trentmkelly/LessWrong-43k huggingface dataset:
What are the long-term outcomes of a catastrophic pandemic?
by Matthew Barnett — 2020-03-01T19:39:17.457Z

Wei Dai now writes,

The world is probably going to lose 5 2.5-10% of its population (380 190-760 million, see here for the reason for my edit), worse than the Spanish flu even on a percentage basis.

I have some questions about this conclusion and I'm still unsure whether to treat this sort of argument very seriously. But suppose it does come out that between 2.5% to 10% of the world population will die. What are likely results?

I have speculated some of the following. Let me know whether anyone here would agree with my tentative reactions. If the death rate is towards the upper end of 10%, my reactions are probably conservative as I see worse things also happening. Individually I expect each to happen with >50% probability conditional on the above death rate:

Net negative GDP growth for 2020, with a 5% or more contraction, making this pandemic much worse than any financial crisis in recent memory (including the 2008 financial crisis).
Scientific progress is slowed down, and some technologies take a few more years to come out than they otherwise would have. These include artificial intelligence, plant based meats, anti-aging medicine. This is good if you think that the serial time for AI safety must be lengthened, but bad if

you thought that the longer we persisted in our current high-risk period of history, the lower chance we have of surviving
you worry about value drift from current norms about AI safety, or society more generally
you personally wanted to live until some technological achievement.

Life expectancy will drop into the mid 70s in developed countries.
Most people will know several people who died of the coronavirus, especially if you knew a lot of old people.
A global day of remembrance is declared, and the history books have an entire section on this year as being pivotal in some aspects of world history.
The funding for the CDC is multiplied by at least a factor of five.
Comprehensive bipartisan legislation is passed that employs tens of thousands of people to continuously monitor the threat of viruses of this magnitude in the future.
Lasting injury from the coronavirus is a major disability in the world, and is viewed somewhat akin to how people view polio victims even after polio leaves a community.
More young students (>100% increase) want to study epidemiology because they are told that it's a major way to help people in the future,

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Decaf vs. regular coffee self-experiment
by  — 2020-03-01T19:19:24.832Z
Link: https://an1lam.github.io/post/2020-03-01-coffee-rct/

For a while, I've been convinced that decaf coffee has roughly the same effect on me as regular coffee. However, I haven't been able to say with certainty because there's huge potential for placebo effects. Starting tomorrow, I'll be conducting a (99%) blinded experiment to test whether drinking regular vs. decaf coffee has a detectable effect on my mood and alertness.

I intend to record the metrics I describe in the next section under the 'Data collection' heading of this post and will also report results here once the experiment is over. I'll make data from my Quantified Mind experiment (discussed below) available as well in CSV format.

See something wrong with this experiment plan, my analysis, and/or my results? Email me at first.last+blog-at-gmail.com (see top left header for spelling) or comment on this post!

Experiment

Preparation

To prepare for the experiment, I split 2 weeks' worth of coffee (7 days of decaf, 7 days of regular) into 14 bags. After I split the coffee into 14 bags, my lab assistant (girlfriend) sorted them into a random order (with labels for each day) by flipping a coin to decide whether that day's coffee would be regular or decaf.

Procedure

Starting tomorrow, for the next 14 days, I'll make my coffee using the grounds from the labeled bags and track a few subjective metrics three times a day (right after having coffee, at 1 PM, and at 6 PM):

Alertness (1-5 scale): loosely defined as how tired and sleepy I feel.

Sharpness (1-5 scale): the opposite of 'fogginess'.

Mood (1-5 scale): a coarse-grained measure of how 'good' I feel emotionally.

Headache (yes/no): I get headaches if I don't have coffee in the morning, so it will be interesting to see whether I get them on decaf days even when I don't know the coffee is decaf.

Regular vs. decaf day (regular/decaf): "Given how I feel today, do I think this morning's coffee was regular or decaf?"

<img src="http://an1lam.github.io/images/coffee_bags.jpg" style="width: 400px; height:200 px; clip: rect(0px,-60px,-200px,0px);">

I've also set up a Quantified Mind (QM) experiment which will give me 8 minutes of cognitive tests each day and record my scores. I'll take these tests immediately upon finishing my coffee in the morning.

Materials

I'm using Swiss Water's version of Joe Coffee Nightcap Decaf and Joe Coffee Colombia La Familia Guarnizo regular coffee both brewed in a Mr. Coffee drip co

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Training Regime Day 16: Hamming Questions
by Mark Xu — 2020-03-01T18:46:32.335Z

Note: Over the past 3 days, COVID-19 preparations have taken precedence over writing. There is still more work to do, but I will likely resume on March 7th.

