TED2017
Martin Ford: How we'll earn money in a future without jobs
马丁·福德: 如果未来没有工作，我们将如何挣钱？
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能够思考、学习并自适应的机器即将登场——这可能意味着我们人类将面临大规模失业。我们将何去何从？针对这一极具争议的观点，未来学家马丁·福德直率建言，提出将收入与传统工作分离，并制定全民基本收入标准。
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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首先，我想提出一个可怕的问题：
我们是否正在迈向一个没有工作的未来？
00:15
Are we headed toward
a future without jobs?
a future without jobs?
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如今目睹了自动驾驶汽车
00:18
The remarkable progress that we're seeing
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00:21
in technologies like self-driving cars
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等技术的显著进步，
00:22
has led to an explosion
of interest in this question,
of interest in this question,
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我们对此问题的关注日益激增，
00:26
but because it's something
that's been asked
that's been asked
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但这一问题在过去
00:28
so many times in the past,
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人们已多次提及，
00:29
maybe what we should really be asking
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也许我们真正应当关心的
00:31
is whether this time is really different.
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是这次情况是否会有所不同。
00:35
The fear that automation
might displace workers
might displace workers
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人类一直担忧，自动化会取代工人
00:38
and potentially lead
to lots of unemployment
to lots of unemployment
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进而导致大量失业，
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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从二百多年前的英国卢德运动开始，
00:44
And since then, this concern
has come up again and again.
has come up again and again.
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这种担忧便一再出现。
00:47
I'm going to guess
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我猜在座各位
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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多数没听说过“三次革命报告”，
00:53
but this was a very prominent report.
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这是一份杰出的报告，
00:55
It was put together
by a brilliant group of people --
by a brilliant group of people --
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出自一群优秀人才之手，
00:58
it actually included
two Nobel laureates --
two Nobel laureates --
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其中包括两名诺奖得主。
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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该报告最终呈送美国总统审阅。
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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报告指出，美国正处于经济和社会动荡的边缘，
01:09
because industrial automation
was going to put millions of people
was going to put millions of people
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因为工业自动化将导致数百万工人
01:13
out of work.
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下岗失业。
01:14
Now, that report was delivered
to President Lyndon Johnson
to President Lyndon Johnson
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时任总统林登·约翰逊收到报告时
01:17
in March of 1964.
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是1964年3月。
01:19
So that's now over 50 years,
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如今五十多年过去了，
01:21
and, of course, that
hasn't really happened.
hasn't really happened.
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美国并没有发生动荡。
这样的故事从此不断上演：
01:24
And that's been the story again and again.
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警钟一再响起，
01:26
This alarm has been raised repeatedly,
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但最终总是虚惊一场。
01:28
but it's always been a false alarm.
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01:30
And because it's been a false alarm,
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随着虚惊不断发生，
01:32
it's led to a very conventional way
of thinking about this.
of thinking about this.
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人们对其产生了思维惯性：
01:35
And that says essentially that yes,
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动荡本质上无可避免，
01:37
technology may devastate
entire industries.
entire industries.
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新技术势必席卷整个工业界
01:40
It may wipe out whole occupations
and types of work.
and types of work.
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并取代所有的工作岗位。
01:43
But at the same time, of course,
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但与此同时，
01:45
progress is going to lead
to entirely new things.
to entirely new things.
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科技进步也将带来全新的变化。
01:47
So there will be new industries
that will arise in the future,
that will arise in the future,
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在未来，新型工业将会兴起，
01:50
and those industries, of course,
will have to hire people.
will have to hire people.
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势必产生新的用人需求。
01:53
There'll be new kinds of work
that will appear,
that will appear,
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未来将会出现全新的工作，
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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有的甚至今天我们根本无法想像。
01:59
And that has been the story so far,
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这便是迄今为止的故事，
02:01
and it's been a positive story.
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一直是令人乐观的。
事实证明，新出现的工作
02:03
It turns out that the new jobs
that have been created
that have been created
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02:06
have generally been
a lot better than the old ones.
a lot better than the old ones.
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通常远胜过旧的工作。
02:08
They have, for example,
been more engaging.
been more engaging.
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新工作更有吸引力，
02:11
They've been in safer,
more comfortable work environments,
more comfortable work environments,
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工作环境更为安全舒适，
02:15
and, of course, they've paid more.
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挣得自然也更多。
02:16
So it has been a positive story.
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所以这个故事是乐观的，
02:18
That's the way things
have played out so far.
have played out so far.
