All of JustinShovelain's Comments + Replies

Nice succinct post. 

A related reference you might like https://www.lesswrong.com/posts/NjYdGP59Krhie4WBp/updating-utility-functions that goes into getting it to care about what we want before it knows what we want. 

Update from Convergence Analysis

In July, we published the following research posts:

• Improving the future by influencing actors' benevolence, intelligence, and power: This post outlines a framework for coming up with, and assesses the expected value of, actions to improve the long-term future, and discusses nine implications of this framework. --We were excited to see this framework already drawn on in two new forum posts by other authors (1,2).
• Moral circles: Degrees, dimensions, visuals: This post overviews the classic concept of moral circles, discuss

Thanks for writing the post! I think we need a lot more strategy research, cause prioritization being one of the most important types, and that is why we founded Convergence Analysis (theory of change and strategy, our site, and our publications). Within our focus of x-risk reduction we do cause prioritization, describe how to do strategy research, and have been working to fill the EA information hazard policy gap. We are mostly focused on strategy research as a whole which lays the groundwork for cause prioritization. Here are some of our articles:

• Heurist

Nice post!

Here are a couple additional posts that I think are worth checking out by Gwern:

https://www.lesswrong.com/posts/ktr39MFWpTqmzuKxQ/notes-on-psychopathy

https://www.lesswrong.com/posts/Ft2Cm9tWtcLNFLrMw/notes-on-the-psychology-of-power

Following Sean here I'll also describe my motivation for taking the bet.

After Sean suggested the bet, I felt as if I had to take him up on it for group epistemic benefit; my hand was forced. Firstly, I wanted to get people to take the nCOV seriously and to think thoroughly about it (for the present case and for modelling possible future pandemics) - from an inside view model perspective the numbers I was getting are quite worrisome. I felt that if I didn't take him up on the bet people wouldn't take the issue as seriously, nor take explicitl... (read more)

Nice find! Hopefully it updates soon as we learn more. What is your interpretation of it in terms of mortality rate in each age bracket?

Sure, I'll take the modification to option (i). Thanks Sean.

The bet is on.

Hmm... I will take you up on a bet at those odds and with those resolution criteria. Let's make it 50 GBP of mine vs 250 GBP of yours. Agreed?

I hope you win the bet!

(note: I generally think it is good for the group epistemic process for people to take bets on their beliefs but am not entirely certain about that.)

Good points! I agree but I'm not sure how significant those effects will be though... Have an idea of how we'd in a principled precise way update based on those effects?

Updating the Fermi calculation somewhat:

• P(it goes world scale pandemic) = 1/3, no updates (the metaculus estimate reference in another comment counteracted my better first principles estimation)
• P(a particular person gets it | it goes world scale pandemic) = 1/2, updating based on the reproduction number of the virus
• P(a particular person dies from it | a particular person gets it) = 0.09, updating based on a guess of 1/2 probability rare equipment is needed and a random guess of 1/2 probability fatality without it. 1/2*1/30 + 1/2*((Probability of pneumonia

Nice list!

Adding to it a little:

• Avoid being sick with two things at once or being sick with something else immediately before.
• When it comes to supplements the evidence and effect sizes are not that strong. Referencing examine.com and what I generally remember, I roughly think that the best immune system strengthening supplements would be zinc and echinacea with maybe mild effects from other things like vitamin C, vitamin D, and whey protein. There may be a couple additional herbs that could do something but it's unclear they are safe to take for a lon

The exponential growth curve and incubation period also have implications about "bugging out" strategies where you get food and water, isolate, and wait for it to be over. Let's estimate again:

Assuming as in the above comment we are 1/3 of the exponential climb (in reported numbers) towards the total world population and it took a month, in two more months (the end of March) we would expect it to reach saturation. If the infectious incubation period is 2 weeks (and people are essentially uniformly infectious during that time) then you'... (read more)

I base it on what Greg mentions in his reply about the swine flu and also the reasoning that the reproduction number has to go below 1 for it to stop spreading. If its normal reproduction number before people have become immune (after being sick) is X (like 2 say), then to get the reproduction number below 1, (susceptible population proportion) * (normal reproduction number) < 1. So with a reproduction number of 2 the proportion who get infected will be 1/2.

This assumes that people have time to become immune so for a fast spreading virus more than that ... (read more)

It's based on a few facts and swirling them around in my intuition to choose a single simple number.

Long invisible contagious incubation period (seems somewhat indicated but maybe is wrong) and high degree of contagiousness (the Ro factor) implies it is hard to contain and should spread in the network (and look something like probability spreading in a Markov chain with transition probabilities roughly following transportation probabilities).