Edit: March 7th is a lie. Probably will be another week or two until time permits.

Later Edit: Turned out to be closer to 5 weeks than 2 weeks. There's something ironic about falling prey to the planning fallacy when trying to write about applied rationality, although applying my normal 2x buffer would have still be a little too short.

Introduction

Richard Hamming was a mathematician at Bell Labs that really liked to know lots of stuff. As legend has it, one of Hamming's favorite questions was "what are the most important problems in your field?" followed up with "why aren't you working on them?"

The general category of "Hamming Questions" are questioned designed to get you to think about the biggest problems in your life. The next move is, of course, to try and solve them.

Hamming Questions

The required material is a non-brain device capable of holding information.

The first hamming question is the obvious one: What's the biggest problem in your life? Take a minute or so to just think about what your biggest problem might be. There is a certain type of person that already sort of knows what the biggest problem in their life is, but can't quite look at it directly. This is a call for you to look.

Now imagine that you're life is perfect. What's different in your perfect life compared to right now? Sometimes the biggest problem in your life is not quite a bug, but the lack of an extremely critical feature.

Sometimes, when people imagine that their life is perfect, they are still chained to notions like "possible" and "realistic". Abandon the shackles of your finitude and boundedness and imagine yourself as infinite and perfect as your imagine allows - what you would become if you were given five million years to grow and grow. Is there something in this world that makes your heart sing? If you were omnipotent and omniscient, what would you do?

Now shift perspectives: imagine someone that's literally the same as you. What are the biggest problems in their life? Is there something obvious that your clone is missing? Sometimes looking at your life from the outside makes it easy to see your flaws.

What would your trusted advisors say? Ask your copies of your friends/family/people whose blogs you read what the biggest

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UML XIII: Online Learning and Clustering
by Rafael Harth — 2020-03-01T18:32:03.584Z

(This is the thirteenth post in a sequence on Machine Learning based on this book. Click here for part I.)

In the previous post, I've mentioned the distinction between supervised and unsupervised learning. Here is a more comprehensive picture:

Supervised learning: learning a fixed predictor based on a fixed training sequence generated by a fixed distribution
Unsupervised learning: learning without training data
Online learning: updating a predictor over time based on data that arrives over time, generated by a process that might change and/or depend on past predictions

In particular, the performance of a predictor in supervised learning is measured after all learning has taken place, whereas, in online learning, the accuracy of our predictor matters at every step along the way.

As an example: while it is possible to model spam detection as a supervised learning problem, it is more accurate to model it as online learning, since (a), we may wish to update our spam filter continually, and (b), people composing spam emails may change their behavior based on existing spam filters. Online learning is also the model that comes closest to describing how real humans learn (especially children).

In this post, we'll look at Online Learning as a whole and at clustering, which is a particular problem of unsupervised learning.

Online Learning

For this post, we restrict ourselves to binary classification problems, i.e., Y={0,1}.

Recall that, in supervised learning, we assume there is a fixed probability distribution D over X×Y according to which the environment generates labeled points. Here, each x∈X is a representation of the real-world thing we wish to label rather than the thing itself. For example, if the task is spam detection of emails, then x would be a vector of some of the email's features (length, address of the sender, number of times the word "money" appears, number of images, ...) rather than an encoding that includes the entire body of text. This means that two different emails may have the same feature representation, and, consequently, the same domain point x∈X might sometimes have label 1 and sometimes label 0.

In some cases, we may wish to assume that labels are deterministic regardless, either because it's a realistic assumption for our particular problem, or for reasons of simplicity. If we do, we can alternativel... ,
Russian x-risks newsletter winter 2019-2020.
by avturchin — 2020-03-01T12:50:25.162Z

As of February, 29, there were no official cases of coronavirus in Russia, except 3 cases from Diamond Princess and 2 older cases from China which recovered. This absence of the new cases seems statistically implausible given around 100 cases in Germany. There were some rumors that some infected people do exist, and some schools are closed and some universities are disinfected. However, there are many people on quarantine or under medical observation, including some people (8 people as of 29 Feb) arrived from Italy and Iran.

The desire of the Russian government to downplay the virus internally is connected with the important voting on the new constitution which will take place April, 22. The goal of the changes is to ensure the stability of the power transit after Putin’s era is over, but nobody actually understands how exactly it will be done. The changes were suggested by Putin at January, 15, and the same day he dismissed the government. This was regarded by analytics as coup de etat started by the president himself in order to change the structure of power. The process is not going as well as was expected by the perpetrators and this means that Russia will have an unstable future. (The alternative to the constitutional change was the “Anschluss” of Belorussia and creation of the “new USSR” which was planned in December, but Belarussian leader Lukashenko did everything to prevent this, despite oil delivery blackmail. If it has happened, a new war in Europe could start. This also explains public attack by Putin on Poland, as only Poland could actively oppose the “Anschluss”, according to prominent analytic Illarionov).

