trentmkelly/LessWrong-43k huggingface dataset:
Book Review: Philosophical Investigations by Wittgenstein
by Chris_Leong — 2021-10-12T20:14:59.043Z

Ludwig Wittgenstein is often considered one of the greatest philosophers of the 20th century and is certainly one of its most fascinating figures. Here are some facts to illustrate:

Wittgenstein was the son of the second-wealthiest family in Austria-Hungry. He gave away his fortune soon after he inherited it, apocryphally, to his siblings because it would do them no harm as they were already wealthy.
After finishing the Tractatus, he quit to become a school teacher, on the basis that he'd already dissolved all the problems of philosophy. Nearly ten years later he returned and frantically set about refuting his previous position. His positions changed so much that people are often advised to treat Early Wittgenstein and Latter Wittgenstein as two separate philosophers.
Wittgenstein fought in WW1 and was decorated for his bravery, refusing to abandon his post amongst heavy shelling. He somehow managed to write Tractatus during this period.
In another apocraphal story, Karl Popper was invited to give a talk at the Cambridge University Moral Sciences Club which Wittgenstein was chairing. Wittgenstein and Popper grew increasingly argumentative over time and Wittgenstein started gesturing with a poker to accentuate his points. Eventually Wittgestein demanded that Popper provided an example of a moral rule, which Popper countered, "Not to threaten visiting lecturers with pokers" leading Wittgenstein to storm out in frustration.

I enjoyed reading this book as Wittgenstein is eminently quotable and he writes with crystal clear language. However, the book is incredibly challenging due to the lack of structure, his preference to be implicit rather than explicit and the challenge of understanding how any particular sentence fits into to the overall picture.

Here are some reasons why I consider this book of relevance to this community:

Wittgenstein introduced the notion of words capturing a family resemblance - which roughly corresponds to Eliezer's description of words as clusters in thingspace.
Eliezer has written about the importance of dissolving the question, whilst Wittgenstein argued that most problems in philosophy were merely linguistic confusions and needed to be dissolved. I don't know if Wittgenstein was the originator of this concept, but he seems to have made it more prominent[1].
Wittgenstein introduced the concept of language-games which I consider to be one of th

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Book Review:  Feeling Great by David Burns
by Fei — 2021-10-12T16:32:30.566Z

I watched Paw Patrol: The Movie because I have a four year old I love. In it, the police puppy Chase was scared of jumping over a gaping chasm between two buildings, so his owner the boy Ryder encourages him by telling him he's the bravest dog he knows, and that type of thing. In the movie, this bit of cheerleading works, and the puppy makes the leap, performs extraordinary feats with his high opinion of himself restored.

What David Burns argues in Feeling Great, which I find so radical, is that in this situation:

The cheerleading wouldn't really work. For one thing, the puppy knows that's a ridiculous claim. How is he the single bravest dog the boy Ryder has ever met? Define brave. Bravest every moment continuously with no other dog cutting in with a bit of bravery of its own ever? Really the bravest compared to even the other puppies on the Paw Patrol team (Marshall the firefighter puppy, Skye the pilot puppy, et al.)? Would Ryder say that were the other puppies within earshot? If not, how can Chase take Ryder's cheerleading seriously? Cheerleading with affirmations, whether from others or as self-dialogue, in the form of "You're/I'm so brave, beautiful, smart, etc." doesn't really work because it feels phony, since we can always find counter examples.
The cheerleading sets the police puppy Chase up for a turbulent inner life, in which how he feels is determined by his fluctuations on the bravery scale, as compared to other external dogs, or even to his own evaluations of his bravery. On days he feels/acts less brave, ought he feel bad about himself? Or ought he maintain an unwaveringly exact amount of self-bravery evaluation?

