in the future,
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有沒有可能，在未來的某個時點，
02:46
a significant fraction of the human
workforce is going to be made redundant
workforce is going to be made redundant
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將有一大部份的人類勞動力過剩，
02:51
in the way that horses were?
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就像馬所遭遇的情況。
02:53
Now, you might have a very visceral,
reflexive reaction to that.
reflexive reaction to that.
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對那個問題，你可能會有
很本能、反射性的反應。
很本能、反射性的反應。
02:56
You might say, "That's absurd.
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你也許會說：「太荒唐了。
02:58
How can you possibly compare
human beings to horses?"
human beings to horses?"
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你怎麼能把人類拿來和馬做比較？」
03:02
Horses, of course, are very limited,
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當然，馬非常受限，
03:04
and when cars and trucks
and tractors came along,
and tractors came along,
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當汽車、卡車、牽引機
（拖拉機）出現，
（拖拉機）出現，
03:07
horses really had nowhere else to turn.
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馬就無處可去了。
03:09
People, on the other hand,
are intelligent;
are intelligent;
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另一方面，人有智慧；
03:12
we can learn, we can adapt.
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我們能學習，我們能適應。
03:14
And in theory,
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理論上，
03:15
that ought to mean that we can
always find something new to do,
always find something new to do,
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那應該意味著
我們總能找到新的事情來做，
我們總能找到新的事情來做，
03:18
and that we can always remain
relevant to the future economy.
relevant to the future economy.
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我們總能與未來的經濟持續相關。
03:21
But here's the really
critical thing to understand.
critical thing to understand.
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但要了解非常重要的一點。
03:24
The machines that will threaten
workers in the future
workers in the future
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在未來會威脅到工作者的機器，
03:27
are really nothing like those cars
and trucks and tractors
and trucks and tractors
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完全不像取代了馬的汽車、
03:30
that displaced horses.
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卡車、牽引機。
03:32
The future is going to be full
of thinking, learning, adapting machines.
of thinking, learning, adapting machines.
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未來將會滿是會思考、
學習、適應的機器。
學習、適應的機器。
03:37
And what that really means
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那意味著，
03:38
is that technology is finally
beginning to encroach
beginning to encroach
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科技最終將會開始侵犯到
03:41
on that fundamental human capability --
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基礎的人類能力──
03:44
the thing that makes us
so different from horses,
so different from horses,
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讓我們和馬大不相同的能力，
03:47
and the very thing that, so far,
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也是這能力，讓我們目前為止
03:49
has allowed us to stay ahead
of the march of progress
of the march of progress
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能走在這進步發展的前端
03:52
and remain relevant,
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並保有相關性，
03:53
and, in fact, indispensable
to the economy.
to the economy.
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事實上，也讓經濟少不了我們。
03:58
So what is it that is really so different
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所以，相對於我們過去所看到的，
04:00
about today's information technology
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現今的資訊科技到底
04:02
relative to what we've seen in the past?
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有什麼如此不同的地方？
04:04
I would point to three fundamental things.
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我要指出根本的三樣。
04:07
The first thing is that we have seen
this ongoing process
this ongoing process
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第一，我們已見到這正在進行的過程
04:12
of exponential acceleration.
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以指數級的速率加速。
04:14
I know you all know about Moore's law,
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我知道你們都明白摩爾定律，
04:16
but in fact, it's more
broad-based than that;
broad-based than that;
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但事實上，它的根基還要更廣；
（註：不止適用於積體電路）
（註：不止適用於積體電路）
04:18
it extends in many cases,
for example, to software,
for example, to software,
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在許多情況下，它會延伸，
比如，延伸到軟體，
比如，延伸到軟體，
04:22
it extends to communications,
bandwidth and so forth.
bandwidth and so forth.
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它也會延伸到通訊、頻寬、等等。
04:25
But the really key thing to understand
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但，需要了解的關鍵點是，
04:27
is that this acceleration has now
been going on for a really long time.
been going on for a really long time.
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這種加速現象已經
發生很長一段時間了。
發生很長一段時間了。
04:30
In fact, it's been going on for decades.
