ABOUT THE SPEAKER
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.

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. 

More profile about the speaker
Martin Ford | Speaker | TED.com
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？

Filmed:
3,167,458 views

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。
- 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

Double-click the English transcript below to play the video.

00:12
I'm going to begin开始 with a scary害怕 question题:
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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当家 toward往
a future未来 without无 jobs工作?
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如今目睹了自动驾驶汽车
00:18
The remarkable卓越 progress进展 that we're seeing眼看
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00:21
in technologies技术 like self-driving自驾车 cars汽车
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等技术的显著进步，
00:22
has led to an explosion爆炸
of interest利益 in this question题,
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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问
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但这一问题在过去
00:28
so many许多 times时 in the past过去,
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人们已多次提及，
00:29
maybe what we should really be asking问
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也许我们真正应当关心的
00:31
is whether是否 this time is really different不同.
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是这次情况是否会有所不同。
00:35
The fear恐惧 that automation自动化
might威力 displace顶替 workers工人
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人类一直担忧，自动化会取代工人
00:38
and potentially可能 lead铅
to lots of unemployment失业
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进而导致大量失业，
00:40
goes去 back at a minimum最低限度 200 years年份
to the Luddite勒德 revolts起义 in England英国.
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从二百多年前的英国卢德运动开始，
00:44
And since以来 then, this concern关心
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猜测
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我猜在座各位
00:48
that most最 of you have probably大概 never
heard听说 of the Triple三 Revolution革命 report报告,
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多数没听说过“三次革命报告”，
00:53
but this was a very prominent突出 report报告.
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这是一份杰出的报告，
00:55
It was put together一起
by a brilliant辉煌 group组 of people --
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出自一群优秀人才之手，
00:58
it actually其实 included包括
two Nobel诺贝尔 laureates获奖者 --
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其中包括两名诺奖得主。
01:01
and this report报告 was presented呈现
to the President主席 of the United联合的 States状态,
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该报告最终呈送美国总统审阅。
01:04
and it argued争论 that the US was on the brink边缘
of economic经济 and social社会 upheaval动荡
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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产业 automation自动化
was going to put millions百万 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报告 was delivered交付
to President主席 Lyndon林登 Johnson约翰逊
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时任总统林登·约翰逊收到报告时
01:17
in March游行 of 1964.
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是1964年3月。
01:19
So that's now over 50 years年份,
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如今五十多年过去了，
01:21
and, of course课程, that
hasn't有没有 really happened发生.
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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故事 again and again.
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警钟一再响起，
01:26
This alarm报警 has been raised上调 repeatedly反复,
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但最终总是虚惊一场。
01:28
but it's always been a false假 alarm报警.
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01:30
And because it's been a false假 alarm报警,
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随着虚惊不断发生，
01:32
it's led to a very conventional常规 way
of thinking思维 about this.
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人们对其产生了思维惯性：
01:35
And that says说 essentially实质上 that yes,
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动荡本质上无可避免，
01:37
technology技术 may可能 devastate蹂躏
entire整个 industries行业.
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新技术势必席卷整个工业界
01:40
It may可能 wipe擦拭 out whole整个 occupations职业
and types类型 of work.
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并取代所有的工作岗位。
01:43
But at the same相同 time, of course课程,
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但与此同时，
01:45
progress进展 is going to lead铅
to entirely完全 new新 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新 industries行业
that will arise出现 in the future未来,
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在未来，新型工业将会兴起，
01:50
and those industries行业, of course课程,
will have to hire聘请 people.
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势必产生新的用人需求。
01:53
There'll有会 be new新 kinds种 of work
that will appear出现,
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未来将会出现全新的工作，
01:56
and those might威力 be things that today今天
we can't really even imagine想像.
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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故事 so far远,
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这便是迄今为止的故事，
02:01
and it's been a positive正 story故事.
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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圈 out that the new新 jobs工作
that have been created创建
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02:06
have generally通常 been
a lot better than the old旧 ones那些.
