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.
一開始,我想先 提出一個駭人的問題: 我們是否正在邁向 一個沒有工作的未來? 我們看到科技的驚人進展, 比如自動駕駛的汽車, 讓很多人注意到我剛問的問題, 但因為在過去這個問題 已經被問過太多次了, 也許我們真正該問的是, 這次是否真的會有所不同? 恐懼自動化會取代工人, 並可能會導致許多人失業, 可追溯回至少兩百年前的 盧德(勒德)份子運動。 從那之後,這種擔憂就 一而再再而三地出現。
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.
我猜測, 在座大部份人可能從來沒有 聽過「三重革命」報告, 但它是份非常重要的報告。 它是由一群聰明人集思廣義出來的, 實際上還包括兩名諾貝爾得主, 這份報告被呈交給美國總統, 報告指出,美國正處在 經濟和社會動亂的邊緣, 因為工業自動化 將會讓數百萬人失去工作。 那份報告被呈交給詹森總統, 當時是 1964 年三月。 那是至少五十年以前的事, 當然,報告說的狀況沒有發生。 那故事從此不斷重覆上演。
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.
警報不斷重覆被發出, 但每次都是假警報。 因為一直都是假警報, 就導致對這狀況的慣性思維。 基本上,那思維是: 對啊,科技可能會破壞所有產業, 它有可能會徹底消滅 所有職業和各種工作; 但同時,當然, 進步也會引來全新的事物。 所以將來會有新的產業出現, 而那些產業,當然,一定會僱用人。 將來會出現新類型的工作會, 可能是我們現今無法想像的。 目前為止,故事一直是如此, 且一直是很正面的。
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.
結果,新創造出來的工作, 一般來說,比舊的工作好很多。 比如,新的工作比較吸引人。 工作環境比較安全、比較舒適, 當然,薪水也比較高。 所以這個故事一直很正面。 目前為止的發展也的確是這樣。 但特別有一類的工作者, 對他們來說,故事相當不同。 對這些工作者而言, 科技可說是大舉毀滅了他們的工作, 且完全沒有再創造出 新的機會給他們。 當然,這些工作者 是馬。
(Laughter)
(笑聲)
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.
我問一個會引發爭議的問題: 有沒有可能,在未來的某個時點, 將有一大部份的人類勞動力過剩, 就像馬所遭遇的情況。 對那個問題,你可能會有 很本能、反射性的反應。 你也許會說:「太荒唐了。 你怎麼能把人類拿來和馬做比較?」 當然,馬非常受限, 當汽車、卡車、牽引機 (拖拉機)出現, 馬就無處可去了。 另一方面,人有智慧; 我們能學習,我們能適應。 理論上, 那應該意味著 我們總能找到新的事情來做, 我們總能與未來的經濟持續相關。
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.
但要了解非常重要的一點。 在未來會威脅到工作者的機器, 完全不像取代了馬的汽車、 卡車、牽引機。 未來將會滿是會思考、 學習、適應的機器。 那意味著, 科技最終將會開始侵犯到 基礎的人類能力── 讓我們和馬大不相同的能力, 也是這能力,讓我們目前為止 能走在這進步發展的前端 並保有相關性, 事實上,也讓經濟少不了我們。 所以,相對於我們過去所看到的, 現今的資訊科技到底 有什麼如此不同的地方? 我要指出根本的三樣。
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,我們已見到這正在進行的過程 以指數級的速率加速。 我知道你們都明白摩爾定律, 但事實上,它的根基還要更廣; (註:不止適用於積體電路) 在許多情況下,它會延伸, 比如,延伸到軟體, 它也會延伸到通訊、頻寬、等等。 但,需要了解的關鍵點是, 這種加速現象已經 發生很長一段時間了。 事實上,已經有數十年了。 如果從 1950 年代末期開始算, 當第一個積體電路被製造出來, 從那時起, 我們目睹電腦運算的效能 倍增了大約三十次。 不論起初的量是多少, 倍增了那麼多次都是很可觀的。 它真正的意涵是, 我們正處在一個時點, 即將要看到很大量的絕對進展, 當然,這個時間點之後的加速 還是會持續下去。 所以當我們期待未來的 幾年及幾十年, 我們將會看到 我們完全沒準備會看到的事物, 我們將會看到讓我們吃驚的事物。
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.