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而事情迄今的发展亦是如此。
但有一类特殊的劳动群体，
02:21
But there is one particular
class of worker
class of worker
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02:24
for whom the story
has been quite different.
has been quite different.
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其境遇却全然不同。
对这个群体来说，
02:27
For these workers,
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02:29
technology has completely
decimated their work,
decimated their work,
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科技彻底取代了他们的工作，
02:32
and it really hasn't created
any new opportunities at all.
any new opportunities at all.
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却并未为其带来任何新的就业机会。
02:35
And these workers, of course,
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当然，我所指的“劳动群体”，
02:37
are horses.
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正是马。
02:38
(Laughter)
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（笑声）
02:40
So I can ask a very provocative question:
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由此我便能提出一个尖锐的问题：
02:43
Is it possible that at some
point in the future,
point in the future,
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在未来，是否有可能
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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会出现相当数量的劳动力冗余
02:51
in the way that horses were?
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正如马的遭遇一般？
出于本能，人们可能会下意识地
02:53
Now, you might have a very visceral,
reflexive reaction to that.
reflexive reaction to that.
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02:56
You might say, "That's absurd.
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反驳道：“荒唐！
02:58
How can you possibly compare
human beings to horses?"
human beings to horses?"
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牲畜岂能和人相比？”
03:02
Horses, of course, are very limited,
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马的能力固然有限，
03:04
and when cars and trucks
and tractors came along,
and tractors came along,
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当汽车、卡车和拖拉机出现后，
03:07
horses really had nowhere else to turn.
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马便没了用武之地。
03:09
People, on the other hand,
are intelligent;
are intelligent;
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但人却是具有智慧的，
能够学习，并且会适应环境。
03:12
we can learn, we can adapt.
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03:14
And in theory,
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因此理论上讲，
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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人应当总能找到新的工作，
始终保持与未来经济的联系。
03:18
and that we can always remain
relevant to the future economy.
relevant to the future economy.
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03:21
But here's the really
critical thing to understand.
critical thing to understand.
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但我们必须意识到的关键是，
03:24
The machines that will threaten
workers in the future
workers in the future
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未来将威胁取代劳动力的机器
03:27
are really nothing like those cars
and trucks and tractors
and trucks and tractors
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和取代了马匹的汽车、卡车或拖拉机
03:30
that displaced horses.
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绝不可同日而语。
03:32
The future is going to be full
of thinking, learning, adapting machines.
of thinking, learning, adapting machines.
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未来的机器将具有思维，学习和适应能力。
03:37
And what that really means
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这便真正意味着
03:38
is that technology is finally
beginning to encroach
beginning to encroach
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技术终将开始入侵
03:41
on that fundamental human capability --
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最根本的人类能力——
03:44
the thing that makes us
so different from horses,
so different from horses,
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那种使我们有别于动物的能力。
03:47
and the very thing that, so far,
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正是由于这种能力，
03:49
has allowed us to stay ahead
of the march of progress
of the march of progress
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人们才能引领时代发展，
03:52
and remain relevant,
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并始终作用于经济
03:53
and, in fact, indispensable
to the economy.
to the economy.
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成为其不可或缺的重要一环。
03:58
So what is it that is really so different
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所以今天的信息技术
04:00
about today's information technology
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相对于过去的技术革新
04:02
relative to what we've seen in the past?
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其不同之处究竟在哪里呢？
04:04
I would point to three fundamental things.
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我将指出三个基本的方面。
04:07
The first thing is that we have seen
this ongoing process
this ongoing process
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第一，我们已经目睹了这一进程
04:12
of exponential acceleration.
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指数爆炸式的增长速度。
04:14
I know you all know about Moore's law,
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想必大家都了解摩尔定律，
04:16
but in fact, it's more
broad-based than that;
broad-based than that;
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但其适用面其实要宽广得多
04:18
it extends in many cases,
for example, to software,
for example, to software,
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涵盖了很多不同领域的发展规律，
比如软件，通讯，带宽增长等。
04:22
it extends to communications,
bandwidth and so forth.
bandwidth and so forth.
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04:25
But the really key thing to understand
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但我们要意识到的关键是
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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这种增长已经持续了很久，
04:30
In fact, it's been going on for decades.