The exponential growth implies that we are only a few doublings away from world scale pandemic (also note we&ap... (read more)

I wonder what sort of Fermi calculation we should apply to this? My quick (quite possibly wrong) numbers are:

• P(it goes world scale pandemic) = 1/3, if I believe the exponential spreading math (hard to get my human intuition behind) and the long, symptom less, contagious incubation period
• P(a particular person gets it | it goes world scale pandemic) = 1/3, estimating from similar events
• P(a particular person dies from it | a particular person gets it) = 1/30, and this may be age or preexisting condition agnostic and could, speculatively, increase if vital equipment is too scarce (see other comment)

=> P(death of a randomly selected person from it) = ~1/300

What are your thoughts?

How confident are you that it affects mainly older people or those with preexisting health conditions? Are the stats solid now? I vaguely recall that SARS and MERS (possibly the relevant reference class), were age agnostic.

By total mortality rate do you mean total number of people eventually or do you mean percentage?

If the former I agree.

If you mean the later... I see it as a toss up between the selection effect of the more severely affected being the ones we know have it (and so decreasing the true mortality rate relative to the published numbers) and time for the disease to fully progress (and so increasing the true mortality rate relative to the published numbers).

Thanks for the article. One thing I'm wondering about that has implications for the large scale pandemic case is how much equipment for "mechanical ventilation and sometimes ECMO (pumping blood through an artificial lung for oxygenation)" does society have and what are the consequences of not having access to such equipment? Would such people die? In that case the fatality rate would grow massively to something like 25 to 32%.

Whether there is enough equipment would depend upon how many get sick at once, can more than one person use the same... (read more)

It's true that this is pretty abstract (as abstract as fundamental epistemology posts), but because of that I'd expect it to be a relevant perspective for most strategies one might build, whether for AI safety, global governance, poverty reduction, or climate change. It's lacking the examples and explicit connections though that make this salient. In a future post that I've got queued on AI safety strategy I already have a link to this one, and in general abstract articles like this provide a nice base to build from toward specifics. I'll definitely think about, and possibly experiment with, putting the more abstract and conceptual posts on LessWrong.

Yes, the model in itself doesn't say that we'll tend towards competitiveness. That comes from the definition of competitiveness I'm using here and is similar to Robin Hanson's suggestion. "Competitiveness" as used here just refers to the statistical tendency of systems to evolve in certain ways - it's similar to the statement that entropy tends to increase. Some of those ways are aligned with our values and others are not. In making the axes orthogonal I was using the, probably true, assumption that most ways of system evolution are not in alignment with our values.

(With the reply I was trying to point in the direction of this increasing entropy like definition.)

The reason why we'd expect it to maximize competitiveness is in the sense that: what spreads spreads, what lives lives, what is able to grow grows, what is stable is stable... and not all of this is aligned with humanity's ultimate values; the methods that sometimes maximize competitiveness (like not internalizing external costs, wiping out competitors, all work and no play) much of the time don't maximize achieving our values. What is competitive in this sense is however dependent on the circumstances and hopefully we can align it better. I hope this clarifies.

I agree with your thoughts. Competitiveness isn't necessarily fully orthogonal to common good pressures but there generally is a large component that is, especially in tough cases.

If they are not orthogonal then they may reach some sort of equilibrium that does maximize competitiveness without decreasing common good to zero. However, in a higher dimensional version of this it becomes more likely that they are mostly orthogonal (apriori, more things are orthogonal in higher dimensional spaces) and if what is competitive can sorta change with time walk... (read more)

Nice! I would argue though that because we do not consider all dimensions at once generally speaking and because not all game theory situations ("games") lend themselves to this dimensional expansion we may, for all practical purposes, sometime find ourselves in this situation.

Overall though, the idea of expanding the dimensionality does point towards one way to remove this dynamic.

My argument is about the later; the variances decrease in size from I to T to C. The unit analysis still works because the other parts are still implicitly there but treated as constants when dropped from the framework.

Nice article Michael. Improvements to EA cause prioritization frameworks can be quite beneficial and I'd like to see more articles like this.

One thing I focus on when trying to make ITC more practical is ways to reduce its complexity even further. I do this by looking for which factors intuitively seem to have wider ranges in practice. Impact can vary by factors of millions or trillions, from harmful to helpful, from negative billions to positive billions. Tractability can vary by factors of millions, from negative millionths to positive digits. The C... (read more)