I'm going to talk about how AI and mankind can coexist, but first, we have to rethink about our human values. So let me first make a confession about my errors in my values.
我將要談的是人類 和人工智慧要如何共存, 但首先,我們先要 重新審視人類的價值觀。 讓我先坦誠我在 我的價值觀中所犯的錯誤。
It was 11 o'clock, December 16, 1991. I was about to become a father for the first time. My wife, Shen-Ling, lay in the hospital bed going through a very difficult 12-hour labor. I sat by her bedside but looked anxiously at my watch, and I knew something that she didn't. I knew that if in one hour, our child didn't come, I was going to leave her there and go back to work and make a presentation about AI to my boss, Apple's CEO. Fortunately, my daughter was born at 11:30 --
那是 1991 年 12 月 16 日 11 點。 我就要成為一個新手爸爸了。 我的太太先玲躺在醫院的病床上, 經歷著一段艱辛 並長達十二個小時的分娩。 我就坐在床邊, 但很焦慮地看著我的手錶, 我知道一件她不知道的事。 我知道,如果一個小時內, 我們的孩子還不出來, 我就得要把她丟在那裡, 回去工作, 去做一場關於人工智慧的簡報, 對象是我的老闆,蘋果的執行長。 幸運的是,我女兒 在 11:30 出生了——
(Laughter)
(笑聲)
(Applause)
(掌聲)
sparing me from doing the unthinkable, and to this day, I am so sorry for letting my work ethic take precedence over love for my family.
讓我不用去做我無法想像的事, 至今,我仍然很後悔 我把工作擺在了我對家人的愛之前。
(Applause)
(掌聲)
My AI talk, however, went off brilliantly.
然而,我的人工智慧演說表現超好。
(Laughter)
(笑聲)
Apple loved my work and decided to announce it at TED1992, 26 years ago on this very stage. I thought I had made one of the biggest, most important discoveries in AI, and so did the "Wall Street Journal" on the following day.
蘋果很愛我的作品, 決定在 TED 1992 宣佈它, 26 年前,就在這個舞台上。 我認為我在人工智慧上 有了最大、最重要的發現, 隔天的《華爾街日報》也這麼認為。
But as far as discoveries went, it turned out, I didn't discover India, or America. Perhaps I discovered a little island off of Portugal. But the AI era of discovery continued, and more scientists poured their souls into it. About 10 years ago, the grand AI discovery was made by three North American scientists, and it's known as deep learning.
但隨著越來越多的「發現」, 結果是, 我沒有發現印度,或美洲。 也許我發現的是 葡萄牙外海的一個小島。 但人工智慧發現的時代 仍然繼續走下去了, 更多的科學家 全心全意地投入其中。 大約十年前,三位北美科學家 有了偉大的人工智慧發現, 即大家所知的深度學習。
Deep learning is a technology that can take a huge amount of data within one single domain and learn to predict or decide at superhuman accuracy. For example, if we show the deep learning network a massive number of food photos, it can recognize food such as hot dog or no hot dog.
深度學習這項技術, 是一個能利用海量數據 在單一領域中 學會做超高精度的預測或判斷的技術。 比如,如果我們給深度學習網路 提供海量的食物照片, 它就能辨識出食物, 比如熱狗,或不是熱狗。
(Applause)
(掌聲)
Or if we show it many pictures and videos and sensor data from driving on the highway, it can actually drive a car as well as a human being on the highway. And what if we showed this deep learning network all the speeches made by President Trump? Then this artificially intelligent President Trump, actually the network --
或者,如果我讓它看很多 在公路上開車的照片、 影片,以及感測器資料, 它就能夠在高速公路上 嫺熟地駕駛一台車, 絲毫不輸給人類。 如果我們向這個深度學習網路展示 川普總統做過的所有演說呢? 那麼,這位人工智慧的川普總統, 其實就是這個網路——
(Laughter)
(笑聲)
can --
能夠——
(Applause)
(掌聲)
You like double oxymorons, huh?
