The 1982 Crash Was the Best Thing That Happened to Ray Dalio

Lex Fridman opens with a line of Dalio's: an accurate understanding of reality is the essential foundation of any good outcome. Then he asks an awkward philosophical question. If you are trying to do something different from everyone else, something that may never have been done, how do you discover what is true? Dalio objects to the premise. The way the question is framed implies that truth and newness are almost at odds. He does not think that is true. Truth, for him, is how reality works.

If you are doing something new, the path is experiment: lay out the premises you are relying on and stress-test them. Almost the only way you understand what is true is through experimentation. Go out and try, and you will learn a lot more about truth. Conventional views of what is true are very often wrong. They fad in one direction for a few years and then the other. Definitions of truth that are merely conventional are not the thing to go by.

How do you know a thing that has not been done before might succeed? Do the homework that gives you a foundation, then go into the world of not knowing—not stupidly, not naively—and learn what is possible. Dalio describes a five-step process: go after your goals; identify the problems that stand in the way; diagnose those problems down to root causes; design a way around the root causes; follow through and do what you designed. Most people get stuck trying to decide whether they will succeed *before* they do it. They do not know how to run the process, so they retreat into probability. A practical person who is also used to making dreams happen does not think that way. You don't know. You run the loop.

Dalio has given personality tests to people he calls shapers: someone who can take an audacious visualization and actually build it so the world is different. The list includes Elon Musk and Bill Gates. They know the five-step process in their bones, not from a book. They go after an audacious goal without treating it as a ridiculous dream, and they learn very rapidly along the way. The pull, he says, is a call to adventure. He cannot tell you how much is genetics and how much is environment, but it shows up early. Being creative is exciting. You get in the habit: how do I know, how do I learn, how do I imagine, how do I experiment? The more you do it, the better you get.

Shapers exist in every domain. He names Marc Benioff at Salesforce, Chris Anderson at TED, Muhammad Yunus in social enterprise and microfinance, Geoffrey Canada at the Harlem Children's Zone. What they share, besides the call to adventure, is range. They can go from the biggest picture down to the detail. After selling PayPal, Musk asked why nobody was going to Mars and what humanity would do if the planet went to hell. He did not know much about rockets. He read, learned, and put half his money into the problem. In the same stretch of life he handed Dalio the keys to an early Tesla and pointed at a button: push this, it does that. Dalio calls the move helicoptering—up to the fate of the species, down to a switch on the dash.

They also hold people to the mission. Yunus lives almost like a saint, a modest life, putting his money into helping others, and still scores low on a workplace inventory category called "concern for others," because the questions in that bucket are really about whether you will have conflict to get the mission done. Canada cares about Harlem children's whole lives, not just their grades, and scores the same way. Dalio did not know Steve Jobs, but he agrees with the A-player remark: put in B players and pretty soon you have C players. Shapers will not let anyone stand in the way of the mission. That is not the opposite of caring. Caring, as he uses it, means seeing whether someone is performing at the extremely high level the dream requires, and helping them understand themselves and their circumstances so they have a fabulous personal-development experience at the same time.

The quality he thinks is most underestimated is knowing how to deal with your not-knowing. Really successful people, unlike the cartoon, are not successful mainly because of what they know. They learn from others. They tap people who see things differently. They are orchestrators. Nobody has enough knowledge in their own head.

Fridman asks whether supreme confidence in a vision sits in tension with being open to people who see the world differently. Dalio says we grow up thinking there is a tension, and that education is wrong. "Confident and accurate are almost negatively correlated." Many people are extremely confident and often inaccurate. The tragedy is not realizing how the two are supposed to go together. The move is: I know a lot, and how do I know I'm still not wrong, and how do I take the best thinking available and raise my probability of being right?

The people he admires think for themselves and also take in ideas like vacuum cleaners. They stress-test their thinking with others, assess what comes back, know what they are not good at, and get the people who are. That, he says, is why Bridgewater worked: idea-meritocratic decision-making, a process for getting the best ideas available and working with a team to achieve them. An idea meritocracy is not a vibe. It is a procedure for extracting good thinking from a group that is willing to disagree.