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通常远胜过旧的工作。
02:08
They have, for example例,
been more engaging卡.
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新工作更有吸引力，
02:11
They've他们已经 been in safer更安全,
more comfortable自在 work environments环境,
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工作环境更为安全舒适，
02:15
and, of course课程, they've他们已经 paid支付 more.
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挣得自然也更多。
02:16
So it has been a positive正 story故事.
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所以这个故事是乐观的，
02:18
That's the way things
have played发挥 out so far远.
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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特定
class类 of worker工人
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02:24
for whom谁 the story故事
has been quite相当 different不同.
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其境遇却全然不同。
对这个群体来说，
02:27
For these workers工人,
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02:29
technology技术 has completely全然
decimated元气大伤 their其 work,
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科技彻底取代了他们的工作，
02:32
and it really hasn't有没有 created创建
any new新 opportunities机会 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工人, of course课程,
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当然，我所指的“劳动群体”，
02:37
are horses马匹.
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正是马。
02:38
(Laughter笑声)
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（笑声）
02:40
So I can ask问 a very provocative挑衅 question题:
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由此我便能提出一个尖锐的问题：
02:43
Is it possible可能 that at some
point点 in the future未来,
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在未来，是否有可能
02:46
a significant重大 fraction分数 of the human人的
workforce劳动力 is going to be made制作 redundant冗
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会出现相当数量的劳动力冗余
02:51
in the way that horses马匹 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威力 have a very visceral内脏,
reflexive反思 reaction反应 to that.
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02:56
You might威力 say, "That's absurd荒诞.
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反驳道：“荒唐！
02:58
How can you possibly或者 compare比较
human人的 beings众生 to horses马匹?"
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牲畜岂能和人相比？”
03:02
Horses马匹, of course课程, are very limited有限,
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马的能力固然有限，
03:04
and when cars汽车 and trucks卡车
and tractors拖拉机 came来了 along沿,
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当汽车、卡车和拖拉机出现后，
03:07
horses马匹 really had nowhere无处 else其他 to turn转.
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马便没了用武之地。
03:09
People, on the other hand手,
are intelligent智能;
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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学习, we can adapt适应.
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03:14
And in theory理论,
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因此理论上讲，
03:15
that ought应该 to mean that we can
always find something new新 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留
relevant相应 to the future未来 economy经济.
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03:21
But here's这里的 the really
critical危急 thing to understand理解.
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但我们必须意识到的关键是，
03:24
The machines机 that will threaten威胁
workers工人 in the future未来
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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汽车
and trucks卡车 and tractors拖拉机
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和取代了马匹的汽车、卡车或拖拉机
03:30
that displaced流离失所 horses马匹.
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绝不可同日而语。
03:32
The future未来 is going to be full充分
of thinking思维, learning学习, adapting适应 machines机.
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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手段
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这便真正意味着
03:38
is that technology技术 is finally最后
beginning开始 to encroach侵犯
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技术终将开始入侵
03:41
on that fundamental基本的 human人的 capability能力 --
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最根本的人类能力——
03:44
the thing that makes品牌 us
so different不同 from horses马匹,
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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远,
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正是由于这种能力，
03:49
has allowed允许 us to stay留 ahead先
of the march游行 of progress进展
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人们才能引领时代发展，
03:52
and remain留 relevant相应,
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并始终作用于经济
03:53
and, in fact事实, indispensable必不可少
to the economy经济.
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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不同
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所以今天的信息技术
04:00
about today's今天的 information信息 technology技术
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相对于过去的技术革新
04:02
relative相对的 to what we've我们已经 seen看到 in the past过去?
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其不同之处究竟在哪里呢？
04:04
I would point点 to three三 fundamental基本的 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看到
this ongoing不断的 process处理
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第一，我们已经目睹了这一进程
04:12
of exponential指数 acceleration促进.
