The Bay Area is a terrible place to live in many ways. I think if we were selecting for the happiness of existing rationalists, there’s no doubt we should be somewhere else.
But if the rationalist project is supposed to be about spreading our ideas and achieving things, it has some obvious advantages. If MIRI is trying to lure some top programmer, it’s easier for them to suggest they move to the Bay (and offer them enough money to overcome the house price hurdle) than to suggest they move to Montevideo or Blackpool or even Phoenix. If CEA is trying to get people interested in effective altruism, getting to socialize with Berkeley and Stanford professors is a pretty big plus. And if we’re trying to get the marginal person who isn’t quite a community member yet but occasionally reads Less Wrong to integrate more, that person is more likely to be in the Bay than anywhere else we could move. I think this is still true despite the coronavirus and fires. Maybe it’s becoming less so, but it’s hard to imagine any alternative hub that’s anywhere near as good by these metrics. *Maybe* Austin.
Separating rationalists interested in quality-of-life from rationalists working for organizations and doing important world-changing work seems potentially net negative.
I think if we were going to move the Berkeley hub, it would have to be to another US hub—most people aren’t going to transfer countries, so even if the community as a whole moved, we would need another US hub for Americans who refused to or coudln’t emigrate.
I don’t think Moraga (or other similar places near the Bay) are worth trying. They’re just as expensive as Berkeley, but almost all single-family homes, so it would be harder for poorer people to rent places there. Although there’s a BART station, there’s not much other transit, and most homes aren’t walkable from the BART station, so poorer people without cars would be in trouble. And it really isn’t much less expensive than Berkeley, and it’s got the same level of fire danger, so we would be splitting the community in two (abandoning the poor people, the people tied to MIRI HQ, etc) while not gaining much more than a scenery upgrade. I think they’re a fair alternative option for people who can’t stand the squalor and crime of the Bay proper, but mostly in the context of those people moving there and commuting to Berkeley for community events.
If we made a larger-scale move, I think it would be to avoid the high housing costs, fires, blackouts, taxes, and social decay of the Bay. That rules out anywhere else in California—still the same costs, fires, blackouts, and taxes, although some places are marginally less decayed. It also rules out Cascadian cities like Portland and Seattle—only marginally better housing costs, worse fires, and worse social decay (eg violence in Portland).
If we wanted to stick close enough to California that it was easy to see families/friends/colleagues, there are lots of great cities in or near the Mountain West—Phoenix, Salt Lake, Colorado Springs, Austin. All of those have housing prices well below half that of the Bay (Phoenix’s cost-of-housing index is literally 20% of Berkeley’s!). Austin is a trendy exciting tech hub, Colorado Springs frequently tops most-liveable lists, Salt Lake City seems unusually well-governed and resilient to potential climate or political crisis, and Phoenix is gratifyingly cheap.
The most successful adjacent past attempt at deliberate-hub-creation like this I know of was the Free State Project, where 20,000 libertarians agreed to create a libertarian hub. They did some analyses, voted on where the hub should be, created an assurance contract where every signatory agreed to move once there were 20,000 signatories, got 20,000 signatories, and moved. They ended up choosing New Hampshire, which means we might want to consider it as well. It’s got great housing prices (Manchester is as cheap as Phoenix!), a great economy, beautiful scenery, a vibrant intellectual scene, it’s less than an hour’s drive to Boston, it’s very politically influential (small, swing state, presidential primaries), and (now) has 20,000 libertarians who are interested in moving places and building hubs.
If people are interested in this, I think the first step would be to consult MIRI, CFAR, CEA, etc, and if they say no, decide whether splitting off “the community” from all of them is worth it. If they say yes, or people decide it’s worth it to split, then make an organization and take a vote on location. Once you have a location in mind, start an assurance contract where once X people sign, everyone moves to the location (I’m not sure what X would be—maybe 50?)
I think this is a really interesting project, but probably am too tied to my group house to participate myself :(
I mostly agree with this—see eg https://slatestarcodex.com/2020/05/12/studies-on-slack/
I think you might find http://www.daviddfriedman.com/Academic/Property/Property.html helpful here. It explains legitimacy as a Schelling point. If everyone thinks you’re legitimate, you’re legitimate. And if everything expects everyone else is going to think you’re legitimate, you’re legitimate.
America has such a strong tradition of democracy that the Constitution makes an almost invincible Schelling point—everyone expects everyone else to follow it because everyone expects everyone else to follow it because...and so on. A country with less of a democratic tradition has less certainty around these points, and so some guy who seizes the treasury might become the best Schelling point anyone has.