Fridman wonders whether, especially at the start of a hero's journey, you need a little self-delusion to get through the abyss. Dalio will not grant the word. What Fridman is calling delusion is a bad name for uncertainty. You form the dream first. You cannot judge whether you will achieve it, because you have not yet learned the things you will learn on the way. That is not delusion. Delusion will not help you; you have to find out the truth. People overemphasize knowing in advance whether they will succeed. Get rid of that. Keep the dream, stay curious, be a learner and an experimenter, and the agreements you make with reality along the way will teach you how to get there. Do not confuse delusion with not knowing.

The abyss sorts people, Dalio says. You crash. Some get off the field. Some learn and go through a metamorphosis that changes how they learn. The gift the crash should give you is uncertainty: you can stay audacious and scared of being wrong at the same time. Keep the big goal, worry that you will be wrong, and you gain the radical open-mindedness that lets you take in what you need for the next level. Fridman asks him to walk through his own darkest moment—the call on an economic depression.

In 1981–82, building a still-small firm, Dalio calculated that American banks had lent Latin American countries far more than those countries could pay back. A debt crisis would follow, and it would send the U.S. economy tumbling. It was an extremely controversial view. Then it started to happen. Mexico defaulted in August 1982. He thought collapse would follow, because a series of other countries would go too. It played out as he had imagined—and he could not have been more wrong. That was the exact bottom in the stock market. Central banks eased. He was very publicly wrong. He lost his own money and his clients' money.

He had to let close people go until he was the last person left. He was so broke he borrowed $4,000 from his father to pay family bills. It was very painful. It was also, he says, maybe the best thing that ever happened to him, because it changed his approach to decision-making. He kept asking: how do I know whether I'm right? How do I know I'm not wrong? He did not give up audaciousness, because the alternative—putting a tie back on and going down to Wall Street—was something he could not bring himself to do. At that juncture he learned techniques: find the smartest people who disagreed with him and have quality disagreement, the art of thoughtful disagreement; learn to diversify; and, person by person, hire independent thinkers willing to disagree with each other and with him. That is what led to the idea meritocracy. He is 70, and the reason he is on the podcast is that he thinks this is a magical path to success and to quality relationships, not just performance.

Idea meritocracies are rare in companies, and rarer in public discourse. Fridman asks what actually happens in Dalio's head when he meets an idea that conflicts with his own. Debate? Empathetic world-building? Dalio first pulls out a line he wants sitting next to the question: what is common produces only common results. Do not judge whether something is good by whether it is common. If you want unique results, you need a unique approach.

Thoughtful disagreement is the capacity to hold two things in your mind at the same time: I think this makes sense, and I'm not sure it makes sense—then ask why it would make sense, and triangulate with others. He always starts with relative expertise. If the other person knows more, he is much more inclined to ask questions. If you want to learn, you are asking questions, not arguing. You take it in and assess: does this make sense, am I learning, am I getting epiphanies? If two reasonably expert people still see truth differently, he will call in another really smart, capable person and explore together what is true.

The whole motion requires open-mindedness and assertiveness at once. Be curious enough to take the other view in, and assertive enough to say that doesn't make sense, why would this be the case, and go back and forth. That is the procedure he wants running in a Twitter argument, a policy fight, or a portfolio meeting.

Fridman calls Dalio's 30-minute video *How the Economic Machine Works* one of the best educational videos he has seen on the internet. The pieces are not each revolutionary; the clarity after they are taken apart is. Three forces drive the economy: productivity growth, the short-term debt cycle, and the long-term debt cycle. Productivity is people creating valuable things. The debt cycles are people borrowing from their future selves in the hope of creating those things faster. Then the number that makes Fridman sit up: most of what people think of as money is actually credit. Total U.S. credit is about $50 trillion. Total money is about $3 trillion.