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事實上，已經有數十年了。
04:32
If you measure from the late 1950s,
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如果從 1950 年代末期開始算，
04:35
when the first integrated
circuits were fabricated,
circuits were fabricated,
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當第一個積體電路被製造出來，
04:38
we've seen something on the order
of 30 doublings in computational power
of 30 doublings in computational power
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從那時起，
我們目睹電腦運算的效能
倍增了大約三十次。
倍增了大約三十次。
04:42
since then.
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04:44
That's just an extraordinary number
of times to double any quantity,
of times to double any quantity,
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不論起初的量是多少，
倍增了那麼多次都是很可觀的。
倍增了那麼多次都是很可觀的。
04:47
and what it really means
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它真正的意涵是，
04:49
is that we're now at a point
where we're going to see
where we're going to see
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我們正處在一個時點，
即將要看到很大量的絕對進展，
04:51
just an extraordinary amount
of absolute progress,
of absolute progress,
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04:54
and, of course, things are going
to continue to also accelerate
to continue to also accelerate
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當然，這個時間點之後的加速
還是會持續下去。
04:57
from this point.
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04:58
So as we look forward
to the coming years and decades,
to the coming years and decades,
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所以當我們期待未來的
幾年及幾十年，
幾年及幾十年，
我們將會看到
05:00
I think that means
that we're going to see things
that we're going to see things
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我們完全沒準備會看到的事物，
05:03
that we're really not prepared for.
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我們將會看到讓我們吃驚的事物。
05:04
We're going to see things
that astonish us.
that astonish us.
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05:06
The second key thing
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第二個要點是
05:08
is that the machines are,
in a limited sense, beginning to think.
in a limited sense, beginning to think.
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機器開始有限的思考。
05:12
And by this, I don't mean human-level AI,
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我並不是指人類水平級的人工智慧，
05:14
or science fiction
artificial intelligence;
artificial intelligence;
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或科幻小說中的人工智慧；
05:17
I simply mean that machines and algorithms
are making decisions.
are making decisions.
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我指的只是會決策的機器和演算法。
05:22
They're solving problems,
and most importantly, they're learning.
and most importantly, they're learning.
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它們會解決問題，
更重要的是，它們會學習。
更重要的是，它們會學習。
05:26
In fact, if there's one technology
that is truly central to this
that is truly central to this
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事實上，有項技術扮演著中心角色，
05:29
and has really become
the driving force behind this,
the driving force behind this,
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同時也是背後的推動力，
05:32
it's machine learning,
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就是機器學習，
05:33
which is just becoming
this incredibly powerful,
this incredibly powerful,
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它開始變得非常強大、
05:36
disruptive, scalable technology.
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具顛覆性，是可擴展的技術。
05:39
One of the best examples
I've seen of that recently
I've seen of that recently
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近期我看過最好的例子之一，
05:42
was what Google's DeepMind
division was able to do
division was able to do
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是 Google 的 DeepMind 團隊
用他們開發的 AlphaGo 系統
能夠做到什麼。
能夠做到什麼。
05:44
with its AlphaGo system.
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05:46
Now, this is the system that was able
to beat the best player in the world
to beat the best player in the world
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這個系統能在古老的圍棋賽中
打敗世界最強的棋手。
05:50
at the ancient game of Go.
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05:52
Now, at least to me,
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至少對我而言，
05:53
there are two things that really
stand out about the game of Go.
stand out about the game of Go.
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圍棋比賽有兩點特別突出。
05:57
One is that as you're playing the game,
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第一，當你在下圍棋時，
05:59
the number of configurations
that the board can be in
that the board can be in
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棋盤上有可能發生的
棋子配置組合數，
棋子配置組合數，
06:02
is essentially infinite.
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基本上是無限多。
06:03
There are actually more possibilities
than there are atoms in the universe.
than there are atoms in the universe.
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可能的組合數，
比宇宙中的原子數還要多。
比宇宙中的原子數還要多。
06:07
So what that means is,
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那意味著，
06:09
you're never going to be able to build
a computer to win at the game of Go
a computer to win at the game of Go
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你永遠不能建造一台
贏得圍棋比賽的電腦，
贏得圍棋比賽的電腦，
採用以前建造下西洋棋的
電腦那類的方式，
電腦那類的方式，
06:12
the way chess was approached, for example,
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06:15
which is basically to throw
brute-force computational power at it.
brute-force computational power at it.
