trentmkelly/LessWrong-43k huggingface dataset:
Six economics misconceptions of mine which I've resolved over the last few years
by Buck — 2020-07-13T03:01:43.717Z

Here are six cases where I was pretty confident in my understanding of the microeconomics of something, but then later found out I was missing an important consideration.

Thanks to Richard Ngo and Tristan Hume for helpful comments.

Here’s the list of mistakes:

I thought divesting from a company had no effect on the company.
I thought that the prices on a prediction market converged to the probabilities of the underlying event.
I thought that I shouldn’t expect to be able to make better investment decisions than buying index funds.
I had a bad understanding of externalities, which was improved by learning about Coase’s theorem.
I didn’t realize that regulations like minimum wages are analogous to taxes in that they disincentivize work.
I misunderstood the economics of price controls.

In each, I’m not talking about empirical situations at all—I’m just saying that I had a theoretical analysis which I think turned out to be wrong. It’s possible that in many real situations, the additional considerations I’ve learned about don’t actually affect the outcome very much. But it was still an error to not know that those considerations were potentially relevant.

1. Divestment

I used to believe that personally divesting in a company didn’t affect its share price, and therefore had no impact on the company. I guess my reasoning here was something like “If the share is worth $10 and you sell it, someone else will just buy it for $10, so the price won’t change”. I was treating shares as if they were worth some fixed amount of money.

The simplest explanation for why you can’t just model shares as being worth fixed amounts of money is that people are risk averse, and so the tenth Google share you buy is worth less to you than the first; and so as the price decreases, it becomes more worthwhile to take a bigger risk on the company.

As a result, divestment reduces the price of shares, in the same way that selling anything else reduces its price.

In the specific case of divestment, this means that when I sell some stocks, the price ends up lower than it was.

I first learned I was wrong about this from this Sideways View post, published May 2019.

2. Index funds

I used to think that it wasn’t possible for individuals like me to get higher returns than I’d get from just buying an ...
What is the current state of knowledge around COVID-19 at-home remedies?
by Dorikka — 2020-07-12T22:50:49.516Z

Followup to: https://www.lesswrong.com/posts/CewTrCRfyCgW4NJQM/rob-bensinger-s-covid-19-overview and https://www.lesswrong.com/posts/ETqyWKoHpP9LytGmS/you-ve-been-exposed-to-covid-19-what-do-you-wish-you-knew

It's been ~4 months since COVID-19 become a globally relevant topic; most of the treatment work that I've seen is focused on reducing mortality in the context of high-severity cases (usually post hospitalization) ie remdesivir, dexamethasone etc. Wanted to share my current synthesis around "what should I take if I'm experiencing covid-like symptoms?"; would greatly appreciate any feedback as well as info around other positive-effect-on-current-balance-of-evidence treatments that I've missed.

Pepcid/famotidine ( https://cen.acs.org/pharmaceuticals/Pepcid-treat-COVID-19/98/i25 ) - I haven't seen anything indicating specific products are better than others, so bought https://www.amazon.com/gp/product/B008VAMEA0/ref=ppx_yo_dt_b_asin_title_o00_s00?ie=UTF8&psc=1
Zinc - zinc acetate might be a bit better than other zinc types? ( https://www.ijidonline.com/article/S1201-9712(20)30441-0/pdf ) - I bought these since they're zinc acetate and have relatively more zinc per losenge than other products ( https://www.amazon.com/gp/product/B01BKURF1A/ref=ppx_yo_dt_b_asin_title_o00_s00?ie=UTF8&psc=1 )
Vitamin C - ( https://www.pharmacytimes.com/news/evaluating-the-efficacy-of-adjunctive-therapies-used-to-treat-covid-19-the-role-of--vitamin-c-and-zinc ) - I bought https://www.amazon.com/gp/product/B07XTKRF5V/ref=ppx_yo_dt_b_asin_title_o00_s00?ie=UTF8&psc=1 since it seemed potentially more bioavailable than tablets (given that in above article it was delivered via IV)
What counts as defection?
by TurnTrout — 2020-07-12T22:03:39.261Z

Thanks to Michael Dennis for proposing the formal definition; to Andrew Critch for pointing me in this direction; to Abram Demski for proposing non-negative weighting; and to Alex Appel, Scott Emmons, Evan Hubinger, philh, Rohin Shah, and Carroll Wainwright for their feedback and ideas.