Banning fresh bread doesn’t decrease human caloric needs. Wouldn’t making fresh bread less desirable just mean people replace it with other foods, spending the same amount of money overall (or more, since bread is probably cheaper than its replacement) and removing any benefit from bread price controls? Or was the English government working off a model where people were overconsuming food because of how tasty fresh bread was?
Re: “revisionist history”:
You criticize my description in “A Failure, But Not Of Prediction”, which was:
The stock market is a giant coordinated attempt to predict the economy, and it reached an all-time high on February 12, suggesting that analysts expected the economy to do great over the following few months. On February 20th it fell in a way that suggested a mild inconvenience to the economy, but it didn’t really start plummeting until mid-March – the same time the media finally got a clue.
As my post said, the market started declining a little in February. Using the S&P link you provide, on March 2⁄28, it reached 2954, just 12% lower than its all-time high, then quickly recovered to only 8% lower a few days later. For comparison, the market fell 7% in May 2019 because Donald Trump made a bad tweet, and then everyone laughed it off and forgot about it within a few weeks. I think my claim that “it fell in a way that suggested a mild inconvenience to the economy” is a fair description of this.
It had its next major fall on March 9, reaching a new low (34% off its all-time high) March 23. I think it is fair to say it started plummeting in mid-March, though I would not blame you if you consider March 9 more “early” than “mid”. For comparison, Jacob wrote his post warning that the coronavirus would be a big deal in late February, and I wrote one saying the same on March 2.Some of this depends on the “correct” amount of market crash. I was writing my post in early April, when the market was near its floor. If that was the “correct” amount of market crash, then the early February crash underpredicted it, and the market didn’t “get it right” until mid-March. As you write this post now, the market has recovered, and if it’s at the “correct” price now, then the early February crash was basically correctly calibrated and the mid-March crash was an overreaction.To be clear, I think time has proven you correct about the EMH (and this is easy for you to say, now that the market has stabilized). I’m not debating any of the points in your post, just your accusation that I am a “revisionist historian”.
Thanks, I look forward to seeing how this goes. I’m impressed with you being willing to bet against me on things you know nothing about like my restaurant preferences (not sarcastic, seriously impressed), and I will be *very* impressed if you end up broadly more accurate than I am in that category. In many cases I agree with your criticism once you explain your reasoning.
There was a pretty credible rumor that Kim Jong-un was dead last week when I wrote this, which is why I gave him such a low probability. Today the news is he was seen in public alive (though in theory this could be a sham), so you are probably right, but it made sense when I wrote it.
Thanks (as always) for your thoughts.I agree most of your methods for evaluating predictions are good. But I think I mostly have a different use case, in two ways. First, for a lot of things I’m not working off an explicit model, where I can compare predictions made to the model to reality in many different circumstances. When I give Joe Biden X% of the nomination, this isn’t coming from a general process that I can check against past elections and other candidates, it’s just something like “Joe Biden feels X% likely to win”. I think this is probably part of what you mean by hard mode vs. easy mode.Second, I think most people who try to make predictions aren’t trying to do something that looks like “beat the market”. Accepting the market price is probably good enough for most purposes for everyone except investors, gamblers, and domain experts. For me the most valuable type of prediction is when I’m trying to operate in a field without a market, either because our society is bad at getting the right markets up (eg predicting whether coronavirus will be a global pandemic, where stock prices are relevant but there’s no real prediction market in it) or because it’s a more personal matter (eg me trying to decide whether I would be happier if I quit my job). Calibration is one of the few methods that works here, although I agree with your criticisms of it.I’m not sure we disagree on Silver’s Trump production and superforecasters’ Brexit prediction. I agree they did as well as possible with the information that they had and do not deserve criticism. We seem to have a semantic disagreement on whether a prediction that does this (but ascribes less than 50% to the winning side on a binary question) should be called “intelligently-made but wrong” or “right”. I’m not really committed to my side of this question except insofar as I want to convey information clearly.I’m not sure it’s possible to do the thing that you’re doing here, which is to grade my predictions (with hindsight of what really happened) while trying not to let your hindsight contaminate your grades. With my own hindsight, I agree with most of your criticisms, but I don’t know whether that’s because you have shown me the error of my ways, or because Scott-with-hindsight and Zvi-with-hindsight are naturally closer together than either of us is to Scott-without-hindsight (and, presumably, Zvi-without-hindsight).A few