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How We'll Earn Money in a Future Without Jobs
Martin Ford
TED2017, Vancouver, BC, Canada
April 25, 2017
如果未来工作被机器取代，我们该如何应对？
马丁·福特
TED2017大会，加拿大温哥华
2017年4月25日
I'm going to begin with a scary question: Are we headed toward a future without jobs? The remarkable progress that we're seeing in technologies like self-driving cars has led to an explosion of interest in this question, but because it's something that's been asked so many times in the past, maybe what we should really be asking is whether this time is really different. The fear that automation might displace workers and potentially lead to lots of unemployment goes back at a minimum 200 years to the Luddite revolts in England. And since then, this concern has come up again and again.
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？ 如今目睹了自动驾驶汽车等技术的显著进步， 我们对此问题的关注日益激增，但这一问题在过去人们已多次提及，也许我们真正应当关心的是这次情况是否会有所不同。 人类一直担忧，自动化会取代工人，进而导致大量失业，从二百多年前的英国卢德运动开始，这种担忧便一再出现。
I'm going to guess that most of you have probably never heard of the Triple Revolution report, but this was a very prominent report. It was put together by a brilliant group of people -- it actually included two Nobel laureates -- and this report was presented to the President of the United States, and it argued that the US was on the brink of economic and social upheaval because industrial automation was going to put millions of people out of work. Now, that report was delivered to President Lyndon Johnson in March of 1964. So that's now over 50 years, and, of course, that hasn't really happened. And that's been the story again and again.
我猜在座各位 多数没听说过“三次革命报告”，这是一份杰出的报告，出自一群优秀人才之手，其中包括两名诺奖得主。 该报告最终呈送美国总统审阅。报告指出，美国正处于经济和社会动荡的边缘，因为工业自动化将导致数百万工人下岗失业。时任总统林登·约翰逊收到报告时 是1964年3月。如今五十多年过去了，美国并没有发生动荡。这样的故事从此不断上演。
This alarm has been raised repeatedly, but it's always been a false alarm. And because it's been a false alarm, it's led to a very conventional way of thinking about this. And that says essentially that yes, technology may devastate entire industries. It may wipe out whole occupations and types of work. But at the same time, of course, progress is going to lead to entirely new things. So there will be new industries that will arise in the future, and those industries, of course, will have to hire people. There'll be new kinds of work that will appear, and those might be things that today we can't really even imagine. And that has been the story so far, and it's been a positive story.
警钟一再响起，但最终总是虚惊一场。随着虚惊不断发生，人们对其产生了思维惯性：动荡本质上无可避免，新技术势必席卷整个工业界并取代所有的工作岗位。但与此同时，科技进步也将带来全新的变化。在未来，新型工业将会兴起，势必产生新的用人需求。未来将会出现全新的工作，有的甚至今天我们根本无法想像。这便是迄今为止的故事，一直是令人乐观的。
It turns out that the new jobs that have been created have generally been a lot better than the old ones. They have, for example, been more engaging. They've been in safer, more comfortable work environments, and, of course, they've paid more. So it has been a positive story. That's the way things have played out so far. But there is one particular class of worker for whom the story has been quite different. For these workers, technology has completely decimated their work, and it really hasn't created any new opportunities at all. And these workers, of course, are horses.
事实证明，新出现的工作通常远胜过旧的工作。新工作更有吸引力，工作环境更为安全舒适，挣得自然也更多。所以这个故事是乐观的，而事情迄今的发展亦是如此。但有一类特殊的劳动群体，其境遇却全然不同。对这个群体来说，科技彻底取代了他们的工作，却并未为其带来任何新的就业机会。当然，我所指的“劳动群体”，正是马。
So I can ask a very provocative question: Is it possible that at some point in the future, a significant fraction of the human workforce is going to be made redundant in the way that horses were? Now, you might have a very visceral, reflexive reaction to that. You might say, "That's absurd. How can you possibly compare human beings to horses?" Horses, of course, are very limited, and when cars and trucks and tractors came along, horses really had nowhere else to turn. People, on the other hand, are intelligent; we can learn, we can adapt. And in theory, that ought to mean that we can always find something new to do, and that we can always remain relevant to the future economy.
