Amazing collection of writings on morality, probability, ai, etc.
Insights, lessons learnt:
Many that have already been internalised from reading parts previously of this over the years
Do you believe that elan vital explains the mysterious aliveness of living beings? Then what does this belief not allow to happen-what would definitely falsify this belief? A null answer means that your belief does not constrain experience; it permits anything to happen to you. It floats.
Back in the old days, people actually believed their religions instead of just believing in them. The biblical archaeologists who went in search of Noah’s Ark did not think they were wasting their time; they anticipated they might become famous. Only after failing to find confirming evidence-and finding disconfirming evidence in its place-did religionists execute what William Bartley called the retreat to commitment, “I believe because I believe.”
Not only did religion used to make claims about factual and scientific matters, religion used to make claims about everything. Religion laid down a code of law-before legislative bodies; religion laid down history-before historians and archaeologists; religion laid down the sexual morals-before Women’s Lib; religion described the forms of government-before constitutions; and religion answered scientific questions from biological taxonomy to the formation of stars. The Old Testament doesn’t talk about a sense of wonder at the complexity of the universe-it was busy laying down the death penalty for women who wore men’s clothing, which was solid and satisfying religious content of that era. The modern concept of religion as purely ethical derives from every other area’s having been taken over by better institutions. Ethics is what’s left.
To assign more than 50% probability to the correct candidate from a pool of 100,000,000 possible hypotheses, you need at least 27 bits of evidence (or thereabouts). You cannot expect to find the correct candidate without tests that are this strong, because lesser tests will yield more than one candidate that passes all the tests. If you try to apply a test that only has a million-to-one chance of a false positive (~20 bits), you’ll end up with a hundred candidates. Just finding the right answer, within a large space of possibilities, requires a large amount of evidence.
Your strength as a rationalist is your ability to be more confused by fiction than by reality. If you are equally good at explaining any outcome, you have zero knowledge.
Once upon a time, there was an instructor who taught physics students. One day the instructor called them into the classroom and showed them a wide, square plate of metal, next to a hot radiator. The students each put their hand on the plate and found the side next to the radiator cool, and the distant side warm. And the instructor said, Why do you think this happens? Some students guessed convection of air currents, and others guessed strange metals in the plate. They devised many creative explanations, none stooping so low as to say “I don’t know” or “ This seems impossible. ” And the answer was that before the students entered the room, the instructor turned the plate around.
I encounter people who are quite willing to entertain the notion of dumber-than-human Artificial Intelligence, or even mildly smarter-than-human Artificial Intelligence. Introduce the notion of strongly superhuman Artificial Intelligence, and they’ll suddenly decide it’s “pseudoscience.” It’s not that they think they have a theory of intelligence which lets them calculate a theoretical upper bound on the power of an optimization process. Rather, they associate strongly superhuman AI to the literary genre of apocalyptic literature; whereas an AI running a small corporation associates to the literary genre of Wired magazine.
How can you realize that you shouldn’t trust your seeming knowledge that “light is waves”? One test you could apply is asking, “Could I regenerate this knowledge if it were somehow deleted from my mind?” This is similar in spirit to scrambling the names of suggestively named LISP tokens in your AI program, and seeing if someone else can figure out what they allegedly “refer” to. It’s also similar in spirit to observing that an Artificial Arithmetician programmed to record and play back Plus-Of(Seven, Six) = Thirteen can’t regenerate the knowledge if you delete it from memory, until another human re-enters it in the database. Just as if you forgot that “light is waves,” you couldn’t get back the knowledge except the same way you got the knowledge to begin with-by asking a physicist. You couldn’t generate the knowledge for yourself, the way that physicists originally generated it.
What should I believe? As it turns out, that question has a right answer. It has a right answer when you’re wracked with uncertainty, not just when you have a conclusive proof. There is always a correct amount of confidence to have in a statement, even when it looks like a “personal belief” and not like an expert-verified “fact.”
But, writes Robin Hanson : 1 You are never entitled to your opinion. Ever! You are not even entitled to “I don’t know.” You are entitled to your desires, and sometimes to your choices. You might own a choice, and if you can choose your preferences, you may have the right to do so. But your beliefs are not about you; beliefs are about the world. Your beliefs should be your best available estimate of the way things are; anything else is a lie.
