I was having an argument with a friend the other day. It went vaguely like this,
Friend: "I'm not very disciplined. At some point I'm going to buckle down and train myself to be much more disciplined."
Me: "From experience and from what I know about humans, that's not going to work."
Friend: "Why? Motivation can come from within. If you can just train yourself like you're in the army, then you can become just as self disciplined as a soldier."
Me: "Yes, but the reason why people in the military are disciplined is because they have social incentives to be. In order to become disciplined, you need to create an environment for yourself that shapes your motivation. You can't just wake up one day and become a soldier."
Friend: "Sure, you might have to set up some environment like that. But once you've trained yourself, the discipline will stick, and you will be able to self motivate yourself from then on."
Me: "This theory would predict that people who were trained in the military would be much more productive three years after their service, compared to people who were never trained in the military. Do you agree?"
Friend: "Yes, I think that is likely."
Me: "I disagree. They might be slightly more productive but I'd predict it would be pretty similar."
So who is right?
I haven't been able to find direct research, but this seems like a classic instance where a debate can be settled by simply referencing a high quality experiment.
Before the pandemic, Scott Alexander's short post reviewing a few correlational studies on gun ownership and violence left me feeling uncertain about the moral status of owning a home defense weapon. Times have changed though, and I suspect that there will be a larger risk of home invasion during the course of COVID-19's spread. Many people are buying guns and ammunition in what is likely preparation for this increased risk.
Assuming that I continue to own the gun after the inflated risk of home invasion due to COVID-19 decreases to a negligible level, should I buy a gun for home defense now?
Kinsa Smart Thermometer Dataset
Kinsa is a company that makes smart thermometers. A few years ago, they found that they could use the data that they got from their smart thermometers (most importantly the temperature reading and location of the user) to track flu trends across the United States. (FitBit has done something similar.)
Kinsa's data science team has now turned their attention to Covid-19 trends and started a tracking website using their thermometer data, using methods which they explain in more detail on their technical approach page. It looks like the most impressive thing that they've been able to do with this dataset so far is to identify new hotspots before other people do, like the increase in cases in southern Florida. But potentially there are a lot of other things that can be done with these sorts of data.Estimating the Number of Coronavirus Infections in the US
One of those other things which might be doable with these sorts of data: coming up with more accurate estimates of the number of people with coronavirus. Testing in the US (and many other places) is spotty and delayed a great deal, estimating the number of infections based on the number of deaths involves a very long delay and a bunch of assumptions, etc. But if you can count the number of people in America with a fever (or extrapolate from a sample), and subtract off the baseline estimate of how many fevers you'd expect from influenza or other causes, then you can get an estimate of the number of people in the US with a fever due to coronavirus. And that gets you close to an estimate of the total number of coronavirus cases.
The coronavirus tracking website that Kinsa set up is already doing much of this - their graph (also shown below) shows something like the number of people with a fever and the baseline expected number of fevers.
So I decided to give it a try and use their graph to estimate the total number of coronavirus cases in the US.
It's a fairly rough first-pass analysis, which may contain errors, and could definitely be improved with some more work. The number I got at the end is that about 1% of Americans have gotten coronavirus, through March 20.My Estimation Method, in Brief
The graph above shows something like "number of new fevers" (on an unclear scale labeled "% ill") and Kinsa's estimate of the expected number of fevers if there was no coronavirus. So the gap between the two lines represents something like the number of new fevers each day due to coronavirus. That trend has an odd shape for a pandemic: it increases and then levels off. I suspect that this is because, once people start taking precautions to avoid coronavirus, the number of flu cases drops dramatically, so their estimated baseline gets farther and farther from reality (of # of flu cases) and coronavirus accounts for a larger and larger number of the new fevers. You can view the regional trends by clicking on particular counties; regions like the SF Bay Area and Seattle have a similar shape on earlier days. The SF Bay Area is actually now anomalously below baseline in number of new fevers on March 21.
I decided to deal with this by focusing on the trend up until March 14, and extrapolating from there. (It would be even better to do this separately for each county and then aggregate them.)
Next step: making sense of the y-axis. A little bit of digging showed that it's from their flu work, where they used their data to fit a particular measure of flu prevalence that the CDC uses, which is ILINet data (explained partly down the page here). A little bit more digging on the relationship between this number and the number of flu cases reported by the CDC (as seen headlines like this) suggests that 1 point on the scale corresponds to roughly 75,000 new flu cases that day (which probably means about 75,000 new fevers). More detailed explanation of where that number comes from in my longer writeup.
So the gap of 0.79 scale points between observed and expected on March 14 corresponds to about 60,000 excess new fevers that day. Which we're guessing are entirely due to coronavirus. Using either their data for previous days, or assumptions about the growth rate in cases, we can turn that into an estimate in the cumulative total number of feverish cases as of that day. I tried both and got numbers of 470,000 and 370,000, so let's call it about 420,000 total cumulative cases through March 14.