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基本上是以蠻力狂加運算的效能。
06:19
So clearly, a much more sophisticated,
thinking-like approach is needed.
thinking-like approach is needed.
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很顯然，需要有
更精密的類思考方式。
更精密的類思考方式。
06:24
The second thing
that really stands out is that,
that really stands out is that,
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第二個特點是，
06:27
if you talk to one
of the championship Go players,
of the championship Go players,
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如果你和圍棋冠軍賽的棋手交談，
06:30
this person cannot necessarily
even really articulate what exactly it is
even really articulate what exactly it is
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這個人不見得能明確表達出
06:34
they're thinking about
as they play the game.
as they play the game.
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他們在比賽時腦中想的是什麼。
06:37
It's often something
that's very intuitive,
that's very intuitive,
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通常他們就是非常直覺地在下棋，
06:39
it's almost just like a feeling
about which move they should make.
about which move they should make.
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就像是他們能夠感覺到
下一步棋要怎麼下。
下一步棋要怎麼下。
06:42
So given those two qualities,
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在這兩種特色的前提下，
06:44
I would say that playing Go
at a world champion level
at a world champion level
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我會說能用世界冠軍的水平來下圍棋
06:48
really ought to be something
that's safe from automation,
that's safe from automation,
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應該是自動化做不到的事，
06:51
and the fact that it isn't should really
raise a cautionary flag for us.
raise a cautionary flag for us.
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但事實卻不是如此，
這應該要讓我們有所警覺。
這應該要讓我們有所警覺。
06:55
And the reason is that we tend
to draw a very distinct line,
to draw a very distinct line,
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原因是，我們都傾向於
畫一條很清楚的線，
畫一條很清楚的線，
06:59
and on one side of that line
are all the jobs and tasks
are all the jobs and tasks
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線一邊的所有工作和任務
07:03
that we perceive as being on some level
fundamentally routine and repetitive
fundamentally routine and repetitive
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被我們歸類於具有某種程度的
基本例行性、可重覆性、
基本例行性、可重覆性、
07:08
and predictable.
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並且是可被預測的。
07:09
And we know that these jobs
might be in different industries,
might be in different industries,
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我們知道這些工作
可能分屬不同的產業，
可能分屬不同的產業，
07:12
they might be in different occupations
and at different skill levels,
and at different skill levels,
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可能是不同的職業，
對技巧的需求也不同；
對技巧的需求也不同；
07:15
but because they are innately predictable,
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但由於它們先天的可預測性，
07:17
we know they're probably at some point
going to be susceptible
going to be susceptible
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我們知道，可能在某個時間點，
它們會受機器學習影響，
07:21
to machine learning,
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07:22
and therefore, to automation.
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而被自動化取代掉。
07:23
And make no mistake --
that's a lot of jobs.
that's a lot of jobs.
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別誤會，很多工作都是如此。
07:25
That's probably something
on the order of roughly half
on the order of roughly half
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可能在經濟體中有大約一半的工作
07:28
the jobs in the economy.
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都屬這一類。
07:30
But then on the other side of that line,
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但在線的另一邊，
07:32
we have all the jobs
that require some capability
that require some capability
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是需要某些能力的所有工作，
07:36
that we perceive as being uniquely human,
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我們認為是人類獨有的能力，
07:38
and these are the jobs
that we think are safe.
that we think are safe.
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我們認為這些工作是安全的。
07:41
Now, based on what I know
about the game of Go,
about the game of Go,
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根據我對圍棋的所知，
07:43
I would've guessed that it really ought
to be on the safe side of that line.
to be on the safe side of that line.
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我會猜測它應該屬於
線的這一邊，安全的這一邊。
線的這一邊，安全的這一邊。
07:47
But the fact that it isn't,
and that Google solved this problem,
and that Google solved this problem,
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但事實是它不在這一邊，
Google 破解了這個問題，
Google 破解了這個問題，
07:50
suggests that that line is going
to be very dynamic.
to be very dynamic.