Believing in Santa Claus gives children a sense of wonder and encourages them to behave well in hope of receiving presents. If Santa-belief is destroyed by truth , the children will lose their sense of wonder and stop behaving nicely. Therefore, even though Santa-belief is false-to-fact, it is a Noble Lie whose net benefit should be preserved for utilitarian reasons. Classically, this is known as a false dilemma , the fallacy of the excluded middle, or the package-deal fallacy . Even if we accept the underlying factual and moral premises of the above argument, it does not carry through. Even supposing that the Santa policy (encourage children to believe in Santa Claus) is better than the null policy (do nothing), it does not follow that Santa-ism is the best of all possible alternatives. Other policies could also supply children with a sense of wonder, such as taking them to watch a Space Shuttle launch or supplying them with science fiction novels. Likewise (if I recall correctly), offering children bribes for good behavior encourages the children to behave well only when adults are watching, while praise without bribes leads to unconditional good behavior.
In this case, I begin to suspect psychology that is more imperfect than usual-that someone may have made a devil’s bargain with their own mistakes, and now refuses to hear of any possibility of improvement. When someone finds an excuse not to try to do better, they often refuse to concede that anyone else can try to do better, and every mode of improvement is thereafter their enemy, and every claim that it is possible to move forward is an offense against them. And so they say in one breath proudly, “I’m glad to be gray,” and in the next breath angrily, “And you’re gray too!”
This isn’t the only way of writing probabilities, though. For example, you can transform probabilities into odds via the transformation O = (P/(1 - P)). So a probability of 50% would go to odds of 0.5⁄0.5 or 1, usually written 1:1, while a probability of 0.9 would go to odds of 0.9⁄0.1 or 9, usually written 9:1. To take odds back to probabilities you use P = (O/(1 + O)), and this is perfectly reversible, so the transformation is an isomorphism-a two-way reversible mapping. Thus, probabilities and odds are isomorphic,
A famous proof called Cox’s Theorem (plus various extensions and refinements thereof) shows that all ways of representing uncertainties that obey some reasonable-sounding constraints, end up isomorphic to each other. Why does it matter that odds ratios are just as legitimate as probabilities? Probabilities as ordinarily written are between 0 and 1, and both 0 and 1 look like they ought to be readily reachable quantities-it’s easy to see 1 zebra or 0 unicorns. But when you transform probabilities onto odds ratios, 0 goes to 0, but 1 goes to positive infinity. Now absolute truth doesn’t look like it should be so easy to reach.
We live in an unfair universe. Like all primates, humans have strong negative reactions to perceived unfairness; thus we find this fact stressful. There are two popular methods of dealing with the resulting cognitive dissonance. First, one may change one’s view of the facts-deny that the unfair events took place, or edit the history to make it appear fair. (This is mediated by the affect heuristic and the just-world fallacy .) Second, one may change one’s morality-deny that the events are unfair. Some libertarians might say that if you go into a “banned products shop,” passing clear warning labels that say THINGS IN THIS STORE MAY KILL YOU, and buy something that kills you, then it’s your own fault and you deserve it. If that were a moral truth, there would be no downside to having shops that sell banned products. It wouldn’t just be a net benefit, it would be a one-sided tradeoff with no drawbacks. Others argue that regulators can be trained to choose rationally and in harmony with consumer interests; if those were the facts of the matter then (in their moral view) there would be no downside to regulation.
Not every change is an improvement, but every improvement is necessarily a change.
What is true is already so. Owning up to it doesn’t make it worse. Not being open about it doesn’t make it go away. And because it’s true, it is what is there to be interacted with. Anything untrue isn’t there to be lived. People can stand what is true, for they are already enduring it. -Eugene Gendlin
In the same sense that every thermal differential wants to equalize itself, and every computer program wants to become a collection of ad-hoc patches, every Cause wants to be a cult.
In a 1989 Canadian study, adults were asked to imagine the death of children of various ages and estimate which deaths would create the greatest sense of loss in a parent. The results, plotted on a graph, show grief growing until just before adolescence and then beginning to drop. When this curve was compared with a curve showing changes in reproductive potential over the life cycle (a pattern calculated from Canadian demographic data), the correlation was fairly strong. But much stronger-nearly perfect, in fact-was the correlation between the grief curves of these modern Canadians and the reproductive-potential curve of a hunter-gatherer people, the !Kung of Africa. In other words, the pattern of changing grief was almost exactly what a Darwinian would predict, given demographic realities in the ancestral environment.
