Harley-ml/lesswrong huggingface dataset:
# Announcement: LessWrong Coronavirus Links Database 2.0

There is a massive amount of information and discussion about the coronavirus, and it can be challenging to keep track of all the things coming in from different sources.

To combat that, 11 days ago we [announced](https://www.lesswrong.com/posts/5LFEDHjCKgXJgJQjR/lesswrong-coronavirus-link-database) that the LessWrong team built and is maintaining a database with all the links that we think are useful, categorizing them, summarizing them, and sorting them.

We've just built a major update for the database. Originally it was a Google spreadsheet but we have now integrated it into the LessWrong site proper and improved the information structure. 

You can find the new version at [**lesswrong.com/coronavirus-link-database**](https://www.lesswrong.com/coronavirus-link-database). It looks like this:

![](https://39669.cdn.cke-cs.com/rQvD3VnunXZu34m86e5f/images/2864f5020d1db61f00bd9f3c5b788c08117feebef2f72800.png)

The database now has 360 links. 

And on mobile it looks like this:

![](https://39669.cdn.cke-cs.com/rQvD3VnunXZu34m86e5f/images/99477d3dae653561f233937da8b31713905a46332ab5cf47.PNG)

We publish daily updates of the added links ([here's the most recent one](https://www.lesswrong.com/posts/quHczL8cQiwj77WxM/march-21st-daily-coronavirus-links)) and you can get notification of those by going to [Habryka's profile page](https://www.lesswrong.com/users/habryka4) and subscribing to his posts.

How to Contribute to the Database
---------------------------------

You can submit links using the [**Link Submission Form**](https://docs.google.com/forms/d/e/1FAIpQLSc5uVDXrowWmhlaDbT3kukODdJotWOZXZivdlFmaHQ6n2gsKw/viewform), which is also findable from the Link Database page itself. This is the primary way to help out.

If you would like to put in the time to help maintain this database, you can help us with the data entry work using the more detailed [LWC19 Database Data Entry Form](https://docs.google.com/forms/d/e/1FAIpQLSdUKNmu1yvr24nolV0QhaZuJjVE8_POBZViEvg4U3sFt_X2HA/viewform), which takes ~5 mins to fill out per link (varying time depending on the link). If you submit 5 links this way, we'll reach out to thank you and give you better access to the database.

If you'd like to help out further with the LessWrong response to the coronavirus, [here is my post on 3 low-key ways to help out](https://www.lesswrong.com/posts/2vkYsqvMmdhFnt2Hi/how-to-contribute-to-the-coronavirus-response-on-lesswrong).

Thank you to the following awesome people who submitted link: Jess Reidel, Ray Arnold, Justin Shovelain, Shri Samson, Jeffrey Ladish, Kyle, Christopher Paul, Roman, VillainMaterial, Sarira, romeostevensit, Jacob Lagerros, ESRogs, Ruby, William-Jose Velez, Matthew Hollett, silverdrake11, Erik Willekens, Eugene Esca, Rod, Vincent Lau, Naryan Wong.
# Advice on reducing other risks during Coronavirus?

I've seen tons of great, useful advice on reducing coronavirus risk, and prepping for the fallout. What I haven't seen is advice on reducing other day-to-day risks which would be unexpectedly dangerous (due to strained infrastructure, reduced medical capacity, etc) during the current period. Some obvious suggestions might include:

*   If you have to drive, do so more slowly and defensively than usual. Try to walk places (while not looking at your phone) if you can.
*   Don't operate power tools.
*   Don't do anything involving significant heights.
*   Be extra careful cooking (burns) and cleaning (chemicals), and handling things like glasses or knives that might cut you if they slip or break.

What other suggestions do people have?
# AGI in a vulnerable world

I’ve been thinking about a class of AI-takeoff scenarios where a very large number of people can build dangerous, unsafe AGI before anyone can build safe AGI. This seems particularly likely if:

*   It is considerably more difficult to build safe AGI than it is to build unsafe AGI.
*   AI progress is software-constrained rather than compute-constrained.
*   Compute available to individuals grows quickly and unsafe AGI turns out to be more of a straightforward extension of existing techniques than safe AGI is.
*   Organizations are bad at keeping software secret for a long time, i.e. it’s hard to get a considerable lead in developing anything.
    *   This may be because information security is bad, or because actors are willing to go to extreme measures (e.g. extortion) to get information out of researchers.

Another related scenario is one where safe AGI is built first, but isn’t defensively advantaged enough to protect against harms by unsafe AGI created soon afterward.

The intuition behind this class of scenarios comes from an extrapolation of what machine learning progress looks like now. It seems like large organizations make the majority of progress on the frontier, but smaller teams are close behind and [able to reproduce impressive results with dramatically fewer resources](https://www.fast.ai/2018/04/30/dawnbench-fastai/). I don’t think the large organizations making AI progress are (currently) well-equipped to keep software secret if motivated and well-resourced actors put effort into acquiring it. There are strong openness norms in the ML community as a whole, which means knowledge spreads quickly. I worry that there are strong incentives for progress to continue to be very open, since decreased openness can hamper an organization’s ability to recruit talent. If compute available to individuals increases a lot, and building unsafe AGI is much easier than building safe AGI, we could suddenly find ourselves in a [vulnerable world](https://nickbostrom.com/papers/vulnerable.pdf).  