Is credit good or bad? Dalio's answer is crisp. Credit is great, even though people often overdo it. Someone has earned money and lends it to someone with better ideas; they cut a deal; the second person is supposed to pay it back. If it works, resources flow to people who can use them—entrepreneurs who need capital they do not have. It is not managed well. His book *Principles for Navigating Big Debt Crises*, which he put online as a free PDF, is about the fact that almost everything happens over and over again for the same reasons. Debt crises repeat. The book is a manual for spotting when credit is overdone, how the adjustment works, and which levers you can pull. Without credit, everyone would be stuck. With it, you can also get hurt.

Credit hides a subtler bet. You hold an IOU that says you will get a certain number of dollars, yen, or euros. Will you get that money, and what will it be worth? A government is on the hook too, and the government has a printing press. Holders of claims are betting both on repayment and on purchasing power. If someone gets over-indebted, they have to sell an asset; that is when assets get cheaper, and the cycle becomes something you can benefit from rather than only suffer—if you understand it.

From an alien's point of view, civilization invented a thing that works because everyone agrees it has value. What is money, and what is its future? Dalio gives the functional definition. Money is a medium of exchange and a store of wealth, and it can pay off a debt. He once visited a Pacific island whose historical money was giant carved stones. People ferried a stone from one island to another; the boat sank; the rock sat on the sea floor and was still treated as valuable, still used in accounts, because somebody owned it. He has seen beads and shells used the same way. The essence is perception. Everyone recognizes it, so it works.

Historically there have been two types of money: a claim on something of value, such as a gold link, or money with no connection behind it. The present system is the second kind—fiat. It lasts as long as it keeps its value. When central banks owe a lot and hold the printing press, they can print, and the currency can be devalued. Forget about today, Dalio says: history shows that every currency has either ended or been devalued over long stretches of time. People will always need a medium of exchange and a store of wealth, so the answer to "what is money" keeps changing.

Bitcoin, in his 2019 view, is not an effective medium of exchange—you cannot easily buy things with it—and not an effective store of wealth, because its volatility is speculative. A stable-value digital currency of the sort Facebook was then exploring, linked to a basket, could in principle be both. Whether some digital currencies succeed will turn on that dual job, and on a harder constraint: governments have to allow it, and a money they do not control is to some extent a threat to their power. He believes a better form of money that central banks do not control is possible. It has not happened. Building confidence that you can hold it without problems is a long evolutionary process. Central banks worried about dollar printing will not flee into digital currency; they will go to gold, which has a thousands-of-years track record, mobility, and the ability to be put in the ground, or to some other currency. A world without a central bank is a very remote possibility, far in the future.

Does the machine amaze him—hundreds of millions of people, billions globally, individual transactions adding up? He goes back and forth between being inside it and stopping. How is a credit card even possible? A stranger does not know him, hands over goods, it clears, it settles. What he marvels at is the mind's capacity to create abstractions that are true: imagine a layer, verify it, stack the next, until the miracles become common. Flying, getting a signal in Africa or Antarctica, seeing a grandchild's face on an iPad in another place: he still says wow.

Is the structure stable, or have we been lucky? Inside his expertise—economics and markets—he can get down to the nitty-gritty, the way you judge whether a plane will fall out of the sky from its fundamentals. That structure, by and large, he believes is right. It can still be hurt by things outside that structure: connectivity, digital journal entries that could take the money away, a system that makes the units worthless. Those do not keep him up the way a misunderstood mechanic would. The complexities still take his breath away. Knowing the mechanics is what does not worry him.

One of the great lessons of his life is about surprise. Many times he saw things he was very surprised about, and almost all of them surprised him because they were the first time it had happened *to him*. When he researched them, they had happened in other places or in other people's lifetimes. In 1971 the dollar's link to gold went out the window and he experienced a devaluation he had not known was a thing. The first oil shock, the second oil shock: the same pattern. They had happened before. They just had not happened in his lifetime. That is why he started studying history, other countries, and other people's life cycles—to get timeless and universal principles. The implausible is often a one-in-a-hundred-year storm. It happens. Just not to you, until it does.