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指数爆炸式的增长速度。
04:14
I know you all know about Moore's摩尔定律 law法,
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想必大家都了解摩尔定律，
04:16
but in fact事实, it's more
broad-based广泛的 than that;
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但其适用面其实要宽广得多
04:18
it extends扩展 in many许多 cases例,
for example例, to software软件,
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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扩展 to communications通讯,
bandwidth带宽 and so forth向前.
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04:25
But the really key键 thing to understand理解
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但我们要意识到的关键是
04:27
is that this acceleration促进 has now
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事实, it's been going on for decades几十年.
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实际上已经有几十年了。
04:32
If you measure测量 from the late晚了 1950s,
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若从五十年代末
04:35
when the first integrated集成
circuits电路 were fabricated制造,
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第一批集成电路问世算起，
04:38
we've我们已经 seen看到 something on the order订购
of 30 doublings倍增 in computational计算 power功率
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我们现今的计算能力已经翻了30番。
04:42
since以来 then.
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04:44
That's just an extraordinary非凡 number数
of times时 to double双 any quantity数量,
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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手段
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它意味着
04:49
is that we're now at a point点
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非凡 amount量
of absolute绝对 progress进展,
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04:54
and, of course课程, things are going
to continue继续 to also也 accelerate加速
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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点.
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04:58
So as we look forward前锋
to the coming未来 years年份 and decades几十年,
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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手段
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准备 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震惊 us.
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05:06
The second第二 key键 thing
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第二，
05:08
is that the machines机 are,
in a limited有限 sense感, beginning开始 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人类水平 AIAI,
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我此话所指，并非是智力堪比人类，
05:14
or science科学 fiction小说
artificial人造 intelligence情报;
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或是科幻小说中出现的人工智能。
05:17
I simply只是 mean that machines机 and algorithms算法
are making制造 decisions决定.
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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解 problems问题,
and most最 importantly重要的, they're learning学习.
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解决问题，以及最重要的，能够自我学习。
05:26
In fact事实, if there's one technology技术
that is truly真 central中央 to this
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其实如果说有一项核心技术
05:29
and has really become成为
the driving主动 force力 behind背后 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机 learning学习,
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05:33
which哪一个 is just becoming变得
this incredibly令人难以置信 powerful强大,
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一项正在显示其惊人威力，
05:36
disruptive破坏性, scalable可扩展性 technology技术.
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颠覆性，以及扩展性的技术。
05:39
One of the best最好 examples例子
I've seen看到 of that recently最近
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近来我见到的最佳事例
05:42
was what Google's谷歌的 DeepMindDeepMind
division师 was able能够 to do
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就有谷歌DeepMind团队研发了
05:44
with its AlphaGoAlphaGo system系统.
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AlphaGo系统，
05:46
Now, this is the system系统 that was able能够
to beat击败 the best最好 player播放机 in the world世界
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在历史悠久的围棋游戏上
05:50
at the ancient古 game游戏 of Go.
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击败了世界最强高手。
05:52
Now, at least最小 to me,
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而至少在我看来，
05:53
there are two things that really
stand站 out about the game游戏 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播放 the game游戏,
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05:59
the number数 of configurations配置
that the board板 can be in
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棋盘上可能的变化
06:02
is essentially实质上 infinite无穷.
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基本上无法穷尽。
06:03
There are actually其实 more possibilities可能性
than there are atoms原子 in the universe宇宙.
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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手段 is,
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这便意味着，
06:09
you're never going to be able能够 to build建立
a computer电脑 to win赢得 at the game游戏 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棋 was approached接近, for example例,
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采用设计国际象棋软件的思路，
06:15
which哪一个 is basically基本上 to throw扔
brute-force蛮力 computational计算 power功率 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明确地, a much more sophisticated复杂的,
thinking-like思考状 approach途径 is needed需要.