One of Feeling Great's philosophical points, separate from the new way of doing therapy (already reviewed by Steven Byrnes) is to embrace that there is no such thing as a brave puppy, by way of Ludwig Wittgenstein. That the words brave puppy are just sounds. A real puppy is not worried about whether he is brave, but is just enjoying life chasing squirrels or saving humans. Those actions can be well or ill done, but a puppy cannot be well or ill performed/to be. Many problems of psychology are essentially linguistic problems.

Another of Feeling Great's revolutionary and creative philosophical points is the argument to accept ...
Quantifying Risk
by devansh — 2021-10-12T14:41:47.401Z

Epistemic Status: Providing a jumping-off point for further discussion, not intended to be a final authority by any means.

With COVID, a lot of people in the rationality community have had to fundamentally reassess what kind of risks they're willing to handle. We've used microCOVID extensively, tried to figure out what our chances of severe illness or death are, and decided on what precautions to take relative to that.

Regardless, it's incredibly difficult to fundamentally assess risk or the tradeoffs of risk. The EPA values a statistical life at $7.4 million based on surveys of people asking what they valued tiny risks to their life to be. So should we measure risk in dollars, trying to quantify risk using the universal currency of utility, and figuring out exactly what the potential impact of that risk is? I'd argue against it.

My moral values don't prohibit valuing life in dollars, nor would I want them to, but I think that in general it's pretty socially frowned upon to use monetary values as a way to measure statistical life; moreover, we get into questions of what trying to quantify life using money means, and generally I think people would value their own lives very differently from $7.4 million dollars if they were ever in that situation.

Microdeaths might work better as a statistical measuring tool. But I think that the best way to quantify any risk might be to relate it directly to a risk that people take every day and generally know is pretty dangerous—driving. Already, driving is considered a good comparison point; when trying to evaluate COVID risk recently, I've consistently compared my chances of dying at any given activity to my chances of dying on the car ride there. (The car ride usually wins, often by an order of magnitude or so). So I think the best way to evaluate risk might actually be in miles, where each mile is equivalent to roughly 12 nanodeaths, or a 12/1,000,000,000 chance of dying.

What does this mean for risks like COVID? Well, combining CDC data with the Economist's calculator from March, there was a 0.1% chance of death for an unvaccinated 35-year-old male who got COVID, which did not change substantially with Delta. Vaccination lowered that risk by a further (pessimistically) 92%, so a fully vaccinated 35-year-old male has around 8,000 microdeaths by getting COVID, or 666,666 miles of driving. Thus, a single mic...
Building Blocks of Politics: An Overview of Selectorate Theory
by Yoav Ravid — 2021-10-12T11:27:59.608Z

From 1865 to 1909, Belgium was ruled by a great king. He helped promote the adoption of universal male suffrage and proportional-representation voting. During his rule Belgium rapidly industrialized and had immense economic growth. He gave workers the right to strike. He passed laws protecting women and children. Employment of children under 12, of children under 16 at night, and of women under 21 underground, was forbidden. Workers also gained compensation rights for workplace accidents and got Sundays off. He improved education, built railways and more.

Around the same time, Congo was ruled by an awful dictator. He ruled the country using a mercenary military force, which he used for his own gain. He extracted a fortune out of ivory. He used forced labor to harvest and process rubber. Atrocities such as murder and torture were common. The feet and hands of men, women and children were severed when the quota of rubber was not met. Millions have died during his rule.

The catch? They were the same person - King Leopold II of Belgium. Leopold II is a prominent example of a person who ruled two nations simultaneously. What made the same person act as a great king in one nation and a terrible dictator in the other? If neither innate benevolence nor malevolence led to his behavior, it has to be something else.

Leopold II, 1900

This post covers Selectorate Theory. We'll come back to the story of Leopold and see how this theory explains it, but first, we have to understand the theory.

The theory takes a game theoretical approach to political behavior, by which I mean two things. First, that it's built on a mathematical model. And second, that it's agent and strategy based. That means the analysis doesn't happen at the level of countries, which aren't agents, but at the level of individuals, like leaders and voters, and that the behavior of these agents is strategic, and not a product of psychology, personality or ideology.