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意味著那條線是非常動態的。
07:52
It's going to shift,
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它會移動，
07:53
and it's going to shift in a way
that consumes more and more jobs and tasks
that consumes more and more jobs and tasks
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它移動和取代掉
越來越多的工作和任務，
越來越多的工作和任務，
07:58
that we currently perceive
as being safe from automation.
as being safe from automation.
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那些我們目前認為是安全、
不會被自動化的。
不會被自動化的。
08:01
The other key thing to understand
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還要了解另一件重要的事，
08:03
is that this is by no means just about
low-wage jobs or blue-collar jobs,
low-wage jobs or blue-collar jobs,
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這現象絕對不會只發生在
低薪或藍領工作上、
低薪或藍領工作上、
08:08
or jobs and tasks done by people
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或由相對比較低教育程度的人
08:10
that have relatively
low levels of education.
low levels of education.
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所做的工作上。
08:12
There's lots of evidence to show
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有很多證據顯示，
08:14
that these technologies are rapidly
climbing the skills ladder.
climbing the skills ladder.
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這些科技所需要的技術
正在快速攀升。
正在快速攀升。
08:17
So we already see an impact
on professional jobs --
on professional jobs --
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我們已經看到影響力
開始觸及專業工作──
開始觸及專業工作──
08:21
tasks done by people like accountants,
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由類似像會計、
財務分析師、
08:25
financial analysts,
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記者、
08:26
journalists,
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律師、放射學家這類人
所做的工作任務。
所做的工作任務。
08:28
lawyers, radiologists and so forth.
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08:30
So a lot of the assumptions that we make
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我們對於這類職業、
08:32
about the kind of occupations
and tasks and jobs
and tasks and jobs
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任務、工作，所做的許多假設，
08:35
that are going to be threatened
by automation in the future
by automation in the future
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在未來將會被自動化給威脅，
往前也將會受到挑戰。
08:38
are very likely to be
challenged going forward.
challenged going forward.
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08:40
So as we put these trends together,
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當我們整合這些趨勢，
08:42
I think what it shows is that we could
very well end up in a future
very well end up in a future
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就會顯示
我們未來可能面臨嚴重的失業。
08:45
with significant unemployment.
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08:48
Or at a minimum,
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或至少，
08:49
we could face lots of underemployment
or stagnant wages,
or stagnant wages,
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我們可能會面臨許多大材小用
或者是薪水停滯不前，
或者是薪水停滯不前，
08:53
maybe even declining wages.
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甚至可能薪水下降。
08:56
And, of course, soaring levels
of inequality.
of inequality.
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當然，不平等的情況也會加劇。
08:58
All of that, of course, is going to put
a terrific amount of stress
a terrific amount of stress
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當然，這一切將會對於社會的結構
09:03
on the fabric of society.
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造成很大的壓力。
09:04
But beyond that, there's also
a fundamental economic problem,
a fundamental economic problem,
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但在那之外，還有個
根本的經濟問題，
根本的經濟問題，
09:08
and that arises because jobs
are currently the primary mechanism
are currently the primary mechanism
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問題出現的原因
是目前主要靠著「工作」這機制
是目前主要靠著「工作」這機制
09:13
that distributes income,
and therefore purchasing power,
and therefore purchasing power,
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來分配收入、和它帶來的購買力，
09:16
to all the consumers that buy the products
and services we're producing.
and services we're producing.
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給那些向我們購買
產品與服務的消費者。
產品與服務的消費者。
09:22
In order to have a vibrant market economy,
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為了要有活躍的市場經濟，
09:25
you've got to have
lots and lots of consumers
lots and lots of consumers
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你得要有很多有能力購買
09:27
that are really capable of buying
the products and services
the products and services
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那些被製造出來之產品和服務
09:30
that are being produced.
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的消費者。
09:31
If you don't have that,
then you run the risk
then you run the risk
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如果沒有，你要冒的風險就是
09:34
of economic stagnation,
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經濟停滯、
09:35
or maybe even a declining economic spiral,
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或甚至下降的經濟螺旋，
09:39
as there simply aren't enough
customers out there
customers out there
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因為就是沒有足夠的客人
09:41
to buy the products
and services being produced.
and services being produced.