由此我便能提出一个尖锐的问题：在未来，是否有可能会出现相当数量的劳动力冗余，正如马的遭遇一般？ 出于本能，人们可能会下意识地反驳道：“荒唐！ 牲畜岂能和人相比？” 马的能力固然有限，当汽车、卡车和拖拉机出现后，马便没了用武之地。但人却是具有智慧的，能够学习，并且会适应环境。 因此理论上讲，人应当总能找到新的工作，始终保持与未来经济的联系。
But here's the really critical thing to understand. The machines that will threaten workers in the future are really nothing like those cars and trucks and tractors that displaced horses. The future is going to be full of thinking, learning, adapting machines. And what that really means is that technology is finally beginning to encroach on that fundamental human capability -- the thing that makes us so different from horses, and the very thing that, so far, has allowed us to stay ahead of the march of progress and remain relevant, and, in fact, indispensable to the economy. So what is it that is really so different about today's information technology relative to what we've seen in the past? I would point to three fundamental things.
但我们必须意识到的关键是，未来将威胁取代劳动力的机器和取代了马匹的汽车、卡车或拖拉机绝不可同日而语。未来的机器将具有思维，学习和适应能力。这便真正意味着技术终将开始入侵最根本的人类能力—— 那种使我们有别于动物的能力。正是由于这种能力，人们才能引领时代发展，并始终作用于经济 成为其不可或缺的重要一环。所以今天的信息技术 相对于过去的技术革新，其不同之处究竟在哪里呢？我将指出三个基本的方面。
The first thing is that we have seen this ongoing process of exponential acceleration. I know you all know about Moore's law, but in fact, it's more broad-based than that; it extends in many cases, for example, to software, it extends to communications, bandwidth and so forth. But the really key thing to understand is that this acceleration has now been going on for a really long time. In fact, it's been going on for decades. If you measure from the late 1950s, when the first integrated circuits were fabricated, we've seen something on the order of 30 doublings in computational power since then. That's just an extraordinary number of times to double any quantity, and what it really means is that we're now at a point where we're going to see just an extraordinary amount of absolute progress, and, of course, things are going to continue to also accelerate from this point. So as we look forward to the coming years and decades, I think that means that we're going to see things that we're really not prepared for. We're going to see things that astonish us.
第一，我们已经目睹了这一进程指数爆炸式的增长速度。想必大家都了解摩尔定律，但其适用面其实要宽广得多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。但我们要意识到的关键是这种增长已经持续了很久，实际上已经有几十年了。若从五十年代末第一批集成电路问世算起，我们现今的计算能力已经翻了30番。对于任何事物，这样的增长量都是惊人的，它意味着 我们正处在一个时间点，能够目睹科技巨大的进步，并且从今往后，科技仍将继续加速增长。 因此，当我们期待若干年后的未来时，我们将面临始料未及的变迁；我们将见证令人惊奇的成就。
The second key thing is that the machines are, in a limited sense, beginning to think. And by this, I don't mean human-level AI, or science fiction artificial intelligence; I simply mean that machines and algorithms are making decisions. They're solving problems, and most importantly, they're learning. In fact, if there's one technology that is truly central to this and has really become the driving force behind this, it's machine learning, which is just becoming this incredibly powerful, disruptive, scalable technology.
第二， 狭义上讲，机器开始具有思考能力。我此话所指，并非是智力堪比人类，或是科幻小说中出现的人工智能。我只想指出，机器和算法将能够进行决策，解决问题，以及最重要的，能够自我学习。其实如果说有一项核心技术是科技进步的关键驱动力，那便是机器学习，一项正在显示其惊人威力，颠覆性以及扩展性的技术。
One of the best examples I've seen of that recently was what Google's DeepMind division was able to do with its AlphaGo system. Now, this is the system that was able to beat the best player in the world at the ancient game of Go. Now, at least to me, there are two things that really stand out about the game of Go. One is that as you're playing the game, the number of configurations that the board can be in is essentially infinite. There are actually more possibilities than there are atoms in the universe. So what that means is, you're never going to be able to build a computer to win at the game of Go the way chess was approached, for example, which is basically to throw brute-force computational power at it. So clearly, a much more sophisticated, thinking-like approach is needed. The second thing that really stands out is that, if you talk to one of the championship Go players, this person cannot necessarily even really articulate what exactly it is they're thinking about as they play the game. It's often something that's very intuitive, it's almost just like a feeling about which move they should make.