But this is only counting the coronavirus cases that do get a fever, and (more importantly) it is only counting them when they get the fever. My guess is that a bit more than a doubling time passes between infection and fever, and also adjusting for the cases that never get a fever, the total number of coronavirus infections on March 14 was about 3x the number of feverish cases, or about 1.3 million.
Extrapolating forward assuming a 4-day doubling time gives an estimate of 3.6 million cases in the US through March 20, or 1.1% of the population.
So that's the basic method and estimate. The longer writeup goes into more detail about each step, and includes various things things I'm still confused or uncertain about and ways in which this analysis might be wrong. For instance, maybe concerns about coronavirus are causing people to take their temperature more often, which is sufficient to cause an increased number of measured fevers, and a large part of the upwards trend line is due to that rather than to actual coronavirus cases.
I'm interested in improving this estimate, or having other people go off and do their own estimate. And I'm especially interested in people finding more good things to do with this sort of dataset.
As part of the LessWrong Coronavirus Link Database, Ben, Elizabeth and I are publishing daily update posts with all the new links we are adding each day that we ranked a 3 or above in our importance rankings. Here are all the top links that we added yesterday (March 21st), by topic.Dashboards
Uses current data to show seasonal illnesses in the US, and indicates whether this is abnormal or expected. Oregon State University.DIY
Clear explanations of why you need oxygen, how the various devices work, links to open source projects for building them, etc.Guides/FAQs/Intros
List of 40 activities to do indoors that are cheap/free.
(BP) ClearerThinking always do things competently and well, and I think the list is genuinely good.Spread & Prevention
Lots of up-to-date info and good graphics. Centre for Mathematical Modelling of Infectious Diseases.Work & Donate
He claims they have a 114x return on donations. Donation page is mrelief.com/donate.Other
Short concrete outline of how it might happen. Briefly explains that the lockdown is not a likely path to authoritarianism, but instead that healthcare tracking could become necessary and go alongside location tracking in a way that becomes overpowered.Full Database Link
Petri Hollmén traveled to Tyrol on the 5th of March. He had a bottle of hand sanitizer with him, used it a lot and washed his hands like never before.
Sunday, the 8th he returned home to hear a day afterwards that Tyrol was declared a COVID-19 epidemic area. He decided to work from home given the higher risk of having been in an epidemic area. On Thursday the 12th he woke up feeling normal but his Oura ring measured that his readiness was down to 54 from being normally at 80-90 which was mostly due to having a 1°C elevated temperature at his finger at night.
Even though he felt normal, he went to the doctor and given that he was from an epidemic area, they decided to test him. He tested positive and went to self-quarantine for 14 days. He measured his temperature several times during the following day and it always came back with 36.5°C. The Oura ring provided evidence that led to his diagnosis that wouldn't have been available otherwise.
While he didn’t have true fever as defined by the official gold standard he did have a kind of clinical relevant fever. It’s my impression that our medical community is too focused on their gold standards that are based on old and outdated technology like mercurial thermometers.
Even when new measurements like nightly finger temperature don’t match with the gold standard there are still cases where the information allows for better clinical decision making.
Today, we have cheap sensors and machine learning that provide us with a different context of making medical decisions then going to the doctors office.
Testing by doctors is very important in the fight against COVID-19 but people need to know when it’s time to go to the doctor. Hollmén needed his Oura to know that it was time to get tested professionally.
We need to get good at catching cases of COVID-19 as fast as possible when they happen in the wild if we want to avoid that millions die without us choking our economy by long-term quarantines.
Analysis of Fitbit users found that their resting heart rate and total amount of sleep can be used to predict the official state numbers for influenza-like illness.
It’s very likely that lower heart rate variance and a higher minimum of the nightly heartrate happens in at least some of the COVID-19 cases. Unfortunately, the WHO is stuck in the last century and the official symptoms charts tell us nothing about how common either of those metrics are in COVID-19 patients. Lack of access to those metrics in the official statistics means it’s harder for people who have an Oura Ring, an Apple watch or another device that can measure nightly heartrate to make good decisions about when to go to the doctor or self-quarantine.
Given that Apple sold around 50 million Apple watches between 2018 and 2019, a sizable portion of people could make better decisions if we would have more information about how COVID-19 affects heart rate.
Even more people have access to a smart phone with a decent camera. Having a sore throat is a typical symptom for many virus infections like COVID-19 and a good machine learning algorithm could produce valuable data from those images.
A priori it’s unclear about how much we can learn from such pictures. If a throat of a patient is red due to inflammation a doctor who looks at it, can’t distinguish whether it’s due to snoring or a virus infection.
If a machine learning algorithm could have access to a steady stream of daily imagine of a person’s throat the algorithm could understand a person’s baseline and use that insight to factor out the effects of snoring.
When the gold standard of diagnosing the throat is to look at one image at a particular point in time at the doctor’s office there’s potentially a big improvement to be gained by looking at a series over multiple days. We don’t know how useful such a diagnostic tool is before building it.