There's a good chance I'd like to publish this at some point as part of a larger work. However, I wanted to make the work available now, in case that doesn't happen soon.

They can't prove the conspiracy... But they could, if Steve runs his mouth.

The police chief stares at you.

You stare at the table. You'd agreed (sworn!) to stay quiet. You'd even studied game theory together. But, you hadn't understood what an extra year of jail meant.

The police chief stares at you.

Let Steve be the gullible idealist. You have a family waiting for you.

Sunlight stretches across the valley, dappling the grass and warming your bow. Your hand anxiously runs along the bowstring. A distant figure darts between trees, and your stomach rumbles. The day is near spent.

The stags run strong and free in this land. Carla should meet you there. Shouldn't she? Who wants to live like a beggar, subsisting on scraps of lean rabbit meat?

In your mind's eye, you reach the stags, alone. You find one, and your arrow pierces its barrow. The beast shoots away; the rest of the herd follows. You slump against the tree, exhausted, and never open your eyes again.

You can't risk it.

People talk about 'defection' in social dilemma games, from the prisoner's dilemma to stag hunt to chicken. In the tragedy of the commons, we talk about defection. The concept has become a regular part of LessWrong discourse.

Informal definition. A player defects when they increase their personal payoff at the expense of the group.

This informal definition is no secret, being echoed from the ancient Formal Models of Dilemmas in Social Decision-Making to the recent Classifying games like the Prisoner's Dilemma:

you can model the "defect" action as "take some value for yourself, but destroy value in the process".

Given that the prisoner's dilemma is the bread and butter of game theory and of many parts of economics, evolutionary biology, and psychology, you might think that someone had already formalized this. However, to my knowledge, no one has.

Formalism

Consider a finite n-player normal-form gam...
School Has It Backwards
by proshowersinger — 2020-07-12T19:24:26.481Z

Life isn't about getting to the right answers; it's about discovering the right questions.

Crossposted from Curious Human.

In school, we're constantly being asked questions and instantly rewarded when we find the right answers. We're praised in class for saying "25" when we're asked what "5x5" is. We're given perfect scores on tests when we answer every question correctly. We get good grades for repeatedly getting good scores. Students who give the right answers when asked are "good students".

We're also instantly punished when we propose the wrong answers. We get scolded, lose points, and get poor grades. Students who don't give the right answers are "bad students".

For 16+ years (12 grades + 4 years of higher education) we're literally conditioned, in artificial learning environments, to find the right answers to other people's questions. How often do students finish a paper assigned to them in a class and want to write more on the subject? Rarely, if ever. Because the questions - the essay prompts - were never truly ours in the first place.

It's the same for every subject. Take the way math is taught in schools. General concepts are broken down into extremely specific questions. Students are then given a list of methods to answer each specific type of question, which they memorize for the sole purpose of using them to quickly find answers on tests. This process only makes sense for basic, fundamental concepts (times tables, finding the areas of common shapes, etc.); anything more complex and it quickly becomes unnecessarily complicated. Even worse, it detaches math from reality and ruins its purpose, which is to allow us to take first principles, generalize them, and apply them to as many real-world cases as possible.

We weren't designed to learn this way. Have you ever seen a child learn something new? They're playing, and suddenly something sparks their interest. They come up with a question. You see their eyes light up as their curiosity takes over. At that point, they're insatiably motivated to learn - it's only natural.

The things you learn by yourself stick; the things that are “taught” to you do not stick. - Nabeel Qureshi

This way of learning - by starting with our own questions - isn't just more effecti...
What is the current process for increases testing?
by jmh — 2020-07-12T17:21:49.847Z

I was just thinking about the current state of things in the USA and realize I don't really have any clue about just how the increased testing is getting done.