近来我见到的最佳事例就是谷歌 DeepMind 团队研发了 AlphaGo 系统，在历史悠久的围棋游戏上击败了世界最强高手。而至少在我看来，围棋有两个突出的特点。其一是在下棋时，棋盘上可能的变化基本上无法穷尽。棋局的数目甚至比宇宙中的原子还要多。这便意味着，若要造出一台下围棋能赢的电脑，采用设计国际象棋软件的思路，通过增加计算资源暴力破解，是不可行的，必然要采用一种更为复杂，更贴近思考的途径。第二个突出的特点便是，即便去请教一位围棋冠军，他也不一定能讲清自己下棋时究竟是如何思考的。棋手常依赖某种直观的判断，几乎是凭感觉，来决定该走哪手棋。
So given those two qualities, I would say that playing Go at a world champion level really ought to be something that's safe from automation, and the fact that it isn't should really raise a cautionary flag for us. And the reason is that we tend to draw a very distinct line, and on one side of that line are all the jobs and tasks that we perceive as being on some level fundamentally routine and repetitive and predictable. And we know that these jobs might be in different industries, they might be in different occupations and at different skill levels, but because they are innately predictable, we know they're probably at some point going to be susceptible to machine learning, and therefore, to automation. And make no mistake -- that's a lot of jobs. That's probably something on the order of roughly half the jobs in the economy.
鉴于以上两点，按说要把围棋下到世界冠军水平，机器是无法胜任的，而事实并非如此，我们应当引起警惕了。究其原因，我们习惯划一条明确的界线在界线的一侧，是我们认为较为基础，常规，重复且容易预测的工作。这类工作可能来自不同行业，不同岗位，所需技能也有高低之分，但本质上都是可以预测的，因此终有一日会受到机器学习的冲击，并走向自动化。这类工作数目可是不少，经济体中差不多一半的工作都属于此类。
But then on the other side of that line, we have all the jobs that require some capability that we perceive as being uniquely human, and these are the jobs that we think are safe. Now, based on what I know about the game of Go, I would've guessed that it really ought to be on the safe side of that line. But the fact that it isn't, and that Google solved this problem, suggests that that line is going to be very dynamic. It's going to shift, and it's going to shift in a way that consumes more and more jobs and tasks that we currently perceive as being safe from automation.
而界线另一侧的工作，我们认为需要特殊的能力，只有人能胜任，所以这些工作是安全的。以我对围棋的了解，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，也说明这条分界线将会剧烈变动，移向安全的一侧，将我们当前认为无法自动化的工作任务逐渐纳入不安全的范围。
The other key thing to understand is that this is by no means just about low-wage jobs or blue-collar jobs, or jobs and tasks done by people that have relatively low levels of education. There's lots of evidence to show that these technologies are rapidly climbing the skills ladder. So we already see an impact on professional jobs -- tasks done by people like accountants, financial analysts, journalists, lawyers, radiologists and so forth. So a lot of the assumptions that we make about the kind of occupations and tasks and jobs that are going to be threatened by automation in the future are very likely to be challenged going forward.