你們喜歡一語雙關,是吧?
(Laughter)
(笑聲) (註:artificial 也是「虛假造作的」)
(Applause)
(掌聲)
So this network, if given the request to make a speech about AI, he, or it, might say --
所以,如果要求這個網路 做出一段關於人工智慧的演說, 他,或它,可能會說——
(Recording) Donald Trump: It's a great thing to build a better world with artificial intelligence.
(錄音)川普:這是很棒的事, 用人工智慧來建造一個更好的世界。
Kai-Fu Lee: And maybe in another language?
講者:換個語言呢?
DT: (Speaking Chinese)
川普:(說中文) 人工智能正在改變世界。
(Laughter)
(笑聲)
KFL: You didn't know he knew Chinese, did you?
講者:你們不知道川普會說中文吧?
So deep learning has become the core in the era of AI discovery, and that's led by the US. But we're now in the era of implementation, where what really matters is execution, product quality, speed and data. And that's where China comes in. Chinese entrepreneurs, who I fund as a venture capitalist, are incredible workers, amazing work ethic. My example in the delivery room is nothing compared to how hard people work in China. As an example, one startup tried to claim work-life balance: "Come work for us because we are 996." And what does that mean? It means the work hours of 9am to 9pm, six days a week. That's contrasted with other startups that do 997.
所以,深度學習已經成為 人工智慧發現時代的核心, 且是由美國來領導的。 但現在,我們已經進入實踐的時代, 在這個時代,重要的是執行、 產品品質、速度,和資料。 這就是中國出場的時候了。 身為創業投資家, 我投資的中國企業家 是很棒的實幹家, 有很了不起的職業道德。 我在產房的那個例子, 完全不及中國人們賣力工作的程度。 舉個例子,有間新興公司 提出「工作—生活」的平衡: 「來為我們工作,因為我們是 996。」 那是什麼意思? 意思是,工作時間從早上 9 點 到晚上 9 點,一週工作 6 天。 相對的,其他新興公司都是 997。
And the Chinese product quality has consistently gone up in the past decade, and that's because of a fiercely competitive environment. In Silicon Valley, entrepreneurs compete in a very gentlemanly fashion, sort of like in old wars in which each side took turns to fire at each other.
而中國的產品品質 在過去十年間持續不斷地提升, 那是因為這個環境中的 競爭太激烈了。 在矽谷,企業家會 以很紳仕的方式競爭, 有點像是古老的戰爭,雙方會輪流 向對方開火。
(Laughter)
(笑聲)
But in the Chinese environment, it's truly a gladiatorial fight to the death. In such a brutal environment, entrepreneurs learn to grow very rapidly, they learn to make their products better at lightning speed, and they learn to hone their business models until they're impregnable. As a result, great Chinese products like WeChat and Weibo are arguably better than the equivalent American products from Facebook and Twitter.
但在中國的環境中, 就像是羅馬競技場, 不死不休的戰鬥。 在這麼殘酷的環境中, 企業家學會要非常快速地成長, 他們學會要雷厲風行地 讓自己的產品變更好, 他們學會要一直鍛鍊 他們的商業模型, 直到堅不可摧為止。 結果就是,優秀的中國產品, 如微信和微博, 可以說比美國 相對應產品, 如臉書和推特,還要好。
And the Chinese market embraces this change and accelerated change and paradigm shifts. As an example, if any of you go to China, you will see it's almost cashless and credit card-less, because that thing that we all talk about, mobile payment, has become the reality in China. In the last year, 18.8 trillion US dollars were transacted on mobile internet, and that's because of very robust technologies built behind it. It's even bigger than the China GDP. And this technology, you can say, how can it be bigger than the GDP? Because it includes all transactions: wholesale, channels, retail, online, offline, going into a shopping mall or going into a farmers market like this. The technology is used by 700 million people to pay each other, not just merchants, so it's peer to peer, and it's almost transaction-fee-free. And it's instantaneous, and it's used everywhere. And finally, the China market is enormous. This market is large, which helps give entrepreneurs more users, more revenue, more investment, but most importantly, it gives the entrepreneurs a chance to collect a huge amount of data which becomes rocket fuel for the AI engine. So as a result, the Chinese AI companies have leaped ahead so that today, the most valuable companies in computer vision, speech recognition, speech synthesis, machine translation and drones are all Chinese companies.