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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第二 thing
that really stands站立 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锦标赛 Go players玩家,
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即便去请教一位围棋冠军，
06:30
this person人 cannot不能 necessarily一定
even really articulate说出 what exactly究竟 it is
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他也不一定能讲清自己下棋时
06:34
they're thinking思维 about
as they play玩 the game游戏.
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究竟是如何思考的。
06:37
It's often经常 something
that's very intuitive直观的,
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棋手常依赖某种直观的判断，
06:39
it's almost几乎 just like a feeling感觉
about which哪一个 move移动 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特定 those two qualities气质,
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鉴于以上两点，
06:44
I would say that playing播放 Go
at a world世界 champion冠军 level水平
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按说要把围棋下到世界冠军水平，
06:48
really ought应该 to be something
that's safe安全 from automation自动化,
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机器是无法胜任的，
06:51
and the fact事实 that it isn't should really
raise提高 a cautionary警示 flag旗 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原因 is that we tend趋向
to draw画 a very distinct不同 line线,
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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侧 of that line线
are all the jobs工作 and tasks任务
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在界线的一侧，是我们认为
07:03
that we perceive感知 as being存在 on some level水平
fundamentally从根本上 routine常规 and repetitive重复
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较为基础，常规，重复
07:08
and predictable可预测.
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且容易预测的工作。
07:09
And we know that these jobs工作
might威力 be in different不同 industries行业,
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这类工作可能来自不同行业，
07:12
they might威力 be in different不同 occupations职业
and at different不同 skill技能 levels水平,
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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天生 predictable可预测,
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但本质上都是可以预测的，
07:17
we know they're probably大概 at some point点
going to be susceptible易感
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因此终有一日会受到
机器学习的冲击，
07:21
to machine机 learning学习,
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并走向自动化。
07:22
and therefore因此, to automation自动化.
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这类工作数目可是不少
07:23
And make no mistake错误 --
that's a lot of jobs工作.
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07:25
That's probably大概 something
on the order订购 of roughly大致 half半
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经济体中差不多一半的工作
07:28
the jobs工作 in the economy经济.
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都属于此类。
07:30
But then on the other side侧 of that line线,
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而界线另一侧的工作，
07:32
we have all the jobs工作
that require要求 some capability能力
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我们认为需要特殊的能力，
07:36
that we perceive感知 as being存在 uniquely独特地 human人的,
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只有人能胜任，
07:38
and these are the jobs工作
that we think are safe安全.
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所以这些工作是安全的。
07:41
Now, based基于 on what I know
about the game游戏 of Go,
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以我对围棋的了解，
07:43
I would've会一直 guessed猜 that it really ought应该
to be on the safe安全 side侧 of that line线.
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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事实 that it isn't,
and that Google谷歌 solved解决了 this problem问题,
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07:50
suggests提示 that that line线 is going
to be very dynamic动态.
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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转移,
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移向安全的一侧，
07:53
and it's going to shift转移 in a way
that consumes消耗 more and more jobs工作 and tasks任务
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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目前 perceive感知
as being存在 safe安全 from automation自动化.
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逐渐纳入不安全的范围。
08:01
The other key键 thing to understand理解
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还有一点需要了解，
08:03
is that this is by no means手段 just about
low-wage低工资 jobs工作 or blue-collar蓝领 jobs工作,
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会遭受冲击的不只是低薪的蓝领工作，
08:08
or jobs工作 and tasks任务 doneDONE by people
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或是教育程度较低的人
08:10
that have relatively相对
low低 levels水平 of education教育.
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所从事的工作。
08:12
There's lots of evidence证据 to show显示
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诸多证据表明
08:14
that these technologies技术 are rapidly急速
climbing攀登 the skills技能 ladder阶梯.
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科技的威力正在飞速攀升。
08:17
So we already已经 see an impact碰撞
on professional专业的 jobs工作 --
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我们已经看到科技对专业工作的冲击，
08:21
tasks任务 doneDONE by people like accountants会计师,
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受到冲击的包括会计师
08:25
financial金融 analysts分析师,
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财政分析师
08:26
journalists记者,
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记者
08:28
lawyers律师, radiologists放射科医生 and so forth向前.