I’m not sure if this is a meaningfully distinct or underemphasized class of scenarios within the AI risk space. My intuition is that there is more attention on incentives failures within a small number of actors, e.g. via arms races. I’m curious for feedback about whether many-people-can-build-AGI is a class of scenarios we should take seriously and if so, what things society could do to make them less likely, e.g. invest in high-effort info-security and secrecy work. AGI development seems much more likely to go existentially badly if more than a small number of well-resourced actors are able to create AGI.

_By Asya Bergal_
# What is the safe in-person distance for COVID-19?

I'm not sure where the 6' number comes from, and I'm skeptical it really holds up as something I'd be comfortable maintaining for an extended period of time (If someone with c19 coughed at me from 6' away I would not feel very safe). I'm guessing the 6' is more like a quick rule for people who are only interacting briefly.

How much does it matter whether you're up/downwind? I've heard conflicting things about how airborne it might be.

I'm interested in this largely for "Okay, assuming we need to be careful about this for months at a time, what sort of practices could we use to maintain in-person social ties, indefinitely, without risk?" (i.e. going on long walks, visiting each other's house where 1-2 people hang out in the street or sidewalk and house denizens hang out on the porch, etc)

I'm guessing this has separate answers for "outdoor" and "indoor." 

**Current Answers:**

*   *Indoors*: Basically it's not safe.
*   *Outdoors*: 10 meters (30 feet) seems safe, if nobody is upwind/downwind of each other. But I'm unclear what the falloff range is.
# What are the most plausible "AI Safety warning shot" scenarios?

A "AI safety warning shot" is some event that causes a substantial fraction of the relevant human actors (governments, AI researchers, etc.) to become substantially more supportive of AI research and worried about existential risks posed by AI.

For example, suppose we build an unaligned AI system which is "only" about as smart as a very smart human politician, and it escapes and tries to take over the world, but only succeeds in taking over North Korea before it is stopped. This would presumably have the "warning shot" effect.

I currently think that scenarios like this are not very plausible, because there is a very narrow range of AI capability between "too stupid to do significant damage of the sort that would scare people" and "too smart to fail at takeover if it tried." Moreover, within that narrow range, systems would probably realize that they are in that range, and thus bide their time rather than attempt something risky.

EDIT: To make more precise what I mean by "substantial:" I'm looking for events that cause >50% of the relevant people who are at the time skeptical or dismissive of existential risk from AI to change their minds.
# Hanson vs Mowshowitz LiveStream Debate: "Should we expose the youth to coronavirus?" (Mar 29th)

I'm running the first *LessWrong LiveStream Debate* *and Meetup*, an experiment in online events.

This Sunday (3/29) at noon PDT, Robin Hanson and Zvi Mowshowitz will debate Robin's policy proposal of deliberate infection of certain parts of the population. This will be on a YouTube LiveStream. After the debate, there will be several chat rooms in Mozilla Hub for a general LW meetup, where you can talk to other LessWrong users and with the two debaters.

### [Link to Youtube Stream](https://www.youtube.com/watch?v=4qYNjZZGLDQ&feature=youtu.be)

After that, there'll be lots of online meetups in Mozilla Hub chatrooms like this one:

[**Please RSVP for the event here**](https://docs.google.com/forms/d/e/1FAIpQLSeO2M2kAWiI5C7bfUS_HC_FC-yaMPiDX3ZmYADLHy-vZaLH4w/viewform), so we know how many people are coming.

**Summary**

*   **Time and Date: March 29 at 12:00 PM PDT (US West Coast Time)**
*   On Feb 17th, Robin wrote the post [Consider Controlled Infection](http://www.overcomingbias.com/2020/02/consider-controlled-infection.html), and has since followed up with [six](http://www.overcomingbias.com/2020/02/deliberate-exposure-intuition.html) [more](http://www.overcomingbias.com/2020/03/simple-sims-on-pandemic-variance.html) [posts](http://www.overcomingbias.com/2020/03/for-fast-escaped-pandemic-max-infection-date-variance-not-average.html) [on](http://www.overcomingbias.com/2020/03/expose-the-young.html) [the](http://www.overcomingbias.com/2020/03/do-you-feel-lucky-punk.html) [policy](http://www.overcomingbias.com/2020/03/know-when-to-fold-em.html) proposal of deliberate exposure of certain parts of the population. Robin and Zvi will be debating that proposal and its alternatives.
*   They will have a 90 min debate followed by a 30 min Q&A that I'll moderate.
*   For the Q&A, if you are selected you will be given an invite link and will join the Zoom call to ask your question.
*   The online meetup will start just after 2pm. (If there's problems with Mozilla Hubs, we have a Discord server prepared as backup.)

I'll update this page with a link to the live stream and further info on how the Q&A and meetup will happen. I look forward to chatting with people! Check back for updates.

Update: the Mozilla Hub meetup rooms are listed [here](https://www.lesswrong.com/posts/8wNBiFXYub5QxDbvr/today-s-online-meetup-we-re-using-mozilla-hubs).