且中國市場擁抱這樣的改變、 加速的改變,以及範式轉移。 舉個例,如果你去中國, 你會發現幾乎沒有 在用現金或是信用卡, 原因就是我們大家都在談的 那樣東西,移動支付, 在中國已經實現。 去年, 行動網路上的交易金額 達到 18.8 兆美元, 那是因為在行動支付背後的技術 非常穩定健全。 這個數字比中國的國內生產總值還高。 你會問,這項技術怎麼可能 超越國內生產總值? 因為它包含所有的交易: 批發、電視台、零售、線上、線下、 到購物中心去買, 或到像這樣的農民市場去買。 有 7 億人使用移動支付 來付錢給彼此,不只付錢給商人, 所以,它是點對點的, 且幾乎不需要交易手續費。 且是立即生效, 到處都在使用。 最後一點,中國的市場很巨大。 這個市場很大, 讓企業家能有更多的 使用者、更多的收益、 更多的投資,最重要的是, 它讓企業家有機會 能收集到大量的數據資料, 這些資料就成了 人工智慧引擎的火箭燃料。 結果就是,中國的人工智慧公司 已經大躍進,跳到前頭, 所以,現今,最有價值的公司, 不論是在電腦視覺、語音識別、 語音合成、機器翻譯, 及無人機的領域, 都是中國公司稱霸。
So with the US leading the era of discovery and China leading the era of implementation, we are now in an amazing age where the dual engine of the two superpowers are working together to drive the fastest revolution in technology that we have ever seen as humans. And this will bring tremendous wealth, unprecedented wealth: 16 trillion dollars, according to PwC, in terms of added GDP to the worldwide GDP by 2030. It will also bring immense challenges in terms of potential job replacements. Whereas in the Industrial Age it created more jobs because craftsman jobs were being decomposed into jobs in the assembly line, so more jobs were created. But AI completely replaces the individual jobs in the assembly line with robots. And it's not just in factories, but truckers, drivers and even jobs like telesales, customer service and hematologists as well as radiologists over the next 15 years are going to be gradually replaced by artificial intelligence. And only the creative jobs --
美國領導的是發現的時代, 而中國領導的是導入的時代, 我們現在身處一個很了不起的時代, 這兩種超能力的雙重引擎 在同心協力, 在科技領域中, 推動我們人類所見過 最快速的革命。 這會帶來驚人的財富, 前所未有的財富: 根據普華永道會計師事務所的資料, 到 2030 年,全世界的國內生產總值 會增加 16 兆美元。 這也會帶來極大的挑戰: 潛在的工作取代性問題。 在工業時代, 它創造了更多的工作, 因為技工的工作被重新 分解成為生產線的工作, 所以創造了更多的工作。 但人工智慧完全取代了個人的工作, 在生產線上直接用機器人。 且不只是在工廠, 還有貨車司機、一般司機, 甚至像電話銷售、客戶服務、 血液學學者,以及放射線研究者 在未來十五年 都可能漸漸被 人工智慧取代。 只有有創意的工作——
(Laughter)
(笑聲) (表中講者被列在「安全」)
I have to make myself safe, right? Really, the creative jobs are the ones that are protected, because AI can optimize but not create.