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实际上已经有几十年了。
04:32
If you measure from the late 1950s,
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若从五十年代末
04:35
when the first integrated
circuits were fabricated,
circuits were fabricated,
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第一批集成电路问世算起，
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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我们现今的计算能力已经翻了30番。
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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对于任何事物，这样的增长量都是惊人的，
04:47
and what it really means
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它意味着
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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我们正处在一个时间点，
能够目睹科技巨大的进步，
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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并且从今往后，科技仍将
继续加速增长。
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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因此，当我们期待若干年后的未来时，
05:00
I think that means
that we're going to see things
that we're going to see things
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我们将面临始料未及的变迁；
05:03
that we're really not prepared for.
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我们将见证令人惊奇的成就。
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，
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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狭义上讲，机器开始具有思考能力。
05:12
And by this, I don't mean human-level AI,
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我此话所指，并非是智力堪比人类，
05:14
or science fiction
artificial intelligence;
artificial intelligence;
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或是科幻小说中出现的人工智能。
05:17
I simply mean that machines and algorithms
are making decisions.
are making decisions.
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我只想指出，机器和算法将能够进行决策，
05:22
They're solving problems,
and most importantly, they're learning.
and most importantly, they're learning.
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解决问题，以及最重要的，能够自我学习。
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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其实如果说有一项核心技术
05:29
and has really become
the driving force behind this,
the driving force behind this,
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是科技进步的关键驱动力，
那便是机器学习，
05:32
it's machine learning,
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05:33
which is just becoming
this incredibly powerful,
this incredibly powerful,
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一项正在显示其惊人威力，
05:36
disruptive, scalable technology.
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颠覆性，以及扩展性的技术。
05:39
One of the best examples
I've seen of that recently
I've seen of that recently
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近来我见到的最佳事例
05:42
was what Google's DeepMind
division was able to do
division was able to do
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就有谷歌DeepMind团队研发了
05:44
with its AlphaGo system.
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AlphaGo系统，
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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在历史悠久的围棋游戏上
05:50
at the ancient game of Go.
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击败了世界最强高手。
05:52
Now, at least to me,
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而至少在我看来，
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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围棋有两个突出的特点。
其一是在下棋时，
05:57
One is that as you're playing the game,
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05:59
the number of configurations
that the board can be in
that the board can be in
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棋盘上可能的变化
06:02
is essentially infinite.
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基本上无法穷尽。
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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棋局的数目甚至比宇宙中的原子还要多。
06:07
So what that means is,
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这便意味着，
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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若要造出一台下围棋能赢的电脑，
06:12
the way chess was approached, for example,
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采用设计国际象棋软件的思路，
06:15
which is basically to throw
brute-force computational power at it.
brute-force computational power at it.
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通过增加计算资源暴力破解，是不可行的，
06:19
So clearly, a much more sophisticated,
thinking-like approach is needed.
thinking-like approach is needed.
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必然要采用一种更为复杂，更贴近思考的途径。
06:24
The second thing
that really stands out is that,
that really stands out is that,
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第二个突出的特点便是，
06:27
if you talk to one
of the championship Go players,
of the championship Go players,
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即便去请教一位围棋冠军，
06:30
this person cannot necessarily
even really articulate what exactly it is
even really articulate what exactly it is
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他也不一定能讲清自己下棋时
06:34
they're thinking about
as they play the game.
as they play the game.
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究竟是如何思考的。
06:37
It's often something
that's very intuitive,
that's very intuitive,
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棋手常依赖某种直观的判断，
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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几乎是凭感觉，来决定该走哪手棋。
06:42
So given those two qualities,
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鉴于以上两点，
06:44
I would say that playing Go
at a world champion level
at a world champion level
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按说要把围棋下到世界冠军水平，
06:48
really ought to be something
that's safe from automation,
that's safe from automation,
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机器是无法胜任的，
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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而事实并非如此，我们应当引起警惕了。
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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究其原因，我们习惯划一条明确的界线
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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在界线的一侧，是我们认为
07:03
that we perceive as being on some level
fundamentally routine and repetitive
fundamentally routine and repetitive
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较为基础，常规，重复
07:08
and predictable.
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且容易预测的工作。
07:09
And we know that these jobs
might be in different industries,
might be in different industries,
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这类工作可能来自不同行业，
07:12
they might be in different occupations
and at different skill levels,
and at different skill levels,
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不同岗位，所需技能也有高低之分，
07:15
but because they are innately predictable,
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但本质上都是可以预测的，
07:17
we know they're probably at some point
going to be susceptible
going to be susceptible
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因此终有一日会受到
机器学习的冲击，
07:21
to machine learning,
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并走向自动化。
07:22
and therefore, to automation.
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这类工作数目可是不少
07:23
And make no mistake --
that's a lot of jobs.
that's a lot of jobs.