Ideally, users of a new app would take an image of their throat every morning after getting up and every evening before going to sleep. They would also measure their temperature with a normal thermometer at both points and enter information about subjective symptoms. If a person gets a proper COVID-19 test, they should also be able to enter the data.
At first we would train the machine learning algorithm to use the images to predict temperature. With enough users our algorithm can learn how the throat of a person having flu differs from their baseline whether or not they are snoring.
As we have more users and some of our users get COVID-19 lab tests our machine learning algorithm can learn to predict the test results directly. It’s the nature of advanced technology that we don’t know how powerful a tool is before it’s developed. Most clinical trials for new drugs find that they don’t live up to their promise.
We need more dakka for COVID-19. Creating an app that does the above function doesn’t cost much and the cost of the project should be worth the potential benefits of catching COVID-19 cases faster and thus preventing people from unknowingly infecting their friends.
Biological global catastrophic risks were neglected for years, while AGI risks were on the top. The main reason for this is that AGI was presented as a powerful superintelligent optimizer, and germs were just simple mindless replicators. However, germs are capable to evolve and they are very extensively searching the space of possible optimisations via quick replication of viruses and quick replication rate. In other words, they perform an enormous amount of computations, far above what our computers can do.
This optimisation power creates several dangerous effects: antibiotic resistance (for bacteria) and obsolescence of vaccines (for flu) as well as a zoonosis: the transfer of viruses from animals to humans. Sometimes it could be also beneficial, as in the case of evolving in the direction of less CFR.
In other words, we should think about coronavirus not as of an instance of a virus on a doorknob, but as a large optimisation process evolving in time and space.
Thus, the main median-term (3-6 months) question is how it will evolve and how we could make it evolve in better ways. In other words, what will be the next wave?
There was a claim that second wave of Spanish flu was more dangerous, because of the large hospitals: the virus was “interested” to replicate in hospitals, so it produced more serious illness; Infected people had to go to hospitals, which were overcrowded after the war, and they infected other people there, including the medical personal which moved it to the next hospital.
Another point is that the size of the virus optimisation power depends on the number of infected and of the number of virus generations, as well as on the selective pressure. The idea of “flattening the curve” is the worst, as it assumes a large number of infections AND a large number of virus generation AND high selective pressure. Cruel but short-term global quarantine may be better.
Suppose I were to say that the American legal system is a criminal organization. The usual response would be that this is a crazy accusation.
Now, suppose I were to point out that it is standard practice for American lawyers to advise their clients to lie under oath in certain circumstances. I expect that this would still generally be perceived as a heterodox, emotionally overwrought, and perhaps hysterical conspiracy theory.
Then, suppose I were to further clarify that people accepting a plea bargain are expected to affirm under oath that no one made threats or promises to induce them to plead guilty, and that the American criminal justice system is heavily reliant on plea bargains. This might be conceded as literally true, but with the proviso that since everyone does it, I shouldn't use extreme language like "lie" and "fraud."
This isn't about lawyers - some cases in other fields:
In American medicine it is routine to officially certify that a standard of care was provided, that cannot possibly have been provided (e.g. some policies as to the timing of medication and tests can't be carried out given how many patients each nurse has to care for, but it's less trouble to fudge it as long as something vaguely resembling the officially desired outcome happened). The system relies on widespread willingness to falsify records, and would (temporarily) grind to a halt if people were to simply refuse to lie. But I expect that if I were to straightforwardly summarize this - that the American hospital system is built on lies - I mostly expect this to be evaluated as an attack, rather than a description. But of course if any one person refuses to lie, the proximate consequences may be bad.
Likewise for the psychiatric system.
In Simulacra and Subjectivity, the part that reads "while you cannot acquire a physician’s privileges and social role simply by providing clear evidence of your ability to heal others" was, in an early draft, "physicians are actually nothing but a social class with specific privileges, social roles, and barriers to entry." These are expressions of the same thought, but the draft version is a direct, simple theoretical assertion, while the latter merely provides evidence for the assertion. I had to be coy on purpose in order to distract the reader from a potential fight.
The End User License Agreements we almost all falsely certify that we've read in order to use the updated version of any software we have are of course familiar. And when I worked in the corporate world, I routinely had to affirm in writing that I understood and was following policies that were nowhere in evidence. But of course if I'd personally refused to lie, the proximate consequences would have been counterproductive.
The Silicon Valley startup scene - as attested in Zvi's post, the show Silicon Valley, the New Yorker profile on Y Combinator (my analysis), and plenty of anecdotal evidence - uses business metrics as a theatrical prop to appeal to investors, not an accounting device to make profitable decisions on the object level.
The general argumentative pattern is:A: X is a fraudulent enterprise.
B: How can you say that?!
A: X relies on asserting Y when we know Y to be false.