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來購買製出的產品和服務。
09:44
It's really important to realize
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非常重要的是要了解到，
09:46
that all of us as individuals rely
on access to that market economy
on access to that market economy
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我們每個人都仰賴市場經濟，
09:52
in order to be successful.
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才有可能成功。
09:53
You can visualize that by thinking
in terms of one really exceptional person.
in terms of one really exceptional person.
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視覺化的方式是，你可以
想像一個非常特殊的人。
想像一個非常特殊的人。
09:58
Imagine for a moment you take,
say, Steve Jobs,
say, Steve Jobs,
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想像一下，比如你可以選賈伯斯，
10:01
and you drop him
on an island all by himself.
on an island all by himself.
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你把他丟在一個無人島上。
10:03
On that island, he's going
to be running around,
to be running around,
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在島上，他會到處跑來跑去，
10:06
gathering coconuts just like anyone else.
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收集椰子，就和所有其他人一樣。
10:08
He's really not going to be
anything special,
anything special,
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他不會有什麼特別的地方，
10:11
and the reason, of course,
is that there is no market
is that there is no market
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而原因當然是因為，那裡沒有市場
10:14
for him to scale
his incredible talents across.
his incredible talents across.
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來讓他發揮他出色的才華。
10:17
So access to this market
is really critical to us as individuals,
is really critical to us as individuals,
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所以對於個人來說，能進入
這個市場是很重要的，
這個市場是很重要的，
10:20
and also to the entire system
in terms of it being sustainable.
in terms of it being sustainable.
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此外，進入這個體制，
在永續面也是很重要的。
在永續面也是很重要的。
10:25
So the question then becomes:
What exactly could we do about this?
What exactly could we do about this?
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於是，問題變成了：
對此，我們到底能做什麼？
對此，我們到底能做什麼？
10:29
And I think you can view this
through a very utopian framework.
through a very utopian framework.
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我想，可以透過一個
非常理想化的框架來看此事。
非常理想化的框架來看此事。
10:32
You can imagine a future
where we all have to work less,
where we all have to work less,
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你可以想像在未來，
我們工作量減少，
我們工作量減少，
10:35
we have more time for leisure,
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有比較多休閒時間，
10:38
more time to spend with our families,
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比較多家庭時間，
10:40
more time to do things that we find
genuinely rewarding
genuinely rewarding
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3255
比較多時間去做我們
真正認為有價值的事，
真正認為有價值的事，
10:43
and so forth.
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諸如此類。
10:44
And I think that's a terrific vision.
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我認為那是很棒的遠景。
10:46
That's something that we should
absolutely strive to move toward.
absolutely strive to move toward.
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我們絕對應該朝那方向努力。
10:50
But at the same time, I think
we have to be realistic,
we have to be realistic,
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但同時，我認為我們得要實際一點，
10:52
and we have to realize
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我們得要了解，
10:54
that we're very likely to face
a significant income distribution problem.
a significant income distribution problem.
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我們非常有可能會要面臨
一個嚴重的收入分配問題。
一個嚴重的收入分配問題。
10:59
A lot of people are likely
to be left behind.
to be left behind.
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很多人可能會被扔在後頭。
11:03
And I think that in order
to solve that problem,
to solve that problem,
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我認為，要解決那個問題，
11:05
we're ultimately going
to have to find a way
to have to find a way
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我們最終得要找到一個方式，
11:07
to decouple incomes from traditional work.
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2606
將收入和傳統工作給分離開。
11:10
And the best, more straightforward
way I know to do that
way I know to do that
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如果要這樣做，我所知道
最好、最直接的方法
最好、最直接的方法
11:13
is some kind of a guaranteed income
or universal basic income.
or universal basic income.
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就是某種保障收入
或是全體基本收入。
或是全體基本收入。
11:16
Now, basic income is becoming
a very important idea.
a very important idea.
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基本收入正變成一個很重要的想法。
11:19
It's getting a lot
of traction and attention,
of traction and attention,
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它得到許多的注意力和關注，
11:21
there are a lot of important
pilot projects
pilot projects
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2273
有許多重要的前導計畫
11:23
and experiments going on
throughout the world.
throughout the world.