cases where I do have thoughts—one reason I priced Biden so low was that in December 2018 when I wrote those it was unclear whether he was even going to run (I can’t find a prediction market for that month, but prediction markets a few months later were only in the low 70s or so). Now it seems obvious that he would run, but at the time you could have made good money on InTrade by predicting that. My Biden estimate was higher than the prediction market’s Biden estimate at that time (and in fact I made lots of money betting on Biden in the prediction markets in January 2019 ), so I don’t think I was clearly and egregiously too low.Same with Trump being the GOP nominee. I agree now it seems like it was always a sure thing. But in late 2018, he’d been president for just under two years, it was still this unprecedented situation of a complete novice who offended everyone taking the presidency, we were in the middle of a government shutdown that Trump was bungling so badly that even the Republicans were starting to grumble, and the idea of GOP falling out of love with Trump just felt much more plausible than it does now. It’s possible this was still silly even in late 2018, but I don’t know how to surgically remove my hindsight.I will defend my very high confidence on Trump approval below 50, based on it never having gotten above 46 in his presidency so far. While I agree a 9-11 scale event could change that, that sort of thing probably only happens once every ten years or so. Trump got a boost from a rally-round-the-flag effect around COVID, and it was clearly bigger than any other boost he’s gotten in his administration, but it only took him up to 45.8% or so, so even very large black swans aren’t enough. The largest boost Obama got in his administration, after killing Osama, was only 5 points above baseline, still not enough for Trump to hit 50. And it wouldn’t just require an event like this to happen, but to happen at exactly the right time to peak on 1/1/2020.May staying in power feels wrong now, but she had beaten Labour recently enough that she didn’t have to quit if she didn’t want to, she had survived a no-confidence motion recently enough that it would have been illegal to no-confidence her again until December (and it probably wouldn’t happen exactly in December), and she had failed badly many times before without resigning. So I figured she wasn’t interested in resigning just because Brexit was hard, and nobody else could kick her out against her will, so she would probably stay in power. I guess she got tired of failing so many times. You were right and I was wrong, but I don’t think you could have (or should have be able to) convinced me of that last year.
Correction: Kelsey gave Biden 60% probability in January 2020. I gave him 20% probability in January 2019 (before he had officially entered the race). I don’t think these contradict each other.
No, it says:
The study design does not allow us to determine whether medical masks had efficacy or whether cloth masks were detrimental to HCWs by causing an increase in infection risk. Either possibility, or a combination of both effects, could explain our results. It is also unknown whether the rates of infection observed in the cloth mask arm are the same or higher than in HCWs who do not wear a mask, as almost all participants in the control arm used a mask. The physical properties of a cloth mask, reuse, the frequency and effectiveness of cleaning, and increased moisture retention, may potentially increase the infection risk for HCWs. The virus may survive on the surface of the facemasks,29 and modelling studies have quantified the contamination levels of masks.30 Self-contamination through repeated use and improper doffing is possible. For example, a contaminated cloth mask may transfer pathogen from the mask to the bare hands of the wearer. We also showed that filtration was extremely poor (almost 0%) for the cloth masks. Observations during SARS suggested double-masking and other practices increased the risk of infection because of moisture, liquid diffusion and pathogen retention.31 These effects may be associated with cloth masks… The study suggests medical masks may be protective, but the magnitude of difference raises the possibility that cloth masks cause an increase in infection risk in HCWs.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4420971/ is skeptical of cloth masks. Does anyone have any thoughts on it, or know any other studies investigating this question?
In most major countries, daily case growth has switched from exponential to linear, an important first step towards the infection being under control. See https://ourworldindata.org/grapher/daily-covid-cases-3-day-average for more, you can change which countries are on the graph for more detail. The growth rate in the world as a whole has also turned linear, https://ourworldindata.org/grapher/daily-covid-cases-3-day-average?country=USA+CHN+KOR+ITA+ESP+DEU+GBR+IRN+OWID_WRL . Since this is growth per day, a horizontal line represents a linear growth rate.
If it was just one country, I would worry it was an artifact of reduced testing. Given almost every country at once, I say it’s real.
The time course doesn’t really match lockdowns, which were instituted at different times in different countries anyway. Sweden and Brazil, which are infamous for not taking any real coordinated efforts to stop the epidemic, are showing some of the same positive signs as everyone else—see https://ourworldindata.org/grapher/daily-covid-cases-3-day-average?country=BRA+SWE—though the graph is a little hard to interpret.
