trentmkelly/LessWrong-43k huggingface dataset:
Resource for the mappings between areas of math and their applications?
by Eli Tyre — 2020-03-30T06:00:10.297Z

One of the things that I want to do while I'm in self-quarantine is to learn more math.

One thing that would be really helpful for me is a mapping between areas of math and the technical subfields that use that math.

I'd want to be able to go in both directions.

From math to application: It's been recommended to me (and it fits my experience so far), that whenever I'm learning new math, I should learn an application of that math in parallel. For instance, when studying calculus, study mechanics at the same time. The applied field gives motivation and grounding to the math. It would be really good if I could take any given math course, and quickly get a list of all the fields that make use of it.

From technical field to mathematical prerequisite: There are lots of bits of science that I am interested in getting a technical understanding of (areas of neuroscience, and psychology, and machine learning, and physics, and economics). But very often I don't know where to start. I know that I am missing some of the prerequisites that these field's methods depend on. But I don't usually know what those prerequisites are. It would be helpful if I could take an area that I am interested in, and quickly backtrack to the math it is using.

Is there any existing resource that captures this information?

If not, how could I go about this, in each case?

Thanks,

Eli
Categorization of Meta-Ethical Theories (a flowchart)
by Tommy Crow — 2020-03-30T04:36:24.774Z

Hi folks! Been a LessWrong lurker for a while. Here's a little project I'm excited about, which has been useful in organizing my thoughts on meta-ethics.

This piece is a walk-through of an original flowchart (made with lots of help from friends) that categorizes the major meta-ethical positions. It lays out the points where different meta-ethical theories diverge and gives a brief intro to each major theory. I think it's a nice tool for getting a sense of the broadest strokes of academic meta-ethics, and being able to hold the different theories in your head.

https://medium.com/@tommycrow/what-is-your-meta-ethical-position-c27939810985
Data on FED and macroeconomy
by Victor Smirnov — 2020-03-30T04:35:39.803Z

Turned out, it's devastating to search for time series of standard macro data as: money supply, savings, data on consumer basket across different classes is also missing.

I am surprised (this is really contradictory with common sense) of shortage of high-quality data in the US on the subject that important to make both research and decisions on monetary policy.

I will be grateful if less-wronger monetary policy fans or macroeconomists can help me here.

The idea behind my research is to find out how CBs and FED were deluting the value of the currency against a consumer basket and salaries, and how the basket changed over time due to this dilution, how it affected rate of savings.

The data I find necessary:

Velocity of money before abandoning golden standard.

Consumer basket - its cost and distribution among categories - time series. Great if not only the US.

Savings of households and their revenues.

Money supply. All money, reserves, cash and digital (created by commercial banks) flowing through the economy.

Central Bank reserve requirement - time series.

At the same time it would be altruistically-ineffective to hide the sources I have found.

The tool allows to find out how the currency depreciated over the years, showing how much goods or labour you could have bought in Sweden:
https://www.historicalstatistics.org/Currencyconverter.html

BIS statistics, compiled in cooperation with central banks and other national authorities, are designed to inform analysis of financial stability, international monetary spillovers and global liquidity.

https://www.bis.org/statistics/index.htm

Monetary Base; Total

https://fred.stlouisfed.org/series/BOGMBASE?utm_source=series_page&utm_medium=related_content&utm_term=related_resources&utm_campaign=categories

U.S. Stock Markets, CAPE Ratio, Federal Funds Rate, Bond, CPI, housing market data (1871-present) by Robert Shiller

http://www.econ.yale.edu/~shiller/data.htm
The Real Standard
by orthonormal — 2020-03-30T03:09:02.607Z

Long-delayed followup To: Roleplaying As Yourself

(Another simple intuition pump, this one especially useful for effective altruists who are struggling with wanting to do more or worrying they're not doing enough.)