This abstraction makes this model more generally applicable beyond countries to any hierarchical power structure, such as small local governments, companies, and even small teams and groups, but to keep things simple I'll only talk about it in the context of countries.

I will try to give a comprehensive overview of the theory based on the book The Logic of Political Survival. We'll start with the basic framework, then go through the predictions an...
Niacin as a treatment for covid? (Probably no, but I’m glad we’re checking)
by Elizabeth — 2021-10-12T05:40:07.503Z

Introduction

This article contains an interview with a doctor who believes NAD+ is the secret to covid’s heavy morbidity and mortality toll. The description was unusually well done for internet crackpottery. This is hard to convey rigorously, but it had a mechanistic-ness and the right level of complexity about it, and it made the right level of promises for a treatment. None of this is to say it’s definitely correct, but it had a bunch better chance of being correct than your average alt-covid-cure scribbled out in crayon. So I did some checks on it.

[Didn’t you say the risk of long covid was small? NO I SAID IT WAS TOO SMALL TO MEASURE AGAINST THE DELUGE OF CRAP THAT HAPPENS TO US EVERYDAY THAT IS NOT THE SAME]

*ahem*

This post is organized as follows:

Description of theory.
Long section defining terms. These are all useful for understanding the claims I check later on, but depending on who you are they may not be helpful, and you may find the contextless infodump kind of a drag. Feel free to skip if it’s not useful to you personally, and know that it’s there if you need it.
Deep dive onto particular claims the article makes.
Does it work?
Is it safe?
My personal experience with the protocol
Some meta

This is your reminder that my only credential is a BA in biology and I didn’t specialize in anything relevant. It is a sign of civilizational inadequacy that this post exists at all, and you should think really hard and do your own research before putting too much weight on it.

For those of you would like to skip to the take home message: science is very hard, I’m glad they’re running larger studies to follow up on all of these because that’s a reasonable thing for a rich society to do, but I’m not super hopeful about this protocol.

The Theory

As described by Dr. Ade Wentze:

There is an extremely widely used coenzyme in your body, NAD. The more active form of this compound, NAD+, is depleted by covid (converted to NADH). In people with a preexisting deficiency or difficulty rebounding after depletion, covid infection results in a persistent NAD+ deficit. This is bad in and of itself, but causes additional problems when your body tries to make up for it by requisitioning all your tryptophan to make more. Tryptophan is also a precursor for serotonin, so this leads to either low serotonin or activation of mast cells to release their serotonin stores, accom...
EDT with updating double counts
by paulfchristiano — 2021-10-12T04:40:02.158Z

I recently got confused thinking about the following case:

Calculator bet: I am offered the opportunity to bet on a mathematical statement X to which I initially assign 50% probability (perhaps X = 139926 is a quadratic residue modulo 314159). I have access to a calculator that is 99% reliable, i.e. it corrupts the answer 1% of the time at random. The calculator says that X is true. With what probability should I be willing to wager?

I think the answer is clearly “99%.” But a naive application of EDT can recommend betting with 99.99% probability. I think this is a mistake, and understanding the mistake helps clarify what it means to be “updateless” and why it’s essentially obligatory for EDT agents. My takeaway is that for an EDT agent, bayesian updating is a description of the expected utility calculation rather than something that EDT agent should do to form its beliefs before calculating expected utility.

Thanks to Joe Carlsmith and Katja Grace for the conversation that prompted this post. I suspect this point is well-known in the philosophy literature. I’ve seen related issues discussed in the rationalist community, especially in this sequence and this post but found those a bit confusing—in particular, I think I initially glossed over how “SSA” was being used to refer to a view which rejects bayesian updating on observations (!) in this comment and the linked paper. In general I’ve absorbed the idea that decision theory and anthropics had a weird interaction, but hadn’t noticed that exactly the same weirdness also applied in cases where the number of observers is constant across possible worlds.