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07:25
That's probably something
on the order of roughly half
on the order of roughly half
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经济体中差不多一半的工作
07:28
the jobs in the economy.
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都属于此类。
07:30
But then on the other side of that line,
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而界线另一侧的工作，
07:32
we have all the jobs
that require some capability
that require some capability
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我们认为需要特殊的能力，
07:36
that we perceive as being uniquely human,
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只有人能胜任，
07:38
and these are the jobs
that we think are safe.
that we think are safe.
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所以这些工作是安全的。
07:41
Now, based on what I know
about the game of Go,
about the game of Go,
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以我对围棋的了解，
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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我猜它应该在分界线“安全”的一侧。
但谷歌攻克了这一难题，否定了我的猜测，
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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07:50
suggests that that line is going
to be very dynamic.
to be very dynamic.
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也说明这条分界线将会剧烈变动，
07:52
It's going to shift,
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移向安全的一侧，
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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将我们当前认为无法自动化的工作任务
07:58
that we currently perceive
as being safe from automation.
as being safe from automation.
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逐渐纳入不安全的范围。
08:01
The other key thing to understand
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还有一点需要了解，
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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会遭受冲击的不只是低薪的蓝领工作，
08:08
or jobs and tasks done by people
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或是教育程度较低的人
08:10
that have relatively
low levels of education.
low levels of education.
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所从事的工作。
08:12
There's lots of evidence to show
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诸多证据表明
08:14
that these technologies are rapidly
climbing the skills ladder.
climbing the skills ladder.
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科技的威力正在飞速攀升。
08:17
So we already see an impact
on professional jobs --
on professional jobs --
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我们已经看到科技对专业工作的冲击，
08:21
tasks done by people like accountants,
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受到冲击的包括会计师
08:25
financial analysts,
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财政分析师
08:26
journalists,
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记者
08:28
lawyers, radiologists and so forth.
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律师，以及放射科医师等。
08:30
So a lot of the assumptions that we make
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而我们目前有很多假设
08:32
about the kind of occupations
and tasks and jobs
and tasks and jobs
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在探讨哪些职业、任务和工作
未来将遭到自动化的冲击。
08:35
that are going to be threatened
by automation in the future
by automation in the future
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这些假设将来都很可能遭到挑战。
08:38
are very likely to be
challenged going forward.
challenged going forward.
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当我们汇总这些趋势后，
08:40
So as we put these trends together,
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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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便能看出，未来我们很可能面临
08:45
with significant unemployment.
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严重的失业。
08:48
Or at a minimum,
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就算退一万步讲，
08:49
we could face lots of underemployment
or stagnant wages,
or stagnant wages,
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我们也会面临就业不足，或者工资水平停滞
08:53
maybe even declining wages.
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乃至下降。
08:56
And, of course, soaring levels
of inequality.
of inequality.
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社会不平等自然也会激增。
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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以上问题势必会给社会结构
09:03
on the fabric of society.
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带来巨大压力。
09:04
But beyond that, there's also
a fundamental economic problem,
a fundamental economic problem,
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除此之外，还有一个根本的经济问题：
09:08
and that arises because jobs
are currently the primary mechanism
are currently the primary mechanism
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就业是我们当前主要的收入分配机制，
09:13
that distributes income,
and therefore purchasing power,
and therefore purchasing power,
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有了收入，消费者就有了购买力
09:16
to all the consumers that buy the products
and services we're producing.
and services we're producing.
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可以购买人们生产出的产品和服务。
09:22
In order to have a vibrant market economy,
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为使市场经济繁荣，
09:25
you've got to have
lots and lots of consumers
lots and lots of consumers
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需要大量有购买力的消费者
09:27
that are really capable of buying
the products and services
the products and services
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来消化社会生产出的产品和服务。
09:30
that are being produced.
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09:31
If you don't have that,
then you run the risk
then you run the risk
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否则我们就会面临经济停滞
09:34
of economic stagnation,
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甚至螺旋式下降的风险，
09:35
or maybe even a declining economic spiral,
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09:39
as there simply aren't enough
customers out there
customers out there
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因为没有足够的消费者
09:41
to buy the products
and services being produced.
and services being produced.
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购买生产出的产品和服务。
09:44
It's really important to realize
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重要的是要认识到，
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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作为个体，我们每个人都要靠参与市场经济
09:52
in order to be successful.
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来获得成功。
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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我们不妨来想象一位杰出的人物，
09:58
Imagine for a moment you take,
say, Steve Jobs,
say, Steve Jobs,
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比如说史蒂夫·乔布斯，
10:01
and you drop him
on an island all by himself.
on an island all by himself.