My guess is that this represents increased awareness of social distancing and increased taking-things-seriously starting about two weeks ago, and that this happened everywhere at once because it was more of a media phenomenon than a political one, and the media everywhere reads the media everywhere else and can coordinate on the same narrative quickly.
Thanks for the shout-out, but I don’t think the thing I proposed there is quite the same as hammer and dance. I proposed lockdown, then gradual titration of lockdown level to build herd immunity. Pueyo and others are proposing lockdown, then stopping lockdown in favor of better strategies that prevent transmission. The hammer and dance idea is better, and if I had understood it at the time of writing I would have been in favor of that instead.
(there was an ICL paper that proposed the same thing I did, and I did brag about preempting them, which might be what you saw)
Sorry, by “complete” I meant “against both types of transmission”. I agree it was confusing/wrong as written, so I edited it to say “generalized”.
Agreed, it seems very similar to (maybe exactly like) the “Martin Luther King was a criminal” example from there.
China is following a strategy of shutting down everything and getting R0 as low as possible. This works well in the short term, but they either have to keep everything shut down forever, or risk the whole thing starting over again.UK is following a strategy of shutting down only the highest-risk people, and letting the infection burn itself out. It’s a permanent solution, but it’s going to be really awful for a while as the hospitals overload and many people die from lack of hospital care.What about a strategy in between these two? Shut everything down, then gradually unshut down a little bit at a time. Your goal is to “surf” the border of the number of cases your medical system can handle at any given time (maybe this would mean an R0 of 1?) Any more cases, and you tighten quarantine; any fewer cases, and you relax it. If you’re really organized, you can say things like “This is the month for people with last names A—F to go out and get the coronavirus”. That way you never get extra mortality from the medical system being overloaded, but you do eventually get herd immunity and the ability to return to normalcy.This would be sacrificing a certain number of lives, so you’d only want to do it if you were sure that you couldn’t make the virus disappear entirely, and sure that there wasn’t going to be vaccine or something in a few months that would solve the problem, but it seems like more long-term thinking than anything I’ve heard so far.I’ve never heard of anyone trying anything like this before, but maybe there’s never been a relevant situation before.
It sounds like you’ve found that by March 17, the US will have the same number of cases that Italy had when things turned disastrous.But the US has five times the population of Italy, and the epidemic in the US seems more spread out compared to Italy (where it was focused in Lombardy). This makes me think we might have another ~3 doubling times (a little over a week) after the time we reach the number of cases that marked the worst phase of Italy, before we get the worst phase here.I agree that it’s going to get worse than most people expect sooner than most people expect, and that now is a good time to start staying inside. But (and I might be misunderstanding) I’m not sure if I would frame this as “tell people to stay inside for the next five days”, because I do think it’s possible that five days from now nothing has gotten obviously worse and then people will grow complacent.
Have you looked into whether cinchona is really an acceptable substitute for chloroquine?
I’m concerned for two reasons. First, the studies I saw were on chloroquine, and I don’t know if quinine is the same as chloroquine for this purpose. They have slightly different antimalarial activity—some chloroquine-resistant malaria strains are still vulnerable to quinine—and I can’t find any information about whether their antiviral activity is the same. They’re two pretty different molecules and I don’t think it’s fair to say that anything that works for one will also work for the other. Even if they do work, I don’t know how to convert doses. It looks like the usual quinine dose for malaria is about three times the usual chloroquine dose, but I have no idea how that translates to antiviral properties.
Second, I don’t know how much actual quinine is in cinchona. Quinine is a pretty dangerous substance, so the fact that the FDA doesn’t care if people sell cinchona makes me think there isn’t much in it. This paper suggests 6 mg quinine per gram of bark, though it’s using literal bark and not the purified bark product they sell in supplement stores. At that rate, using this as an example cinchona preparation and naively assuming that quinine dose = chloroquine dose, the dose corresponding to the Chinese studies would be 160 cinchona pills, twice a day, for ten days - a level at which some other alkaloid in cinchona bark could potentially kill you.
Also, reverse-quarantining doesn’t just benefit you, it also benefits the people who you might infect if you get the disease, and the person whose hospital bed you might be taking if you get the disease. I don’t know what these numbers are but they should probably figure into your calculation.
I tried to answer the same question here and got very different numbers—somewhere between 500 and 2000 cases now.
I can’t see your images or your spreadsheet, so I can’t tell exactly where we diverged. One possible issue is that AFAIK most people start showing symptoms after 5 days. 14 days is the preferred quarantine period because it’s almost the maximum amount of time the disease can incubate asymptomatically; the average is much lower.