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及實驗在全世界進行。
11:26
My own view is that a basic income
is not a panacea;
is not a panacea;
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我自己的看法是，
基本收入並非萬靈丹；
基本收入並非萬靈丹；
11:29
it's not necessarily
a plug-and-play solution,
a plug-and-play solution,
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它未必是插電就可以解決的方案，
11:32
but rather, it's a place to start.
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但總是個起始點，
11:34
It's an idea that we can
build on and refine.
build on and refine.
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我們可以從這想法開始，再改善它。
11:36
For example, one thing that I have
written quite a lot about
written quite a lot about
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比如，我寫了很多的一個題材，
11:39
is the possibility of incorporating
explicit incentives into a basic income.
explicit incentives into a basic income.
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4592
是明確地將獎勵
納入基本收入當中的可行性。
納入基本收入當中的可行性。
11:44
To illustrate that,
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讓我解釋一下，
11:46
imagine that you are a struggling
high school student.
high school student.
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2768
想像你是個讀得很辛苦的高中生。
11:48
Imagine that you are at risk
of dropping out of school.
of dropping out of school.
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2834
想像你有可能會被退學。
11:52
And yet, suppose you know
that at some point in the future,
that at some point in the future,
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但假設你知道在未來某個時間點，
11:55
no matter what,
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1224
不論如何，
11:56
you're going to get the same
basic income as everyone else.
basic income as everyone else.
256
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3697
你和別人得到的基本收入是一樣的。
12:00
Now, to my mind, that creates
a very perverse incentive
a very perverse incentive
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3042
我認為那會在你腦中
產生橫下心來的動機，
產生橫下心來的動機，
12:03
for you to simply give up
and drop out of school.
and drop out of school.
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2497
使你直接放棄並退學。
12:06
So I would say, let's not
structure things that way.
structure things that way.
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2505
我會說，咱們
不要設計成那樣的結構。
不要設計成那樣的結構。
12:08
Instead, let's pay people who graduate
from high school somewhat more
from high school somewhat more
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5316
而是支付高中畢業生較高的薪水，
12:14
than those who simply drop out.
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1696
比中綴生要高。
12:16
And we can take that idea of building
incentives into a basic income,
incentives into a basic income,
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我們可以把這個將獎勵
納入基本收入中的想法，
納入基本收入中的想法，
12:19
and maybe extend it to other areas.
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也許再延伸至其他的領域。
12:21
For example, we might create
an incentive to work in the community
an incentive to work in the community
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3577
比如，我們可以針對
在社區中助人的行為，
在社區中助人的行為，
12:25
to help others,
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1158
創造一種獎勵；
12:26
or perhaps to do positive
things for the environment,
things for the environment,
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3064
或是去獎勵人們
為環境做出正面的貢獻，
為環境做出正面的貢獻，
12:29
and so forth.
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諸如此類。
12:30
So by incorporating incentives
into a basic income,
into a basic income,
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3011
把獎勵納入到基本收入當中，
12:33
we might actually improve it,
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1629
我們可能可以改善它，
12:35
and also, perhaps, take at least
a couple of steps
a couple of steps
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2626
另外，也許也可以更接近
12:37
towards solving another problem
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2425
解決另一個我認為
12:40
that I think we're quite possibly
going to face in the future,
going to face in the future,
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2944
在未來也很可能要面臨的問題，
12:43
and that is, how do we all find
meaning and fulfillment,
meaning and fulfillment,
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3752
就是：我們要如何
找到意義和實現人生、
找到意義和實現人生、
12:47
and how do we occupy our time
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以及我們要如何把時間
12:49
in a world where perhaps
there's less demand for traditional work?
there's less demand for traditional work?
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花在一個也許比較不需求
傳統工作的世界裡？
傳統工作的世界裡？
12:54
So by extending and refining
a basic income,
a basic income,
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透過延伸和改善基本收入，
12:57
I think we can make it look better,
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我想我們可以讓它看起來更好，
12:59
and we can also, perhaps, make it
more politically and socially acceptable
more politically and socially acceptable
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我們也能讓它在政治面
和社會面更容易被接受，
和社會面更容易被接受，
13:04
and feasible --
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也更可行──
13:05
and, of course, by doing that,
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當然，透過那樣做，
13:07
we increase the odds
that it will actually come to be.
that it will actually come to be.