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律师，以及放射科医师等。
08:30
So a lot of the assumptions假设 that we make
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而我们目前有很多假设
08:32
about the kind类 of occupations职业
and tasks任务 and jobs工作
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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受威胁
by automation自动化 in the future未来
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这些假设将来都很可能遭到挑战。
08:38
are very likely容易 to be
challenged挑战 going forward前锋.
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当我们汇总这些趋势后，
08:40
So as we put these trends趋势 together一起,
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08:42
I think what it shows节目 is that we could
very well end结束 up in a future未来
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便能看出，未来我们很可能面临
08:45
with significant重大 unemployment失业.
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严重的失业。
08:48
Or at a minimum最低限度,
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就算退一万步讲，
08:49
we could face面对 lots of underemployment就业不足
or stagnant滞 wages工资,
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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下降 wages工资.
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乃至下降。
08:56
And, of course课程, soaring冲天 levels水平
of inequality不等式.
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社会不平等自然也会激增。
08:58
All of that, of course课程, is going to put
a terrific了不起 amount量 of stress强调
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以上问题势必会给社会结构
09:03
on the fabric布 of society社会.
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带来巨大压力。
09:04
But beyond外 that, there's also也
a fundamental基本的 economic经济 problem问题,
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除此之外，还有一个根本的经济问题：
09:08
and that arises出现 because jobs工作
are currently目前 the primary主 mechanism机制
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就业是我们当前主要的收入分配机制，
09:13
that distributes分配 income收入,
and therefore因此 purchasing购买 power功率,
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有了收入，消费者就有了购买力
09:16
to all the consumers消费者 that buy购买 the products制品
and services服务 we're producing生产.
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可以购买人们生产出的产品和服务。
09:22
In order订购 to have a vibrant充满活力 market市场 economy经济,
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为使市场经济繁荣，
09:25
you've got to have
lots and lots of consumers消费者
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需要大量有购买力的消费者
09:27
that are really capable能 of buying购买
the products制品 and services服务
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来消化社会生产出的产品和服务。
09:30
that are being存在 produced生成.
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09:31
If you don't have that,
then you run跑 the risk风险
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否则我们就会面临经济停滞
09:34
of economic经济 stagnation停滞,
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甚至螺旋式下降的风险，
09:35
or maybe even a declining下降 economic经济 spiral螺旋,
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09:39
as there simply只是 aren't不 enough足够
customers顾客 out there
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因为没有足够的消费者
09:41
to buy购买 the products制品
and services服务 being存在 produced生成.
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购买生产出的产品和服务。
09:44
It's really important重要 to realize实现
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重要的是要认识到，
09:46
that all of us as individuals个人 rely依靠
on access访问 to that market市场 economy经济
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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订购 to be successful成功.
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来获得成功。
09:53
You can visualize想象 that by thinking思维
in terms条款 of one really exceptional优秀 person人.
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我们不妨来想象一位杰出的人物，
09:58
Imagine想像 for a moment时刻 you take,
say, Steve史蒂夫 Jobs工作,
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比如说史蒂夫·乔布斯，
10:01
and you drop下降 him
on an island岛 all by himself他自己.
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把他一个人丢在荒岛上，
10:03
On that island岛, he's going
to be running赛跑 around,
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让他四处奔走
10:06
gathering搜集 coconuts椰子 just like anyone任何人 else其他.
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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特别,
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他肯定成不了什么“乔帮主”，
10:11
and the reason原因, of course课程,
is that there is no market市场
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原因很显然，岛上没有手机市场
10:14
for him to scale规模
his incredible难以置信 talents人才 across横过.
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能让他施展才智，大显身手。
10:17
So access访问 to this market市场
is really critical危急 to us as individuals个人,
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所以市场对我们个人来说至关重要，
10:20
and also也 to the entire整个 system系统
in terms条款 of it being存在 sustainable可持续发展.