B: But X produces benefit Z, and besides, everyone says Y and the system wouldn't work without it, so it's not reasonable to call it fraud.
This wouldn't be as much of a problem if terms like "fraud", "lie," "deception" were unambiguously attack words, with a literal meaning of "ought to be scapegoated as deviant." The problem is that there's simultaneously the definition that the dictionaries claim the word has, with a literal meaning independent of any call to action.
There is a clear conflict between the use of language to punish offenders, and the use of language to describe problems, and there is great need for a language that can describe problems.
For instance, if I wanted to understand how to interpret statistics generated by the medical system, I would need a short, simple way to refer to any significant tendency to generate false reports. If the available simple terms were also attack words, the process would become much more complicated.
In January 2020 I did a zero content life. This was partly justified by the book “the info diet” but mostly based on a philosophy that proposes,in a lifetime with limited hours, there is a choice to either consume or create. And I’d rather create than consume.
To be honest, the idea for me was born in response to a meme complaining that if you think art should be free, try going without art for a month. This sounded like a fun and interesting idea.
My main sources of content were:
- Facebook feed
- Books (paper and TTS audiobook)
- Some music
- Youtube videos
I decided to not get fussy about content that I was actively reciprocal in creating. For example a dance form and a conversation are two different types of content that I am engaged in. The difference would be between playing sport and watching sport (I’m allowed to play sport but not watch sport). I wanted to make an exception for live music but I would not usually see live music anyway.
So how did I go?
On the 1st of January I rearranged my phone screen to make my content less accessible than my creation pathways. I don’t think I recorded anything, but in the first week I wrote 5000 words with all that time I had. In the silence I noticed my mind go quieter. In the time that I spent not reading, I did thinking. I drove places in silence. I started having phone calls with my friends. I just let myself go with whatever I wanted to go towards.
Without music coming in I started to get earworms appearing in my mind. Without content ideas coming from books I had to start generating my own, or applying my existing methods. Even making my own.
I didn’t realise how badly an entrenched habit of reading (134 books in 2019) could limit my growth. I was doing a good thing adding more information to the parts of me that needed more information and also, now that I’ve slowed down, I’m more balanced.
I probably only needed to do book free for a day to get the benefit but I committed and I wasn’t sure if there was a deepening after more time. There wasn’t but one of the major benefits I retained was that I freely chose to think or read a book or call a friend. This was previously a more compulsive choice to urgently read books.
I spend a lot more time having phone calls and exploring relationally now. For the handful of people that I am talking with, we are growing therapeutically together and healing each other as we reflect on our stuff together.
I read less, I talk more, I write more. I consider this experiment a success.
I am told that unsupervised machine translation is a thing. This is amazing. I ask: Could we use it to understand dolphin language? (Or whales, perhaps?)
I don't currently see a convincing reason why not. Maybe dolphins aren't actually that smart or communicative and their clicks are mostly just very simple commands or requests, but that should just make it really easy to do this. Maybe the blocker is that dolphins have such a different set of concepts than English that it would be too hard?
As people start coming into hospitals with the coronavirus, the number of masks we go through with standard protocols goes up enormously. These masks are normally single-use, and you put on a new mask every time one is needed. Roughly, a hospital could increase its daily usage of masks 100x as they get their first few covid-19 patients, and then even more as the full force of the epidemic hits. This is a ton of stress on the supply chain, and not surprisingly suppliers haven't been able to ramp up. Running your factory around the clock and bringing on extra workers can help some, but when even doubling output would be impressive this is nowhere near enough.
There are many types of mask, but the two main ones in health care are surgical masks and N95 respirator masks:
A surgical mask is primarily intended to protect others from the wearer by catching droplets, but provides limited protection to the wearer.
A vented N95 mask protects the wearer against not just droplets but also airborne transmission.
An unvented N95 mask protects both the wearer and others.
When I say "mask" below, I'm talking about N95 masks. We can get something to replace surgical masks, even if it's people sewing reusable cloth ones, but N95 production is bottlenecked on machines that can make good enough melt-blown fabric.
Luckily, health care is not the only field where people need respiratory protection. Industrial N95 masks are very widely used in construction, demolition, and other situations where there's moderately hazardous dust. These masks aren't rated as surgical N95 masks, and they're more likely to be vented, but their requirements are very similar and the government is now allowing them to be used.
As hospitals are unable to get resupplied with their regular masks, they're asking for donations from the community and industry. This makes a lot of sense: people and organizations that use masks generally keep extras, and medical use is now much more urgent.
On the other hand, donations of masks will not get us through this epidemic on their own: hospitals also need to make massive adjustments in how quickly they go through masks, and this is a hard adjustment. Reusing masks is moderately dangerous, but it's much less dangerous than the very likely prospect of later not having them at all. It looks like hospitals used masks at nearly their regular rate throughout February and in early March, even though the shortage goes back to late January. Reports of mask rationing are haphazard, and in the last couple days I've seen posts from health care workers saying they're using N95 masks:
- At their regular rate, but they're worried about running out.
