Whether you like it or not, radical transparency and algorithmic decision-making is coming at you fast, and it's going to change your life. That's because it's now easy to take algorithms and embed them into computers and gather all that data that you're leaving on yourself all over the place, and know what you're like, and then direct the computers to interact with you in ways that are better than most people can.
不論你喜不喜歡 徹底的透明化 與演算決策法都來勢洶洶 它們也將改變你的生活 但這是因為把演算法 放進電腦中很容易 然後收集你身上各式各樣的資料 來了解你是個什麼樣的人 然後讓電腦以比任何人 都好的方式跟你互動
Well, that might sound scary. I've been doing this for a long time and I have found it to be wonderful. My objective has been to have meaningful work and meaningful relationships with the people I work with, and I've learned that I couldn't have that unless I had that radical transparency and that algorithmic decision-making. I want to show you why that is, I want to show you how it works. And I warn you that some of the things that I'm going to show you probably are a little bit shocking.
嗯,這或許聽起來有點嚇人 我已經做這件事很久了 而且我發現這是件很棒的事 我的任務是做有意義的事情 以及和我的同事們建立良好的關係 而我發現如果少了 透明化與演算決策法 我將做不到上面提到的兩件事 我想告訴你們這是為什麼 我也想告訴你們這是如何運作的 我要先警告你們我將要告訴你們的事 或許會有些驚人
Since I was a kid, I've had a terrible rote memory. And I didn't like following instructions, I was no good at following instructions. But I loved to figure out how things worked for myself. When I was 12, I hated school but I fell in love with trading the markets. I caddied at the time, earned about five dollars a bag. And I took my caddying money, and I put it in the stock market. And that was just because the stock market was hot at the time. And the first company I bought was a company by the name of Northeast Airlines. Northeast Airlines was the only company I heard of that was selling for less than five dollars a share.
從我小的時候,就很不擅長死記硬背 我也不喜歡照著指示走 也不擅長照指示做事 但我喜歡自己去發現 事物是如何運作的 我 12 歲的時候 我討厭上學但我熱愛市場交易 我那時候是個桿弟 提一個袋子賺五塊美金 然後我把當桿弟賺的錢拿去買股票 就只是因為那時候流行買股票 我投資的第一家公司 是一家名叫東北航空的公司 東北航空是那時候我所知道 唯一一家股票 每股低於五塊美金的公司
(Laughter)
(笑聲)
And I figured I could buy more shares, and if it went up, I'd make more money. So, it was a dumb strategy, right? But I tripled my money, and I tripled my money because I got lucky. The company was about to go bankrupt, but some other company acquired it, and I tripled my money. And I was hooked. And I thought, "This game is easy." With time, I learned this game is anything but easy.
我發現我可以買進更多股票 如果股票漲價,我就可以賺更多錢 所以,這個策略很蠢,對吧? 但我的錢翻了三倍 我的錢翻了三倍,就因為我運氣好 這家公司瀕臨破產 但其它公司把它買了下來 然後我賺了三倍回來 我上癮了 我心想:這個遊戲真容易 過了一段時間之後 我發現這個遊戲其實相當困難
In order to be an effective investor, one has to bet against the consensus and be right. And it's not easy to bet against the consensus and be right. One has to bet against the consensus and be right because the consensus is built into the price. And in order to be an entrepreneur, a successful entrepreneur, one has to bet against the consensus and be right. I had to be an entrepreneur and an investor -- and what goes along with that is making a lot of painful mistakes. So I made a lot of painful mistakes, and with time, my attitude about those mistakes began to change. I began to think of them as puzzles. That if I could solve the puzzles, they would give me gems. And the puzzles were: What would I do differently in the future so I wouldn't make that painful mistake? And the gems were principles that I would then write down so I would remember them that would help me in the future. And because I wrote them down so clearly, I could then -- eventually discovered -- I could then embed them into algorithms. And those algorithms would be embedded in computers, and the computers would make decisions along with me; and so in parallel, we would make these decisions. And I could see how those decisions then compared with my own decisions, and I could see that those decisions were a lot better. And that was because the computer could make decisions much faster, it could process a lot more information and it can process decisions much more -- less emotionally. So it radically improved my decision-making.