Updated 2: for the Q&A, please leave a comment on this post with a question or PM [jacobjacob](https://www.lesswrong.com/users/jacobjacob) with your question. He will select the questions he likes and invite you onto the zoom call to ask the question.
# March 25: Daily Coronavirus Updates

Aggregators
-----------

[**Clusters C19 literature for easier filtering and digestion**](https://maksimekin.github.io/COVID19-Literature-Clustering/plots/t-sne_covid-19_interactive.html)

Given a target article, identifies similar articles

Economics
---------

[**Balancing the cost in lives of C19 and shutdown**](https://medium.com/@jseims/covid-19-measuring-the-urgency-to-act-f54b75a12fca)

Plea to consider both the cost in lives of doing nothing and of gutting the economy, and spend more money to get things fixed faster

Spread & Prevention
-------------------

[**Disinfection and reuse of N95 masks (guidelines and data)**](https://stanfordmedicine.app.box.com/v/covid19-PPE-1-2)

A report on disinfecting N95 disposable respirators. The second half of the document is a paper with fresh results: 70C air for 30 min (good), UV 254nm@8W for 30 min (good, but light must reach all surfaces), hot steam for 10 min (significant degradation after 5-10 cycles), bleach or alcohol (destroys filtration, do not use).

Work & Donate
-------------

[**Empathetic listening for frontline medics**](https://worldwideempathyformeds.org/)

Connects front line medics and carers with volunteer listeners

[Full Database Link](https://www.lesswrong.com/coronavirus-link-database)
-------------------------------------------------------------------------
# What are the best online tools for meetups and meetings?

*tl;dr – If you have tried at least two telepresence tools, explain their relative strengths, and which one you prefer.*

A key question for both remote organizations, and apparently all social life now, is "what tools can best keep me connected to people in the way that in-person-meetings used to."

There are plenty of tools available, ranging from videoconferencing (like Skype or Zoom) to video-games (like Minecraft). But it can be hard to evaluate them in isolation.

So instead of posting "Hey, I like X", this thread is modeled after [The Best Textbooks on Any Subject](https://www.lessestwrong.com/posts/xg3hXCYQPJkwHyik2/the-best-textbooks-on-every-subject) – don't just post about a tool you like. Instead, compare that tool to at least one other tool (preferably two)*,* and explain what's superior about your favorite software.
# "No evidence" as a Valley of Bad Rationality

Quick summary of [Doctor, There are Two Kinds of “No Evidence”](http://www.overcomingbias.com/2008/08/doctor-there-ar.html):

*   Author has a relative with cancer. Relative is doing well after chemo and is going to a doctor to see if it's worth getting more chemo to kill the little extra bits of cancer that might be lingering.
*   Doctor says that there is _no evidence_ that getting more chemo does _any_ good in these situations.
*   Author says that this violates common sense.
*   Doctor says that common sense doesn't matter, evidence does.
*   Author asks whether "no evidence" means 1) a lot of studies showing that it doesn't do any good, or 2) not enough studies to conclusively say that it does good.
*   Doctor didn't understand the difference.

Let me be clear about the mistake the doctor is making: he's focused on _conclusive_ evidence. To him, if the evidence isn't conclusive, it doesn't count.

I think this doctor is stuck in a [Valley of Bad Rationality](https://wiki.lesswrong.com/wiki/Valley_of_bad_rationality). Here's what I mean:

*   The average Joe doesn't know anything about t-tests and p-values, but the average Joe does know to update his beliefs incrementally. Lamar Jackson just had another 4 touchdown game? It's not conclusive, but it starts to point more in the direction of him winning the MVP.
*   The average Joe doesn't know anything about formal statistical methods. He updates his beliefs in a hand-wavy, wishy-washy way.
*   The doctor went to school to learn about these formal statistical methods. He learned that theorizing is error prone and that we need to base our beliefs on hard data. And he learned that if our p-value isn't less than 0.05, we can't reject the null hypothesis.
*   You can argue that so far, the doctors education didn't move him forward. That it instead caused him to take a step _backwards_. Think about it: he's telling a patient with cancer to not even consider more chemo because there is "no evidence" that it will do "any" good. I think Average Joe could do better than that.
*   But if the doctor continued his education and learned more about statistics, he'd learn that his intro class didn't paint a complete picture. He'd learn that you don't always have access to "conclusive" evidence, and that in these situations, sometimes you just have to work with what you have. He'd also learn that he was [privileging the null hypothesis](http://blog.philbirnbaum.com/2012/06/privileging-null-hypothesis.html) in a situation where it'd make sense to do the opposite. The null hypothesis of "more chemo has no effect" probably isn't true.
*   Once the doctor receives this further education, it'd push him two steps forward.
*   In the intro class, he took one step backwards. At that point he's in the Valley of Bad Rationality: education made him worse than where he started. But then when he received more education, he took two steps forward. It brought him out of this valley and further along than where he started.