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把他一个人丢在荒岛上，
10:03
On that island, he's going
to be running around,
to be running around,
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让他四处奔走
10:06
gathering coconuts just like anyone else.
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去收集椰子，和其他人一样。
10:08
He's really not going to be
anything special,
anything special,
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他肯定成不了什么“乔帮主”，
10:11
and the reason, of course,
is that there is no market
is that there is no market
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原因很显然，岛上没有手机市场
10:14
for him to scale
his incredible talents across.
his incredible talents across.
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能让他施展才智，大显身手。
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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所以市场对我们个人来说至关重要，
10:20
and also to the entire system
in terms of it being sustainable.
in terms of it being sustainable.
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同时也是整个社会可持续发展的重中之重。
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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那么问题就变成了，我们究竟该如何应对挑战？
我们可以在非常理想的框架中看待这一问题。
10:29
And I think you can view this
through a very utopian framework.
through a very utopian framework.
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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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设想在未来，我们都会减少工作，
10:35
we have more time for leisure,
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拥有更多闲暇时光陪伴家人，
10:38
more time to spend with our families,
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或者做些真正怡情养性的事情，等等。
10:40
more time to do things that we find
genuinely rewarding
genuinely rewarding
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10:43
and so forth.
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这是非常美妙的愿景，
10:44
And I think that's a terrific vision.
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10:46
That's something that we should
absolutely strive to move toward.
absolutely strive to move toward.
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值得我们为之全力奋斗。
10:50
But at the same time, I think
we have to be realistic,
we have to be realistic,
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但同时我们也要务实，
10:52
and we have to realize
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要意识到
10:54
that we're very likely to face
a significant income distribution problem.
a significant income distribution problem.
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我们极有可能面临严重的收入分配问题。
10:59
A lot of people are likely
to be left behind.
to be left behind.
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许多人可能会落在后面。
11:03
And I think that in order
to solve that problem,
to solve that problem,
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要解决收入分配问题，
11:05
we're ultimately going
to have to find a way
to have to find a way
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我们最终要找到一条途径
11:07
to decouple incomes from traditional work.
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将收入与传统的工作分离。
11:10
And the best, more straightforward
way I know to do that
way I know to do that
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而据我所知，最直接有效的方法
11:13
is some kind of a guaranteed income
or universal basic income.
or universal basic income.
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便是设立某种无条件基本收入。
11:16
Now, basic income is becoming
a very important idea.
a very important idea.
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基本收入已经成为重要的概念，
11:19
It's getting a lot
of traction and attention,
of traction and attention,
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广受关注及推崇，
11:21
there are a lot of important
pilot projects
pilot projects
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世界各国也相继开展了
11:23
and experiments going on
throughout the world.
throughout the world.
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很多重大试点项目。
11:26
My own view is that a basic income
is not a panacea;
is not a panacea;
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我认为基本收入不是灵丹妙药，
11:29
it's not necessarily
a plug-and-play solution,
a plug-and-play solution,
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不是“一用就见效”的解决方案。
11:32
but rather, it's a place to start.
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这仅是一个起点，一个设想
11:34
It's an idea that we can
build on and refine.
build on and refine.
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还有待我们在其基础上加以完善。
11:36
For example, one thing that I have
written quite a lot about
written quite a lot about
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例如，我围绕这样一个设想写过不少文章，
11:39
is the possibility of incorporating
explicit incentives into a basic income.
explicit incentives into a basic income.
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那便是，将显性激励整合到基本收入中。
我具体解释一下，
11:44
To illustrate that,
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11:46
imagine that you are a struggling
high school student.
high school student.
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想象你是个苦苦挣扎的高中生，
11:48
Imagine that you are at risk
of dropping out of school.
of dropping out of school.
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正面临被开除的风险。
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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但假设你知道未来有这么一天，
不管什么情况下，
11:55
no matter what,
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11:56
you're going to get the same
basic income as everyone else.
basic income as everyone else.
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你都能得到和其他人一样的基本收入。
12:00
Now, to my mind, that creates
a very perverse incentive
a very perverse incentive
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在我看来，这将造成一种不当动机
12:03
for you to simply give up
and drop out of school.
and drop out of school.
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使你甘心直接退学。
12:06
So I would say, let's not
structure things that way.
structure things that way.
