trentmkelly/LessWrong-43k huggingface dataset:
Against Street Epistemology
by Eponym — 2019-04-25T05:01:00.307Z

According to https://streetepistemology.com/publications/street_epistemology_the_basics , street epistemology is a "conversational technique" which is intended to be "a more productive and positive alternative to debates and arguments." Street epistemologists assume a role similar to Socrates in Plato's dialogues, asking questions of his interlocutor to try to create a realisation of ignorance in them. The goal of street epistemology is to find incoherences in people's beliefs, and to convince them of the value of "scepticism."

A street epistemologist tries to remain calm and pleasant throughout the entire interaction, and to build rapport at the beginning in order to make their interlocutor comfortable with the exchange. After introductions and rapport are established,they can ask their interlocutor to identify a belief and give an approximate level of confidence in it (on a scale of 1 to 10). The early stages of the conversation, after identifying the belief, are devoted to making the belief clear and precise so that there is as little ambiguity as possible, and less wiggle room if and when incoherences are found. Terms are defined, clarifying questions are asked and answered. To confirm that the belief is understood, before trying to undermine it, the street epistemologist will try to give a paraphrase of the view that his interlocutor finds charitable and acceptable.

Having pinpointed what the claim is, the street epistemologist then asks which methods the interlocutor used to arrive at their confidence level in this belief. This is the very first question in what might be called the cross-examination stage, and it reveals what sort of incoherence is being sought in these conversations. Street epistemology is all about finding poorly articulated or unarticulated spots in people's epistemological views. One the interlocutor has given a few answers and it comes time to dive into them, the website recommends focusing only on "one or two" of the methods listed, ideally those that are identified as most important. The idea here is to ask many questions about the methods and sources of evidence, hoping that at some point there will be a stumper that causes the interlocutor to notice mistakes or incoherence in their thought. Whether the street epistemologist succeeds is identified partly by observing thei...
"Tsuyoku Naritai!" (the 'becoming stronger' podcast): Episode 2 - Yoda Timers
by Bae's Theorem — 2019-04-25T04:37:48.693Z

Youtube: https://www.youtube.com/watch?v=ZoCI4E17eSc&feature=youtu.be

Podcast: http://bit.ly/2IEJtAh

Transcript and link to original material in the description/show notes.
When is rationality useful?
by Richard_Ngo — 2019-04-24T22:40:01.316Z

In addition to my skepticism about the foundations of epistemic rationality, I’ve long had doubts about the effectiveness of instrumental rationality. In particular, I’m inclined to attribute the successes of highly competent people primarily to traits like intelligence, personality and work ethic, rather than specific habits of thought. But I’ve been unsure how to reconcile that with the fact that rationality techniques have proved useful to many people (including me).
Here’s one very simple (and very leaky) abstraction for doing so. We can model success as a combination of doing useful things and avoiding making mistakes. As a particular example, we can model intellectual success as a combination of coming up with good ideas and avoiding bad ideas. I claim that rationality helps us avoid mistakes and bad ideas, but doesn’t help much in generating good ideas and useful work.
Here I’m using a fairly intuitive and fuzzy notion of the seeking good/avoiding bad dichotomy. Obviously if you spend all your time thinking about bad ideas, you won’t have time to come up with good ideas. But I think the mental motion of dismissing bad ideas is quite distinct from that of generating good ones. As another example, if you procrastinate all day, that’s a mistake, and rationality can help you avoid it. If you aim to work productively for 12 hours a day, I think there’s very little rationality can do to help you manage that, compared with having a strong work ethic and a passion for the topic. More generally, a mistake is doing unusually badly at something, but not failing to do unusually well at it.
This framework tells us when rationality is most and least useful. It’s least useful in domains where making mistakes is a more effective way to learn than reasoning things out in advance, and so there’s less advantage in avoiding them. This might be because mistakes are very cheap (as in learning how to play chess) or because you have to engage with many unpredictable complexities of the real world (as in being an entrepreneur). It’s also less useful in domains where success requires a lot of dedicated work, and so having intrinsic motivation for that work is crucial. Being a musician is one extreme of this; more relevantly, getting deep expertise in a field often also looks like this.
It’s most useful in domains where there’s very little feedback either from other people or from...
Interview with Putanumonit
by Jacob Falkovich — 2019-04-24T14:53:00.096Z