I think that a lot of people are stuck in this same valley.
# [Update: New URL] Today's Online Meetup: We're Using Mozilla Hubs

That's right! Tomorrow/Today (Sunday Mar 29th) we're having an online LessWrong meetup in Mozilla Hubs. You're welcome to join and chat with some of the interesting people who read LessWrong, SSC, Overcoming Bias, and so on. I am personally quite excited to talk with a bunch of you. **Make sure you read the rules for joining the hub.**

At 12 noon PDT we'll be having the [Hanson/Mowshowitz "Expose The Youth" Debate](https://www.lesswrong.com/posts/xB9A7xymXY4xAqeMT/hanson-vs-mowshowitz-livestream-debate-should-we-expose-the), then after that at around 2pm we'll having a post-debate meetup. This an experiment, I'll do it more if it's fun.

Basic controls:

*   WASD to move
*   G to toggle flying
*   Click and Drag to look around
*   You can hear and be heard by people in proportion to how close you are to them

The rules:

*   **Only 25 people can be in a room.** Move around and check out the other rooms!
*   **Login as soon as you arrive** and use either your real name or a standard alias like your LessWrong username. I'd like some basic accountability please, and today I will remove people who don't follow this rule.
*   **Use headphones.** Mozilla Hubs does not have any basic feedback reduction tech, all sound will get unenjoyably recursive quite quickly unless everyone uses headphones.
*   Being weird is positively fine and I don't think you have a limited budget to spend, you can just be super weird. But if you're too loud and **if people are having a bad time because of your presence, a moderator will remove you from the rooms.**

I've made a few basic rooms. If you've not visited before or need some help, enter the tutorial room. Here's the first:

Please leave the tutorial room once you've solved your problems, to make space for others.

And here are the hangout rooms.

*   [Taking Joy in the Merely Real](https://hubs.mozilla.com/gggwqWd/)
*   [Many Worlds Interpretation](https://hubs.mozilla.com/WRYAGjB/many-worlds-interpretation/)
*   [In Favour of Niceness, Community, and Civilization](https://hubs.mozilla.com/aZxp2BF/twin-stable-zone)

Extra rooms in case you want them for whatever reason:

*   [Don't Touch the Floor](https://hubs.mozilla.com/sBVaege/don-t-touch-the-floor/)
*   [Slack and the Sabbath](https://hubs.mozilla.com/765zpPv/slack-and-the-sabbath/)
*   [Beyond the Reach of God](https://hubs.mozilla.com/uC6FNvT/beyond-the-reach-of-god/)

For anyone who has trouble with the Mozilla Hubs setup, we also have a backup Discord server that you can join [here](https://discord.gg/vbwYk8).
# Would Covid19 patients benefit from blood transfusions from people who have recovered? 

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.
# Resource for the mappings between areas of math and their applications?

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
# Why do we have offices?

Also:
- Why do we have in person talks?
- Why do people prefer live events?

They seem expensive, and not useful for jobs that can apparently be done remotely.

h/t Matthew Barnett for making me wonder

Followup question: how can we translate those benefits to remote work?
# What happens in a recession anyway?

I know the technical definition of a recession- a GDP contraction lasting at least two quarters- but do not have a satisfactory answer as to what _happens._

A non-exhaustive list of the kinds of consequences I'm thinking of, sometimes including references, which are intended to be suggestive not definitive:

*   How do employment and wages change?

*   How does it vary by demographics and industry

*   Does life expectancy go up or down?

*   For [which demographics](https://www.theatlantic.com/health/archive/2012/11/how-the-recession-improved-life-expectancy-but-didnt-make-us-healthier/265401/)?
*   Changes in [suicide specifically](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4473496/)?

*   Which good become cheaper? Which [more expensive](https://en.wikipedia.org/wiki/Inferior_good)?
*   How does mobility change?
*   How do social norms change?

*   Church attendance?
*   Sexual and romantic norms?

*   Marriage rates? Divorce rates?

*   [Child rearing patterns](https://scholars.unh.edu/cgi/viewcontent.cgi?article=1230&context=carsey)?
# How will this recession differ from the last two?

My model is that the last recession (2008) was essentially financial in nature- a bunch of wealth was destroyed on paper but we lost no productive capacity. The 2002 recession was similar- most of what happened was revealing that things were valueless, rather than destroying value.

I expect this recession to be different, because it stems from an actual decrease in the availability of labor (although it's still subject to demand spirals stemming from that). I'd expect it to have more in common with the 1972 oil embargo (on which I can find zero books), which was also a sudden decrease in the supply of a crucial production component. How will the supply shock nature change the consequences of the recession? Or am I wrong that this one will be different at all?

  

Note: These questions are intended to provoke more [babble](https://www.lesswrong.com/posts/i42Dfoh4HtsCAfXxL/babble) than [prune](https://www.lesswrong.com/s/pC6DYFLPMTCbEwH8W/p/rYJKvagRYeDM8E9Rf). But even the babbliest thing should be presented such that other people can build on it. So if you have a prediction, please share the reasoning or data behind it as well.
# What will happen to supply chains in the era of COVID-19?

[Bucky](https://www.lesswrong.com/posts/owk7eBzwjPHNQbNeL/what-will-the-economic-effects-of-a-3-week-quarantine-be-3?commentId=rpM3LWksq9FrzDQKJ) and [skybian](https://www.lesswrong.com/posts/owk7eBzwjPHNQbNeL/what-will-the-economic-effects-of-a-3-week-quarantine-be-3?commentId=S4vJnBLFCvw2GbHkJ) both asked questions about how COVID-19 and associated shutdowns will affect supply chains. This is a question just to discuss that. I'm interested anything from "observations of very concrete things that have already happened in China" to "speculation about weird counterintuitive effects" to "here are some facts about supply chains in general".

