how to use causal graphical models to study why ordinary people have the beliefs they do, and how to intervene to make them be less wrong.
Note to self—a good reason to listen carefully to people’s reasons for their beliefs, even/especially when they are nonsensical. They may have structure that can be exploited.
As with much philosophizing, I agree with your diagnosis of the problem, but the solution seems dubious.
ultimate reality can be experienced
You see this claim all the time (e.g. Ken Wilber) but I have yet to see a shred of evidence for it. Given how the brain works, there seems to be no pathway to experience ultimate reality directly.
Bear in mind also the claim
the ultimate reality is the source of all existence
So we are supposed to be able to directly apprehend the source of all existence. The fact that many people experience similar feelings/insights/beliefs is weak evidence for the claim. Not much stronger than the common feeling among each and every new generation that they are the most virtuous and ethical of all generations. (As an aside, which usually comes with the feeling that they are the first to discover the wonders of sex and drugs/alcohol).
On the question of enlightenment this is a very overloaded term.
One use of the term that I found useful and other rationalists might is “The Finders” by Jeffery A Martin. This is a practical and useful version of enlightenment with very little mystification and few grandiose claims.
Interesting that there seems to be very little research in preventing tolerance effects. Maybe there is an opportunity there.
I suggest it is important to separate the desirability of a course of action and its political feasibility e.g. in relation to border closures.
In epidemiology it is a basic fact in the 101 textbook that slowing long distance transmission (using quarantines / travel restrictions) is very important. Unfortunately this got caught up in claims of xenophobia etc. Countries that have been relatively successful have implemented such restrictions.
I would be interested in some justification of the claim that face masks are not very useful. From all my reading, this seems to be false.
One mistake I made was not to aggressively look for countries that were successful (like Taiwan) and to enquire what they did (border closures/tightly enforced quarantine, face masks, isolating people with cold/flu/fever symptoms—even though this is not a “valid” test for CV it gathers and uses much useful information).
Like many I got caught up in the false dichotomy of lockdown=ruined economy versus no-lockdown=many will die.
More in this paper. https://www.jstor.org/stable/2937765?seq=1 Noise Trader Risk in Financial Markets.
Anyone interested in this should also read https://en.wikipedia.org/wiki/Limits_to_arbitrage
Search also for books A Random Walk Down Wall St, and A Non-Random Walk Down Wall St.
LWers in my experience tend to be a little too ready to accept the Efficient Markets Hypothesis as truth. The Ludic fallacy as Taleb calls it.
Bottom line: markets may not be quite efficient, and indeed prices can stray far from fundamentals at times, but it is still pretty hard to beat buy and forget broad indexing.
That analysis has been trenchantly criticised and I don’t find it convincing.
Apart from Trump making the obvious and true point that mail-in ballots are ripe for fraud, all the evidence for people not accepting presidential election results seems to be from the Democrat side. For example:
Not my president.
The disbelief that Trump could possibly have won.
The denial that Trump even had a chance. https://www.theguardian.com/commentisfree/2016/oct/20/hillary-clinton-president-debate-us-election
The “Russian collusion” hoax.
This anxiety about whether Trump would concede seems to include a significant element of projection.
inb4 “So you’re saying Trump is a good man, a good president, an honest man”.
No I am not saying that.
The market is really weird.
The EMH is only true at a zero-th approximation. There are many reasons why arbitragers cannot fix wrong prices, see e.g. “The Limits of Arbitrage” by Schliefer. There is a whole literature on this, not all of which is valid. Keynes said that markets can stay wrong longer than you can stay solvent.
All this suggests that prices can vary from value, but that it may not be too easy to make money from this insight.
I don’t know the specifics of Hertz but very low stock prices tend to reflect the option values inherent in the asset. There might be a possibility that a Venture capital fund may want the stock for some reason. Even small possibilities, of large payouts, can move the price.
There is a lot more to finance than first appears. In the book series “market wizards”, several traders comment that they have read hundreds of books on the topic, on top of their own research. My own experience over almost 40 years is that it is at a degree of difficulty similar to learning physics to an advanced level, and on top of that it is very challenging psychologically.
There is a great book along these lines, highly recommended: “Parent Effectiveness Training” by Thomas Gordon.
One thing the book emphasises more than OP is letting children make their own decisions wherever possible. This encourages them to take responsibility for their own outcomes and massively helps them to learn. It is important—and empowering—to allow them to experience the consequences of their decisions.