A declared epidemic may prevent people to go to voting stations (but there is also a new option to vote via the internet), which would undermine the legitimacy of the power transfer.

Meanwhile, Putin’s daughter becomes the head of the new AI development center. It is possible that she will be Putin’s successor.

Also, Russia almost has started a war with Turkey, after more than 30 Turkish soldiers were killed by an airstrike on 27 of February. Some claimed that the strike was performed by Russian jets. Eventually, Erdogan downplayed the situation by claiming that this was done by Syrian planes, but the situation is still very dangerous. Russian mercenaries are also fighting Turkish...
Blog Post Day Retrospective
by Daniel Kokotajlo — 2020-03-01T11:32:00.601Z

Yesterday was Blog Post Day. I think it was a success! In this post I'll link to all the blog posts that were written as part of Blog Post Day, and then say some things about what I learned and when we'll do another one.

The posts (in no particular order) were:

My Updating Thoughts on AI Policy, by Ben Pace.

How to Choose a Massage Therapist, by mingyuan

An Analytic Perspective on AI Alignment, by Daniel Filan

Bayesian Inference with Partially Specified Priors, by Christopher Clark

Cortés, Pizarro, and Afonso as Precedents for Takeover by me

Edit: Also Ben Goldhaber's shortform about depression

I think I missed a few from this list--for example, Coscott said they finished a post but would not put it up yet because it was part of a planned sequence. There may have been people who participated but didn't finish, or at least didn't post about it where I could see that they finished. Please let me know if I missed you and I can link to your post here (if you want).

There was less chatting in the discord than I expected; for the most part people just worked on their posts. Nevertheless the chatting that did happen was positive and encouraging and made me feel good. There wasn't really any draft-swapping because everyone was finishing right before the deadline.

We had about 12 people express interest in participating, and maybe about 8 people actually participate, and it looks like we got 5+ posts out of it. (Maybe more will trickle in) That sounds good enough to me! I for one am happy with what I accomplished in just one day; I definitely want to repeat this procedure even if no one else joins me.

So, anyone interested in another Blog Post Day? Obviously not soon, but how far away? Three months from now? One month? I could make this a regular scheduled event if there is interest.
Any systems to rate more abstract things?
by Long try — 2020-03-01T10:16:03.384Z

We have many in place to give us aggregated reviews on books (example: goodreads), films (imdb), restaurants (yelp), places (tripadvisor), apps, etc... Yet it seems like there's no such thing for abstract yet important stuffs like theories (e.g. Maslow hierarchy), techniques (CFAR's various), methods...

Without proper research on the issue, I'm still going forth and saying that it's actually in pretty high need. Do you agree? If not, why? If yes, what does the system look like in your mind, in detail? And more important, how many of us here are willing to roll up their sleeves and together build such thing?
My Updating Thoughts on AI policy
by Ben Pace — 2020-03-01T07:06:11.577Z

My conversation on policy and AI with Richard was over a year ago, so for Daniel Kokotajlo's LW writing day I thought I’d write down new thoughts I’ve thought since then (warning: it's pretty rambly). I've structured the post around what what I did that lead to my updated thoughts.

1) I read many posts on strategy

Paul’s post What Failure Looks Like is something I’ve thought about a lot, which lays out how the abstract technical problems turn into practical catastrophes. It is a central example of what (I think) strategy work looks like. The strategic considerations are deeply tied up with the specifics of the technology.

Eliezer’s dialogue on Security Mindset and Scott Garrabrant’s post about how Optimization Amplifies have been key in my thinking about alignment and strategy, best summarised by Scott’s line “I am not just saying that adversarial optimization makes small probabilities of failure large. I am saying that in general any optimization at all messes with small probabilities and errors drastically.”

(I tried to re-state some of my own understandings of Paul’s, Eliezer’s and Scott’s posts when I talked about ML transparency in ‘Useful Doesn’t Mean Secure’. I’m glad I wrote it, it was helpful for sorting out my own thoughts, though I expect isn’t as helpful for other people.)

Eliezer wrote There's No Fire Alarm for Artificial General Intelligence which has been key for how I think about timelines (as I said two years ago). I wrote down some of my worries about the discussion of timelines in an off-topic comment on the recent CFAR AMA, talking about how the broad x-risk network is acting like a herd stampeding away from a fear regarding AI risk, and the problems with that. I’ll clean that up and turn into a post sometime, I managed to say some things there more clearly than I’d been able to think them before.