Like the parent question, this is intended to provoke more [babble](https://www.lesswrong.com/posts/i42Dfoh4HtsCAfXxL/babble) than [prune](https://www.lesswrong.com/s/pC6DYFLPMTCbEwH8W/p/rYJKvagRYeDM8E9Rf). But even the babbliest thing should be presented such that other people can build on it. So if you have an idea, please share the reasoning or data behind it as well.
# What are some good / fun / informative treatises on good governance?

Like many of us, I find both (1) an unusual amount of time on my hands to read and (2) a renewed interest in systems of governance which lead to competent collective decision-making.

I honestly haven't read much in this sphere. I was hoping for something which is to, say, political science as _Thinking, Fast and Slow_ is to psychology and rationality: something that is interesting, gives me a good notion of some big problems, which is probably partly wrong, but remains nevertheless informative.

Although I'd be yet more interested which is to political science as, say, CFAR's handbook is to rationality: an attempt to both identify problems and provide means by which they could be solved. A kind of compressed, economically aware, game-theoretically involved, historically anecdoted look at ways of governing and trying to fix classical problems of malice and incompetence within government.

I know the question has a hopeless scope; any suggestions welcome.
# Blog Post Day II Retrospective

Saturday was [Blog Post Day II](https://www.lesswrong.com/posts/FredSMMXc77kMAquA/blog-post-day-ii). It wasn't as good as [Blog Post Day](https://www.lesswrong.com/posts/q972DHxCwZKFbEPMn/blog-post-day-unofficial). However, I'm still glad I did it.

To my knowledge six people wrote posts for Blog Post Day II. However, only one person (Ben Pace) [finished on time and posted on LW](https://www.lesswrong.com/posts/w2oBQ8sZJdSiiMexJ/small-comment-on-organisational-disclaimers). One other person (myself) took an extra two days [to post](https://www.lesswrong.com/posts/sD6KuprcS3PFym2eM/three-kinds-of-competitiveness), because I wanted to get feedback from some friends. Interestingly, both Ben and I didn't write the posts we originally intended to write; we gave up on those and switched to our Plan B's instead.

The remaining four people seem to have mostly made good progress, even finishing their posts, but they are either posting elsewhere (I don't know where) or saving up their drafts to post later as part of a sequence.

This is about 75% as much participation as we had last time. I'm thinking I should do these less frequently than every month. I'll do the next one in 2-3 months probably. If you want it to happen sooner, say so! These things exist to serve the public interest, so if you are interested, make it public.
# What are the costs, benefits, and logistics of opening up new vaccine facilities?

In [this comment](https://www.lessestwrong.com/posts/wFTRgeaq5wceEfb2X/lesswrong-coronavirus-agenda#9gzrdmKELqKiAjEnd) on the parent question, David Manheim makes the case for building new vaccine production facilities before we have a vaccine ready to produce, and for this to be subsidized. I find this question interesting in its own right, but it's also an opportunity to dig into the nitty-gritty of producing something, which I wish happened more on LessWrong. I don't expect this to lead directly to a vaccine facility coming into existence- presumably the people who have the power to do that already have access to the knowledge as well- but I think it's a useful exercise in how things actually get done.

To recap, David's argument as I understand it is:

*   The world is under-capacity for vaccines as it is
*   Building a vaccine production facility takes a lot of time and money, so we need to start funding and building them now to have them ready when we have candidates ready.
*   We're likely to want to mass-produce multiple vaccines until we know which ones work the best, increasing the amount of capacity needed.

There's already a great discussion of this in the replies to his thread, and I encourage you to read it before commenting here. Some questions that came up in that discussion:

*   Is there such a thing as a generic vaccine production facility, or do different vaccines require different facilities?
*   What raw materials (e.g. sterile eggs) are we also likely to need large quantities of, and should perhaps start sourcing now?

Some additional questions I have are:

*   Are there costs besides the obvious financial ones to building these facilities ahead of time? Are they competing for a resource we need more elsewhere?
*   Who does have the power and knowledge to make these facilities?
*   What are some historical equivalents?
# April Coronavirus Open Thread

[Last month’s Coronavirus Open Thread](https://www.lesswrong.com/posts/ACyGvQchWzGjGkKgS/coronavirus-open-thread) did a fantastic job at being a place for coronavirus-related information and questions that didn’t merit a top level post, but at almost 400 comments, many of which were great at the time but are now obsolete, it’s getting a little creaky. So for the next month (probably. Who knows what’s going to happen in that month) this is the new spot for comments and questions about coronavirus that don’t fit anywhere else and aren’t worth a top level post.