我得讓我自己很安全,對吧? 說真的,有創意的工作 是受到保護的工作, 因為人工智慧能夠 做到最佳化,但不能創造。
But what's more serious than the loss of jobs is the loss of meaning, because the work ethic in the Industrial Age has brainwashed us into thinking that work is the reason we exist, that work defined the meaning of our lives. And I was a prime and willing victim to that type of workaholic thinking. I worked incredibly hard. That's why I almost left my wife in the delivery room, that's why I worked 996 alongside my entrepreneurs. And that obsession that I had with work ended abruptly a few years ago when I was diagnosed with fourth stage lymphoma. The PET scan here shows over 20 malignant tumors jumping out like fireballs, melting away my ambition. But more importantly, it helped me reexamine my life. Knowing that I may only have a few months to live caused me to see how foolish it was for me to base my entire self-worth on how hard I worked and the accomplishments from hard work. My priorities were completely out of order. I neglected my family. My father had passed away, and I never had a chance to tell him I loved him. My mother had dementia and no longer recognized me, and my children had grown up.
但比失去工作更嚴重的, 是失去意義, 因為在工業時代的工作倫理 已經將我們洗腦, 認為工作是我們存在的理由, 認為工作定義了我們人生的意義。 我就曾是那種工作狂思想的 主要受害者,也是自願受害者。 我工作非常努力。 那就是為什麼在產房時 我差一點就要丟下我太太, 那就是為什麼我和我的 企業家們的工作時間是 996。 我先前對於工作的這種迷戀, 在幾年前突然終止了, 因為我被診斷出第四期的淋巴癌。 這裡的正子掃描結果顯示 有超過 20 個惡性腫瘤 像火球一樣跳出來, 融化了我的野心。 但,更重要的是, 它讓我重新檢視我的人生。 知道我可能只剩下幾個月能活, 讓我看清了我有多愚蠢, 因為我把我的整個自我價值 建立在工作努力程度上, 以及努力帶來的成就上。 我的優先順序完全錯亂。 我忽視了我的家庭。 我父親已經過世, 我從來沒有機會告訴他我愛他。 我母親有失智症,已經不認得我, 我的孩子已經長大。
During my chemotherapy, I read a book by Bronnie Ware who talked about dying wishes and regrets of the people in the deathbed. She found that facing death, nobody regretted that they didn't work hard enough in this life. They only regretted that they didn't spend enough time with their loved ones and that they didn't spread their love.
在我做化療期間, 我讀了一本布羅妮韋爾寫的書, 談到臨終的人的死前願望和悔恨。 她發現,面對死亡時, 沒有人後悔這一生的 工作不夠努力。 他們只會後悔沒有花 足夠時間陪他們愛的人, 沒有把他們的愛散播出去。
So I am fortunately today in remission.
現在,我很幸運處於緩解期。
(Applause)
(掌聲)
So I can be back at TED again to share with you that I have changed my ways. I now only work 965 -- occasionally 996, but usually 965. I moved closer to my mother, my wife usually travels with me, and when my kids have vacation, if they don't come home, I go to them. So it's a new form of life that helped me recognize how important it is that love is for me, and facing death helped me change my life, but it also helped me see a new way of how AI should impact mankind and work and coexist with mankind, that really, AI is taking away a lot of routine jobs, but routine jobs are not what we're about.
所以我能再次回到 TED, 和各位分享, 我已經改變了我的方式。 我現在的工作方式是 965 —— 偶爾是 996,但通常是 965。 我搬到離我母親比較近的地方, 我太太通常與我一同旅行, 當我的孩子有假期時, 若他們不回家,我會去找他們。 這是一種新的生活形式, 協助我了解到 愛對我而言有多重要, 面對死亡,協助我改變了我的生活, 也協助我找到了一種新的方式, 看待人工智慧對於人類的衝擊, 以及如何和人類合作與共存, 確實,人工智慧會奪走 很多例行性的工作, 但我們並不只會做例行性的工作。
Why we exist is love. When we hold our newborn baby, love at first sight, or when we help someone in need, humans are uniquely able to give and receive love, and that's what differentiates us from AI.