Previously I wrote about a mental tool for prompting good consequentialist reasoning: ask yourself what a skilled alien roleplayer (here Gurgeh, from Player of Games) would do if they were controlling you, had to take only actions you could plausibly take, and scored points for achieving your goals.

This also serves as a standard for comparing your own actions, though as an aspiration rather than as an expectation.

The reason I mention this is that a good number of people in the rationality and effective altruism communities suffer from scrupulosity, the sense of guilt for not living up to an unattainable standard of conduct. And if we're going to speak to that sense, we need to start by getting the right standard of excellence to bargain with.

(If you're feeling scrupulous about altruism in particular, then you can imagine that Gurgeh gets points for achieving only your altruistic aims, though he's still constrained by your actual needs - he wouldn't steer you into a burnout, that wouldn't maximize his score.)

This standard is insanely daunting. Fortunately, it's not fair to ask you to meet it.

After all, you're not perfectly altruistic, and the other parts get to bargain too.

In Nobody Is Perfect, Everything Is Commensurable, Scott suggests that we deal with scrupulosity by letting ourselves be okay with the standard of giving 10% of our output to the most effective charitable causes. He runs into a bit of a problem when dealing with the fact that people are in different places in their careers (and that a tenth of one's income can be a large or small chunk of one's disposable income), and punts on the question a bit:

If you make $30,000 and you accept 10% as a good standard you want to live up to, you can either donate $3000 to charity, or participate in political protests until your number of lives or dollars or DALYs saved is equivalent to that.

I think this is the right place to introduce the alien gamer roleplaying your character. Are you building intangible expertise or career capital? Gurgeh notices the high payoff in later rounds of the game from these resources, and would be happy to forgo a littl...
For those of us living in the middle of nowhere, any cool meetup groups we can finally participate in during our lockups?
by lisperati — 2020-03-30T01:41:35.787Z

Are there any rationality groups in Silicon Valley/Tokyo/Berlin/etc that have transitioned to online meetings? It might be fun for those of us who don't live in the "cool places" to be able to participate at this time. I'd love it if folks could share some links, if they exist!
My current framework for thinking about AGI timelines
by zhukeepa — 2020-03-30T01:23:57.195Z

At the beginning of 2017, someone I deeply trusted said they thought AGI would come in 10 years, with 50% probability.

I didn't take their opinion at face value, especially since so many experts seemed confident that AGI was decades away. But the possibility of imminent apocalypse seemed plausible enough and important enough that I decided to prioritize investigating AGI timelines over trying to strike gold. I left the VC-backed startup I'd cofounded, and went around talking to every smart and sensible person I could find who seemed to have opinions about when humanity would develop AGI.

My biggest takeaways after 3 years might be disappointing -- I don't think the considerations currently available to us point to any decisive conclusion one way or another, and I don't think anybody really knows when AGI is coming. At the very least, the fields of knowledge that I think bear on AGI forecasting (including deep learning, predictive coding, and comparative neuroanatomy) are disparate, and I don't know of any careful and measured thinkers with all the relevant expertise.

That being said, I did manage to identify a handful of background variables that consistently play significant roles in informing people's intuitive estimates of when we'll get to AGI. In other words, people would often tell me that their estimates of AGI timelines would significantly change if their views on one of these background variables changed.

I've put together a framework for understanding AGI timelines based on these background variables. Among all the frameworks for AGI timelines I've encountered, it's the framework that most comprehensively enumerates crucial considerations for AGI timelines, and it's the framework that best explains how smart and sensible people might arrive at vastly different views on AGI timelines.

Over the course of the next few weeks, I'll publish a series of posts about these background variables and some considerations that shed light on what their values are. I'll conclude by describing my framework for how they come together to explain various overall viewpoints on AGI timelines, depending on different prior assumptions on the values of these variables.

By trade, I'm a math competition junkie, an entrepreneur, and a hippie. I am not an expert on any of the topics I'll be writing about -- m...
The Great Annealing
by Jacob Falkovich — 2020-03-30T01:08:24.268Z

Cross-posted as always from Putanumonit.