為了成為一名有效率的投資人 不能隨波逐流 而且要眼光準確 不隨波逐流且眼光準確並不容易 你必須不隨波逐流且眼光準確 因為社會大眾的看法 會反映在股價上面 為了成為一名企業家 而且是一名成功的企業家 就必須不隨波逐流且眼光準確 為了同時成為企業家以及投資人 在這條路上我犯了許多嚴重的錯誤 我就是這麼過來的 隨著時間過去 我對於這些錯誤的態度開始有了改變 我開始把它們看作是一塊塊的拼圖 如果我能夠把它們拼在一起的話 我就能得到寶石 這些拼圖就是: 未來我要怎麼做 才能避免再犯這些錯誤? 而那些寶石就是我寫下並牢記的原則 這些原則在未來會對我有所幫助 就是因為我清楚地把它們寫下來 我最後才能發現 我可以把這些原則寫進演算法裡面 然後就可以把這些演算法 植入到電腦裡 最後電腦就可以跟我一起做出決定 電腦會和我一起做出決定 之後我會去比較我們一起所做的決定 和我自己做的決定 然後我發現電腦和我 一起做的決定好多了 這是因為電腦做決定的速度快多了 而且它可以處理更多的資訊 它在做決定的時候 也不會被情緒所影響 電腦大大改善了我做決定的過程
Eight years after I started Bridgewater, I had my greatest failure, my greatest mistake. It was late 1970s, I was 34 years old, and I had calculated that American banks had lent much more money to emerging countries than those countries were going to be able to pay back and that we would have the greatest debt crisis since the Great Depression. And with it, an economic crisis and a big bear market in stocks. It was a controversial view at the time. People thought it was kind of a crazy point of view. But in August 1982, Mexico defaulted on its debt, and a number of other countries followed. And we had the greatest debt crisis since the Great Depression. And because I had anticipated that, I was asked to testify to Congress and appear on "Wall Street Week," which was the show of the time. Just to give you a flavor of that, I've got a clip here, and you'll see me in there.
在我成立對沖基金橋水聯合 (Bridgewater) 八年之後 我經歷了我最大的失敗 最大的錯誤 當時是 1970 年代晚期 當年我 34 歲 我計算出美國的銀行 借給新興國家太多的錢 多到這些國家還不起 這可能會讓我們遭遇 自從經濟大蕭條以來最大的債務危機 伴隨而來的就會是經濟危機 還有嚴重的熊市 這個觀點在當時很具爭議性 大家覺得這是個有點瘋狂的想法 但在 1982 年 8 月 墨西哥宣布了債務違約 然後一些其它的國家也跟進 我們就這樣遇到了 經濟大蕭條以來最大的債務危機 因為我早就已經預料到這件事 我被邀請到國會作見證 以及上當時熱門電視「本周華爾街」 (Wall Street Week) 當來賓 為了讓你們親身體驗 我準備了一段影片 我就出現在這影片當中
(Video) Mr. Chairman, Mr. Mitchell, it's a great pleasure and a great honor to be able to appear before you in examination with what is going wrong with our economy. The economy is now flat -- teetering on the brink of failure.
(影片)主席、米歇爾先生 很高興也很榮幸能夠來到這裡 檢視我們的經濟出了什麼問題 經濟沒有成長 在崩潰的邊緣搖搖欲墜
Martin Zweig: You were recently quoted in an article. You said, "I can say this with absolute certainty because I know how markets work."
馬汀.茲維格:「最近一篇文章提到 你說『我非常肯定我所說過的話, 因為我瞭解市場是如何運作的』。」
Ray Dalio: I can say with absolute certainty that if you look at the liquidity base in the corporations and the world as a whole, that there's such reduced level of liquidity that you can't return to an era of stagflation."
雷.達里歐: 「我非常確定我的論點是對的, 如果把企業的流動資金 和全世界看做一體的話, 目前資金流動性大幅降低, 不可能回到停滯性通膨時代。」
I look at that now, I think, "What an arrogant jerk!"
看了這段影片,我只覺得 「這傢伙真是個傲慢的混蛋!」
(Laughter)
(笑聲)
I was so arrogant, and I was so wrong. I mean, while the debt crisis happened, the stock market and the economy went up rather than going down, and I lost so much money for myself and for my clients that I had to shut down my operation pretty much, I had to let almost everybody go. And these were like extended family, I was heartbroken. And I had lost so much money that I had to borrow 4,000 dollars from my dad to help to pay my family bills.
我當時非常傲慢,而且錯得離譜 我是說,當債務危機發生的時候 股市還有經濟是成長的,而不是下跌 而我和我的客戶損失了一大筆錢 我的公司幾乎面臨倒閉 我得讓幾乎所有的員工走人 這些人對我來說就像家人一樣 我痛徹心扉 我的損失大到 我得向我父親借 4,000 美金 來付家裡的帳單
It was one of the most painful experiences of my life ... but it turned out to be one of the greatest experiences of my life because it changed my attitude about decision-making. Rather than thinking, "I'm right," I started to ask myself, "How do I know I'm right?" I gained a humility that I needed in order to balance my audacity. I wanted to find the smartest people who would disagree with me to try to understand their perspective or to have them stress test my perspective. I wanted to make an idea meritocracy. In other words, not an autocracy in which I would lead and others would follow and not a democracy in which everybody's points of view were equally valued, but I wanted to have an idea meritocracy in which the best ideas would win out. And in order to do that, I realized that we would need radical truthfulness and radical transparency.