Wondering what happened in [last month’s thread](https://www.lesswrong.com/posts/ACyGvQchWzGjGkKgS/coronavirus-open-thread)? Here are the timeless and not-yet-eclipsed-by-events highlights:

*   Spiracular on why SARS-Cov-2 is [unlikely](https://www.lesswrong.com/posts/ACyGvQchWzGjGkKgS/coronavirus-open-thread?commentId=JF9K87MRYGBMekpBw) to be lab-created.
*   [Two](https://github.com/midas-network/COVID-19/tree/master/parameter_estimates/2019_novel_coronavirus) [documents](https://docs.google.com/document/d/1QdoCEXmZqj_4ptywXOKFe8I8rS6ijveqvdYXWT1quQI/edit#) collating estimates of basic epidemiological parameters, in response to [this thread](https://www.lesswrong.com/posts/ACyGvQchWzGjGkKgS/coronavirus-open-thread?commentId=37MRQmvJRcRbua2dS)
*   [Discussion](https://www.lesswrong.com/posts/ACyGvQchWzGjGkKgS/coronavirus-open-thread?commentId=QS4jzrzWZuMNAmor9) on whether the tuberculosis vaccine provides protection against COVID-19.
*   [Suggestive evidence](https://www.lesswrong.com/posts/ACyGvQchWzGjGkKgS/coronavirus-open-thread?commentId=TSP5KNPxnSZRM8Sai) that COVID-19 removes sense of taste and smell.
*   [Could](https://www.lesswrong.com/posts/ACyGvQchWzGjGkKgS/coronavirus-open-thread?commentId=DJKvarDrYGYo9gWz5) copper tape be net harmful?

Want to know what’s coming up in the future? Check out the [Coronavirus Research Agenda](https://www.lesswrong.com/posts/wFTRgeaq5wceEfb2X/lesswrong-coronavirus-agenda) and its related questions.

Wondering why the April thread is going up on 3/31? Because everything’s a little more confusing on 4/1 and I didn’t want the extra hassle.
# Outperforming the human Atari benchmark

I haven't paid much attention to Atari in a long time, and so would appreciate takes from anyone who follows this more closely. My take:

A single architecture that can handle both the games that require significant exploration, and the games that require long-term credit assignment, and the 'easy' games, without tricks or expert performance, seems like an achievement to me. The main question then becomes "does it scale out of the simulator to problems we care about more than Atari?"

What does it use? It looks like it's a lot of 'engineering improvements' and data. That is, lots of approaches will have tons of small components that are set to some simple default. You need to explore, so you use the simplest possible method of exploration, which is every action you roll a die and epsilon percent of the time you take a random action. Of course you could do better if you thought about it more, but there are many places like that in the code, and 'thinking about it more' requires both developer effort and compute (which, since the efficiency of the whole thing depends on how much compute it can spend, might mean you're spending dollars to earn cents if you use a fancy method where a simple one would do).

That is, this doesn't look like a radical new competitor to DQN; this looks like DQN after five years of iteration and testing, where some defaults are swapped to fancier settings and others aren't, and thus is updating me a little upward on the importance of engineering and data as an input factor.

They say this isn't the end of Atari research:

> This by no means marks the end of Atari research, not only in terms of data efficiency, but also in terms of general performance. We offer two views on this: firstly, analyzing the performance among percentiles gives us new insights on how general algorithms are. While Agent57 achieves strong results on the first percentiles of the 57 games and holds better mean and median performance than NGU or R2D2, as illustrated by [MuZero](https://arxiv.org/abs/1911.08265), it could still obtain a higher average performance. Secondly, all current algorithms are [far from achieving optimal performance](https://arxiv.org/abs/1908.04683) in some games. To that end, key improvements to use might be enhancements in the representations that Agent57 uses for exploration, planning, and credit assignment.
# What achievements have people claimed will be warning signs for AGI?

In MIRI's March newsletter, they link [this post](https://www.technologyreview.com/s/615264/artificial-intelligence-destroy-civilization-canaries-robot-overlords-take-over-world-ai/) which argues against the importance of AI safety because we haven't yet achieved a number of "canaries in the coal mines of AI". The post lists:

*   The automatic formulation of learning problems
*   Self-driving cars
*   AI doctors
*   Limited versions of the Turing test

What other sources identify warning signs for the development of AGI?
# A quick and crude comparison of epidemiological expert forecasts versus Metaculus forecasts for COVID-19

Katherine Milkman on Twitter notes how far off the epidemiological expert forecasts were in the linked sample:

[https://twitter.com/katy_milkman/status/1244668082062348291](https://twitter.com/katy_milkman/status/1244668082062348291)

They gave an average estimate of 20,000 cases. The actual outcome was 122,653 by the stated date in the U.S. That's off by a factor of 6.13, and those were experts. Only 3 out of 18 survey respondents managed to get the actual outcome to fall in their 80% confidence interval. If they were perfectly calibrated on this one-off prediction, about 14 should've had the actual outcome fall in their 80% confidence interval. EDIT: No that's not right; Daniel Filan points out that we wouldn't expect 14 of 18 to get it in their range. Error between users in a one-off forecast is often correlated.

I was curious how this compares to the Metaculus community forecast (note: not the machine learning fed one, just the simple median prediction). Unfortunately the interface doesn't tell me the full distribution at date x, it just says what the median was at the time. If the expert central tendency was off by a factor of 6.13, how far off was it for Metaculus?