If you read Judea Pearl’s Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference , 1 then you will see that the basic insight behind graphical models is indispensable to problems that require it.
But that’s not the a priori irrational part: The a priori irrational part is where, in the course of the argument, someone pulls out a dictionary and looks up the definition of “atheism” or “religion.” (And yes, it’s just as silly whether an atheist or religionist does it.) How could a dictionary possibly decide whether an empirical cluster of atheists is really substantially different from an empirical cluster of theologians? How can reality vary with the meaning of a word? The points in thingspace don’t move around when we redraw a boundary.
When you find yourself in philosophical difficulties, the first line of defense is not to define your problematic terms, but to see whether you can think without using those terms at all. Or any of their short synonyms. And be careful not to let yourself invent a new word to use instead. Describe outward observables and interior mechanisms; don’t use a single handle, whatever that handle may be.
A word itself can have the destructive force of clich茅 ; a word itself can carry the poison of a cached thought
eyeballing suggests that using the phrase by definition, anywhere outside of math, is among the most alarming signals of flawed argument I’ve ever found. It’s right up there with “Hitler,” “God,” “absolutely certain,” and “can’t prove that.”
it sometimes seems to me that at least 20% of the real-world effectiveness of a skilled rationalist comes from not stopping too early . If you keep asking questions, you’ll get to your destination eventually. If you decide too early that you’ve found an answer, you won’t.
In one of the standard fantasy plots, a protagonist from our Earth, a sympathetic character with lousy grades or a crushing mortgage but still a good heart, suddenly finds themselves in a world where magic operates in place of science. The protagonist often goes on to practice magic, and become in due course a (superpowerful) sorcerer. Now here’s the question-and yes, it is a little unkind, but I think it needs to be asked: Presumably most readers of these novels see themselves in the protagonist’s shoes, fantasizing about their own acquisition of sorcery. Wishing for magic. And, barring improbable demographics, most readers of these novels are not scientists. Born into a world of science, they did not become scientists. What makes them think that, in a world of magic, they would act any differently?
Modern science is built on discoveries, built on discoveries, built on discoveries, and so on, all the way back to people like Archimedes, who discovered facts like why boats float, that can make sense even if you don’t know about other discoveries. A good place to start traveling that road is at the beginning.
There is an acid test of attempts at post-theism. The acid test is: “If religion had never existed among the human species-if we had never made the original mistake-would this song, this art, this ritual, this way of thinking, still make sense?” If humanity had never made the original mistake, there would be no hymns to the nonexistence of God. But there would still be marriages, so the notion of an atheistic marriage ceremony makes perfect sense-as long as you don’t suddenly launch into a lecture on how God doesn’t exist. Because, in a world where religion never had existed, nobody would interrupt a wedding to talk about the implausibility of a distant hypothetical concept. They’d talk about love, children, commitment, honesty, devotion, but who the heck would mention God?
As Cialdini remarks, a chief sign of this malfunction is that you dream of possessing something, rather than using it. (Timothy Ferriss offers similar advice on planning your life: ask which ongoing experiences would make you happy, rather than which possessions or status-changes.)
The problem is that, in the present world, very few people bother to study science in the first place. Science cannot be the true Secret Knowledge, because just anyone is allowed to know it-even though, in fact, they don’t. If the Great Secret of Natural Selection, passed down from Darwin Who Is Not Forgotten, was only ever imparted to you after you paid \$2,000 and went through a ceremony involving torches and robes and masks and sacrificing an ox, then when you were shown the fossils, and shown the optic cable going through the retina under a microscope, and finally told the Truth, you would say “That’s the most brilliant thing ever!” and be satisfied.
The sound of these words is probably represented in your auditory cortex, as though you’d heard someone else say it. (Why do I think this? Because native Chinese speakers can remember longer digit sequences than English-speakers. Chinese digits are all single syllables, and so Chinese speakers can remember around ten digits, versus the famous “seven plus or minus two” for English speakers. There appears to be a loop of repeating sounds back to yourself, a size limit on working memory in the auditory cortex, which is genuinely phoneme-based.)