Our daughter picked her own clothes from the age of 8, for example. There were only two instances where we overruled her about her own life choices after she turned 12. We never forced her to do homework. [She ended up with a PhD in a hard science, so yes she mostly did her homework. But it is her life.]
A lot of this seems counter-intuitive to people. Parenthood seems to trigger some sort of authoritarian program in many otherwise liberal people. It may be that you could make better decisions on a given issue than your children, but they lose the opportunity to learn when you do that.
It may also be that you would not actually make better decisions than your child. Conjure up in your mind a 16 year old dressed for a party a) in clothes of their own choosing, b) in clothes chosen by their parents. Who did the better job?
Mod note: Copied over from one of Zvi’s Covid posts to keep the relevant thread on-topic:
I would simply like to point out here 3 things.
1. The definition of homicide from wikipedia “A homicide requires only a volitional act by another person that results in death, and thus a homicide may result from accidental, reckless, or negligent acts even if there is no intent to cause harm” Such a finding in an autopsy report does not imply a crime let alone murder.
2. The autopsy report ordered by his family showed quantities of numerous drugs including very significant, potentially lethal, quantities of Fentanyl, a drug often associated with respiratory failure, in George Floyd’s blood. Floyd was also positive for Coronavirus, which is known to impact heart and lung function, and had heart disease and various other relevant medical conditions. Consider the possibility that the causal chain is less clear than might appear superficially.
3. I see at this point no court finding of murder.
OP asked for only comments on the CV pandemic but I think that his inflammatory comment requires some clarification.
not as well as New York.
I take issue with the use of the word “well” in relation to the debacle in New York, past or current.
Taiwan; 0.3 deaths per million total, 1 death / 24 million in the last month
Australia 4 deaths per million total. 7 deaths / 25 million in the last month.
New York State: 1,550 deaths / million total. 5,000 deaths per 9 million in the last month. To compare to Taiwan or Australia it would be 12,000⁄25 million in the last month. Let the scale of that failure sink in.
New York’s current *daily* death rate (10/million) exceeds Australia’s total across the whole pandemic.
I see no evidence of herd immunity being a significant factor yet. I see no indication that things are under control.
Impact of the demonstrations.
I don’t know the numbers of people in the demonstrations, let’s say 100,000. Let’s say 3% get infected as a result. That would be 3,000, significantly more than the reported daily new cases of ca 1,000. However given a ratio of 10% for deaths to reported cases, it is evident that reported cases are massively understated, perhaps 10 fold. Even so 3,000/(10*1,000)= 30% is a significant increment on the daily case load. And the people infected in the demonstrations may be people who might not have been infected in more normal circumstances.
[Rest of the comment moved to Open Thread]
Wish I’d watched this before. Very good insight into the perils of making models.
I think you dismiss the non-lockdown options too glibly. Like many, you seem trapped in the dilemma “lockdown and kill the economy vs no lockdown and kill the people”. You, and many others, need to have a close look at what countries like Taiwan (and others) have done—no lockdown and few deaths.
Possibly there is an element of western arrogance in the way many western countries refuse to learn from Asian countries that have been far more successful in keeping their economies open and deaths low. Two key elements that are surprisingly effective: ubiquitous use of face masks, and the use of cheap, simple, rapid metrics to exclude people from schools, shops, workplaces, and public transportation.
Simple metrics like checking for cold/flu symptoms and taking temperatures are not infallible ways to determine if someone has the SARS-CoV2 virus. But they are very useful, and can be done at a rate that dwarfs the possible rate of PCR tests. As a result you can actually gather more information across the whole society, and the information is more current.
Lockdown is also ruinously expensive and unsustainable. In my simulations maybe $20M/life saved, $300K/capita over a year.
Remember we need only get R0(eff)< 1. We do not need to get it to zero. That means a bit more than a 50% reduction, maybe 60% from the base rate ~2.5.
The level of infection at which “herd immunity” occurs is IMHO very much up in the air. The simple SIR models tend to overstate the level needed, because they generally don’t take into account the fact that in epidemics the super-spreaders get taken out, one way or another, quite early, and the remaining more cautious and safer people have a much lower effective R0. IMHO it may be as low as 15% or as high as 50%, but unlikely to be as high as 65%. Epidemiologists talk about epidemics dying out for mysterious reasons, and it is speculated it is something about the microstructure of society, like superspreaders and more generally the variance of infectivity/susceptibility of people and groups, that is responsible.