If you’ve ever wondered what Putanumonit will sound like as a podcast, wonder no more! An interview with me was recorded at a public meetup, it started with the basic tenets of rationality and putting numbers on things, then seamlessly segued to audience questions about Israel-Palestine and my sex life.

This was recorded in a public space, so there is quite a bit of background noise. This is my first time being interviewed about this topic, so there are a lot of filler noises such as “umm” and “like” coming from me. Both issues markedly improve as the interview goes on but, unfortunately, neither disappears completely.

The audio is here.
How good are chatbots?
by bipolo — 2019-04-24T14:17:58.218Z

Recently, I tried some chatbots, like Mitsuku, rose, a.l.ic.e. and some more.

I read in wiki about loebner prize, and it looks that these chatbots should be good(they took part in the competitions and won in some of them)

But in practice, they are not so good - at list, not the online version, I dont know if the real version is different. There main weak point is to follow the conversetion - for example, when I ask them "why?" about there previous message, they answer something vague that not saying much.

So, how good are chatbots? Is the online version weaker?
Show LW: Debate on Philosophy being dead 
by CaiwitzAzaria — 2019-04-24T13:35:11.457Z
Link: https://youtube.com/watch?v=hzicGhxQ2z8

Philosophy as Hawking controversial view misquoting Wittgenstein that philosophy couldn't catch up to science and is left to study language is discussed in The Institute of Art and Ideas' debate Full Debate | Lewis Wolpert, Steve Fuller, Jonathon Derbyshire

Reminding me that philosophy was the first ever self help book (the Bible count as one too) because it helps clarify, as the Steve Fuller point in the video.
Lewis Wolpert misunderstanding is because of pure scientific faith. But it also reminds me of Carl Sagan's A demon haunted world and how we shouldn't misrepresent science anyways.

The debate is worth watching and thought provoking.
Many maps, Lightly held
by Elo — 2019-04-24T02:25:12.621Z

Original post: http://bearlamp.com.au/many-maps-lightly-held/

Many maps, lightly held.

As described in The fox and the hedgehog, among other places (munger, systems thinking). This post holds the theory statement above quite “strong”, to try to clarify the need for it. It does not apply in some places. For example gravity. It would be difficult to hold gravity lightly although it’s a neat thought experiment to wonder how brains and thinking might develop differently in a place that didn’t have (almost perfectly) uniform gravity.

I wish I could say the concept of many maps, lightly held was mentioned in Lens that sees it’s flaws– but it was not. I believe many maps would fit that post if it were around at the time.

1.

A group of blind men heard that a strange animal, called an elephant, had been brought to the town, but none of them were aware of its shape and form. Out of curiosity, they said: “We must inspect and know it by touch, of which we are capable”. So, they sought it out, and when they found it they groped about it. In the case of the first person, whose hand landed on the trunk, said “This being is like a thick snake”. For another one whose hand reached its ear, it seemed like a kind of fan. As for another person, whose hand was upon its leg, said, the elephant is a pillar like a tree-trunk. The blind man who placed his hand upon its side said the elephant, “is a wall”. Another who felt its tail, described it as a rope. The last felt its tusk, stating the elephant is that which is hard, smooth and like a spear.

If I was a blind man feeling at an elephant, I’d need the principle of many maps to make sense of the world and the information it presented. How can the elephant be both a rope and a spear and a wall? Many maps. Lightly held.

2.