Bridgewater then managed about $160 billion. Fridman asks what role AI will play in a data-rich, high-impact domain. For 25 years, Dalio says, they have put their thinking into algorithms. The computer takes those criteria, takes data, and operates as an independent decision-maker in parallel with the humans. He describes it as two chess games: the machine made that move, he made this move, how do they compare? Then the rule he wants on the desk of anyone building an AI decision system: if the future can be different from the past and you do not have deep understanding, you should not rely on AI. You need deep understanding of the cause-and-effect relationships that lead you to place the bet.

There are two ways to get algorithms. You can take your thinking and express it. Or you can put the data in and ask what the algorithm is—machine learning—which often returns equations that are not understandable. Try to get it to describe what it is telling you; it is very difficult. "They can escape understanding." Repeating cases with a large sample are different. Film every surgeon, convert the footage into algorithms, put them on robots, and he would be comfortable, even without understanding the algorithm, because appendicitis will be handled the same way next time. If the future is different and you lack deep understanding, you will get in trouble. Division of labor follows: the mind should invent and create; the computer should process, because it is faster, more accurate, and less emotional. Processing-type thinking belongs to the machine. "Does this make sense?" belongs to the brain.

Who should I marry, how should I raise my children? Machine learning on dumped data will not find those answers. If you extract your own criteria and put them in an algorithm, you will be better off. Fridman hears a reversal: first computers cannot raise a child, then they can. Dalio says it is two stages of the same thing. The original principle has to come from a person. You will be shocked how much you can express once you force yourself to write it down. His practical advice is specific: in the moment of a decision, or just after, write your criteria in words—what age, which school, why. He built a Principles app, then on iPhone with Android a few months out, to help people do that. Written principles can be reused, shown to others for stress-testing, and then, piece by piece, turned into equations and variables in a computer. Collective decision-making is the payoff. People now decide from whatever is stuck in their heads, with ignorant criteria. Medicine will look like this: not the rushed local doctor, but input going into a system that tells you what to do. The next big move, he thinks, is from systems of record—organized information, GPS-style guidance—to intelligence: data reduced to principles, principles to algorithms, algorithms to judgment, including personalized intelligence about your strengths and who you work well with. He is 70. He wants to pass the tools along.

If lives get reduced to principles and then automated, what happens to emotion and irrationality? Dalio does not dodge it. There are two yous: a subliminal you that wants things it cannot quite say, and a conscious, logical you. They are often at odds. Emotion itself is not the problem. He wants inspiration, love, the ability to have a good impact. The work is reconciling subliminal wants with intellectual wants so they are aligned. Irrationality is bad when it does not get you what you want; you still have to decide which you you are satisfying. His method is a double-check: let the subliminal want surface, run it past the logical me, and proceed when they match. Meditation, which he has practiced for a long time, is fantastic for that alignment. He also takes it outside his head: does this make sense? Triangulation with other people is the same move he uses on markets.

Fridman adds that rationality's goals are defined by those non-rational things. Dalio agrees, and pushes it to the edge of a principle set. You are always at the edge, always doing new things. That is where intellect is needed. Why you go to the edge at all is inspiration, curiosity, hunger. Asked to play Freud on what drives shapers, he refuses a single answer. Different people are driven by different things. In the shapers he deals with he has not seen much in the way of demons or fear. He sees the dream—if I can do that, that would be the most—and the pleasure of the creative act, plus tenacity, empathy, the emotional thrill of impact, and a spirituality he defines as connectedness to the whole.

Do these people walk the line between madness and genius? Dalio does not shut the idea down. There is a continuum. Genius is often at the edge; some kinds of imaginative genius sit at the edge of insanity, like a radio: tune it just right and it plays, go a little too far and it goes off. He mentions Kay Jamison's work on bipolar disorder as evidence that this is sometimes the case. Going out into imagination can be near the edge. It does not always have to be.

Is worry about automation overblown? It is not overblown, Dalio says. It is a giant thing, it will come at us in a very big way, and we are at the edge of accelerating it. It has already had a big impact. It is a two-edged sword. Humans have climbed from raw labor to tractors to the mind. Anything related to mental processing, the computer can probably do better. Other than inventing, we are at a point where machines will probably do it better, and that is accelerating. That force is good for the average. It also displaces people, produces wealth gaps, and is creating a lot of the polarity, disenfranchisement, and failure of equal education we see. He wants it viewed as a national emergency, with a plan, because it is good for the average and not good for everyone.

