Algorithms to Live By: The Computer Science of Human Decisions

by Brian Christian

Optimal stopping tells us when to look and when to leap. The explore/exploit tradeoff tells us how to find the balance between trying new things and enjoying our favorites. Sorting theory tells us how (and whether) to arrange our offices. Caching theory tells us how to fill our closets. Scheduling theory tells us how to fill our time.

tackling real-world tasks requires being comfortable with chance, trading off time with accuracy, and using approximations.

Any yardstick that provides full information on where an applicant stands relative to the population at large will change the solution from the Look-Then-Leap Rule to the Threshold Rule and will dramatically boost your chances of finding the single best applicant in the group.

I expect to pass through this world but once. Any good therefore that I can do, or any kindness that I can show to any fellow creature, let me do it now. Let me not defer or neglect it, for I shall not pass this way again.

Spend the afternoon. You can’t take it with you.

“Seize the day, boys. Make your lives extraordinary.”

“Eat, drink, and be merry, for tomorrow we die,”

“Start learning a new language or an instrument, and make small talk with a stranger, because life is long, and who knows what joy could blossom over many years’ time.”

When balancing favorite experiences and new ones, nothing matters as much as the interval over ...

A sobering property of trying new things is that the value of exploration, of finding a new favorite, can only go down over time, as the remaining opportunities to savor it dwindle.

So explore when you will have time to use the resulting knowledge, exploit when you’re ready to cash in. The interval makes the strategy.

Exploration in itself has value, since trying new things increases our chances of finding the best. So taking the future into account, rather than focusing just on the present, drives us toward novelty.

Regrets, I’ve had a few. But then again, too few to mention. —FRANK SINATRA

For myself I am an optimist. It does not seem to be much use being anything else. —WINSTON CHURCHILL

“To try and fail is at least to learn; to fail to try is to suffer the inestimable loss of what might have been.”

The framework I found, which made the decision incredibly easy, was what I called—which only a nerd would call—a “regret minimization framework.” So I wanted to project myself forward to age 80 and say, “Okay, now I’m looking back on my life. I want to have minimized the number of regrets I have.” I knew that when I was 80 I was not going to regret having tried this. I was not going to regret trying to participate in this thing called the Internet that I thought was going to be a really big deal. I knew that if I failed I wouldn’t regret that, but I knew the one thing I might regret is not ever having tried. I knew that that would haunt me every day, and so, when I thought about it that way it was an incredibly easy decision.

A/B testing works as follows: a company drafts several different versions of a particular webpage. Perhaps they try different colors or images, or different headlines for a news article, or different arrangements of items on the screen. Then they randomly assign incoming users to these various pages, usually in equal numbers. One user may see a red button, while another user may see a blue one; one may see DONATE and another may see CONTRIBUTE. The relevant metrics (e.g., click-through rate or average revenue per visitor) are then monitored. After a period of time, if statistically significant effects are observed, the “winning” version is typically locked into place—or becomes the control for another round of experiments.

Displacement happens when an animal uses its knowledge of the hierarchy to determine that a particular confrontation simply isn’t worth it.

the famously accurate “Moore’s Law” prediction, made by Intel’s Gordon Moore in 1975, that the number of transistors in CPUs would double every two years.

Depend upon it there comes a time when for every addition of knowledge you forget something that you knew before. It is of the highest importance, therefore, not to have useless facts elbowing out the useful ones. —SHERLOCK HOLMES

Random Eviction, adding new data to the cache and overwriting old data at random.

First-In, First-Out (FIFO), where you evict or overwrite whatever has been sitting in the cache the longest

Least Recently Used (LRU): evicting the item that’s gone the longest untouched

So as you age, and begin to experience these sporadic latencies, take heart: the length of a delay is partly an indicator of the extent of your experience.

The effort of retrieval is a testament to how much you know. And the rarity of those lags is a testament to how well you’ve arranged it: keeping the most important things closest to hand.

Do the difficult things while they are easy and do the great things while they are small. —LAO TZU

Priority inheritance. If a low-priority task is found to be blocking a high-priority resource, well, then all of a sudden that low-priority task should momentarily become the highest-priority thing on the system, “inheriting” the priority of the thing it’s blocking.

preemption isn’t free. Every time you switch tasks, you pay a price, known in computer science as a context switch.

When a computer processor shifts its attention away from a given program, there’s always a certain amount of necessary overhead.

a CPU only works on one program at a time, but by swapping between them quickly enough (on the scale of ten-thousandths of a second) it appears to be playing a movie, navigating the web, and alerting you to incoming email all at once.

thrashing: a system running full-tilt and accomplishing nothing at all.

responsiveness and throughput: how quickly you can respond to things, and how much you can get done overall.

So the rule that computer operating systems follow when deciding how long they can afford to dedicate themselves to some task is simple: as long as possible without seeming jittery or slow to the user.

you should try to stay on a single task as long as possible without decreasing your responsiveness below the minimum acceptable limit.

All human knowledge is uncertain, inexact, and partial. —BERTRAND RUSSELL

In fact, for any possible drawing of w winning tickets in n attempts, the expectation is simply the number of wins plus one, divided by the number of attempts plus two: (w+1)⁄(n+2). This incredibly simple scheme for estimating probabilities is known as Laplace’s Law,

Copernican Principle seems reasonable exactly in those situations where we know nothing at all—such as looking at the Berlin Wall in 1969,

In the broadest sense, there are two types of things in the world: things that tend toward (or cluster around) some kind of “natural” value, and things that don’t.

the Additive Rule: always predict that things will go on just a constant amount longer.

our future selves often “pay good money to remove the tattoos that we paid good money to get.”)

Research in machine learning has yielded several concrete strategies for detecting overfitting, and one of the most important is what’s known as Cross-Validation.

Cross-Validation means assessing not only how well a model fits the data it’s given, but how well it generalizes to data it hasn’t seen.

If you can’t explain it simply, you don’t understand it well enough. —ANONYMOUS

Occam’s razor principle, which suggests that, all things being equal, the simplest possible hypothesis is probably the correct one.

using constraints that penalize models for their complexity—as Regularization.

When you’re truly in the dark, the best-laid plans will be the simplest. When our expectations are uncertain and the data are noisy, the best bet is to paint with a broad brush, to think in broad strokes.

There are consequences to everything, and you get to decide whether you want to face those consequences.”

I must admit that after many years of work in this area, the efficacy of randomness for so many algorithmic problems is absolutely mysterious to me. It is efficient, it works; but why and how is absolutely mysterious. —MICHAEL RABIN

it is much easier to multiply primes together than to factor them back out. With big enough primes—say, a thousand digits—the multiplication can be done in a fraction of a second while the factoring could take literally millions of years; this makes for what is known as a “one-way function.”

There is no such thing as absolute certainty, but there is assurance sufficient for the purposes of human life. —JOHN STUART MILL