When the platypus was first encountered by Europeans in 1798, a pelt and sketch were sent back to Great Britain by Captain John Hunter, the second Governor of New South Wales. British scientists’ initial hunch was that the attributes were a hoax. George Shaw, who produced the first description of the animal in the Naturalist’s Miscellany in 1799, stated it was impossible not to entertain doubts as to its genuine nature, and Robert Knox believed it might have been produced by some Asian taxidermist. It was thought that somebody had sewn a duck’s beak onto the body of a beaver-like animal. Shaw even took a pair of s...
Moral Weight Doesn't Accrue Linearly
by bgaesop — 2019-04-23T22:14:37.880Z

This post: https://slatestarcodex.com/2019/03/26/cortical-neuron-number-matches-intuitive-perceptions-of-moral-value-across-animals/

begs a very important question as part of its central premise. Even given the idea that animals have moral weight, it does not follow that there exist a number of them that are of equal moral weight to a human (or another kind of animal, etc). There exist infinite sequences that converge to finite values.

It seems pretty clear to me that moral weight is not linearly additive. This is why we consider it worse when a species goes from 1,000 members to 0 members than when it goes from 1,001,000 members to 1,000,000 members, for instance.
[Answer] Why wasn't science invented in China?
by Ruby — 2019-04-23T21:47:46.964Z

Credit for the question to Eli Tyre.

Preface + Epistemic Status

I spent roughly two days attempting to learn the answer this question plus several more writing it up. What is presented is more accurately described as a partial answer or contribution towards answering the question - this report isn’t actually a confident, solid answer. The question is too large for that.

I need to provide a couple of epistemic caveats:

I am not experienced at this kind of research, I don’t know what kind of rookie mistakes I might be making.
I have not attempted to assess the reliability of the historians who I quote, though my prior is to be less than completely confident. It might to be too easy to start with a conclusion, a nice narrative, and just find evidence for that. Though I quote what they say, I urge skepticism.

I have relatively more trust in statements like “Ibn al-Haytham lived in Cairo in the around the year 1000 and wrote the Book of Optics” more than broad statements like “[there was a] virtual absence in ancient Chinese philosophy of anything resembling the socratic method.”

Writing a research report like this one turned out to be remarkably effortful, more so than the pure research and obtaining answers for myself. To keep it from being even longer and more time-consuming, I found myself having to simplify heavily and then often fearing that the result is too simple and leaves too much out (and possibly important stuff out).

Clarifying and Refining the Question

If you don’t know why you’re doing something, you’re likely to instantiate a version of it which doesn’t help your upstream goal, assuming it’s the right general thing at all. This applies to research too:

almost all questions are sub-questions

.

In this case, I didn’t have an expansion of the question from its author, but I did have their other questions and was aware of their general interests. Other questions they had were: Are there patterns in what makes great scientists? Were there other intellectual subcultures anything like the rationality community any time in the past few hundred years? What was it that made the intellectual high points of human history high? What made the renaissance, the enlightenment, etc., work?

The real agenda is clearly about understanding the factors which cause intellectual progress. The expanded question is more like What were the factors which were present in Europe but abse...
The Principle of Predicted Improvement
by Ronny Fernandez — 2019-04-23T21:21:41.018Z

I made a conjecture I think is cool. Mark Sellke proved it. I don't know what else to do with it, so I will explain why I think it's cool and give the proof here. Hopefully, you will think it's cool, too.

______________________________________________________________________

Suppose we are trying to assign as much probability as possible to whichever of several hypotheses is true. The law of conservation of expected evidence tells us that for any hypothesis, we should expect to assign the same probability to that hypothesis after observing a test result that we assign to it now. Suppose that H takes values hi. We can express the law of conservation of expected evidence as, for any fixed hi:

E[P(H=hi|D)]=P(H=hi)

In English this says that the probability we should expect to assign to hi after observing the value of D equals the probability we assign to hi before we observe the value of D.