Paul’s post Arguments about fast takeoff and linked post about hyperbolic growth, was key in my understanding of takeoff speeds, and helped me understand the gears there much better.

I’ve increasingly been thinking a lot about secrecy. I think a lot of people’s actions regarding keeping secrets have been much more damaging that they realised (the herd stampede above regarding timelines is but one example), and work needs to be done to square the necessity of secrecy with the fact that the public record has been necessary for scientific and intellectual

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High Variance Productivity Advice
by lynettebye — 2020-03-01T07:05:36.544Z

Despite being literally inapplicable for half the population, my post on birth control and productivity was one of my most popular Facebook posts. In that spirit, here’s a roundup of my favorite weird productivity tips that aren’t for everyone.

I chose hacks that several people rated as extremely high ROI…and that other people rated from “meh” to “absolutely awful.” Basically, this is my list of tips that I don’t think everyone should try. But since most blogs try to only give generally good advice, maybe you’ll find something new that is fantastic for you.

Attempt them with a spirit of experimentation and caution. A few wins can be worth a lot of useless experiments, but

be careful about large negative impacts

; try 10 experiments that each have a 10% chance of going horribly wrong, and you’ll probably have a bad experience.

Magic Pills

No, not that kind. Antidepressants.

Obviously you should talk to your doctor about medication if you think you’re severely depressed. The more interesting edge case is whether people who don’t qualify as severely depressed should still try antidepressants.

If you score below mild on the

PHQ-9

, then ignore this. If you score mild or above more than a quarter of the time, consider talking to your doctor about antidepressants (even if you don’t think you’re depressed).

I think too many people hesitate to try antidepressants unless absolutely convinced they are definitely depressed. That doesn’t really make sense to me. I mean, there are a lot of problems with antidepressants in the real world and it makes sense to want to do your homework. But after you do your homework, if the expected value calculation says you’ll probably be happier and more productive, then you just discovered a magic pill that delivers utility. (To be clear, antidepressants usually don’t work this way, or else I would be lobbying GiveWell to make Universal Antidepressants Inc. their new top charity.)

Scott Alexander

wrote

that “There is a lot of worry that SSRIs are not much better than a placebo for people with mild to moderate depression….However, this is a completely academic debate for you, because you are not going to get placebo. Your choice is between SSRIs or nothing. Everyone everywhere agrees SSRIs are much better t...
How to choose a massage therapist 
by mingyuan — 2020-03-01T06:53:44.608Z

Written for Daniel Kokotajlo's unofficial blog post day! I didn't very effort here, so sorry that it's pretty rambly and full of personal anecdotes. I hope it's still at least somewhat helpful!

Background

Recently several people have asked me how to go about finding a good massage therapist. I had thought about writing a post on this for a while but didn’t realize there was an actual audience! I guess there is! I have chronic problems with muscle tension and have been to about fifteen different massage therapists, so I hopefully have some wisdom to share.

My basic advice is to use Yelp (or equivalent, e.g. Google reviews). I expect this to work significantly better on average than recommendations from friends, because your preferences and body are likely different enough from theirs. However, recommendations from friends can be worth a shot too.

I will note up front that I have never had a massage therapist try to sexualize the massage. People seem disproportionately concerned about this when getting a massage for the first time, but I really don’t think it’s that common.

What are your goals?

The first question to answer is: What are your goals? Why do you want to get a massage? Do you have a particular pain that bothers you, such as an old injury or a bad knee, or is it more that you just feel generally tense? Are you looking for temporary pain relief or someone who will work with you for a long time to address the underlying problem? Are you not looking for pain relief at all but just a nice relaxing experience? These are all important things to know going in.

Are they good?

The main measure of whether you should keep seeing a massage therapist is whether you think they’re good. This will obviously be a subjective judgment, and may change over time (e.g. if you thought someone had the potential to give you long-term relief, but after a few sessions that hasn’t materialized.)

A big thing I look for when seeing a new massage therapist is whether they can read my body without my having to give them verbal information. This is particularly important for me since I’m really hesitant to speak up when I’m in pain (a good massage therapist should notice the flinch reaction in the surrounding muscles and ease off automatically), but I think it’s also a good litmus test in general. For example, if you say “I have pain in my forearms”, they should be able to find the sp

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How many people in the Bay Area are infected with Covid-19 as of the end of 2/29/2020?
by Pee Doom — 2020-03-01T05:37:26.751Z

I want to know your estimate for how many people you think currently have it within the San Francisco Bay Area. Not how many people who have been measured to have it, since our measurement is garbage. Answers can be given as a distribution or point estimate.