我們存在的目的是愛。 當我們抱著新生的嬰兒, 第一眼就產生了愛, 當我們協助了需要幫忙的人, 人類能給予愛和接收愛, 這是獨一無二的, 這就是我們和人工智慧的差別。
Despite what science fiction may portray, I can responsibly tell you that AI has no love. When AlphaGo defeated the world champion Ke Jie, while Ke Jie was crying and loving the game of go, AlphaGo felt no happiness from winning and certainly no desire to hug a loved one.
不論科幻小說怎麼寫, 我可以很確定地告訴各位, 人工智慧沒有愛。 當 AlphaGo 打敗世界冠軍柯潔, 當柯潔在哭泣,他很愛圍棋比賽, AlphaGo 卻不會感到勝利的喜悅, 肯定也不會想要去擁抱愛人。
So how do we differentiate ourselves as humans in the age of AI? We talked about the axis of creativity, and certainly that is one possibility, and now we introduce a new axis that we can call compassion, love, or empathy. Those are things that AI cannot do. So as AI takes away the routine jobs, I like to think we can, we should and we must create jobs of compassion. You might ask how many of those there are, but I would ask you: Do you not think that we are going to need a lot of social workers to help us make this transition? Do you not think we need a lot of compassionate caregivers to give more medical care to more people? Do you not think we're going to need 10 times more teachers to help our children find their way to survive and thrive in this brave new world? And with all the newfound wealth, should we not also make labors of love into careers and let elderly accompaniment or homeschooling become careers also?
所以,在人工智慧的時代, 我們要如何讓人類有所不同? 我們剛有談到「創意」這個軸, 那肯定是其中一種可能性, 現在,我們要再介紹一個新的軸, 我們可以稱之為 同情心、愛,或是同理心。 那些是人工智慧做不到的。 所以,當人工智慧奪走 例行性的工作時, 我會認為 ,我們能夠、應該而且必須 創造出同情心相關的工作。 你可能會問,這類工作有多少個? 但我會反問你: 你不認為我們會需要很多社工 來協助我們做這項轉變嗎? 你不認為我們會需要 很多有同情心的照護者 來給予更多人醫療照護嗎? 你不認為我們會需要十倍的老師 來協助我們的孩子找到他們的路, 在這個勇敢的新世界中 存活並茁壯嗎? 且當有這麼多新的財富產生時, 我們不應該創造以人性為本的職業, 把陪伴老人, 或是居家教育也變成職業嗎?
(Applause)
(掌聲)
This graph is surely not perfect, but it points at four ways that we can work with AI. AI will come and take away the routine jobs and in due time, we will be thankful. AI will become great tools for the creatives so that scientists, artists, musicians and writers can be even more creative. AI will work with humans as analytical tools that humans can wrap their warmth around for the high-compassion jobs. And we can always differentiate ourselves with the uniquely capable jobs that are both compassionate and creative, using and leveraging our irreplaceable brains and hearts. So there you have it: a blueprint of coexistence for humans and AI.
這張圖的確不完美, 但它能展示出我們 和人工智慧合作的四種方式。 人工智慧會到來, 也會奪走例行性的工作, 到時,我們會很感激。 對有創意的人, 人工智慧會變成很棒的工具, 讓科學家、藝術家、音樂家及作家 都更有創意。 人工智慧也會扮演 分析工具的角色來和人類合作, 對於高同情心的工作, 人類可以將溫暖傾注其中。 我們還有方式讓我們自己不同, 就是通過參與需要獨特能力的工作, 要有同情心又要有創意, 充分利用和發揮 我們無可替代的頭腦和内心, 所以,這就是: 人類和人工智慧共存的藍圖。
AI is serendipity. It is here to liberate us from routine jobs, and it is here to remind us what it is that makes us human. So let us choose to embrace AI and to love one another.
人工智慧的發展是種機緣。 它的出現將我們 從例行性的工作中解放出來, 它也是來提醒我們,人因何為人。 所以,讓我們選擇 擁抱人工智慧,並去關愛彼此吧。
Thank you.
謝謝。
(Applause)
(掌聲)