Tag: Lindy Effect

How to Choose Your Next Book

If you’re wondering what to read, here are two simple ideas that we can combine to help us choose what to read next.

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Are you making the most of your reading time?

While I read a lot of books that doesn’t mean I don’t spend a lot of time thinking about how I read. I constantly ask myself if I’m making the most use of my limited reading time.

It turns out that most of the time the best way to improve your Reading Return on Invested Time (RROIT) is to carefully filter the books you read.

Here is the simple two-step process I use to filter books.

“The more basic knowledge you have … the less new knowledge you have to get.”

— Charlie Munger

1. Understand Deeply

Get back to basics. Understanding the basics, as boring as it sounds, is one of the key elements of effective thinking. A lot of people assume the basics are not important and never really take the time to learn them, preferring the sexiness of complexity. Understanding a simple idea deeply, however, creates more lasting knowledge and builds a solid foundation for complex ideas later.

Build your foundation. The key here is brutal honesty with yourself about what you really know. Take the time to do a Feynman One Pager on an idea you think you know really well. While easy, this process will reveal any gaps you have in your knowledge.

The multidisciplinary mind understands the basic ideas. Acquiring the basic mental models from multiple disciplines allows you to see things that other people can’t. You don’t need to understand the latest study in biology, but you sure as heck better understand the concept of evolution because it applies to so much more than animals.

Understanding the basics allows us to predict what matters. Put simply, people who understand the basics are better at understanding second and subsequent order consequences. Plus, how are we to have a chance of understanding complex ideas without a firm understanding of the basics.

Remember, the slightest wind blows over a house without a foundation.

2. The Lindy Effect

What has been will continue to be. The second idea is the Lindy Effect, which is just a fancy way of saying what’s been around will continue to be around. In his book Antifragile, author Nassim Taleb, who builds on the idea of Benoit Mandelbrot, writes:

For the perishable, every additional day in its life translates into a shorter additional life expectancy. For the nonperishable, every additional day may imply a longer life expectancy. So the longer a technology lives, the longer it can be expected to live.

The nonperishable is anything that does not have organic or avoidable expiration dates.

Time can predict value. While produce and humans have a mathematical life expectancy that decreases with each day, some things, like books, increase in life expectancy with each passing day.

The perishable is typically an object, the nonperishable has an informational nature to it. A single car is perishable, but the automobile as a technology has survived about a century (and we will speculate should survive another one). Humans die, but their genes—a code—do not necessarily. The physical book is perishable—say, a specific copy of the Old Testament—but its contents are not, as they can be expressed into another physical book.

When I see a toddler walking down the street holding the hands of their grandparents, I can reasonably assert that the toddler will survive the elder. When something is nonperishable that is not the case.

Taleb writes:

We have two possibilities: either both are expected to have the same additional life expectancy (the case in which the probability distribution is called exponential), or the old is expected to have a longer expectancy than the young, in proportion to their relative age. In that situation, if the old is eighty and the young is ten, the elder is elected to live eight times as long as the younger one.

Here is a chart Taleb provides in his book:

Life Expectancy

The longer something non-perishable has lived, the longer we can expect it to live.

If a book has been in print for forty years, I can expect it to be in print for another forty years. But, and that is the main difference, if it survives another decade, then it will be expected to be in print another fifty years.

This is where Taylor Pearson helped me put something together that I was just too stupid to do myself. He connects reading to the Lindy effect.

Older isn’t better, it’s exponentially better. 

Lindy-Effect-Modeled1

Pearson writes:

If you were to look at a typical person’s reading list, the vast majority of books would be crammed into the recent, low-value portion of the curve while many fewer books would occupy the much larger high-value, older section of the curve.

So your ROI on reading and understanding a concept from 500 years ago is highly likely to be exponentially greater in the long run than one presented only 5 years ago.

What I’m trying to get at is that the more fundamental or closer to the source that you move, the better the ROI in the long run.

Understanding Time-Tested Ideas

So let’s combine these ideas and focus on reading basic ideas that have stood the test of time as a means to understanding them better.

Knowledge has a half-life. The most useful knowledge is a broad-based multidisciplinary education of the basics. These ideas are ones that have lasted, and thus will last, for a long time. And by last, I mean mathematical expectation; I know what will happen in general but not each individual case.

In the words of Charlie Munger, “take a simple idea and take it seriously.”

The Copernican Principle: How To Predict Everything

An old (1999) New Yorker article introduces us to J. Richard Gott III, a Princeton astrophysicist and some of his ideas on prediction. The core idea is that — despite what we’d like — we are not that special. So when we encounter something, we are unlikely to be doing so at a special time in its life. This is the Copernican Principle.