那是我這輩子最痛苦的經驗之一 但後來變成是 我這輩子最好的經驗之一 因為那次的經驗改變了 我對決策的態度 我開始問我自己 「我怎麼確定我是對的?」 而不是認為「我是對的」 我學會了謙遜 來平衡我的放肆 我想要找最聰明的人來反駁我 讓我了解他們的觀點 或讓他們來對我觀點做壓力測試 我希望優秀想法勝出的功績主義 也就是說,不是我說什麼 你做什麼這種獨裁主義 也不是人人的意見都平等的民主 我想要的是那種 最好的想法會勝出的功績主義 為了做到這一點 我了解到我們需要擁有徹底的誠實 還有徹底的透明化
What I mean by radical truthfulness and radical transparency is people needed to say what they really believed and to see everything. And we literally tape almost all conversations and let everybody see everything, because if we didn't do that, we couldn't really have an idea meritocracy. In order to have an idea meritocracy, we have let people speak and say what they want. Just to give you an example, this is an email from Jim Haskel -- somebody who works for me -- and this was available to everybody in the company. "Ray, you deserve a 'D-' for your performance today in the meeting ... you did not prepare at all well because there is no way you could have been that disorganized." Isn't that great?
我所說的徹底的誠實 還有徹底的透明化 是讓人們能夠說出他們 真正相信的,並看到一切 我們確實地把幾乎 每個對話都錄了下來 然後讓所有的人看見 因為如果我們不這麼做 我們就沒辦法確實做到優秀想法勝出 為了達到優秀想法勝出的功績主義 我們讓人們說出他們想要什麼 下面是個例子 這是吉米寄的一封電子郵件 他是我的員工 每個在公司的人都看得到這封郵件 「雷,你今天在會議裡的 表現只有 60 分, 你根本沒有準備好, 因為你不是一個這麼 沒有組織的人。」 這不是很棒嗎?
(Laughter)
(笑聲)
That's great. It's great because, first of all, I needed feedback like that. I need feedback like that. And it's great because if I don't let Jim, and people like Jim, to express their points of view, our relationship wouldn't be the same. And if I didn't make that public for everybody to see, we wouldn't have an idea meritocracy.
這真的很棒 第一,我需要像這樣的回饋 我需要像這樣的回饋 很棒的點在於如果我不讓吉米 還有其他像吉米的人 表達他們的觀點 我們的關係就不會像現在這樣 如果我不讓所有人都看得見這封信 我們就無法實踐 優秀想法勝出的功績主義
So for that last 25 years that's how we've been operating. We've been operating with this radical transparency and then collecting these principles, largely from making mistakes, and then embedding those principles into algorithms. And then those algorithms provide -- we're following the algorithms in parallel with our thinking. That has been how we've run the investment business, and it's how we also deal with the people management.
所以過去 25 年來 我們就是這麼經營公司的 我們用徹底的透明化來經營公司 然後收集這些原則 這些原則大部分是來自犯錯 然後把這些原則放進演算法裡面 然後演算法會做出選擇 我們就根據演算法 還有自己的想法來做出選擇 這就是我們怎麼讓 這間投資公司運作的 也是我們怎麼管理員工的
In order to give you a glimmer into what this looks like, I'd like to take you into a meeting and introduce you to a tool of ours called the "Dot Collector" that helps us do this. A week after the US election, our research team held a meeting to discuss what a Trump presidency would mean for the US economy. Naturally, people had different opinions on the matter and how we were approaching the discussion. The "Dot Collector" collects these views. It has a list of a few dozen attributes, so whenever somebody thinks something about another person's thinking, it's easy for them to convey their assessment; they simply note the attribute and provide a rating from one to 10. For example, as the meeting began, a researcher named Jen rated me a three -- in other words, badly --
為了讓你們對我在說的東西有點概念 我想帶你們一起參加一場會議 並向你們介紹我們一個 名叫「集點」的工具 這個工具幫助我們做到這些事 美國大選的一星期之後 我們的研究團隊舉行了一場會議 來討論川普的勝選 對美國經濟有何意義 很正常的,人們對這個議題 還有我們怎麼去看這件事情 有著不一樣的想法 「集點」收集了這些想法 這些想法總共可以分成好幾十種 所以當有某個人 對別人的看法有想法的時候 他們就可以很容易地作出評估 他們會記下這個想法 然後給一個 1 到 10 分的分數 舉例來說,在會議開始的時候 一位名叫詹的研究員給了我 3 分 就是很爛的意思
(Laughter)
(笑聲)
for not showing a good balance of open-mindedness and assertiveness. As the meeting transpired, Jen's assessments of people added up like this. Others in the room have different opinions. That's normal. Different people are always going to have different opinions. And who knows who's right? Let's look at just what people thought about how I was doing. Some people thought I did well, others, poorly. With each of these views, we can explore the thinking behind the numbers. Here's what Jen and Larry said. Note that everyone gets to express their thinking, including their critical thinking, regardless of their position in the company. Jen, who's 24 years old and right out of college, can tell me, the CEO, that I'm approaching things terribly.