Michael Johnson of the Qualia Research Institute wrote an overview of the theory of neural annealing.

The metaphor comes from metalsmithing. A newly forged sword is ductile and tough. Then you bash the outgroup on the head with it and every bash creates a stress point in the sword: some part is bent, or stretched, or slightly cracked. Even elastic metal can’t spring back perfectly to it’s original shape, and the sword becomes brittle and stiff. To restore it, you heat the metal to the point where its microstructure breaks down, then let it slowly cool and crystallize into stable unstressed patterns again.

Johnson, building on the work of Robin Carhart-Harris and others, proposes that the same process applies to brains. In the predictive processing paradigm, the brain starts a cycle from a stable state: neural activity is low-entropy and proceeds in fixed patterns. From the inside, this feels like confidence in your models of the world, and consistent affect in your reaction to things.

As more input comes in, the brain accumulates stress in the form of prediction errors. This manifests as confusion, anxiety, or unease: a person who reacted unexpectedly to something you said, news that upset you, an action that failed to achieve it’s intended consequences.

An ideal Bayesian brain would immediately update all of its model in light of every new bit of information, but our brains cannot physiologically do that. The stress of prediction error accumulates in the form of electrical energy in particular neural circuits, but can’t propagate everywhere (or even reach consciousness) until it crosses a particular threshold of excitation. Your conscious and unconscious models of reality live in silos with their own accumulated errors, separated from the rest of the brain by potential energy barriers (Scott Alexander calls them mental mountains).

To update, your brain needs to heat up, to build up too much energy at once to route through the habitual circuits of thought. Meditation and psychedelics are powerful tools for achieving that, but anything that fills your brain with new and unusual inputs can do the trick like a retreat into the woods or “mindblowing” sex. From the inside, a brain pumped full of entropy feels like a trip: unusual and novel thoughts without strong affect, creative e...
C19 Prediction Survey Thread
by jacob_cannell — 2020-03-30T00:53:49.375Z

I'm curious about people's current predictions of future:

US confirmed case count
US death count

As a schelling point, let's use May 1 (5/01/2020) as the prediction date, and worldometer as the data source.

Predictions should be in the form of a simple distribution such as a normal or lognormal.

My current predictions:

US cases: lognormal(13.0, 0.3) mode: 404k

US deaths: lognormal(10.0, 0.6) mode: 15.3k
Would Covid19 patients benefit from blood transfusions from people who have recovered? 
by Donald Hobson — 2020-03-29T22:27:58.373Z

Epistemic status: wild idea thrown out there in case it is brilliant.

Presumably, the blood of recovered patients has some antibody that targets the virus. Blood transfusions are widely understood and known safe. (Or at least safe so long as you don't do a few things that doctors know not to do, like giving AB blood to an O patient. ) Is it another thing that should work in principle, is more likely than not to work in practice, but by the time someone has run the medical trial, it will be all over. Of course, the recovered patients blood contains enough antibodys to make them immune, but I don't know how big an effect a fraction of the concentration would have. Of course given exponential growth rates, there might be far more critically ill patients than recovered patients. It might be possible to separate the antibody from the rest of the blood, or even grow it by infecting cells with covid19 in a lab.
Approaches to Electronic Contra
by jefftk — 2020-03-29T22:20:02.514Z

I've been thinking about the various ways that musicians have
approached combining elements of electronic dance music with contra
dance. Examples:

Lisa
Greenleaf, Concord 2008

YDW 2008

Asheville
2010

Perpetual
eMotion, Dance Flurry 2011

Double Apex,
BIDA 2011

DJ Improper,
Amherst 2012

Phase X,
Philly 2012

Firecloud,
Portland 2012

D.R. Shadow,
2014

Buddy System,
Amherst 2016

Rushfest,
Carrboro 2016

This is not at all a complete list, but I think it shows the range of
what people have tried.