But the conjunction rule does give us a rule of monotonic decrease in probability: as you tack more details onto a story, and each additional detail can potentially be true or false, the story’s probability goes down monotonically. Think of probability as a conserved quantity: there’s only so much to go around. As the number of details in a story goes up, the number of possible stories increases exponentially, but the sum over their probabilities can never be greater than 1. For every story “X and Y,” there is a story “X and 卢Y.” When you just tell the story “X,” you get to sum over the possibilities Y and 卢Y. If you add ten details to X, each of which could potentially be true or false, then that story must compete with 210 - 1 other equally detailed stories for precious probability.
Tell people to choose an important problem and they will choose the first cache hit for “important problem” that pops into their heads, like “global warming” or “string theory.” The truly important problems are often the ones you’re not even considering, because they appear to be impossible, or, um, actually difficult, or worst of all, not clear how to solve. If you worked on them for years, they might not seem so impossible … but this is an extra and unusual insight; naive realism will tell you that solvable problems look solvable, and impossible-looking problems are impossible.
This parable helps illustrate why Bayesians must think about prior probabilities. There is a branch of statistics, sometimes called “orthodox” or “classical” statistics, which insists on paying attention only to likelihoods. But if you only pay attention to likelihoods, then eventually some fixed-coin hypothesis will always defeat the fair coin hypothesis, a phenomenon known as “overfitting” the theory to the data. After thirty flips, the likelihood is a billion times as great for the fixed-coin hypothesis with that sequence, as for the fair coin hypothesis. Only if the fixed-coin hypothesis (or rather, that specific fixed-coin hypothesis) is a billion times less probable a priori can the fixed-coin hypothesis possibly lose to the fair coin hypothesis.
Therefore do I advocate that Bayesian probability theory should be taught in high school. Bayesian probability theory is the sole piece of math I know that is accessible at the high school level, and that permits a technical understanding of a subject matter-the dynamics of belief-that is an everyday real-world domain and has emotionally meaningful consequences. Studying Bayesian probability would give students a referent for what it means to “explain” something.
Once there was a conflict between nineteenth century physics and nineteenth century evolutionism. According to the best physical models then in use, the Sun could not have been burning very long. Three thousand years on chemical energy, or 40 million years on gravitational energy. There was no energy source known to nineteenth century physics that would permit longer burning. Nineteenth century physics was not quite as powerful as modern physics-it did not have predictions accurate to within one part in 1014. But nineteenth century physics still had the mathematical character of modern physics, a discipline whose models produced detailed, precise, quantitative predictions. Nineteenth century evolutionary theory was wholly semitechnical, without a scrap of quantitative modeling. Not even Mendel’s experiments with peas were then known. And yet it did seem likely that evolution would require longer than a paltry 40 million years in which to operate-hundreds of millions, even billions of years. The antiquity of the Earth was a vague and semitechnical prediction, of a vague and semitechnical theory. In contrast, the nineteenth century physicists had a precise and quantitative model, which through formal calculation produced the precise and quantitative dictum that the Sun simply could not have burned that long.
Fascinating words have no power, nor yet any meaning, without the math. The fascinating words are not knowledge but the illusion of knowledge, which is why it brings so little satisfaction to know that “gravity results from the curvature of spacetime.” Science is not in the fascinating words, though it’s all you’ll ever read as breaking news.
There is a shattering truth, so surprising and terrifying that people resist the implications with all their strength. Yet there are a lonely few with the courage to accept this satori. Here is wisdom, if you would be wise: Since the beginning Not one unusual thing Has ever happened. Alas for those who turn their eyes from zebras and dream of dragons! If we cannot learn to take joy in the merely real, our lives shall be empty indeed.
Anthony, only those who have moralities worry over whether or not they have them . If your metaethic tells you to kill people, why should you even listen? Maybe that which you would do even if there were no morality, is your morality.