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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题 then becomes变:
What exactly究竟 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视图 this
through通过 a very utopian乌托邦 framework骨架.
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10:32
You can imagine想像 a future未来
where we all have to work less减,
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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闲暇,
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拥有更多闲暇时光陪伴家人，
10:38
more time to spend花 with our families家庭,
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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真正的 rewarding奖励
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10:43
and so forth向前.
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这是非常美妙的愿景，
10:44
And I think that's a terrific了不起 vision视力.
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10:46
That's something that we should
absolutely绝对 strive努力 to move移动 toward往.
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值得我们为之全力奋斗。
10:50
But at the same相同 time, I think
we have to be realistic实际,
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但同时我们也要务实，
10:52
and we have to realize实现
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要意识到
10:54
that we're very likely容易 to face面对
a significant重大 income收入 distribution分配 problem问题.
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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容易
to be left behind背后.
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许多人可能会落在后面。
11:03
And I think that in order订购
to solve解决 that problem问题,
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要解决收入分配问题，
11:05
we're ultimately最终 going
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脱钩 incomes收入 from traditional传统 work.
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将收入与传统的工作分离。
11:10
And the best最好, more straightforward直截了当
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类 of a guaranteed保证 income收入
or universal普遍 basic基本 income收入.
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便是设立某种无条件基本收入。
11:16
Now, basic基本 income收入 is becoming变得
a very important重要 idea理念.
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基本收入已经成为重要的概念，
11:19
It's getting得到 a lot
of traction牵引 and attention注意,
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广受关注及推崇，
11:21
there are a lot of important重要
pilot飞行员 projects项目
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世界各国也相继开展了
11:23
and experiments实验 going on
throughout始终 the world世界.
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很多重大试点项目。
11:26
My own拥有 view视图 is that a basic基本 income收入
is not a panacea万能药;
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我认为基本收入不是灵丹妙药，
11:29
it's not necessarily一定
a plug-and-play即插即用 solution解,
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不是“一用就见效”的解决方案。
11:32
but rather宁, it's a place地点 to start开始.
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这仅是一个起点，一个设想
11:34
It's an idea理念 that we can
build建立 on and refine提炼.
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还有待我们在其基础上加以完善。
11:36
For example例, one thing that I have
written书面 quite相当 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可能性 of incorporating结合
explicit明确的 incentives奖励 into a basic基本 income收入.
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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说明 that,
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11:46
imagine想像 that you are a struggling奋斗的
high高 school学校 student学生.
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想象你是个苦苦挣扎的高中生，
11:48
Imagine想像 that you are at risk风险
of dropping落下 out of school学校.
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正面临被开除的风险。
11:52
And yet然而, suppose假设 you know
that at some point点 in the future未来,
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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物 what,
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11:56
you're going to get the same相同
basic基本 income收入 as everyone大家 else其他.
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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心神, that creates创建
a very perverse悖 incentive激励
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在我看来，这将造成一种不当动机
12:03
for you to simply只是 give up
and drop下降 out of school学校.
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使你甘心直接退学。
12:06
So I would say, let's not
structure结构体 things that way.
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所以说，办事不能这样一刀切。
12:08
Instead代替, let's pay工资 people who graduate毕业
from high高 school学校 somewhat有些 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只是 drop下降 out.
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12:16
And we can take that idea理念 of building建造
incentives奖励 into a basic基本 income收入,
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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延伸 it to other areas区.
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12:21
For example例, we might威力 create创建
an incentive激励 to work in the community社区
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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其他,
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12:26
or perhaps也许 to do positive正
things for the environment环境,
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鼓励保护环境的行为，等等。
12:29
and so forth向前.