One axis of variation here is how much of the playing is live. At one end you're dancing to an
entirely premixed track, while at the other all the sounds are
triggered in the moment by the musicians:

Fully pre-mixed: Lisa Greenleaf, Emily Rush (Rushfest), and several
other callers come to the dance with fully mixed-down recordings.
Some "DJ"s are here, doing all
their composition ahead of time.

Mostly pre-mixed: DJ Improper and some
other contra DJs prepare their sets in advance, but can remix them
some on the fly. This is what a live DJ traditionally does.

Hybrid: Julie Vallimont's various bands [1], Phase X, and D. R. Shadow
combine live elements (fiddle, piano, jawharp, accordion, sax, banjo)
with loops, beats, samples, and mashups.

Live looping: Perpetual e-Motion would come in with nothing
pre-recorded, and would build up a complex texture with loops.

Fully live: this is mostly not a thing, though this is close.
It's very hard to make the full sound of a modern electronic dance
track with a reasonable number of live musicians.

Another axis of variation is originality, in the sense of "from
scratch". At one end you have music that is based around commercial
recordings, with edits, remixes and mashups, while at the other end
you have musicians writing their own music. This is separate from the
previous axis: you can make pre-mixed tracks from club hits or your
own compositions; you can play faithful pop covers live or figure out
your own arrangements.

Even though it's separate, they do tend to go together: people who
work pre-mixed are mostly remixing and editing recordings, while
people who work hybrid, looped, or fully live are mostly making their
own thing. I've been thinking some about why. Part of this is that
the easiest way to get started is to find existing recordings that support the structure of the
dance, or make...
COVID transmission by talking (& singing)
by Steven Byrnes — 2020-03-29T18:26:55.839Z

TL;DR: This is an argument that (1) Talking is a major way that COVID-19 transmits from person to person (at least when people aren't wearing facemasks and goggles, and possibly to a much lesser extent even if they are), right up there with coughing, and probably more important than touching contaminated surfaces; (2) The public is not generally aware of this, at least where I am; plus (3) Sketchy ideas for what to do about it.

Epistemic status: Low confidence, open to criticism.

Background: Why think that talking (at least without facemasks) is a major transmission risk?

This NIH video shows how talking creates droplets and aerosols, just like coughing does, and strongly advocates that everyone should avoid face-to-face conversations. They also made a follow-up video showing that facemasks help, even the kind of DIY facemask made from old T-shirts.

This CDC webpage emphasizes respiratory droplets and avoiding close proximity, adding that "contaminated surfaces or objects … [are] not thought to be the main way the virus spreads." The Chinese government guide concurs.

This article by a domain expert argues that the main way people catch it is probably if someone is talking or coughing nearby, and agrees with the CDC that touching contaminated surfaces is probably less of a big deal, albeit with considerable uncertainty from the lack of data.

(She gets really pedantic in arguing that we should use the terminology "short-range aerosols" for what's going on, while the CDC, WHO, and everyone else seems to call the same thing "inhaled droplets". I really don't care about the terminology. Everyone agrees about what's going on. But to be clear, the term "aerosol" usually refers to long-range aerosol transmission, like measles, and there seems to be a consensus that this type of traditional long-range aerosol transmission is not a major part of COVID-19 transmission, for reasons discussed here, including observations about who catches it from whom. (ETA: ok, maybe the word "consensus" is too strong, see here.)

As jimrandomh and others have argued, there is a lot of asymptomatic transmission—so it’s not just people coughing.

Super-spreader events seem to involve singing indoors and/or face-to-face conversations

Two known COVID-19 super-spreader events may have involved the infected person singing indoors for an extended period:

First, the Skagit Valley Chora

...
Small Comment on Organisational Disclaimers
by Ben Pace — 2020-03-29T17:07:48.339Z

[This post has been sitting in my drafts since I first wrote it. I'm publishing it with minimal polishing for Daniel's Blog Post Writing Day II. Sorry that it's not as clear as it could be.]

