Brian Christian Quotes
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So explore when you will have time to use the resulting knowledge, exploit when you’re ready to cash in.
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Even the best strategy sometimes yields bad results—which is why computer scientists take care to distinguish between “process” and “outcome.” If you followed the best possible process, then you’ve done all you can, and you shouldn’t blame yourself if things didn’t go your way.
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The satirical Peter Principle, articulated in the 1960s by education professor Laurence J. Peter, states that “every employee tends to rise to his level of incompetence.” The idea is that in a hierarchical organization, anyone doing a job proficiently will be rewarded with a promotion into a new job that may involve more complex and/or different challenges. When the employee finally reaches a role in which they don’t perform well, their march up the ranks will stall, and they will remain in that role for the rest of their...
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Pleasantries are low entropy, biased so far that they stop being an earnest inquiry and become ritual. Ritual has its virtues, of course, and I don't quibble with them in the slightest. But if we really want to start fathoming someone, we need to get them speaking in sentences we can't finish.
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One of the chief goals of design ought to be protecting people from unnecessary tension, friction, and mental labor.
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The Gittins index, then, provides a formal, rigorous justification for preferring the unknown, provided we have some opportunity to exploit the results of what we learn from exploring.
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Want to calculate the chance your bus is late? The chance your softball team will win? Count the number of times it has happened in the past plus one, then divide by the number of opportunities plus two. And the beauty of Laplace’s Law is that it works equally well whether we have a single data point or millions of them.
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Learning the structure of the world around us and forming lasting social relationships are both lifelong tasks.
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Computational kindness isn’t just a principle of behavior; it’s also a design principle.
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In fact, for any possible drawing of winning tickets in attempts, the expectation is simply the number of wins plus one, divided by the number of attempts plus two: (w+1)⁄(n+2).
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The old adage tells us that the grass is always greener on the other side of the fence, but the math tells us why: the unknown has a chance of being better, even if we actually expect it to be no different, or if it’s just as likely to be worse.
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Unless we have good reason to think otherwise, it seems that our best guide to the future is a mirror image of the past. The nearest thing to clairvoyance is to assume that history repeats itself — backward.
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Information, defined intuitively and informally, might be something like 'uncertainty's antidote.' This turns out also to be the formal definition- the amount of information comes from the amount by which something reduces uncertainty...The higher the [information] entropy, the more information there is. It turns out to be a value capable of measuring a startling array of things- from the flip of a coin to a telephone call, to a Joyce novel, to a first date, to last words, to a Turing test...Entropy suggests that we gain the most insight on a question when we take it to the friend, colleague, or mentor of whose reaction and response we're least certain. And it suggests, perhaps, reversing the equation, that if we want to gain the most insight into a person, we should ask the question of qhose answer we're least certain... Pleasantries are low entropy, biased so far that they stop being an earnest inquiry and become ritual. Ritual has its virtues, of course, and I don't quibble with them in the slightest. But if we really want to start fathoming someone, we need to get them speaking in sentences we can't finish.
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When the future is foggy, it turns out you don't need a calendar -- just a to-do list.
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To try and fail is at least to learn; to fail to try is to suffer the inestimable loss of what might have been.
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You should be excited to meet new people and try new things—to assume the best about them, in the absence of evidence to the contrary. In the long run, optimism is the best prevention for regret.
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Why not simply allow them unlimited vacation? Anecdotal reports thus far are mixed—but from a game-theoretic perspective, this approach is a nightmare. All employees want, in theory, to take as much vacation as possible. But they also all want to take just slightly less vacation than each other, to be perceived as more loyal, more committed, and more dedicated (hence more promotion-worthy). Everyone looks to the others for a baseline, and will take just slightly less than that. The Nash equilibrium of this game is zero. As the CEO of software company Travis CI, Mathias Meyer, writes, “People will hesitate to take a vacation as they don’t want to seem like that person who’s taking the most vacation days. It’s a race to the bottom.
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After all, the whole time you’re searching for a secretary, you don’t have a secretary. What’s more, you’re spending the day conducting interviews instead of getting your own work done.
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Existence without essence is very stressful.
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This procedure focuses on decisively resolving the question of which treatment is better, rather than on providing the best treatment to each patient in the trial itself.
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At first glance it would seem, of course, that no two subjects could possibly be further apart than an underground society of pickup artists and supercomputer chess. What on earth do these two narratives have to do with each other—and what do they have to do with asserting myself as human in the Turing test? The answer is surprising, and it hinges on what chess players call “getting out of book.” We’ll look at what that means in chess and in conversation, how to make it happen, and what the consequences are if you don’t.
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Sorting something that you will never search is a complete waste; searching something you never sorted is merely inefficient.
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Service works by the gradual buildup of sympathy through failed attempted solutions.
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If you want to be a good intuitive Bayesian—if you want to naturally make good predictions, without having to think about what kind of prediction rule is appropriate—you need to protect your priors. Counterintuitively, that might mean turning off the news.