Why EDT bets at 99.99% odds (under some conditions)

I’ll make four assumptions:

I have impartial values. Perhaps I’m making a wager where I can either make 1 person happy or 99 people happy—I just care about the total amount of happiness, not whether I am responsible for it. I’ll still describe the payoffs of the bets in $, but imagine that utility is a linear function of total $ earned by all copies of me.
We live in a very big universe where many copies of me all face the exact same decision. This seems plausible for a variety of reasons; the best one is accepting an interpretation of quantum mechanics without collapse (a popular view).
I handle logical uncertainty in the same way I handle empirical uncertainty. You could construct a similar case to the ca

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my new shortsight reminder
by mike_hawke — 2021-10-11T20:06:30.678Z

Some user named Dan L commented on an ACX post:

[...]things can feel more intense now than ever before because more people now care about {things we care about now} than ever before. People used to care less about {things we care about now}, so past times feel like they were less intense. But actually, people used to care *a whole lot* about {things people used to care about}, which we don't care nearly as much about now. So people back then would have felt like things were uniquely intense, and would look at modern disagreements about {things we care about now} and not really get it.

This is all very tautological and makes the very dry statistical bias obvious, but requires confronting that things we used to care about aren't the things we care about now, and almost certainly won't be the things we care about in the future. It is not easy to accept that the answer to "who will win this culture war?" will very possibly be "you won't care". Oh, you'll still have an opinion all right, but *this* fire in your belly will fade faster than you thought possible. As it will for nearly everyone else. This too shall pass.

I found this very powerful when I came across it, and I have been trying to keep it in mind ever since.

(See also: https://en.wikipedia.org/wiki/This_too_shall_pass )
Yet Another Covid Risk Calculator
by Thomas Colthurst — 2021-10-11T19:24:05.073Z

https://thomaswc.com/crisk.html

There are many covid risk calculators online. Some express your risk in arbitrary units, some give you your probability of getting infected, and some tell you how likely you are to die if you get infected. Mine calculates both of those last two things to get your risk of death, and further multiplies that by your expected lifespan to give you an expected reduction in life duration. I'm sharing it here because we all love decision theory, and expected reduction in life duration seems like the relevant decision theoretic quantity to use when deciding whether to go to that board game party tomorrow night.

Suggestions welcomed, either here or via the "give feedback" link on the page.
Book Review: Free Will
by Ape in the coat — 2021-10-11T18:41:35.549Z

Introduction

Sam Harris' Free Will isn't a conventional philosophy book. Rather, it's a laconic manifesto full of bold and provocative statements invoking us to free ourselves from the delusion of free will and abolish the whole concept as misleading and unnecessary. The book quickly shatters the naïve layperson’s intuition in the light of scientific advancements, then briefly explains Harris’ dissatisfaction with compatibilism as a half measure, and finally argues that our morality, penal and political systems would only benefit from the dispelling of the illusion which the “free will” is.

Or at least it's what the book tries to be. For me, however, it turned out to be something different. While my initial craving for deep arguments in favour of a position I disagree with wasn’t satisfied, I got interesting insight from Harris' attempts at resolving confusion and reinventing existing theories with different aesthetics. Most surprisingly, I got a new perspective on religious tolerance. Predictably, the publication of the book led to a philosophical debate on the matter of free will between Sam Harris and Daniel Dennet which turned out to be larger than the book itself. I’ll touch it a little in this review as well.

Main thesis

Harris begins his book with a description of a terrible crime. He points out how our perception of this crime can be shifted if we are informed of the underlying causes. But, under scrutiny, these causes go beyond the control of any of the perpetrators, leaving no extra place for their personal responsibility. He uses it as a high stakes example to make his point.

Of course, if we learned that both these men had been suffering from brain tumors that explained their violent behavior, our moral intuitions would shift dramatically. But a neurological disorder appears to be just a special case of physical events giving rise to thoughts and actions. Understanding the neurophysiology of the brain, therefore, would seem to be as exculpatory as finding a tumor in it. How can we make sense of our lives, and hold people accountable for their choices, given the unconscious origins of our conscious minds?

And therefore he concludes:

Free will is an illusion. Our wills are simply not of our own making. Thoughts and intentions emerge from background causes of which we are unaware and over which we exert no conscious control. We do not have the freedo

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NVIDIA and Microsoft releases 530B parameter transformer model, Megatron-Turing NLG
by Ozyrus — 2021-10-11T15:28:47.510Z
Link: https://developer.nvidia.com/blog/using-deepspeed-and-megatron-to-train-megatron-turing-nlg-530b-the-worlds-largest-and-most-powerful-generative-language-model/?fbclid=IwAR1XidfXX_6bis17pbPqLc9iTq5-a21Bwipnod3kziubSWEiWUGCyw2tRg0

In addition to reporting aggregate metrics on benchmark tasks, we also qualitatively analyzed model outputs and have intriguing findings (Figure 4). We observed that the model can infer basic mathematical operations from context (sample 1), even when the symbols are badly obfuscated (sample 2). While far from claiming numeracy, the model seems to go beyond only memorization for arithmetic.

We also show samples (the last row in Figure 4) from the HANS task where we posed the task containing simple syntactic structures as a question and prompted the model for an answer. Despite the structures being simple, existing natural language inference (NLI) models often have a hard time with such inputs. Fine-tuned models often pick up spurious associations between certain syntactic structures and entailment relations from systemic biases in NLI datasets. MT-NLG performs competitively in such cases without finetuning.

Seems like next big transformer model is here. No way to test it out yet, but scaling seems to continue, see quote.
It is not mixture of experts, so parameters mean something as compared to WuDao (also it beats GPT-3 on PiQA and LAMBADA).
How big of a deal is that?
On Solving Problems Before They Appear: The Weird Epistemologies of Alignment
by adamShimi — 2021-10-11T08:20:36.521Z

Crossposted to the EA Forum

Introduction

Imagine you are tasked with curing a disease which hasn’t appeared yet. Setting aside why you would know about such a disease’s emergence in the future, how would you go about curing it? You can’t directly or indirectly gather data about the disease itself, as it doesn’t exist yet; you can’t try new drugs to see if they work, as the disease doesn’t exist yet; you can’t do anything that is experimental in any way on the disease itself, as… you get the gist. You would be forgiven for thinking that there is nothing you can do about it right now.

AI Alignment looks even more hopeless: it’s about solving a never-before seen problem on a technology which doesn’t exist yet.

Yet researchers are actually working on it! There are

papers

,

books

,

unconferences

,

whole online forums

full of alignment research, both

conceptual and applied

. Some of these work in a purely abstract and theoretical realm, others study our best current analogous of Human Level AI/Transformative AI/AGI, still others iterate on current technologies that seem precursors to these kinds of AI, typically large language models. With so many different approaches, how can we know if we’re making progress or just grasping at straws?

Intuitively, the latter two approaches sound more like how we should produce knowledge: they take their epistemic strategies (ways of producing knowledge) out of Science and Engineering, the two cornerstones of knowledge and technology in the modern world. Yet recall that in alignment, models of the actual problem and/or technology can’t be evaluated experimentally, and one cannot try and iterate on proposed solutions directly. So when we take inspiration from Science and Engineering (and I want people to do that), we must be careful and realize that most of the guarantees and checks we associate with both are simply not present in alignment, for the decidedly pedestrian reason that Human Level AI/Transformative AI/AGI doesn’t exist yet.

I thus claim that:

Epistemic strategies from Science and Engineering don’t dominate other strategies in alignment research.
Given the hardness of grounding knowledge in alignment, we should leverage every epistemic strategy we can find and get away with.
These epistemic strategies should be made explicit and examined. Both the ones taken or adapted from Science and Engineering, and every other one (for example

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