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12:30
So by incorporating结合 incentives奖励
into a basic基本 income收入,
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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威力 actually其实 improve提高 it,
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1629
12:35
and also也, perhaps也许, take at least最小
a couple一对 of steps脚步
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或者把步子迈得再大些，
12:37
towards向 solving解 another另一个 problem问题
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去解决另一个问题
12:40
that I think we're quite相当 possibly或者
going to face面对 in the future未来,
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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含义 and fulfillment履行,
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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占据 our time
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那我们又该如何利用时间，
12:49
in a world世界 where perhaps也许
there's less减 demand需求 for traditional传统 work?
275
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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扩展 and refining精制
a basic基本 income收入,
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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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2336
我们可以令其更为合意，
12:59
and we can also也, perhaps也许, make it
more politically政治上 and socially社交上 acceptable接受
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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可行 --
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1164
13:05
and, of course课程, by doing that,
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最终有更大的几率
13:07
we increase增加 the odds可能性
that it will actually其实 come to be.
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使这项制度真正落地。
13:11
I think one of the most最 fundamental基本的,
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对于推行基本收入制度，
13:14
almost几乎 instinctive直觉的 objections反对
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或者任何重大的保险金制度，
13:16
that many许多 of us have
to the idea理念 of a basic基本 income收入,
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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重大
expansion扩张 of the safety安全 net净,
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几乎是出于本能，我们会担心
13:23
is this fear恐惧 that we're going to end结束 up
with too many许多 people
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最终有太多人安于坐享其成，
13:27
riding骑术 in the economic经济 cart大车,
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而没有足够的人真正去推动经济发展。
13:28
and not enough足够 people pulling拉 that cart大车.
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13:31
And yet然而, really, the whole整个 point点
I'm making制造 here, of course课程,
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而我在此要表达的观点是
13:33
is that in the future未来,
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在未来，
13:35
machines机 are increasingly日益 going
to be capable能 of pulling拉 that cart大车 for us.
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机器将会替我们更好地推动经济发展。
13:39
That should give us more options选项
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1990
这给我们构建社会，组织经济
13:41
for the way we structure结构体
our society社会 and our economy经济,
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提供了更多选择方案。
13:45
And I think eventually终于, it's going to go
beyond外 simply只是 being存在 an option选项,
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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成为 an imperative势在必行.
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原因很显然，当今发生的一切
13:50
The reason原因, of course课程,
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这样 a degree度 of stress强调 on our society社会,
297
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2014
13:55
and also也 because jobs工作 are that mechanism机制
298
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而就业机制又是
13:57
that gets得到 purchasing购买 power功率 to consumers消费者
299
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1965
赋予消费者购买力，
13:59
so they can then drive驾驶 the economy经济.
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驱动经济发展的重要抓手。
14:02
If, in fact事实, that mechanism机制
begins开始 to erode侵蚀 in the future未来,
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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更换
it with something else其他
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否则我们便将面临
14:08
or we're going to face面对 the risk风险
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1563
14:10
that our whole整个 system系统 simply只是
may可能 not be sustainable可持续发展.
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社会无法持续运转的风险。
14:12
But the bottom底部 line线 here
is that I really think
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但有一点我坚信不疑，
14:15
that solving解 these problems问题,
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那便是：如何解决这些问题，
14:17
and especially特别 finding发现 a way
to build建立 a future未来 economy经济
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尤其是寻找一条构建未来经济的途径
14:21
that works作品 for everyone大家,
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2013
使得社会中每个阶层
14:23
at every一切 level水平 of our society社会,
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均能从中受益，
14:25
is going to be one of the most最 important重要
challenges挑战 that we all face面对
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将是我们未来亟需共同面对的
14:28
in the coming未来 years年份 and decades几十年.
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至关重要的挑战。
14:30
Thank you very much.
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谢谢大家！
14:32
(Applause掌声)
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（掌声）
Translated by Eric Yang
Reviewed by Kerry Chen

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ABOUT THE SPEAKER
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.

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. 

More profile about the speaker
Martin Ford | Speaker | TED.com
THE ORIGINAL VIDEO ON TED.COM