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我們就會增加實現它的可能性。
13:11
I think one of the most fundamental,
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我想，對於基本收入這個想法，
13:14
almost instinctive objections
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或是擴展安全網，
13:16
that many of us have
to the idea of a basic income,
to the idea of a basic income,
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我們所有人最主要、
13:19
or really to any significant
expansion of the safety net,
expansion of the safety net,
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也最直覺的反對意見，
13:23
is this fear that we're going to end up
with too many people
with too many people
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就是害怕最後會有太多人
13:27
riding in the economic cart,
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爬上這經濟車箱，
13:28
and not enough people pulling that cart.
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而沒有足夠人去拉這車廂。
13:31
And yet, really, the whole point
I'm making here, of course,
I'm making here, of course,
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但，其實，我在這裡要說的重點是，
13:33
is that in the future,
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在未來，
13:35
machines are increasingly going
to be capable of pulling that cart for us.
to be capable of pulling that cart for us.
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機器將會有能力為我們拉車。
13:39
That should give us more options
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那就會讓我們有更多選項，
13:41
for the way we structure
our society and our economy,
our society and our economy,
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可用以不同的方式
架構我們的社會和經濟，
架構我們的社會和經濟，
13:45
And I think eventually, it's going to go
beyond simply being an option,
beyond simply being an option,
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我認為，最終它將不只是個選項，
13:48
and it's going to become an imperative.
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而將變成勢在必行。
13:50
The reason, of course,
is that all of this is going to put
is that all of this is going to put
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當然，因為這一切
將會帶給社會一定程度的壓力，
13:53
such a degree of stress on our society,
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13:55
and also because jobs are that mechanism
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也因為要靠「工作」這個機制，
13:57
that gets purchasing power to consumers
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將購買力分配給消費者，
13:59
so they can then drive the economy.
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他們接著才能夠帶動經濟。
14:02
If, in fact, that mechanism
begins to erode in the future,
begins to erode in the future,
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事實上，如果未來那機制開始腐蝕了，
14:05
then we're going to need to replace
it with something else
it with something else
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我們就得要用其他東西來取代它，
14:08
or we're going to face the risk
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不然我們就要面臨
14:10
that our whole system simply
may not be sustainable.
may not be sustainable.
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整個體制不夠永續的風險。
14:12
But the bottom line here
is that I really think
is that I really think
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但這裡的關鍵是，我真的認為
14:15
that solving these problems,
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解決這些問題，
14:17
and especially finding a way
to build a future economy
to build a future economy
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特別是找出方法來建立一種對社會
14:21
that works for everyone,
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每個層級的每個人都
14:23
at every level of our society,
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行得通的未來經濟，
14:25
is going to be one of the most important
challenges that we all face
challenges that we all face
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將會是未來幾年和幾十年間，
我們所有人要面臨
的最重大挑戰之一。
的最重大挑戰之一。
14:28
in the coming years and decades.
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14:30
Thank you very much.
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非常謝謝。
14:32
(Applause)
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（掌聲）
ABOUT THE SPEAKER
Martin Ford - FuturistMartin Ford imagines what the accelerating progress in robotics and artificial intelligence may mean for the economy, job market and society of the future.
Why you should listen
Martin Ford was one of the first analysts to write compellingly about the future of work and economies in the face of the growing automation of everything. He sketches a future that's radically reshaped not just by robots but by the loss of the income-distributing power of human jobs. How will our economic systems need to adapt?
He's the author of two books: Rise of the Robots: Technology and the Threat of a Jobless Future (winner of the 2015 Financial Times/McKinsey Business Book of the Year Award ) and The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future, and he's the founder of a Silicon Valley-based software development firm. He has written about future technology and its implications for the New York Times, Fortune, Forbes, The Atlantic, The Washington Post, Harvard Business Review and The Financial Times.
Martin Ford | Speaker | TED.com