I looked into it in this document:

[https://docs.google.com/document/d/1TcG1gceeVgimr8lBTCAYUscOt_ADyuSpdmt1d6Scve8/edit?usp=sharing](https://docs.google.com/document/d/1TcG1gceeVgimr8lBTCAYUscOt_ADyuSpdmt1d6Scve8/edit?usp=sharing)

Sadly a direct comparison is not really feasible, since we weren't predicting the same questions. But suppose if all predictions of importance were inputted into platforms such as the Good Judgement Project Open or Metaculus. Then making comparisons between groups could be trivial and continuous. This isn't even "experts versus non-experts". The relevant comparison is at the platform-level. It is "untrackable and unworkable one-off PDFs of somebody's projections" versus proper scoring and aggregation over time. Since Metaculus accounts can be entirely anonymous, why wouldn't we want every expert to input their forecast into a track record? That would make it possible to find out if the person is a dart-throwing chimp. You should assume half of them are.
# Call for volunteers: assessing Kurzweil, 2019

**EDIT**: To help assessing, go [here](https://www.lesswrong.com/posts/GhDfTAtRMxcTqAFmc/assessing-kurzweil-s-1999-predictions-for-2019). Cheers!

Many years ago, I helped organise [an assessment of Kurzweil's predictions for 2009](https://www.lesswrong.com/posts/kbA6T3xpxtko36GgP/assessing-kurzweil-the-results), in his 1999 book ["The Age of Spiritual Machines"](http://en.wikipedia.org/wiki/The_Age_of_Spiritual_Machines). The results were mixed - I feel he had a decent track record, but it was much worse than his own self-evaluation:

![](https://www.dropbox.com/s/elzb0bmcus3fkjj/assessing_kurzweil.png?raw=1)

Following Gwern's [suggestion](https://www.lesswrong.com/posts/kbA6T3xpxtko36GgP/assessing-kurzweil-the-results?commentId=4aeLHSwG7EfRctKnz), let's do the same for his 2019 predictions.

Since many people have extra time on their hands, for some odd reason, I'm asking for volunteers to do this assessment. You'll be getting a certain number of predictions (how many is up to you) and giving an assessment of their correctness on a five point scale of "True", "Weakly True", "Cannot Decide", "Weakly False", and "False".

So, add a comment here if you'd like to volunteer for this assessment, or know a person/group who might want to.

Cheers!

**EDIT**: I've now split Kurzweil's 2019 predictions into 105 separate individual predictions.
# What is the subjective experience of free will for agents?

Jessica recently wrote about [difficulties with physicalist accounts of the world](https://www.lesswrong.com/posts/my5pbcmQPb6ASSHYM/puzzles-for-physicalists) and [alternatives to logical counterfactuals](https://www.lesswrong.com/posts/yBdDXXmLYejrcPPv2/two-alternatives-to-logical-counterfactuals). In my recent post about the deconfus[ing human values research agenda](https://www.lesswrong.com/posts/k8F8TBzuZtLheJt47/deconfusing-human-values-research-agenda-v1), [Charlie left a comment](https://www.lesswrong.com/posts/k8F8TBzuZtLheJt47/deconfusing-human-values-research-agenda-v1?commentId=WK5hKMNaPRvCpFSpQ#comments) highlighting that my current model depends on a notion of "could have done something else" to talk about decisions.

Additionally, I have a strong belief that the world is subjectively deterministic, i.e. that from my point of view the world couldn't have turned out any other way than the way it did because I only ever experience myself to be in a single causal history. Yet I also suspect this is not the whole story because it appears the world I find myself in is one of many possible causal histories, possibly realized in many causally isolated worlds after the point where they diverge (i.e. a non-collapse interpretation of quantum physics).

So this leaves me in a weird place. When thinking about values, it often make sense to think about the downstream effects of values on decisions and actions and in fact many people try to infer upstream values from observations of downstream behaviors, yet the notion of "deciding" implies there was some choice to make, which I think maybe there wasn't. Thus I have theories that conflict with each other yet seek to explain the same phenomena, so I'm confused.

**Seeking to see through this confusion, what are some ways of reconciling both the experience of determinism and the experience of freedom of choice or free will?**

Since this has impacts on how to think about decision theory, my hope is that people might be able to share how they've thought about this question and tried to resolve it.
# What should you do regarding footwear to protect against COVID-19?

From [\[Effectiveness of personal protective measures in prevention of nosocomial transmission of severe acute respiratory syndrome\]:](https://www.ncbi.nlm.nih.gov/pubmed/15061941)

"Univariate analysis showed that mask, gown, gloves, goggles, footwear, "hand-washing and disinfecting", gargle, "membrane protection", "taking shower and changing clothing after work", "avoid from eating and drinking in ward", oseltamivir phospha tall had protective effects (P < 0.05), but stepwise logistic regression showed significant differences for mask (OR = 0.78, 95% CI: 0.60 - 0.99), goggles (OR = 0.20, 95% CI: 0.10 - 0.41) and footwear (OR = 0.58, 95% CI: 0.39 - 0.86). "

This paper is about protecting healthcare workers from infection with the old SARS which seems near to SARS-COV-2. Unfortunately, the main text is in Chinese so it's unclear to me what they did about footwear that was effectful.
# Mask wearing: do the opposite of what the CDC/WHO has been saying?