“On May 27, 1993, I looked up all the plays that were listed in The New Yorker—Broadway and Off Broadway plays and musicals—and called up each of the theatres and asked when each play had opened,” Gott recalls. “I predicted how long each would run, based solely on how long it had been running already. Forty-four shows were playing at the time. So far, thirty-six of them have closed, all in agreement with my predictions of how long they would last. And the others, which are still running, are also within the range I’d predicted.”

It must be said that Gott’s predictions are, well, broad. He predicted, for instance, that “Marisol,” which had been open for a week when he called the theatres, would close in less than thirty-nine weeks; it lasted 10 more days. To “Cats,” which had then been running for three thousand eight hundred and eighty-five days, Gott assigned a longevity of not less than a hundred days and not more than four hundred and fourteen years.

The significance of Gott’s approach rests in its competence in addressing issues previously inaccessible to scientific inquiry, such as, say, trying to predict how long the human species will endure.

“As time goes on, you’ll understand. What lasts, lasts; what doesn’t, doesn’t. Time solves most things. And what time can’t solve, you have to solve yourself.”

― Haruki Murakami

“My approach is based on the Copernican principle, which has been one of the most famous and successful scientific hypotheses in the history of science,” Gott said. “It’s named after Nicolaus Copernicus, who proved that the earth is not the center of the universe; and it’s simply the idea that your location is not special. The more we’ve learned about the universe, the more non-special our location has looked. The earth is orbiting an ordinary star in an ordinary galaxy. The reason the Copernican principle works is that, of all the places for intelligent observers to be, there are, by definition, only a few special places and many non-special places. So you’re simply more likely to be in one of the many non-special places.”

The predictions that I make are based on applying this principle to time. I first thought of it in 1969. I’d just graduated from Harvard and was traveling around Europe, and I visited the Berlin Wall. People at the time wondered how long the Wall might last. Was it a temporary aberration, or a permanent fixture of modern Europe? Standing at the Wall in 1969, I made the following argument, using the Copernican principle. I said, Well, there’s nothing special about the timing of my visit. I’m just travelling—you know, Europe on five dollars a day—and I’m observing the Wall because it happens to be here. My visit is random in time. So if I divide the Wall’s total history, from the beginning to the end, into four quarters, and I’m located randomly somewhere in there, there’s a fifty-percent chance that I’m in the middle two quarters—that means, not in the first quarter and not in the fourth quarter.

Let’s suppose that I’m at the beginning of that middle fifty percent. In that case, one-quarter of the Wall’s ultimate history has passed, and there are three-quarters left in the future. In that case, the future’s three times as long as the past. On the other hand, if I’m at the other end, then three-quarters have happened already, and there’s one-quarter left in the future. In that case, the future is one-third as long as the past.

The Wall was 8 years old at the time. “So I said to a friend, ‘There’s a fifty-percent chance that the Wall’s future duration will be between two-thirds of a year (I believe this should be two and two-thirds of a year – i.e. 1/3 of 8) and twenty-four years.’ Twenty years later, in 1989, the Wall came down, within those two limits that I had predicted. I thought, maybe I should write this up.”

Recently, it’s come to be understood that systems may behave chaotically and therefore be unpredictable. You know, a butterfly in the Amazon can affect the weather thousands of miles away, that sort of thing. This has led some people to say that predicting the future of complex systems is impossible. Which is true if you are concerned with the precise specifics. To predict the name of the President of the United States in the year 2085, for instance, is impossible. But if you ask the right question maybe you can get an interesting answer.

As for the question of how long the human species will last Gott offers some wise words.

When the author of the New Yorker article, Timothy Ferris, asked his friends how long humans would last, “most people predicted either that humans beings will last less than two hundred years or that we’re good for more than ten million years.” To which Gott responded, “That’s because people like to think they’re living in special times. We like to think of ourselves as near the beginning of things, or in an apocalyptic situation near the end. It’s more dramatic that way. A lot of people might say, ‘Oh, but we are in a special epoch. We’re in the epoch when men first went to the mood, when we discovered genetic engineering, nuclear energy, and so forth.’ My answer to this is that the Copernican principle predicts that you will be living in a high-population century—most people do, just as most people come from cities with higher than average populations, in larger than average nations. It’s people who make discoveries, so if you live when there are more people around, you should expect to live in an age when a lot of interesting discoveries are being made.”

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Still curious? Gott is the author of Time Travel in Einstein’s Universe and Sizing Up the Universe: The Cosmos in Perspective.