So all this suggests that you should be willing to accept that you might know a little about morality. Nothing unquestionable, perhaps, but an initial state with which to start questioning yourself . Baked into your brain but not explicitly known to you, perhaps; but still, that which your brain would recognize as right is what you are talking about. You will accept at least enough of the way you respond to moral arguments as a starting point to identify “morality” as something to think about. But that’s a rather large step. It implies accepting your own mind as identifying a moral frame of reference, rather than all morality being a great light shining from beyond (that in principle you might not be able to perceive at all). It implies accepting that even if there were a light and your brain decided to recognize it as “morality,” it would still be your own brain that recognized it, and you would not have evaded causal responsibility-or evaded moral responsibility either, on my view.
The experimental rule is that losing a desideratum-\$50, a coffee mug, whatever-hurts between 2 and 2.5 times as much as the equivalent gain.
Once upon a time, three groups of subjects were asked how much they would pay to save 2,000 / 20,000 / 200,000 migrating birds from drowning in uncovered oil ponds. The groups respectively answered \$80, \$78, and \$88. 1 This is scope insensitivity or scope neglect: the number of birds saved-the scope of the altruistic action-had little effect on willingness to pay.
People visualize “a single exhausted bird, its feathers soaked in black oil, unable to escape.” 4 This image, or prototype, calls forth some level of emotional arousal that is primarily responsible for willingness-to-pay-and the image is the same in all cases. As for scope, it gets tossed out the window-no human can visualize 2,000 birds at once, let alone 200,000. The usual finding is that exponential increases in scope create linear increases in willingness-to-pay-perhaps
I believe that one experiment showed that a shift from 100% probability to 99% probability weighed larger in people’s minds than a shift from 80% probability to 20% probability.
Whenever you try to price a probability shift from 24% to 23% as being less important than a shift from ~1 to 99%-every time you try to make an increment of probability have more value when it’s near an end of the scale-you open yourself up to this kind of exploitation.
Save 400 lives, with certainty. Save 500 lives, with 90% probability; save no lives, 10% probability. Most people choose option 1. Which, I think, is foolish; because if you multiply 500 lives by 90% probability, you get an expected value of 450 lives, which exceeds the 400-life value of option 1. (Lives saved don’t diminish in marginal utility, so this is an appropriate calculation.) “What!” you cry, incensed. “How can you gamble with human lives? How can you think about numbers when so much is at stake? What if that 10% probability strikes, and everyone dies? So much for your damned logic! You’re following your rationality off a cliff!” Ah, but here’s the interesting thing. If you present the options this way: 100 people die, with certainty. 90% chance no one dies; 10% chance 500 people die. Then a majority choose option 2. Even though it’s the same gamble. You see, just as a certainty of saving 400 lives seems to feel so much more comfortable than an unsure gain, so too, a certain loss feels worse than an uncertain one.
Occasionally people object to any discussion of morality on the grounds that morality doesn’t exist, and in lieu of explaining that “exist” is not the right term to use here, I generally say, “But what do you do anyway?” and take the discussion back down to the object level.
you see people insisting that no amount of money whatsoever is worth a single human life, and then driving an extra mile to save \$10;
But any human legal system does embody some answer to the question “How many innocent people can we put in jail to get the guilty ones?,” even if the number isn’t written down.
Being the lone voice of dissent in the crowd and having everyone look at you funny is much scarier than a mere threat to your life, according to the revealed preferences of teenagers who drink at parties and then drive home.
Particularly damaging, I think, was the bad example set by the pretenders to Deep Wisdom trying to stake out a middle way; smiling condescendingly at technophiles and technophobes alike, and calling them both immature. Truly this is a wrong way; and in fact, the notion of trying to stake out a middle way generally, is usually wrong. The Right Way is not a compromise with anything; it is the clean manifestation of its own criteria.
I once lent Xiaoguang “Mike” Li my copy of Probability Theory: The Logic of Science. Mike Li read some of it, and then came back and said: Wow . . . it’s like Jaynes is a thousand-year-old vampire. Then Mike said, “No, wait, let me explain that-” and I said, “No, I know exactly what you mean.” It’s a convention in fantasy literature that the older a vampire gets, the more powerful they become. I’d enjoyed math proofs before I encountered Jaynes. But E. T. Jaynes was the first time I picked up a sense of formidability from mathematical arguments. Maybe because Jaynes was lining up “paradoxes” that had been used to object to Bayesianism, and then blasting them to pieces with overwhelming firepower-power being used to overcome others.