- For aerosol-generating procedures on suspected patients only.
- One per day, only as needed.
- One indefinitely.
- Not at all, because there are no more.
Since most of this change in behavior is happening in response to masks being unavailable or in very short supply, mask production is hard to ramp up, and we don't expect this to peak for at least a month, if you donate masks today I expect them to be used much more quickly than if you wait and donate them when things are worse. You don't want to wait too long, because at some point the shortage really will be over and the need will decrease, but I expect the need for masks to be much higher in two weeks than it is today.
I saw some evidence from the recent covid-19 threads that some viruses permanently stay in the brain and cause some damage; This has made me wonder how effective (or alternatively unsafe) vaccines are (flu vaccines in particular).
Here is one study on h5n1 on mice:
Since I can't post an image in a comment I've created this post.
I've seen a fair bit written about digital oxymeters (pulse ox) and percentage figures but no mention of the underlying physiology to increase understanding of the significance of those figures.
Haemoglobin (in red blood cells) takes up oxygen in the lungs to then carry around the body.
Oxygen disassociates from haemoglobin (Hb) when the partial pressure of O2 in surrounding tissues is reduced according to this graph:
Note the steep drop in oxygen saturation (the % given by an oxymeter) when PO2 (level of oxygen in surrounding tissues) is low i.e. a lot of oxygen leaves red blood cells quickly at those levels so there isn't enough oxygen in the blood to get round everywhere.
SOURCE: (and much more info.)
- In Germany it is reported that more than 2 in 3 confirmed cases have anosmia.
- In South Korea, ... 30% of patients testing positive have had anosmia as their major presenting symptom in otherwise mild cases
- There is potential that if any adult with anosmia but no other symptoms was asked to self-isolate for seven days, in addition to the current symptom criteria used to trigger quarantine, we might be able to reduce the number of otherwise asymptomatic individuals who continue to act as vectors, not realising the need to self-isolate.
Simple clinical test for anosmia (from Davidson & Murphy, 1997):Standard 70% isopropyl alcohol preparation pad is opened such that 0.5 cm of the pad itself is visible. The alcohol pad is placed beneath the patient's nostrils while the patient inspires twice, to familiarize himself or herself with the alcohol odor, and the subject is asked if he or she detects an odor. Odor thresholds for alcohols are 2 or more orders of magnitude lower than trigeminal thresholds for the same stimuli.6 Thus, an anosmic will detect the presence of alcohol trigeminally only when it is extremely close to the nose. The alcohol pad is withdrawn and the threshold test begun. The subject is asked to close the mouth and eyes, breathe normally, and indicate when the odor is detected. Active sniffing and deep inspiration are discouraged. The basic procedure follows the method of limits. A standard metric tape measure is extended downward from the patient's nares and held in place (Figure I ). The alcohol pad is placed 30 cm below the nose and, with each expiration, is moved 1 cm closer to the nares until the subject detects the presence of odor. The distance from the anterior nares to the alcohol pad is measured in centimeters at the point at which the subject first detects the odor. The procedure is repeated 4 times and the mean distance defines the threshold. Threshold For purposes of comparison, all of the subjects completed a standard olfactory threshold test. A series of 10 concentrations of butanol ( -butyl alcohol) was used to determine absolute olfactory threshold sensitivity. The highest butanol concentration consisted of 4% vol/vol in distilled water. Each successive dilution was one third of the preceding dilution. Two "blanks," containing only distilled water, were also prepared. All bottles, including blanks, contained 60 mL of liquid. Olfactory threshold was assessed with a modified version 7 of a 2-alternative, forced-choice,ascending method of limits procedure. The subject was presented with 2 bottles, one containing the odorant and the other consisting of distilled water. Each nostril was tested separately. The spout of the bottle was inserted into the nostril of interest. The subject was asked to squeeze the bottle to generate a puff of air. The subject did this with both bottles. Subjects were asked to identify which of the 2 bottles contained the stronger odor.All subjects began at the lowest concentration to avoid adaptation.9 Incorrect choices led to presentation of a higher concentration and correct choices led to continued presentation of the same concentration to a criterion of 5 successive correct responses. The presentation of the odorant and blank were randomized for each comparison trial and the nostril to be tested first was also randomly determined. There were approximately 45 seconds between trials to allow time for recovery of the olfactory system and for the odor molecules to collect in the head space of the bottle.
The Coronavirus Tech Handbook is a crowdsourced collection of tools, websites and data relating to the coronavirus outbreak.
If you are working on something to prevent or mitigate the Coronavirus pandemic, this might be a good place to share information and find collaborator. There is also a facebook group for discussions, and a newsletter.
I'm not involved in this but I know the people who built the Coronavirus Tech Handbook. I be happy to put you in touch with them, or forward any feedback.