So the standard advice has been not to wear surgical masks if you have no symptoms, justified by the two mutually contradictory arguments uttered in the same breath: "they don't help" AND "healthcare workers need them". Well, it turns out that surgical masks don't help much in a hospital setting, where there is a high concentration of virus-containing aerosol, and N95 respirators or even more stringent protective equipment is needed. On the other hand, the community transmission is much more likely through droplets and surface contact, something where masks are likely to be effective against, especially to avoid infecting others, together with washing hands, disinfecting surfaces and social distancing. Goggles might be a good idea, too, to avoid accidentally touching one's eyes. In retrospect, that was pretty obvious, but hindsight is, well, 2020.
# How credible is the theory that COVID19 escaped from a Wuhan Lab?

It sounds like a conspiracy theory. Apparently, it's big on the Chinese Internet.

[https://www.econjobrumors.com/topic/chinese-internet-thinks-patient-zero-was-a-grad-student-at-the-wuhan-lab](https://www.econjobrumors.com/topic/chinese-internet-thinks-patient-zero-was-a-grad-student-at-the-wuhan-lab)

which links

[https://www.youtube.com/watch?v=bpQFCcSI0pU](https://www.youtube.com/watch?v=bpQFCcSI0pU)

The details in the video are rather vague since I don't speak Chinese I have trouble evaluating its credibility. What do you think?
# How About a Remote Variolation Study?

Robin in [Variolation May Cut Covid19 Deaths 3-30x](http://www.overcomingbias.com/2020/03/variolation-may-cut-covid19-deaths-3-30x.html):

> Just as replacing accidental smallpox infections with deliberate low dose infections cut smallpox deaths by a factor of 10 to 30, a factor of 3-30 is plausible for Covid19 death rate cuts due to replacing accidental Covid19 infections with deliberate small dose infections.

> \[...\] Systematic variolation experiments involving at most a few thousand volunteers seem sufficient to get evidence not only on death rates, but also on ideal infection doses and methods, and on the value of complementary drugs that slow viral replication (e.g., remdesivir). \[...\] A small early trial could generate much useful attention and discussion regarding this strategy

Zvi in [Taking Initial Viral Load Seriously](https://www.lesswrong.com/posts/3ArEA7tHDXQxE6PED/taking-initial-viral-load-seriously):

> My prior at this point is that the difference between a low and high initial viral load of Covid-19 is large. \[...\] That difference is a really, really big deal. It’s a much bigger deal than getting enough ventilators. It’s potentially a bigger deal than having a medical system at all.

> \[...\] The more I think about the Covid-19 situation, the more I think the highest leverage thing most people reading this can do is to find ways to get our hands on better data.

  

Right now we are all very keen to know the values of X and P in this statement:

**"If you have an X% risk of infection with a large inoculum in the next month, you should deliberately infect yourself now with a small inoculum via protocol P"**

  

The following are sufficient for many people to undertake variolation for themselves and their loved ones:

A. An easy variolation protocol

B. Proof that variolation works to reduce COVID hospitalization rate 3x+

  

What we're missing right now:

1\. A few plausible ideas for variolation protocols

2\. A study where 10k volunteers try the various protocols, then get tested for how large of an inoculum they got (data on the variolation protocols), then report their outcomes (data on variolation itself)

  

Does anyone have any ideas for #1?

  

For #2, a **remote study** on thousands of volunteer heroes self-variolating from within their current self-quarantines (isolated from all non-volunteers) seems like the fastest and cheapest way to get initial data.

This doesn't necessarily have to be a "Scientific" study. It can be a crowdsourced, crowdfunded movement. The data will be lower quality than scientific-study data, but higher quantity. We could plausibly get 100k volunteers' worth of data on variolation protocol design and variolation effectiveness.

How about a remote variolation study?
# Research on repurposing filter products for masks?

A local organization is looking to produce masks for the hospital, and they reached out to me for guidance. Since this is outside of my expertise and I haven't been following all of the recent research, I'm passing the questions along here.

> We are looking for some valid research on the use of commercial products for face masks. We have a couple of designs that can fit over or have  a pocket to insert an additional filter. I have found multiple sources online that refer to furnace filters, air filtration system filters, even HEPA vacuum bags, as ideal products to use to either completely comprise a face mask or be inserted into a pocket between layers of fabric to provide extra protection. 

> My questions are:

> •	Which of these products are or are not safe to be breathing through? The only caution I have found is to be careful to check for fiberglass in the content.

> •	Which are most effective, or does it come down to the MERV/MRP rating? We have been looking at filters at MERV 13-16 and/or MRP 2500-2800 in range. Are these safe as long as they can be breathed through?

> •	Can these types of materials be layered to provide extra protection i.e. is layering two ply of MERV 11 like a MERV 22 or is there a loss ratio? Is there a formula which can be applied?

> •	Could other materials be used to enhance the filter’s effectiveness, safety, smell, etc.? I have seen models that added an activated charcoal filter over the top, coffee filter, etc.? I have also heard that layers create a dispersion effect that increases the protective factor i.e. a thick bundled knitted scarf has a higher protective factor because of the density.

> There is so much out there but it is mostly DIY crafters, and I am interested in a more empirical opinion!