还有一点需要了解，会遭受冲击的不只是低薪的蓝领工作，或是教育程度较低的人所从事的工作。诸多证据表明，科技的威力正在飞速攀升。我们已经看到科技对专业工作的冲击，受到冲击的包括会计师、财政分析师、记者、律师，以及放射科医师等。而我们目前有很多假设在探讨哪些职业、任务和工作未来将遭到自动化的冲击。这些假设将来都很可能遭到挑战。
So as we put these trends together, I think what it shows is that we could very well end up in a future with significant unemployment. Or at a minimum, we could face lots of underemployment or stagnant wages, maybe even declining wages. And, of course, soaring levels of inequality. All of that, of course, is going to put a terrific amount of stress on the fabric of society. But beyond that, there's also a fundamental economic problem, and that arises because jobs are currently the primary mechanism that distributes income, and therefore purchasing power, to all the consumers that buy the products and services we're producing.
当我们汇总这些趋势后，便能看出，未来我们很可能面临严重的失业。就算退一万步讲，我们也会面临就业不足，或者工资水平停滞乃至下降。社会不平等自然也会激增。以上问题势必会给社会结构带来巨大压力。除此之外，还有一个根本的经济问题：就业是我们当前主要的收入分配机制，有了收入，消费者就有了购买力，可以购买人们生产出的产品和服务。
In order to have a vibrant market economy, you've got to have lots and lots of consumers that are really capable of buying the products and services that are being produced. If you don't have that, then you run the risk of economic stagnation, or maybe even a declining economic spiral, as there simply aren't enough customers out there to buy the products and services being produced.
为使市场经济繁荣，需要大量有购买力的消费者来消化社会生产出的产品和服务。否则我们就会面临经济停滞，甚至螺旋式下降的风险，因为没有足够的消费者购买生产出的产品和服务。
It's really important to realize that all of us as individuals rely on access to that market economy in order to be successful. You can visualize that by thinking in terms of one really exceptional person. Imagine for a moment you take, say, Steve Jobs, and you drop him on an island all by himself. On that island, he's going to be running around, gathering coconuts just like anyone else. He's really not going to be anything special, and the reason, of course, is that there is no market for him to scale his incredible talents across. So access to this market is really critical to us as individuals, and also to the entire system in terms of it being sustainable.
重要的是要认识到，作为个体，我们每个人都要靠参与市场经济来获得成功。我们不妨来想象一位杰出的人物，比如说史蒂夫·乔布斯，把他一个人丢在荒岛上，让他四处奔走去收集椰子，和其他人一样。 他肯定成不了什么“乔帮主”，原因很显然，岛上没有手机市场能让他施展才智，大显身手。所以市场对我们个人来说至关重要，同时也是整个社会可持续发展的重中之重。
So the question then becomes: What exactly could we do about this? And I think you can view this through a very utopian framework. You can imagine a future where we all have to work less, we have more time for leisure, more time to spend with our families, more time to do things that we find genuinely rewarding and so forth. And I think that's a terrific vision. That's something that we should absolutely strive to move toward. But at the same time, I think we have to be realistic, and we have to realize that we're very likely to face a significant income distribution problem. A lot of people are likely to be left behind. And I think that in order to solve that problem, we're ultimately going to have to find a way to decouple incomes from traditional work. And the best, more straightforward way I know to do that is some kind of a guaranteed income or universal basic income.
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。设想在未来，我们都会减少工作，拥有更多闲暇时光陪伴家人，或者做些真正怡情养性的事情，等等。这是非常美妙的愿景，值得我们为之全力奋斗。 但同时我们也要务实，要意识到 我们极有可能面临严重的收入分配问题。许多人可能会落在后面。要解决收入分配问题，我们最终要找到一条途径将收入与传统的工作分离。而据我所知，最直接有效的方法便是设立某种无条件基本收入。
Now, basic income is becoming a very important idea. It's getting a lot of traction and attention, there are a lot of important pilot projects and experiments going on throughout the world. My own view is that a basic income is not a panacea; it's not necessarily a plug-and-play solution, but rather, it's a place to start. It's an idea that we can build on and refine. For example, one thing that I have written quite a lot about is the possibility of incorporating explicit incentives into a basic income. To illustrate that, imagine that you are a struggling high school student. Imagine that you are at risk of dropping out of school. And yet, suppose you know that at some point in the future, no matter what, you're going to get the same basic income as everyone else. Now, to my mind, that creates a very perverse incentive for you to simply give up and drop out of school.