Part of the reason I was musing about this was the idea of doing testing a bit like intoxication stops on roads to check for drunk/intoxicated driving. That does reduce the event and get some to do the designated driver or take uber/taxi home.

If part of the problem with getting, particularly the younger people, but in general all the people that are stubbornly refusing to to simple things like wear masks and keep reasonable distance from others such stop and test might change the equation a bit.
Science eats its young
by George3d6 — 2020-07-12T12:32:39.066Z
Link: https://cerebralab.com/SCIENCE_EATS_ITS_YOUNG

Let's start by talking about scientific literacy. I'm going to use a weak definition of scientific literacy, one that simply requires familiarity with the Baconian method of inquiry.

I don't want to place an exact number on this issue, but I'd wager the vast majority of the population of "educated" countries scientifically illiterate.

I - The gravity of the issue

I first got a hint that this could be a real issue when I randomly started asking people about the theory of gravity. I find gravity to be interesting because it's not at all obvious. I don't think any of us would have been able to come up with the concept in Newton's shoes. Yet it is taught to people fairly early in school.

Interestingly enough, I found that most people were not only unaware of how Newton came up with the idea of gravity, but not even in the right ballpark. I think I can classify the mistakes made into three categories, which I'll illustrate with an answer each:

The Science as Religion mistake: Something something, he saw apples falling towards earth, and then he wrote down the formula for gravity (?)
The Aristotelian Science mistake: Well, he observed that objects of different mass fell towards Earth with the same speed, and from that he derived that objects attract each other. Ahm, wait, hmmm.
The Lack of information mistake: Well, he observed something about the motion of the planets and the moon... and, presumably he estimated the mass of some, or, hmmm, no that can't be right, maybe he just assumed mass_sun >> mass_plant >> mass_moon and somehow he found that his formula accounted for the motion of the planets.

I should caveat this by saying I don't count mistake nr 3 as scientific illiteracy, in this case, I think most of us fall in that category most of the time. Ask me how gravity can be derived in principle and I might be able to make an educated guess and maybe (once the observations are in) I could even derive it. But the chances of that are small, I probably wouldn't know the exact information I'd need which can be measured with 17th-century devices. I most certainly don't have the information readily sitting in my brain.

It's mainly failure modes 1 and 2 that I'm interested in here.

II - And Science said: Let there be truth

I think failure mode 1 is best illu...
Gödel Incompleteness: For Dummies
by jollybard — 2020-07-12T09:13:47.182Z

The Gödel incompleteness theorems are notorious for being surprising. I mean, they did put a hard stop to Hilbert's programme of completely, thoroughly formalizing mathematics.

And most laypeople find them very difficult to wrap their heads around.

It is, however, my belief that nothing should ever be unintuitive. That intuition, like conscious beliefs, can be trained. The territory is never weird, but your brain certainly can be.

My goal is not to give an intuitive explanation of the actual proof, nor even the actual statements, but to give you intuitive evidence that the statements make sense. The core idea is actually from E. T. Jaynes' Probability Theory, I'm only fleshing it out.

First, let's look at the statement of the second theorem, as cited on Wikipedia:

Assume F is a consistent formalized system which contains elementary arithmetic. Then F⊬Cons(F)

That is, F does not prove its own consistency.

Let's unwrap some of the definitions.

By "formalized system", we mean a bunch of statements that you could (assuming the Church-Turing thesis) fully enumerate, either with a computer, or, with a bit of patience, pencil and paper. Mostly you have a bunch of starting axioms and a few rules to produce more statements from them, which means you can just apply all of them in turn to produce all of the statements.

By a "consistent" system, we mean one that's not completely insane. It doesn't believe anything contradictory. This has wider implications. In fact, if your system proves just one contradiction, it actually proves everything! Why? Because if you once tell a lie, the truth is ever after your enemy.

And so, suppose we have a system -- no, a guy, standing in front of you, who is currently telling you that he is not, in fact, insane. Perhaps he tells you that he believes in the latest conspiracy theory surrounding Ghislaine Maxwell and Wayfair, and that you must also believe in it, since he trusts his own epistemic process (he believes that he is not, in fact, insane).