因為我的論點沒有在包容性 與自信之間取得平衡 會議公開之後 詹對於人們的分析總結如下 在會議室裡的其他人各有不同的意見 這很正常 不同的人總是有著不同的意見 誰知道誰是對的呢? 我們來看看大家 對我當時的說法是怎麼想的 有些人認為我說得很好 其他人覺得我說得很差 透過這些觀點 我們可以探索在數字背後的這些想法 詹和賴利是這麼說的 無論他們在公司的位階 每個人都可以表達他們的想法 包括他們的批判性思考 24 歲、剛剛從學校畢業的詹 可以說我這個執行長 觀察事情的能力很差
This tool helps people both express their opinions and then separate themselves from their opinions to see things from a higher level. When Jen and others shift their attentions from inputting their own opinions to looking down on the whole screen, their perspective changes. They see their own opinions as just one of many and naturally start asking themselves, "How do I know my opinion is right?" That shift in perspective is like going from seeing in one dimension to seeing in multiple dimensions. And it shifts the conversation from arguing over our opinions to figuring out objective criteria for determining which opinions are best.
這個工具幫人們表達他們的意見 然後讓他們從更高的 一個客觀角度來看事情 當詹和其他人從提供意見 變成綜觀全局的時候 他們的觀點就改變了 他們了解到他們的想法 只是眾多想法的其中之一 並很自然地開始思考 「我怎麼知道我的想法是對的?」 這就像是從一個維度看事情 變成從多個維度看事情 也把對話從針對這些想法的爭論 變為找出客觀的標準 來決定哪個意見是最好的
Behind the "Dot Collector" is a computer that is watching. It watches what all these people are thinking and it correlates that with how they think. And it communicates advice back to each of them based on that. Then it draws the data from all the meetings to create a pointilist painting of what people are like and how they think. And it does that guided by algorithms. Knowing what people are like helps to match them better with their jobs. For example, a creative thinker who is unreliable might be matched up with someone who's reliable but not creative. Knowing what people are like also allows us to decide what responsibilities to give them and to weigh our decisions based on people's merits. We call it their believability. Here's an example of a vote that we took where the majority of people felt one way ... but when we weighed the views based on people's merits, the answer was completely different. This process allows us to make decisions not based on democracy, not based on autocracy, but based on algorithms that take people's believability into consideration.
在「集點」的背後 有一台在監控的電腦 他監控了所有人的想法 然後去和他們是怎麼想的做連結 然後根據這些結果回傳建議 最後電腦會從所有的會議中收集資料 並產生一個點描清單 顯示他們是怎麼樣的人 以及是怎麼思考的 電腦做的這些事就是從演算法來的 瞭解人們是怎麼樣的人 能夠幫助他們找到更適合他們的職位 舉例來說 一個有創意但是不可靠的人 可以和一個可靠但沒創意的人做搭配 瞭解人們是怎麼樣的人 也讓我們可以決定 要派給他們什麼樣的職責 同時也可以根據大家的表現 來衡量我們的決定 我們把它稱為這些人的可信度 在某次投票裡 多數人投給了一邊 但當我們對人們的功績作加權之後 得到了完全相反的答案 這個過程讓我們的決策過程 不再根據民主 也不是根據獨裁 而是根據演算法 把人們的可信度納入考量
Yup, we really do this.
沒錯,我們真的這麼做
(Laughter)
(笑聲)
We do it because it eliminates what I believe to be one of the greatest tragedies of mankind, and that is people arrogantly, naïvely holding opinions in their minds that are wrong, and acting on them, and not putting them out there to stress test them. And that's a tragedy. And we do it because it elevates ourselves above our own opinions so that we start to see things through everybody's eyes, and we see things collectively. Collective decision-making is so much better than individual decision-making if it's done well. It's been the secret sauce behind our success. It's why we've made more money for our clients than any other hedge fund in existence and made money 23 out of the last 26 years.
