Citati iz knjige „Rationality: From AI to Zombies“ autora Eliezer Yudkowsky

Surely You’re Joking, Mr. Feynman
Experimental psychologists use two gold standards: probability theory, and decision theory.

Probability theory is the set of laws underlying rational belief.

decision theory is the set of laws underlying rational action, and is equally applicable regardless of what one’s goals and available options are.

We need a concept like “rational” in order to note general facts about those ways of thinking that systematically produce truth or value—and the systematic ways in which we fall short of those standards.
“Rational agents make decisions that maximize the probabilistic expectation of a coherent utility function”
“True models usually produce better experimental predictions than false models” is a useful generalization
rationality is about forming true beliefs and making winning decisions.
When you open your eyes and look at the room around you, you’ll locate your laptop in relation to the table, and you’ll locate a bookcase in relation to the wall. If something goes wrong with your eyes, or your brain, then your mental model might say there’s a bookcase where no bookcase exists, and when you go over to get a book, you’ll be disappointed.

This is what it’s like to have a false belief, a map of the world that doesn’t correspond to the territory. Epistemic rationality is about building accurate maps instead. This correspondence between belief and reality is commonly called “truth,”
“The fish trap exists because of the fish; once you’ve gotten the fish, you can forget the trap.”20

I invite you to explore this book in that spirit. Use it like you’d use a fish trap, ever mindful of the purpose you have for it. Carry with you what you can use, so long as it continues to have use; discard the rest. And may your purpose serve you well.
What Do I Mean By “Rationality”?

I mean:

Epistemic rationality: systematically improving the accuracy of your beliefs.
Instrumental rationality: systematically achieving your values.
it might be necessary to distinguish between experience and expertise, with expertise meaning “the development of a schematic principle that involves conceptual understanding of the problem,” which in turn enables the decision maker to recognize particular biases. However, using expertise as countermeasure requires more than just being familiar with the situational content or being an expert in a particular domain. It requires that one fully understand the underlying rationale of the respective bias, is able to spot it in the particular setting, and also has the appropriate tools at hand to counteract the bias.19
Paolo Freire said, “Washing one’s hands of the conflict between the powerful and the powerless means to side with the powerful, not to be neutral.
Every guess of belief should begin by flowing to a specific guess of anticipation, and should continue to pay rent in future anticipations. If a belief turns deadbeat, evict it.
The whole idea of Science is, simply, reflective reasoning about a more reliable process for making the contents of your mind mirror the contents of the world.
We’re especially loathe to think of our views as inaccurate compared to the views of others. Even when we correctly identify others’ biases, we have a special bias blind spot when it comes to our own flaws.14 We fail to detect any “biased-feeling thoughts” when we introspect, and so draw the conclusion that we must just be more objective than everyone else.15

Studying biases can in fact make you more vulnerable to overconfidence and confirmation bias, as you come to see the influence of cognitive biases all around you—in everyone but yourself. And the bias blind spot, unlike many biases, is especially severe among people who are especially intelligent, thoughtful, and open-minded.16,17

This is cause for concern.
To solve problems, our brains have evolved to employ cognitive heuristics—rough shortcuts that get the right answer often, but not all the time. Cognitive biases arise when the corners cut by these heuristics result in a relatively consistent and discrete mistake.

The representativeness heuristic, for example, is our tendency to assess phenomena by how representative they seem of various categories. This can lead to biases like the conjunction fallacy.
as behavioral economist Dan Ariely notes: we’re predictably irrational. We screw up in the same ways, again and again, systematically.

If we can’t use our gut to figure out when we’re succumbing to a cognitive bias, we may still be able to use the sciences of mind.
Psychologists who work on dual process theories distinguish the brain’s “System 1” processes (fast, implicit, associative, automatic cognition) from its “System 2” processes (slow, explicit, intellectual, controlled cognition).5 The stereotype is for rationalists to rely entirely on System 2, disregarding their feelings and impulses. Looking past the stereotype, someone who is actually being rational—actually achieving their goals, actually mitigating the harm from their cognitive biases—would rely heavily on System-1 habits and intuitions where they’re reliable.

Unfortunately, System 1 on its own seems to be a terrible guide to “when should I trust System 1?” Our untrained intuitions don’t tell us when we ought to stop relying on them. Being biased and being unbiased feel the same.6
Real-world rationality isn’t about ignoring your emotions and intuitions. For a human, rationality often means becoming more self-aware about your feelings, so you can factor them into your decisions.

Rationality can even be about knowing when not to overthink things. When selecting a poster to put on their wall, or predicting the outcome of a basketball game, experimental subjects have been found to perform worse if they carefully analyzed their reasons.3,4 There are some problems where conscious deliberation serves us better, and others where snap judgments serve us better.
If you can lighten your burden you must do so.
There is no straw that lacks the power to break your back
Adding detail can make a scenario SOUND MORE PLAUSIBLE, even though the event necessarily BECOMES LESS PROBABLE.
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