If you know of anything you think should be added to the Coronavirus Tech Handbook, but are to busy/lazy/whatever (no judgement) to add it yourself, pleas tell me and I'll add it for you.
I have not followed the corona related discussion here on LW so I don't know what projects you've been up to here.
A key question for people figuring out good longterm isolation practices is "how long do I have to be symptom-free before I'm 'certified safe'?"
This post on the typical-course-of-COVID-19 provides some studies that inform on the question, but doesn't directly answer it yet.
I recall hearing something like "most cases last less than two weeks", but I'm not sure if two weeks is actually a strong enough upper bound that I'd feel comfortable encouraging lots of people to act on it.
A couple weeks back, as coronavirus content took over LessWrong, we thought "Hmm, so... we've almost finished this new tagging feature. Maybe we should hurry to finish that up so that we can use it to help manage this avalanche of COVID-19 posts?"
For the past week we've been rolling out features to help with this. Right now, since Tagging is still in beta, we're testing it out just with a Coronavirus tag.1. You can now filter out Coronavirus-tagged posts from the Home Page.
If you click the gear icon to the right of the "Latest Posts" section, you'll open up a settings tab where you can test the new tag filtering system. You can currently filter on Personal Blogposts, and Coronavirus-tagged posts. You can choose to hide them, or to only show posts with a matching tag. (Later on, once we've implemented a wider-ranging tag system, you'll be able to filter arbitrary combinations of tags).
Right now the filter system only applies to the Latest Posts section, but soon we'll most likely extend this to the Recent Discussion section and the "/allPosts" page.2. Home Page Coronavirus Section
We've also recently added a section at the top of the home page which displays the top 3 posts on the Coronavirus Tag Page. We found that we wanted more than one stickied post, to keep multiple conversations going on the Justified Advice Thread, Open Thread, and Link Database, and other important posts we wanted people to be able to keep track of.
But! If you are sick of CV content, you can open up the gear-icon in the Recommendations section, and hide Top Coronavirus Content widget.
Meanwhile, it you want all the CV content...3. There's a Coronavirus Tag Page!
If you want to catch up on all the COVID-19 content, it's all available over at https://www.lesswrong.com/tag/coronavirus.
Currently, only admins can add a tag to a post. But all users can upvote or downvote the relevance of a tag to a particular post. On the Tag Page, you'll see a little vote button to the left of the karma. Voting affects the post's Tag Relevance Score, which determines the sort order on a tag page.
(It's fine to be a bit more strategic about how to upvote or downvote on tag-relevance. The goal is not to determine "how good is this post overall?" but "how high on the tag page should the post appear?". The system is designed so that the collective decision-making of the LessWrong userbase can output a pretty good set of "top posts" that new users see when they first come to the page, or when glance at the Tag Hover Preview.)4. Beta Feedback, Upcoming Features
What sort of additional features would you like for Tags, or for Coronavirus content in particular?
Some features we're currently considering include:
- Better sorting and filtering on the tag page (in particular, being able to see all Coronavirus un-resolved questions)
- Possibly including a "Recent Discussion" section for the Tag page.
- Subscribing to a tag, so you're alerted to all new posts with that tag.
Two years ago, I would have proclaimed a cautious bias towards thinking religion is a bad idea.
Since then, having read a bunch of “religious” philosophers and observed a bunch of “religious” people, I came to the conclusion that “religion” is a term I will start shying away from using at all, because it’s ill defined. It encompasses too many ideas to be a useful point of discussion.
As a specific example, let’s look at Sunni Islam and some things most people would probably like and dislike about it:
1. I once visited Burj Khalifa and was told that the highest livable floor in the building (158) is dedicated to a mosque. (Googling this fact I find claims that it’s an urban myth, but I can’t find strong evidence one way or another. For the purposes of this article let’s assume the tour guide wasn’t lying).
I find this to be a very nice thing. Here you have the tallest building in the world and you could sell the top floor for billions of dollars, or have it be the king’s apartment, or show it off to important officials to brag and to flatter them… but instead you decide to build a place of worship.
It’s the sort of act that says “Yeah, we made this awe-inspiring thing, but we really owe it to thousands of of past generations. None of us can fully comprehend how we managed to do this, so let’s dedicate its highest floor to something transcendent, something that symbolizes the beautiful, impossible and absurd experiment that made it possible, our society”.
It’s the sort of thing I like about the Catholic faith or any other faith when I walk into their places of worship, adorned in such beauty that they really make you stop, calm down and contemplate in awe and wonder.
2. On 11-9-2001 a group of Sunni terrorists decided that Americans were the worst possible evil and that harming them and their country is an act so moral and just that it’s worth dying for.
This is the kind of action born out of an ethical smugness that even I can’t comprehend, and I’m quite an ethically smug person.
It’s thinking that you can be so right as to warrant doing an action which will be viewed as horrible by most of the world, but completely disregarding their opinion because you obviously have it right.
It’s the same kind of thing I dislike about an atheist SS officer murdering hundreds of Jews because he is certain his normally atrocious action serves “the greater good”.