This law raises a question. If all I want is to assign as much probability to the true hypothesis as possible, and I should expect to assign the same probability I currently assign to each hypothesis after getting a new piece of data, why would I ever collect more data? A. J. Ayer pointed out this puzzle in The Conception of Probability as a Logical Relation (I unfortunately cannot find a link). I. J. Good solved Ayer's puzzle in On the Principle of Total Evidence. Good shows that if I need to act on a hypothesis, the expected value of gaining an extra piece of data is always greater than or equal to the expected value of not gaining that new piece of data. Although there is nothing wrong with Good's solution, I found it somewhat unsatisfying. Ayer's puzzle is purely epistemic, and while there is nothing wrong with a pragmatic solution to an epistemic puzzle, I still felt that there should be a solution that makes no reference to acts or utility at all.

Herein I present a theorem that I think constitutes such a solution. I have decided to call it the principle of predicted improvement (PPI):

E[P(H|D)]≥E[P(H)]

In English the theorem says that the probability we should expect to assign to the true value of H after observing the true value of D is greater than or equal to the expected probability we assign to the true value of H before observing the value of D. This inequality is strict when H and D are not independent. In other words, you should predict that your epistemic state wi...
Degree of duplication and coordination in projects that examine computing prices, AI progress, and related topics?
by riceissa — 2019-04-23T12:27:18.314Z

I have been noticing that an increasing number of organizations and researchers are looking into historical computing hardware prices, progress in AI systems, the relationship between hardware and AI progress, and related topics.

To list the research efforts/outputs that I am aware of:

Open Philanthropy Project: "One of my first projects was a study of how hardware advances have fed into artificial intelligence progress in the past decades. As a first step, I gathered historical data on computing hardware prices. This alone turned out to be much more difficult and complicated than anyone expected - which is one of the great lessons of research! Once the hardware data was roughly in place, I could compare it with historical AI progress. This requires estimating the level of “intelligence” of various AI systems, which is a qualitative and somewhat speculative task. My ongoing projects aim to put such estimates on a more empirical and quantitative footing."

AI Impacts: "Effect of marginal hardware on artificial general intelligence", "Progress in general purpose factoring", "Trends in algorithmic progress"

Median Group: "Insight-based AI timelines model" and list of insights, "The Brain and Computation", "How rapidly are GPUs improving in price performance?"

OpenAI: "AI and Compute", "How AI Training Scales"

Ryan Carey: "Interpreting AI Compute Trends"

Ben Garfinkel: "Reinterpreting “AI and Compute”"

Some posts on LessWrong: "Reasons compute may not drive AI capabilities growth" by Kythe and "On AI and Compute" by johncrox.

Vipul Naik: Computing Data Project, a data portal for historical computing, network, and storage costs. (Note that this project is in its very early stages. Also I am helping out with this project.)

Going back further in time, there is e.g. Eliezer Yudkowsky's "Intelligence Explosion Microeconomics".

I am curious to hear about the degree of overlap/duplication in this kind of work, and also the extent to which different groups are coordinating/talking to each other (I also welcome other projects/outputs that I missed in my list). In particular, I am potentially worried about a bunch of groups doing a lot of work "in-house" without coordination/sharing work, leading to duplicated effort (and correspondingly fewer insights as different projects don't build on each other). Another potential worry I have is if there are a bunch of scattered pro

...
How to make plans?
by Pee Doom — 2019-04-23T08:29:58.809Z

What models are out there for how humans can personally make plans, especially grand master plans that scale to a whole lifespan or beyond?

What is the set of good plan components? (e.g. "backchaining")
What useful tools are out there to help with planning? (e.g. "pen and paper")
How does one make flexible plans that adapt to change?
How granular and detailed vs simple and high-level should plans be?
What are the biggest disagreements between different schools of planning?
What are the most common/biggest planning mistakes?
1960: The Year The Singularity Was Cancelled
by Scott Alexander — 2019-04-23T01:30:01.224Z

[Epistemic status: Very speculative, especially Parts 3 and 4. Like many good things, this post is based on a conversation with Paul Christiano; most of the good ideas are his, any errors are mine.]