第二個要點是 機器開始有限的思考。 我並不是指人類水平級的人工智慧, 或科幻小說中的人工智慧; 我指的只是會決策的機器和演算法。 它們會解決問題, 更重要的是,它們會學習。 事實上,有項技術扮演著中心角色, 同時也是背後的推動力, 就是機器學習, 它開始變得非常強大、 具顛覆性,是可擴展的技術。
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.
近期我看過最好的例子之一, 是 Google 的 DeepMind 團隊 用他們開發的 AlphaGo 系統 能夠做到什麼。 這個系統能在古老的圍棋賽中 打敗世界最強的棋手。 至少對我而言, 圍棋比賽有兩點特別突出。 第一,當你在下圍棋時, 棋盤上有可能發生的 棋子配置組合數, 基本上是無限多。 可能的組合數, 比宇宙中的原子數還要多。 那意味著, 你永遠不能建造一台 贏得圍棋比賽的電腦, 採用以前建造下西洋棋的 電腦那類的方式, 基本上是以蠻力狂加運算的效能。 很顯然,需要有 更精密的類思考方式。 第二個特點是, 如果你和圍棋冠軍賽的棋手交談, 這個人不見得能明確表達出 他們在比賽時腦中想的是什麼。 通常他們就是非常直覺地在下棋, 就像是他們能夠感覺到 下一步棋要怎麼下。
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.
在這兩種特色的前提下, 我會說能用世界冠軍的水平來下圍棋 應該是自動化做不到的事, 但事實卻不是如此, 這應該要讓我們有所警覺。 原因是,我們都傾向於 畫一條很清楚的線, 線一邊的所有工作和任務 被我們歸類於具有某種程度的 基本例行性、可重覆性、 並且是可被預測的。 我們知道這些工作 可能分屬不同的產業, 可能是不同的職業, 對技巧的需求也不同; 但由於它們先天的可預測性, 我們知道,可能在某個時間點, 它們會受機器學習影響, 而被自動化取代掉。 別誤會,很多工作都是如此。 可能在經濟體中有大約一半的工作 都屬這一類。
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.
但在線的另一邊, 是需要某些能力的所有工作, 我們認為是人類獨有的能力, 我們認為這些工作是安全的。 根據我對圍棋的所知, 我會猜測它應該屬於 線的這一邊,安全的這一邊。 但事實是它不在這一邊, Google 破解了這個問題, 意味著那條線是非常動態的。 它會移動, 它移動和取代掉 越來越多的工作和任務, 那些我們目前認為是安全、 不會被自動化的。
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.
還要了解另一件重要的事, 這現象絕對不會只發生在 低薪或藍領工作上、 或由相對比較低教育程度的人 所做的工作上。 有很多證據顯示, 這些科技所需要的技術 正在快速攀升。 我們已經看到影響力 開始觸及專業工作── 由類似像會計、 財務分析師、 記者、 律師、放射學家這類人 所做的工作任務。 我們對於這類職業、 任務、工作,所做的許多假設, 在未來將會被自動化給威脅, 往前也將會受到挑戰。
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.
當我們整合這些趨勢, 就會顯示 我們未來可能面臨嚴重的失業。 或至少, 我們可能會面臨許多大材小用 或者是薪水停滯不前, 甚至可能薪水下降。 當然,不平等的情況也會加劇。 當然,這一切將會對於社會的結構 造成很大的壓力。 但在那之外,還有個 根本的經濟問題, 問題出現的原因 是目前主要靠著「工作」這機制 來分配收入、和它帶來的購買力, 給那些向我們購買 產品與服務的消費者。
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.
為了要有活躍的市場經濟, 你得要有很多有能力購買 那些被製造出來之產品和服務 的消費者。 如果沒有,你要冒的風險就是 經濟停滯、 或甚至下降的經濟螺旋, 因為就是沒有足夠的客人 來購買製出的產品和服務。
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.