我們這麼做是因為它可以消除 我認為人類最大的悲劇 也就是人們把傲慢且天真的 錯誤想法放在心裡 並根據這些想法做事情 而且不肯開誠布公地接受壓力測試 這真的是個悲劇 我們這麼做是因為 可以讓我們超脫於自我 然後從每一個人的眼睛看每件事 來看見事情的全貌 如果好好地去做的話 集體決策比個人決策要好得太多了 這就是我們成功背後的原因 也是我們幫客戶賺得 比其它現有對沖基金更多的原因 而且過去 26 年有 23 年是獲利的
So what's the problem with being radically truthful and radically transparent with each other? People say it's emotionally difficult. Critics say it's a formula for a brutal work environment. Neuroscientists tell me it has to do with how are brains are prewired. There's a part of our brain that would like to know our mistakes and like to look at our weaknesses so we could do better. I'm told that that's the prefrontal cortex. And then there's a part of our brain which views all of this as attacks. I'm told that that's the amygdala. In other words, there are two you's inside you: there's an emotional you and there's an intellectual you, and often they're at odds, and often they work against you. It's been our experience that we can win this battle. We win it as a group. It takes about 18 months typically to find that most people prefer operating this way, with this radical transparency than to be operating in a more opaque environment. There's not politics, there's not the brutality of -- you know, all of that hidden, behind-the-scenes -- there's an idea meritocracy where people can speak up. And that's been great. It's given us more effective work, and it's given us more effective relationships. But it's not for everybody. We found something like 25 or 30 percent of the population it's just not for. And by the way, when I say radical transparency, I'm not saying transparency about everything. I mean, you don't have to tell somebody that their bald spot is growing or their baby's ugly. So, I'm just talking about --
那麼彼此間徹底的誠實 和徹底透明會有什麼問題呢? 有人說是情感上的困難 評論家說這是殘酷的職場 神經科學家告訴我 這和大腦的網絡有關 大腦裡有一個部位會試著去找出 我們犯的錯誤還有弱點 然後讓我們表現更好 有人告訴我這個部位叫前額葉皮質區 大腦還有個部位 會把錯誤和弱點視為攻擊 這個部位叫杏仁核 換句話說,你的身體裡面有兩個你 一個是情緒化的你 一個是理性的你 他們常常是互相衝突的 也常常和你做對 我們的經驗告訴我們 我們能贏得這場競爭 透過團結合作 通常要花 18 個月 才會讓大家習慣並選擇徹底的透明 而不是個看不清的環境 這無關政治,也無關殘酷 在這些的背後 有個優秀想法勝出的功績主義 讓每個人都能發聲 這一直都很棒 它讓我們的工作更有效果 也讓人們之間的關係更有效果 不過這不適用於所有人 我們發現有大約 百分之 25 到 30 的人不適用 附帶一提,我說的徹底透明 不是說什麼都不掩飾 我是說,你不必告訴 某人他越來越禿了 或是他們的小孩很醜 我說的是──
(Laughter)
(笑聲)
talking about the important things. So --
說的是那些比較重要的事 所以──
(Laughter)
(笑聲)
So when you leave this room, I'd like you to observe yourself in conversations with others. Imagine if you knew what they were really thinking, and imagine if you knew what they were really like ... and imagine if they knew what you were really thinking and what were really like. It would certainly clear things up a lot and make your operations together more effective. I think it will improve your relationships. Now imagine that you can have algorithms that will help you gather all of that information and even help you make decisions in an idea-meritocratic way. This sort of radical transparency is coming at you and it is going to affect your life. And in my opinion, it's going to be wonderful. So I hope it is as wonderful for you as it is for me.
當你離開這個會場的時候 我想要你在和別人 對話的時候觀察自己 想像你知道他們真正的想法 想像你知道他們其實是個什麼樣的人 想像他們知道你真正的想法 和真正的你 這一定會讓事情明朗化 並讓你的做法更有效 我覺得這可以讓你的關係變得更美好 現在想像你有演算法 幫你收集所有的資料 甚至幫你在優秀想法勝出的 功績主義之下做出決定 這樣的徹底透明化將會進入你的世界 而且會影響你的生活 我認為 這將會是很美好的一件事 所以我希望這對你們來說 會跟對我來說一樣美好
Thank you very much.
非常謝謝你們
(Applause)
(掌聲)