I.

In the 1950s, an Austrian scientist discovered a series of equations that he claimed could model history. They matched past data with startling accuracy. But when extended into the future, they predicted the world would end on November 13, 2026.

This sounds like the plot of a sci-fi book. But it’s also the story of Heinz von Foerster, a mid-century physicist, cybernetician, cognitive scientist, and philosopher.

His problems started when he became interested in human population dynamics.

(the rest of this section is loosely adapted from his Science paper “Doomsday: Friday, 13 November, A.D. 2026”)

Assume a perfect paradisiacal Garden of Eden with infinite resources. Start with two people – Adam and Eve – and assume the population doubles every generation. In the second generation there are 4 people; in the third, 8. This is that old riddle about the grains of rice on the chessboard again. By the 64th generation (ie after about 1500 years) there will be 18,446,744,073,709,551,615 people – ie about about a billion times the number of people who have ever lived in all the eons of human history. So one of our assumptions must be wrong. Probably it’s the one about the perfect paradise with unlimited resources.

Okay, new plan. Assume a limited world with a limited food supply / limited carrying capacity. If you want, imagine it as an island where everyone eats coconuts. But there are only enough coconuts to support 100 people. If the population reproduces beyond 100 people, some of them will starve, until they’re back at 100 people. In the second generation, there are 100 people. In the third generation, still 100 people. And so on to infinity. Here the population never grows at all. But that doesn’t match real life either.

But von Foerster knew that technological advance can change the carrying capacity of an area of land. If our hypothetical islanders discover new coconut-tree-farming techniques, they may be able to get twice as much food, increasing the maximum population to 200. If they learn to fish, they might open up entirely new realms of food production, increasing population into the thousands.

So the rate of p...
Book review: The Sleepwalkers by Arthur Koestler
by Richard_Ngo — 2019-04-23T00:10:00.972Z

The progress of Science is generally regarded as a kind of clean, rational advance along a straight ascending line; in fact it has followed a zigzag course, at times almost more bewildering than the evolution of political thought. The history of cosmic theories, in particular, may without exaggeration be called a history of collective obsessions and controlled schizophrenias; and the manner in which some of the most fundamental discoveries were arrived at reminds one more of a sleepwalker’s performance than an electronic brain’s.

Arthur Koestler

The Sleepwalkers is an enlightening history of astronomy from the Ancient Greeks to Newton. It particularly focuses on three characters who shifted scientific consensus from the Ptolemaic geocentric model of the solar system to a heliocentric one: Copernicus, Kepler, and Galileo. And characters is the right word, because Koestler digs into their personal quirks and foibles with gusto. If he is to be believed, these three key scientists were all temperamental to the point of self-destructiveness.

Copernicus and Kepler

Copernicus, according to Koestler, was “a man of the Middle Ages: haunted by its anxieties, ridden with its complexes, a timid, conservative cleric, who started the revolution against his will.” The origin of his heliocentric system was in fact his attempt to fix an aesthetic flaw which made Ptolemy’s system “neither sufficiently absolute nor sufficiently pleasing": that it modelled planets as moving at variable speeds. In doing so, he was inspired by Ancient Greek writings, and in particular references to the heliocentric system that Heraclides of Pontos and Aristarchus of Samos proposed in the 3rd century BC. Copernicus was terrified by the prospect of criticism, so that it took decades for him to publish his conclusions (On the revolutions of the celestial spheres only came out just before his death in 1543). But in fact, the publication itself was fairly irrelevant: it was tedious and actually more complicated than existing geocentric systems. As previous astronomers had done, Copernicus explained complex-looking orbits using models in which planets rotated on circles which themselves rotated in circles (known as epicycles). Epicycles were a very powerful modelling tool (in fact, equivalent to Fourier series!) but made theories much uglier and more complex - and Copernicus needed more of them than ...