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所以说，办事不能这样一刀切。
12:08
Instead, let's pay people who graduate
from high school somewhat more
from high school somewhat more
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反之，与辍学的人相比，应该给高中毕业的人
更多一些的收入。
12:14
than those who simply drop out.
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12:16
And we can take that idea of building
incentives into a basic income,
incentives into a basic income,
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这种将激励整合到基本收入中的做法，
我们也可以用在其他领域中。
12:19
and maybe extend it to other areas.
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1667
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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比如，我们可以创造激励来鼓励社区义工，
鼓励互相帮助，
12:25
to help others,
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12:26
or perhaps to do positive
things for the environment,
things for the environment,
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鼓励保护环境的行为，等等。
12:29
and so forth.
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12:30
So by incorporating incentives
into a basic income,
into a basic income,
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通过将激励纳入基本收入制度中，
我们便能改善这一制度，
12:33
we might actually improve it,
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12:35
and also, perhaps, take at least
a couple of steps
a couple of steps
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或者把步子迈得再大些，
12:37
towards solving another problem
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去解决另一个问题
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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——未来我们很可能要面对的问题。
12:43
and that is, how do we all find
meaning and fulfillment,
meaning and fulfillment,
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那就是：未来我们可能不再需要大量的传统工作了，
12:47
and how do we occupy our time
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那我们又该如何利用时间，
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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4349
寻找生命的意义，实现人生的圆满呢？
12:54
So by extending and refining
a basic income,
a basic income,
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因此，通过改良并推广基本收入制度，
12:57
I think we can make it look better,
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我们可以令其更为合意，
12:59
and we can also, perhaps, make it
more politically and socially acceptable
more politically and socially acceptable
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5298
并且更容易为政界采纳，
也更容易在社会中实施，
13:04
and feasible --
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1164
13:05
and, of course, by doing that,
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最终有更大的几率
13:07
we increase the odds
that it will actually come to be.
that it will actually come to be.
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使这项制度真正落地。
13:11
I think one of the most fundamental,
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2270
对于推行基本收入制度，
13:14
almost instinctive objections
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或者任何重大的保险金制度，
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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3453
我想很多人都会持反对意见。
其中有一条意见尤为根本，
13:19
or really to any significant
expansion of the safety net,
expansion of the safety net,
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3732
几乎是出于本能，我们会担心
13:23
is this fear that we're going to end up
with too many people
with too many people
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最终有太多人安于坐享其成，
13:27
riding in the economic cart,
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1738
而没有足够的人真正去推动经济发展。
13:28
and not enough people pulling that cart.
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2047
13:31
And yet, really, the whole point
I'm making here, of course,
I'm making here, of course,
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2834
而我在此要表达的观点是
13:33
is that in the future,
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1361
在未来，
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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3826
机器将会替我们更好地推动经济发展。
13:39
That should give us more options
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807160
1990
这给我们构建社会，组织经济
13:41
for the way we structure
our society and our economy,
our society and our economy,
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3811
提供了更多选择方案。
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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3442
而我相信，最终这将不仅只是一种选择，
更将成为大势所趋。
13:48
and it's going to become an imperative.
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1901
原因很显然，当今发生的一切
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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2822
将使社会面临巨大的压力，
13:53
such a degree of stress on our society,
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2014
13:55
and also because jobs are that mechanism
298
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2514
而就业机制又是
13:57
that gets purchasing power to consumers
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1965
赋予消费者购买力，
13:59
so they can then drive the economy.
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2516
驱动经济发展的重要抓手。
14:02
If, in fact, that mechanism
begins to erode in the future,
begins to erode in the future,
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3547
如果未来这一机制遭到侵蚀，
我们便需要采用其他措施。
14:05
then we're going to need to replace
it with something else
it with something else
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2815
否则我们便将面临
14:08
or we're going to face the risk
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1563
14:10
that our whole system simply
may not be sustainable.
may not be sustainable.
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2567
社会无法持续运转的风险。
14:12
But the bottom line here
is that I really think
is that I really think
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2382
但有一点我坚信不疑，
14:15
that solving these problems,
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2436
那便是：如何解决这些问题，
14:17
and especially finding a way
to build a future economy
to build a future economy
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3400
尤其是寻找一条构建未来经济的途径
14:21
that works for everyone,
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使得社会中每个阶层
14:23
at every level of our society,
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851266
1861
均能从中受益，
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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将是我们未来亟需共同面对的
14:28
in the coming years and decades.
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2043
至关重要的挑战。
14:30
Thank you very much.
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1248
谢谢大家！
14:32
(Applause)
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（掌声）
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