3. Avicenna deciphered and translated old texts in order to better learn what dozens of generations before him thought about the world.
He observed, poked and prodded the world around him to learn its mysteries. He generated knowledge which was so precious it was taught in medical schools around the world more than half a millennium after his death.
He did this, as far as I understand, partially because of some mystical ideas about the will of God for man to master and understand his creation. I admire Avicenna for basically the same reasons I admire Francis Bacon or Richard Feynman or Alan Turing.
4. Avicenna spent most of his life writing nonsense about his interpretation of old religious texts. Coming up with unfounded and useless systems to explain the soul. Producing a bunch of work that are illogical and childish.
His quest to say something relevant about metaphysics is as irrelevant to anything we have today as those of Thales or Bostrom.
Out of this he gathered up a bunch of ideas about man’s purpose in life and ethics which are pointless at best and harmful at worst.
I dislike Avicenna for basically the same reasons I dislike Thomas Aquinas: he wasted his life and added pointless mental fluff to the zeitgeist, which materialized into nothing.Questions that need not be asked
There are questions which need not be asked, that is simply because they are ill-phrased, so answering them is just going to result in you playing around with words until you’ve convinced your brain that you found and answer or embedded them into your mind so much that they seem “sacred”.
The basic example of this is the whole “If a tree falls in a forest and nobody hears it, does it make a sound ?”.
This question has 4 ways of answering it:
- Thinking about it for 10 years, coupled with deep meditation and becoming “enlightened”
- Do you mean “sound” as in “someone hearing something” or do you mean “sound” as in “acoustic vibrations being transmitted through the earth and air starting at the points of impact” ?
See more on this here.
Out of those answers “4” is correct.
This is basically the case with all “grand” questions:
- What is the meaning of life ?
- Does God exist ?
- Is there free will ?
Deconstruct these questions and you will soon find out that they are ill posed. Once you try to further refine the terms in order to get to an answerable question you reach a very simple answer to a bunch of separate questions.
Those questions contain terms that upon further inspection are impossible to define (e.g. “free will”, “God”) or terms incompatible with one another (e.g. “meaning”, “life”).
- “What is the meaning of life” is as nonsensical as saying “Is it honorable to drink high-PH water ?” or “Are neutrons afraid of bees ?”
- “Does God exist ?” can mean “Is there an absolute system of morality we should bide by ?”, “Is there something more powerful than humans out in the universe ?”, “Is there an invisible all-powerful man in the sky ?”, “Are we living in controlled a simulation ?”, “Does our consciousness transcend death ?”.
- “Is there free will ?” relies on a term so ill-defined it’s like asking “Can magrugleblegs eat bloxorgs ?” Try imaging the difference between a world where “ free will” exists versus one where it doesn’t … or read Avicenna or 101 other philosophers who wasted their time trying to define the term.
In the end, spending too much time answering questions that cannot be asked can lead down two paths.
Path number one is writing a bunch of philosophy and/or religious books, ending up being very uncertain about your answer and only being able to explain it in a format longer than the one required to understand all of modern physics.
Path number two leads to the mind tricking itself into thinking the answer existing and is certain, which leads to the kind of self-assured megalomania that can cause you to fly planes into towers in order to reach the kingdom of eternal bliss, or to torture and rape young single mothers because that is the only way their sins can be absolved (Hi, Irish Catholic Church!).
It’s like feeding code into a compiler, getting the compiler stuck in an infinite loop and, instead of pressing ctrl-C, waiting forever for an answer or getting an OOM error and interpreting that as the compiled code.
This is what I now assume I hate about religion.
You have people wasting their time and other’s people resources shoveling air in order to find a treasure.
You have people wasting their time and other’s people resources (and sometimes life and well-being) because they reached a nonsensical answer which they consider to be the absolute truth.
Both of these things might stem from trying to answer these “trick” questions.
This pattern is by no means sequestered to religion, however. It’s just that most of the questions seem to fall under the umbrella of religion.
But go to the opposite end of spectrum and look at something like the “rationalist atheist” community and you’ll basically find the same pattern. A bunch of people assuming an air of smugness because they think they’ve found an unshakable moral truth and a bunch of people wasting their time thinking about ill-phrased questions, just replacing “God” with “a simulation” or replacing “repenting for the end times” with “handling AI risk”.
Indeed, go to the extreme end of any movement, be it a far-right cult, a progressive propaganda machine, a libertarian echo chamber or a communist party… and you find the same pattern. A combination of “philosopher” getting trapped by unanserable questions and spouting nonsense and fanatics convinced they have the absolute moral truth and committing acts of violence and hate because of it.
But that part of me is likely wrong. I’d be a hypocrite if I thought otherwise since a long time spent on these kind of questions is what got me to where I am… and I kind of enjoy the place where I am mentally. It feels cozy and happy and the ideas I’m able to generate from it, whilst almost certainly not yet useful for almost anything, at least feel to me like “the kind of things which I will be able to develop into useful works of engineering if I refine them for long enough”.