非常重要的是要了解到, 我們每個人都仰賴市場經濟, 才有可能成功。 視覺化的方式是,你可以 想像一個非常特殊的人。 想像一下,比如你可以選賈伯斯, 你把他丟在一個無人島上。 在島上,他會到處跑來跑去, 收集椰子,就和所有其他人一樣。 他不會有什麼特別的地方, 而原因當然是因為,那裡沒有市場 來讓他發揮他出色的才華。 所以對於個人來說,能進入 這個市場是很重要的, 此外,進入這個體制, 在永續面也是很重要的。
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.
於是,問題變成了: 對此,我們到底能做什麼? 我想,可以透過一個 非常理想化的框架來看此事。 你可以想像在未來, 我們工作量減少, 有比較多休閒時間, 比較多家庭時間, 比較多時間去做我們 真正認為有價值的事, 諸如此類。 我認為那是很棒的遠景。 我們絕對應該朝那方向努力。 但同時,我認為我們得要實際一點, 我們得要了解, 我們非常有可能會要面臨 一個嚴重的收入分配問題。 很多人可能會被扔在後頭。 我認為,要解決那個問題, 我們最終得要找到一個方式, 將收入和傳統工作給分離開。 如果要這樣做,我所知道 最好、最直接的方法 就是某種保障收入 或是全體基本收入。
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.
基本收入正變成一個很重要的想法。 它得到許多的注意力和關注, 有許多重要的前導計畫 及實驗在全世界進行。 我自己的看法是, 基本收入並非萬靈丹; 它未必是插電就可以解決的方案, 但總是個起始點, 我們可以從這想法開始,再改善它。 比如,我寫了很多的一個題材, 是明確地將獎勵 納入基本收入當中的可行性。 讓我解釋一下, 想像你是個讀得很辛苦的高中生。 想像你有可能會被退學。 但假設你知道在未來某個時間點, 不論如何, 你和別人得到的基本收入是一樣的。 我認為那會在你腦中 產生橫下心來的動機, 使你直接放棄並退學。
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?
我會說,咱們 不要設計成那樣的結構。 而是支付高中畢業生較高的薪水, 比中綴生要高。 我們可以把這個將獎勵 納入基本收入中的想法, 也許再延伸至其他的領域。 比如,我們可以針對 在社區中助人的行為, 創造一種獎勵; 或是去獎勵人們 為環境做出正面的貢獻, 諸如此類。 把獎勵納入到基本收入當中, 我們可能可以改善它, 另外,也許也可以更接近 解決另一個我認為 在未來也很可能要面臨的問題, 就是:我們要如何 找到意義和實現人生、 以及我們要如何把時間 花在一個也許比較不需求 傳統工作的世界裡?
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.
透過延伸和改善基本收入, 我想我們可以讓它看起來更好, 我們也能讓它在政治面 和社會面更容易被接受, 也更可行── 當然,透過那樣做, 我們就會增加實現它的可能性。
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.
我想,對於基本收入這個想法, 或是擴展安全網, 我們所有人最主要、 也最直覺的反對意見, 就是害怕最後會有太多人 爬上這經濟車箱, 而沒有足夠人去拉這車廂。 但,其實,我在這裡要說的重點是, 在未來, 機器將會有能力為我們拉車。 那就會讓我們有更多選項, 可用以不同的方式 架構我們的社會和經濟, 我認為,最終它將不只是個選項, 而將變成勢在必行。 當然,因為這一切 將會帶給社會一定程度的壓力, 也因為要靠「工作」這個機制, 將購買力分配給消費者, 他們接著才能夠帶動經濟。 事實上,如果未來那機制開始腐蝕了, 我們就得要用其他東西來取代它, 不然我們就要面臨 整個體制不夠永續的風險。
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.
但這裡的關鍵是,我真的認為 解決這些問題, 特別是找出方法來建立一種對社會 每個層級的每個人都 行得通的未來經濟, 將會是未來幾年和幾十年間, 我們所有人要面臨 的最重大挑戰之一。
Thank you very much.
非常謝謝。
(Applause)
(掌聲)