A while back I was chatting with someone about representing themself and their organisation on the internet - they're someone at an org in the EA/Rationality professional network who sometimes comments on various public online platforms. They were encouraging a colleague at their org to include a few sentences of disclaimer to tell everyone that they're not speaking on behalf of their org and that they're speaking for themselves.

Here are some messages I wrote back:

I think there's something weirdly formal and slightly bad about the way most people write those sorts of sentences, but I've not been able to put my finger on it.

I think people often signal something like "You're supposed to pretend to not believe things about my organisation as a result of things I say here", and that's often not quite true, because if you're in the core 5-10 people or something it actually is evidence, but you don't know if it's a consensus view in the org.

I think folks should try to say something more like "The causal process behind my comment/post is I wrote down my thoughts and answered in a way that is representative of my thinking. I did't run this past my colleagues, I'm not actually sure what they think, and I'm not trying to report consensus views here."

They replied

I think you’ve hit the nail on the head on why I’ve always disliked ‘I’m speaking in my personal capacity’ comments. It feels like it’s requesting that we pretend not to update on something that by all rights has to be evidence.

It feels a bit contentless or allowing of too many interpretations.

Whereas ‘I didn’t run this by my colleagues’ feels helpful, and perfectly reasonable given how costly it is to run everything you publicly say by everyone on your team.

I'm not a fan of boilerplate disclaimers on message boards, since they force you to keep re-disclaiming on each new comment. Otherwise, you leave the disclaimer off and potentially imply that your new comment is 'the organization's belief', whatever that means.

Let me use an example that's on LessWrong. Vaniver, in his brilliant post Public Positions and Private Guts, has the following disclaimer:

[Note: the concept for this post comes from a talk given by Anna Salam

...
Peter's COVID Consolidated Brief for 29 March
by Peter Wildeford — 2020-03-29T17:07:39.085Z

...See the latest in my 2 Apr Brief!

COVID-19 is a rapidly changing situation and it is hard to keep up to date. However, right now I am following COVID-19 full time and I read widely and I read a lot. I’m going to experiment with providing a public consolidated brief that tries to consolidate everything I read into one short, actionable list so other people don’t have to re-create my work. This way I can save time and

fight research debt

.

This brief assumes you are up to date on most things that have happened since around the 25th of March and will aim to keep you up to date on the latest over the past three days or so.

Note that I am not a domain expert and I urge some caution in over-relying on my selection and interpretation of these links.

This brief follows

my research agenda

. I am going to keep that up to date as well. I will also keep eyes on the

LessWrong Coronavirus Agenda

and submit to the

LessWrong links database

. Further discussion will be in the

EA Coronavirus Facebook Group

.

Doing Your Part! How You Can Stay Safe and Help the Fight!

Rob Besinger

offers some advice for staying safe

that I have not had the time or expertise to verify, but will reprint uncritically:

definitely, definitely self-quarantine
Avoid people
If you do need to be around people, wear something over your mouth and nose
Don’t touch your face (duh)
Wash your hands (duh)
Eat well, sleep well, get exercise
Consider stockpiling a month of food (...if you still can at this point, IMO good to have a at least a week or so above your usual amount of food)
Consider printing out copies of your health records
Regularly disinfect commonly touched surfaces like door handles and light switches
Consider covering commonly touched surfaces with copper tape
Probably stop taking NSAIDs like ibuprofen
Probably even-better-advice-than-normal to consume 2000-6000 IU of Vitamin D daily, in the morning
Consider running an air purifier
Understand how COVID-19 usually presents and progresses, so you can make an informed guess about how likely you are to have it
Take zinc immediately if you start feeling any cold-, flu-, or COVID-19-like symptoms
Start monitoring your oxygen immediately if you develop a fever or experience significant chest tightness or difficulty breathing

~

80,000 Hours puts out a list of things people can do to help with COVID

:

Research to understand the disease and to develop new trea

...