I think we have our answer to the Fermi paradox in our hopeless response to the CV pandemic. The median European country has had deaths/million more than 10 times worse than best practice (Taiwan etc). https://www.worldometers.info/coronavirus/#countries
Civilizations will arise when the species concerned is only barely able to manage the job. I think world history suggests that this is very true of us. The chances of being up to handling the much more complex, difficult challenges of going to the next level seem low.
You seem to have the idea that a programming language should define a certain set of abstractions and that is that. But to many one of the key powers that programming brings is the ability to define and model new abstractions. In addition to your list I also would therefore also require
Ability to create powerful abstractions within the language, and
Ease of avoiding redundancy/repetition and/or boiler plate code in aid of such abstractions.
If deliberately infecting yourself, consider taking measures to check and to optimize your immune response.
Nutritionally rich diet, protein, vitamin D3/sunshine, etc.
The phenotypes affect the environment e.g. via competition for resources. At the same time, prey species are evolving. It looks to me like this model works in a limit where the environment is large and/or in the short term, but breaks down beyond that.
It is an interesting connection. By the way another way you can look at evolution is that the organisms absorb information from the environment.
Could you expand on which momentum anomaly you tested? One type is cross-sectional momentum (buy the top 1/10th of stocks that went up and short the bottom 1/10th), which is subject to major periods of drastic underperformance. This is all well documented in the literature. The other type is using momentum on the market as a whole, perhaps switching between asset classes based on momentum. I would not think that you could assess a strategy based on 6 months of performance.
My view as an investor since the 1980s is that the EMH is true to a 0th approximation. However massive agency issues in the fund management industry leave room to outperform on a risk adjusted basis if your incentives are different from the average fund manager. Some anomalies are just not exploitable by fund managers/agents because they would lose all their funds under management after periods > 12 months of underperformance.
LW readers interested in the topic may like reading the Alphaarchitect blog. https://alphaarchitect.com/blog/
1. Most people tend to be right about 60% of the time when they feel fairly certain. If we apply this logic to your assumptions, the chance that they are all correct is approximately 0. Many things we were told about CV2 turned out to be wrong. That is a bit simplistic, but your analysis should take into account that your assumptions may not all be correct, and the consequences of this. For example what if young people have silent organ damage, as has been reported? What if immunity is limited, uncertain, or short-lived, as if often the case with corona viruses? Such errors could be very costly. In general the strategy of “pick the most likely scenario and bet erh farm on that one scenario” is a poor strategy.
2. By getting infected now, you are giving away much by way of option value. The value of getting immunized later, of having better treatment later, of having better and less costly methods of limiting infection, etc.
3. You are falling for the false dichotomy of lockdown versus uncontrolled pandemic. I suggest you have a close look at Taiwan, which has had approximately 1/700th the death rate of the US for example, and which did not have a lockdown. While Taiwan did make a fast start, Australia got down into the Taiwan range of active cases within about 5 weeks, and other countries could also do this with a brief lockdown.
Techniques used by Taiwan include contact tracing, strict controls on entrants to the country, enforcement of quarantine of cases, use of soft metrics like temperature and cold/fever symptoms with exclusion from schools/work/transport for the symptomatic, and others. They have selectively closed some high risk businesses like “hostess bars”.
This problem of becoming fixated on one aspect of a problem or one one thing generally, “Einstellung” in German, is an important cognitive bias that is not talked about often enough IMHO. A common example these days is the notion that the USA has one problem, Donald Trump, and with him gone all would be right with the world again.
In my program I assume
Fraction of people compliant with the masks policy(asymmetric-distancing-fraction-compliant-fv) 0.7Fraction of infection that still gets through from mask wearer to other person (asymmetric-distancing-outbound-ineffectiveness) 0.3Fraction of infection that still gets through from non-mask-wearer to mask-wearing person (asymmetric-distancing-inbound-ineffectiveness) 0.8
Given this, and numerous other assumptions including no other measures taken, the death rate falls from 0.65% to 0.48% of the population. This is a good benefit but not a total solution.
If you have better numbers for mask effectiveness than the ones I guesstimated above please let me know.
The other main dubious assumption in my model (other than no other measures taken) is uniformity of people. I am adding some options on that tomorrow.