基本收入已经成为重要的概念，广受关注及推崇，世界各国也相继开展了很多重大试点项目。我认为基本收入不是灵丹妙药，不是“一用就见效”的解决方案。这仅是一个起点，一个设想还有待我们在其基础上加以完善。例如，我围绕这样一个设想写过不少文章，那便是，将显性激励整合到基本收入中。我具体解释一下，想象你是个苦苦挣扎的高中生，正面临被开除的风险。但假设你知道未来有这么一天，不管什么情况下，你都能得到和其他人一样的基本收入。在我看来，这将造成一种不当动机使你甘心直接退学。
So I would say, let's not structure things that way. Instead, let's pay people who graduate from high school somewhat more than those who simply drop out. And we can take that idea of building incentives into a basic income, and maybe extend it to other areas. For example, we might create an incentive to work in the community to help others, or perhaps to do positive things for the environment, and so forth. So by incorporating incentives into a basic income, we might actually improve it, and also, perhaps, take at least a couple of steps towards solving another problem that I think we're quite possibly going to face in the future, and that is, how do we all find meaning and fulfillment, and how do we occupy our time in a world where perhaps there's less demand for traditional work?
所以说，办事不能这样一刀切。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。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。比如，我们可以创造激励来鼓励社区义工，鼓励互相帮助，鼓励保护环境的行为，等等。通过将激励纳入基本收入制度中，我们便能改善这一制度，或者把步子迈得再大些，去解决另一个问题 ——未来我们很可能要面对的问题。那就是：未来我们可能不再需要大量的传统工作了，那我们又该如何利用时间，寻找生命的意义，实现人生的圆满呢？
So by extending and refining a basic income, I think we can make it look better, and we can also, perhaps, make it more politically and socially acceptable and feasible -- and, of course, by doing that, we increase the odds that it will actually come to be.
因此，通过改良并推广基本收入制度，我们可以令其更为合意，并且更容易为政界采纳，也更容易在社会中实施，最终有更大的几率使这项制度真正落地。
I think one of the most fundamental, almost instinctive objections that many of us have to the idea of a basic income, or really to any significant expansion of the safety net, is this fear that we're going to end up with too many people riding in the economic cart, and not enough people pulling that cart. And yet, really, the whole point I'm making here, of course, is that in the future, machines are increasingly going to be capable of pulling that cart for us. That should give us more options for the way we structure our society and our economy, And I think eventually, it's going to go beyond simply being an option, and it's going to become an imperative. The reason, of course, is that all of this is going to put such a degree of stress on our society, and also because jobs are that mechanism that gets purchasing power to consumers so they can then drive the economy. If, in fact, that mechanism begins to erode in the future, then we're going to need to replace it with something else or we're going to face the risk that our whole system simply may not be sustainable.
对于推行基本收入制度，或者任何重大的保险金制度，我想很多人都会持反对意见。其中有一条意见尤为根本，几乎是出于本能，我们会担心 最终有太多人安于坐享其成，而没有足够的人真正去推动经济发展。而我在此要表达的观点是在未来， 机器将会替我们更好地推动经济发展。这给我们构建社会，组织经济提供了更多选择方案。而我相信，最终这将不仅只是一种选择，更将成为大势所趋。原因很显然，当今发生的一切将使社会面临巨大的压力，而就业机制又是赋予消费者购买力，驱动经济发展的重要抓手。如果未来这一机制遭到侵蚀，我们便需要采用其他措施。否则我们便将面临社会无法持续运转的风险。
But the bottom line here is that I really think that solving these problems, and especially finding a way to build a future economy that works for everyone, at every level of our society, is going to be one of the most important challenges that we all face in the coming years and decades.
但有一点我坚信不疑，那便是：如何解决这些问题，尤其是寻找一条构建未来经济的途径使得社会中每个阶层均能从中受益，将是我们未来亟需共同面对的至关重要的挑战。
Thank you very much.
谢谢大家！
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