Naturally, you would be skeptical. An insane person can very well not realize that they are insane. Perhaps the guy has a habit of believing in absolutely everything, even contradictory things (he's a pretty inconsistent dude), in which case of course he would in particular believe that he's sane, though if you press him he m...
Covid-19: Analysis of Mortality Data
by Zvi — 2020-07-11T21:30:01.397Z

Data source: The CDC, my spreadsheets are here and here which should be easier to work with.

Previous Covid-19 work here that is potentially relevant these days: Covid 7/9: Lies, Damn Lies and Death Rates, Covid 7/2: It Could Be Worse, Covid-19: My Current Model, On R0, Taking Initial Viral Load Seriously, On “COVID-19 Superspreader Events in 28 Countries: Critical Patterns and Lessons”

Something very bizarre seemed to be happening with the death data.

This post attempts to figure out what the hell is going on. The obvious first explanations didn’t seem to fit the data.

It now looks like the main effect discussed is mostly delays. This is mostly deaths that are pending – it really does take months and months, somehow, for us to figure out what killed a substantial fraction of those who die. Thanks to a screenshot in the comments I was able to compare data from different snapshots, and confirm this.

Thus, we can treat most of this as a fun little exercise that still revealed a bunch of interesting and useful stuff along the way. The C.D.C. seems to have put out a report on this years ago, here.

I’ve chosen to mostly leave the rest of this post unedited, to reflect the thinking process. I think it’s important to learn from such things, to get better at analyzing things and figuring things out.

Death Reporting Delayed Not Death Reporting Denied, Is Actually Death Reporting Backdated Or Something

We’ll start with the basic problem of delays.

The C.D.C.’s data set takes a while to fill in. I downloaded my data set on July 10. At that time, the last week on record in the data was the week of June 27, already two weeks old.

That two week delay didn’t even seem like enough. The week of 6/27 we only see 49% of the previous year’s overall death rate (note: I do smoothing with the two surrounding weeks throughout this post for 2019, whenever possible). The week of 6/20 we only see 81%, and the week of 6/1 we only see 95%. No other week is under 99%. The 95% is possible, but the 81% isn’t. There is at least a four week delay in reporting a substantial number of deaths.

[Added later: Note that the C.D.C. report the other post linked to actually has more of a delay in reporting than this! It says that ten weeks out only 80% of all deaths are available for analysis. My brain doesn’t know to process that. Even after verifying it

...
How well can the GPT architecture solve the parity task?
by FactorialCode — 2020-07-11T19:02:07.730Z

Suppose I give it pairs of strings and ask it to output 1 if the the number of 1s in the string is even and zero if it's odd.

e. g.

0 -> 0

1 -> 1

11 -> 0

101 -> 0

1101-> 1

10101001 -> 0

111000101110 -> 1

How well does it do on this task? What if we finetune it on sample data?
Canonical forms
by sen — 2020-07-11T18:53:10.191Z
Link: https://www.fimfiction.net/blog/908518/canonical-forms

This post in the link gives an intuitive connection between canonical forms in mathematics and easy-to-understand examples in day-to-day conversations. It was motivated by the following question I posed to myself:

Why do mathematicians value canonical forms?

I think this addresses an important class of communication problems that people experience, and that's especially true of intelligent people that see the world through the lens of specialized knowledge. It's easy to trap yourself inside your head when you learn to (usefully!) pile on the complexity. Canonical forms offer one strategy for escape.
Lurking More Before Joining Complex Conversations
by Raemon — 2020-07-11T17:11:21.745Z

Opinion About Rationalist Parties:

At a nerdy party, when people are in the middle of discussing a complicated idea, if a new person joins the conversation, I'd prefer if the norm were to *not* try to get that person up to speed. Instead, they lurk for awhile, try to guess what's going on and offer some brief comments, and then only fully join the conversation if they guess right.