Before universal basic income—Fridman mentions Andrew Yang's $1,000-per-person campaign—Dalio wants to start with opportunity, education, and development. Equality of opportunity is the most important thing, fleshed out as money into public schools, teaching, early childhood. Earlier is better: from birth until you are an adult on your own. Child care, non-traumatic stability, parental guidance, and education are the most important inputs. Completing high school or not changes outcomes not only for the person but for incarceration and crime costs. Providing those things is fairer and, he argues, economically better for society. Anything less from birth through that process is a tragedy.

Then UBI. What happens to the thousand dollars? Does it come from another program, from early childhood development? Who gets it, and what do they do with it? He likes the idea that everyone should have about a thousand dollars of wiggle room. He does not want it taken from the budgets that do the fundamental work. In the hands of responsible parents making good choices for children, it sounds great. In the hands of an alcoholic or drug-addicted parent who will not use it well, it can produce more harm than good. Same check, opposite flow.

Does money buy happiness? No, he says, and research shows it. Past a basic income that covers health and the pain of deprivation, there is no correlation between happiness and wealth. The highest correlation, across surveys and societies, is quality relationships and a sense of community—true in poor native tribes and in every other kind of community. He is lucky to have started with nothing: a jazz-musician father on Long Island, two parents who loved him, a good public school. That is basically the equal-opportunity package. What money buys is the ability to make choices—enough to take care of family, learn, have relationships and health care, maybe a little security but not too much—and, beyond that, help to make dreams happen, including, at his age, impact on others. Bill Gates can feel almost broke relative to what the Gates Foundation wants to do. People who spend on status symbols are probably in an unhealthy place, though he will not judge someone who truly loves a painting. Money is a medium of exchange and a store of wealth. The question is what you are going to buy. It can also get in the way of deep relationships. That is the two-sidedness of a neutral tool.

Fridman quotes Alan Watts: the secret of life is to be completely engaged with what you are doing in the here and now, and instead of calling it work, realize it is play. Dalio's principle is to make your work and your passion the same thing. He does not want to be theoretical. People have to take care of families; money is an important component of work up to a point. Beyond that, the most important things are meaningful work and meaningful relationships: a mission you are excited about, done with people you are close to. That is fabulous for most people. Why, then, does "work-life balance" even exist? Because of the arc of a life, which runs from zero to somewhere around 80 and comes in three phases. First you learn and depend on others. Second you work, others depend on you, and you try to be successful. Third you want people to be successful without you.

The lowest happiness is ages 45 to 55, when the second phase demands that you succeed at work, at parenting, at everything that takes time. The stress is real and it produces bad results. The highest happiness, interestingly, is between 70 and 80. Kids are making their own first-to-second-phase transition and you want them to succeed without you; your parents are gone; freedom comes back, now with friendships and perspective. Surveys that ask how good you look and feel score that decade highest, even though people are not looking or feeling their best—35 is better for that. The attitude is what ranks. The practical move on balance, he argues, is learning how to get more out of an hour. People think they must choose A or B, and they do, but they do not realize that skill at extracting more from an hour is the equivalent of having many more hours. That is a section of *Principles*.

The pattern is widely shared. Childhood is happy; 16 brings a driver's license and a taste of freedom, though junior year can be stressful; college is high on freedom and friendship; the early twenties are a peak of dating and then finding someone and starting a family. Responsibilities mount. In the middle you will probably crash, have a series of failures, go into the abyss, learn, metamorphose, and come out taking more responsibility. Then the third phase: you want others successful without you. He is 70, in that third phase, having walked the earlier ones, including the wall. Asked what it all means when he meditates on mortality, he does not reach for a new metaphysics. Evolution is the greatest force in the universe; we are tiny bits of that process, with a deeply embedded inclination to evolve and contribute to evolution. Meaning is to personally evolve and to contribute to evolution. Fridman says he could have predicted the answer. The episode closes with Dalio's line: pain plus reflection equals progress.