You can argue that Avicenna could have spent all his time researching medicine and astronomy and none looking into the nature of “the soul” and “God”, but it requires the same smugness that I warned against a few paragraphs ago to make that assumption. It might well be that Avicenna needed to waste his time on pointless questions in order to get the perspective and motivation that allowed him to create the closest thing to modern medicine that existed before late Renaissance.
I think the world need more Avicennas and if the price we must pay is a bunch of bad books about phenomenology and metaphysics it’s a very advantageous trade.
But the world could probably do without a bunch of Thomas Aquinas throwing away hereditary money on whoring and gambling then publishing nonsense about metaphysics due to thinking that “existence” is a characteristic the same way “blue” is. The world would almost certainly be better off without people committing genocide and flying commercial planes into tall buildings.
Maybe there is a sweet spot in terms of musing on these questions, around that sweet spot you get Edmund Burke or a Quaker doctor dedicating his life to curing tropical diseases in Rwanda. If you don’t venture into these kind of questions at all, you get an accountant or a store clerk; venture to deeply or go the wrong way and you get a Thomas Aquinas or a fundamentalist preacher who wants to kill homosexuals.
Alas, I can’t speak much as to how you can find that sweet-spot, besides the vaguely-related article I linked above. So this train of thought about unanswerable questions leads me to an unanswerable question. Possibly because I’m asking it in the wrong way or because my assumptions are completely wrong to being with… On which I just wasted almost 2,000 words saying almost nothing at all, the very thing I am railing against.
As part of the LessWrong Coronavirus Link Database, Ben, Elizabeth and I are publishing daily update posts with all the new links we are adding each day that we ranked a 3 or above in our importance rankings. Here are all the top links that we added yesterday (March 20th), by topic.Dashboards
History of number and percent infections, recoveries, deaths, worldwide. Uses John Hopkins dataGuides/FAQs/Intros
High quality (in both production values and content) intro to the physical form of C19 and how it interacts with the body
(EV): They state that C19 can invade immune cells, but the only identified C19 receptor isn't on immune cells, and the paper they cite is for SARS proper, not C19Medical System
WHO to coordinate multinational testing of remdesivir (lopinavir + ritonavir) (HIV) and chloroquine (malaria)
Batching multiple people's samples could give us much more information with the same number of tests, at the cost of slower results
A guide to the vaccine and treatment regiments currently in testing
Aggregation of hospital requests for donors to tackle
(RS): hope I did that right, lmk if not (first link added)Progression & Outcome
Long now explores a set of assumptions, unproven but consistent with current knowledge, under which things might be pretty okay
Great explanation of C19's form and lifecycle, including explanations of how certain potential treatments could workSpread & Prevention
Estimating actual COVID 19 cases (novel corona virus infections) in an area based on deaths. Based on work by Tomas Pueyo.
(EV): They're still only using cases that came to the attention of medical authorities, potentially missing people w/o severe symptomsWork & Donate
A short list of recommendations for organizations that would benefit from more money and are (perhaps indirectly) fighting COVID-19Link to Full Database
TL;DR: You are invited to join us online on Saturday the 28th of March, to write that blog post you've been thinking about writing but never got around to. This is the second event of this type; the first one went well. Please comment if you are thinking about joining so I can gauge interest.The Problem:
Like me, you are too scared and/or lazy to write up this idea you've had. What if it's not good? I started a draft but... Etc.
Alternatively: Coronavirus got you down? Cooped up inside? Looking for something new to do, someone new to talk to? How about you write a blog post?The Solution:
1. Higher motivation via Time Crunch and Peer Encouragement
We'll set an official goal of having the post put up by midnight. Also, we'll meet up in a special-purpose discord channel to chat, encourage each other, swap half-finished drafts, etc. If like me you are intending to write the thing one day eventually, well, here's a reason to make that day this day.
2. Lower standards via Time Crunch and Safety in Numbers
Since we have to be done by midnight, we'll all be under time pressure and any errors or imperfections in the posts will be forgivable. Besides, they can always be fixed later via edits. Meanwhile, since a bunch of us will be posting on the same day, writing a sloppy post just means it won't be read much, since everyone will be talking about the handful of posts that turn out to be really good. If you are like me, these thoughts are comforting and encouraging.Evidence this Works:
MIRI Summer Fellows Program had a Blog Post Day towards the end, and it was enormously successful. It worked for me, for example: It squeezed two good posts out of me. (OK, so one of them I finished up early the next morning, so I guess it technically doesn't count. But in spirit it does: It wouldn't have happened at all without Blog Post Day.) More importantly, MSFP keeps doing this every year, even though opportunity cost for them is much higher (probably) than the opportunity cost for you or me. And we did a Blog Post Day on LW last month and it worked great.Side Benefits:
It'll be fun!