This puts a big burden on newcomers, but the alternative is that every single time,, attempting to bring a new person into a high-context conversation just kills the conversation, without even successfully onboarding the newcomer.

(this is specifically for conversations where the participants are exploring complicated ideas that depend on a lot of shared context. Other conversations are more about vibing, and catching up, and in those ones welcoming newcomers makes more sense)

This is tricky because not letting someone join your conversation is often seen as a sign that they're unwelcome/you-don't-like-them, and I wish this could change as an overall rationalist-culture-norm specifically so that it _wouldn't_ send that signal. Instead it's just understood that "having a high context conversation" is an activity you can't really interrupt once it's started.

I think this would benefit from some standardized social niceties where you briefly acknowledge the person, smile at them and say "hey, sorry this is is a high context conversation. I'd listen awhile until you get a sense of what it's about before joining it."

Lurk till you grok the deeper context

It's worth noting that to do a _good job_ at lurking and figuring out what the conversation's about, it's not enough to just identify the current topic. You need to figure out how that topic relates to previous topics, and why the various participants are interested in it. This takes awhile, and requires some patience.

After listening awhile, I usually try to make a brief comment, see if that comment is well received, and only if it seems like I've successfully slotted myself into the full-conversational-context do I try participating in earnest. Meanwhile, be ready to gracefully bow out or lurk awhile more.

The reason for all this is I've _never_ seen people try to get a newcomer up to speed, and have that actually help. Instead, it just derails the original conversation, and then everyone invests some effort onboarding the new person, and most

...
Meta Programming GPT: A route to Superintelligence?
by dmtea — 2020-07-11T14:51:38.919Z

Imagine typing the following meta-question into GPT-4, a revolutionary new 20 Trillion parameter language model released in 2021:

"I asked the superintelligence how to cure cancer. The superintelligence responded __"

How likely are we to get an actual cure for cancer, complete with manufacturing blueprints? Or will we get yet another "nice sounding, vague suggestion" like "by combining genetic engineering and fungi based medicine"- the sort GPT-2/3 is likely to suggest?

The response depends on whether GPT focuses on either:

1. What GPT thinks humans think that the superintelligence would say; or

2. Using basic reasoning, solve for what the character (an actual superintelligence) would say if this scenario were playing out in real life.

If GPT takes the second approach, by imitating the idealised superintelligence, it would in essence have to act superintelligent.

The difference between the two lies on the fine semantic line: whether GPT thinks the conversation is a human imitating superintelligence, or an actual words of a superintelligence. Arguably, since it only has training samples of the former, it will do the former. Yet that's not what it did with numbers - it learnt the underlying principle, and extrapolated to tasks it had never seen.

If #1 is true, that still implies that GPT-3/4 could be very useful as an AXI: we just need it to imitate a really smart human. More below under "Human Augmentation".

Human-Like Learning?

Human intelligence ['ability to achieve goals'] can be modelled purely as an optimisation process towards imitating an agent that achieves those goals. In so far as these goals can be expressed in language, GPT exhibits a similar capacity to "imagine up an agent" that is likely to fulfil a particular goal. Ergo, GPT exhibits primitive intelligence, of the same kind as human intelligence.

More specifically, I'm trying to clarify that there is a spectrum between imitation and meta-imitation; and bigger GPT models are getting progressively better at meta-imitation.

Meta-Imitation is the imitation of the underlying type of thinking that is represented by a class of real or fictional actors. Eg., mathematics.
Imitation is direct (perfect/imperfect) copying of an observed behaviour : eg. recalling the atomic number of Uranium.

Language allows humans to imagine ideas that they then imi...
Hierarchy of Evidence
by B Jacobs — 2020-07-11T12:54:27.536Z

There have been many hierarchies of evidence made for various fields of science. I was looking for an image of a more general hierarchy that could easily be dropped into any online conversation to quickly improve the debate. I found none that had all the features I was looking for. So I took an old hierarchy: expanded it, made it more aesthetically pleasing and made it into a jpeg, pdf and pages-file so people can easily share and modify it (e.g translate it or convert it to different files). Here it is: