Can you explain in a bit more detail, and without complicated formalisation, why life expectancy after LEV is 1000. I note life expectancy is 1000 and the chance of death in 1 year is 1/1000. Is that a coincidence, or is life expectancy post-LEV just 1/annual chance of death?
I know you’ve said you’re going to cover this later, but I want to flag how sensitive this is to population ethics. On totalism (the value of the outcome is the sum total of well-being of everyone who will ever life), it’s good to create lives, so it’s not necessarily a problem that there’s a higher ‘turnover’ of lives, i.e. people die and other people replace them. Totalists will want to know how longevity affects the long run for everyone, not just those that get to live longer. By contrast, if you’re a person-affecting deprivationism (there is no value creating new lives, but for those lives that count, the badness of death is the amount of well-being they would have had had they lived), life extension looks super important!
Yes, if the chance of death each year is constant it turns out that remaining life expectancy is around 1/chance of death. In fact in a previous draft of the post I just used this fact and called it a day. I had to use more formalism though, because chance of death is not constant. After LEV hits there will be a period in which it will fall down, and that needs to be taken into account in order to find a true lower bound for life expectancy. The question that is still open is what is the minimum initial decrease of risk of death that ensures LEV.
Regarding the point about population ethics: Yes, impact depends on population ethics, in the sense that it is for sure as large as it can be under person-affecting deprivationism. Even on totalism though (which seems a more reasonable view of ethics to me), I expect the considerations made to really change the view on the impact of this cause area. This because, for example, a Malthusian outcome in which the disposable resources are always all employed is not necessarily the default outcome, and also not necessarily the most desirable one if well being is took into consideration. It’s also not clear if, under a non Malthusian condition, old people would take resources that would be also useful for young people. There could be vast amount of not used resources. Then added years to life expectancy could be “for free”, without negating the new younger people that would be born anyway. I think you could argue both ways, so the impact evaluation needs a downward correction but it is not invalidated. Another important thing to consider on totalism are moral weights: in general I don’t think that it would be better ethically to have generations and generations of people with a 5 years life span. At least if we don’t only account for how much time a person lives in our ethics, but how valuable that time is. The same argument could apply for much longer lifespans. Maybe a 1000 years life span is much more preferable than a 100 year one. Or maybe not, and time discounting is needed. Again, I think you could argue both ways, because the answer largely depends on informations we currently don’t have: how a 1000 years old mind looks like and how it is different from the one of a current adult.
Yes, if the chance of death each year is constant it turns out that remaining life expectancy is around 1/chance of death
Can you explain this is the case? Sorry if this is obvious, but I’m not getting it and can’t think offhand how to do the maths.
On population ethics, for totalists it then seems the dominating concern will be how valuable it is to have a population with longer lives, which puts the emphasis in a difference place from the value of keeping particular individuals alive longer.
It’s not necessarily obvious that this is the case.
Premise: In probability theory the chance of two independent events (which are events that don’t affect each other) happening together, like six coming up after you toss a dice and head coming up after you toss a coin, is calculated by multiplying the probability of the two events. In the case of the dice and the coin 1/6⋅1/2=1/12.
In the case of calculating expected future lifetime you need to sum all the additional number of years you could possibly live, each multiplied by their probability. This is how an expected value is calculated, and if you think about it it’s basically a weighted average: you want to know the “average” year you will live to, but in making the average each year can weight more or less depending on its probability.
It turns out, though, that in this case you can simplify the expected value formula, by only adding the probabilities of being alive at any given future year. This works, intuitively, because you are basically adding up all expected values that are made like this: 1MoreYear⋅probabilityOfSurvivingToThatYear. But what is the probability of surviving one more year? It is the probability of not dying all of the previous years! And so to find the probability you need to multiply all the independent events of not dying in a particular year between your current age and the year you are measuring the probability of arriving to. If the chance of dying any given year is constant at 1/1000 then the probability of not dying is 1−1/1000, and the multiplication is like this (1−1/1000)(1−1/1000)(1−1/1000)… the number of factors is the number of years between now and the year you are calculating the probability to arrive to. Let’s call this number k. The the multiplication becomes (1−1/1000)k
So you are basically adding up probabilities made like this: (1−1/1000)k but with k growing till infinite, since you want to account the probability of surviving to any arbitrary future year when calculating the expected value.
Why those probabilities add up exactly to 1/chance of death? I would think about it this way: when k is small, the term (1−1/1000)k is large, but still smaller than 1. The subsequent terms of the addition will be subsequently each time a little smaller. So you are basically adding up terms a little smaller than 1 but each time smaller and smaller. So what happens when you will have added 1000 terms? You will not quite reach 1000 in your sum. But this is compensated by all the subsequent super small terms you add till the infinite addition is complete.
Regarding population ethics: I finished to write the first draft of the second post in the series, and it is exactly about this topic. Can I send the Google Doc to you so you can comment in advance on it? It’s around 2k words. I know you are a moral philosopher (I remember you writing so in your post about Hippo), so it would be great to have feedback.
If you want to look up the maths elsewhere, it may be helpful to know that a constant, independent chance of death (or survival) per year is modelled by a negative binomial distribution.
Yes, looking back at this, I should have just said that on average, if someone dies with a probability of 1/1000, then he will live 999 years and die in the 1000th. And then I should have linked him the “Expectation” section of the Wikipedia page of the negative binomial distribution.
Thanks for writing this.
Can you explain in a bit more detail, and without complicated formalisation, why life expectancy after LEV is 1000. I note life expectancy is 1000 and the chance of death in 1 year is 1/1000. Is that a coincidence, or is life expectancy post-LEV just 1/annual chance of death?
I know you’ve said you’re going to cover this later, but I want to flag how sensitive this is to population ethics. On totalism (the value of the outcome is the sum total of well-being of everyone who will ever life), it’s good to create lives, so it’s not necessarily a problem that there’s a higher ‘turnover’ of lives, i.e. people die and other people replace them. Totalists will want to know how longevity affects the long run for everyone, not just those that get to live longer. By contrast, if you’re a person-affecting deprivationism (there is no value creating new lives, but for those lives that count, the badness of death is the amount of well-being they would have had had they lived), life extension looks super important!
Hey, I just published the second post of the framework, which answers your comment pretty well. I even mentioned you inside it. Here it is: https://forum.effectivealtruism.org/posts/uR4mEzMR7fiQzb2c7/aging-research-and-population-ethics
Yes, if the chance of death each year is constant it turns out that remaining life expectancy is around 1/chance of death. In fact in a previous draft of the post I just used this fact and called it a day. I had to use more formalism though, because chance of death is not constant. After LEV hits there will be a period in which it will fall down, and that needs to be taken into account in order to find a true lower bound for life expectancy. The question that is still open is what is the minimum initial decrease of risk of death that ensures LEV.
Regarding the point about population ethics: Yes, impact depends on population ethics, in the sense that it is for sure as large as it can be under person-affecting deprivationism. Even on totalism though (which seems a more reasonable view of ethics to me), I expect the considerations made to really change the view on the impact of this cause area. This because, for example, a Malthusian outcome in which the disposable resources are always all employed is not necessarily the default outcome, and also not necessarily the most desirable one if well being is took into consideration. It’s also not clear if, under a non Malthusian condition, old people would take resources that would be also useful for young people. There could be vast amount of not used resources. Then added years to life expectancy could be “for free”, without negating the new younger people that would be born anyway. I think you could argue both ways, so the impact evaluation needs a downward correction but it is not invalidated. Another important thing to consider on totalism are moral weights: in general I don’t think that it would be better ethically to have generations and generations of people with a 5 years life span. At least if we don’t only account for how much time a person lives in our ethics, but how valuable that time is. The same argument could apply for much longer lifespans. Maybe a 1000 years life span is much more preferable than a 100 year one. Or maybe not, and time discounting is needed. Again, I think you could argue both ways, because the answer largely depends on informations we currently don’t have: how a 1000 years old mind looks like and how it is different from the one of a current adult.
Can you explain this is the case? Sorry if this is obvious, but I’m not getting it and can’t think offhand how to do the maths.
On population ethics, for totalists it then seems the dominating concern will be how valuable it is to have a population with longer lives, which puts the emphasis in a difference place from the value of keeping particular individuals alive longer.
It’s not necessarily obvious that this is the case.
Premise: In probability theory the chance of two independent events (which are events that don’t affect each other) happening together, like six coming up after you toss a dice and head coming up after you toss a coin, is calculated by multiplying the probability of the two events. In the case of the dice and the coin 1/6⋅1/2=1/12.
In the case of calculating expected future lifetime you need to sum all the additional number of years you could possibly live, each multiplied by their probability. This is how an expected value is calculated, and if you think about it it’s basically a weighted average: you want to know the “average” year you will live to, but in making the average each year can weight more or less depending on its probability.
It turns out, though, that in this case you can simplify the expected value formula, by only adding the probabilities of being alive at any given future year. This works, intuitively, because you are basically adding up all expected values that are made like this: 1MoreYear⋅probabilityOfSurvivingToThatYear. But what is the probability of surviving one more year? It is the probability of not dying all of the previous years! And so to find the probability you need to multiply all the independent events of not dying in a particular year between your current age and the year you are measuring the probability of arriving to. If the chance of dying any given year is constant at 1/1000 then the probability of not dying is 1−1/1000, and the multiplication is like this (1−1/1000)(1−1/1000)(1−1/1000)… the number of factors is the number of years between now and the year you are calculating the probability to arrive to. Let’s call this number k. The the multiplication becomes (1−1/1000)k
So you are basically adding up probabilities made like this: (1−1/1000)k but with k growing till infinite, since you want to account the probability of surviving to any arbitrary future year when calculating the expected value.
Why those probabilities add up exactly to 1/chance of death? I would think about it this way: when k is small, the term (1−1/1000)k is large, but still smaller than 1. The subsequent terms of the addition will be subsequently each time a little smaller. So you are basically adding up terms a little smaller than 1 but each time smaller and smaller. So what happens when you will have added 1000 terms? You will not quite reach 1000 in your sum. But this is compensated by all the subsequent super small terms you add till the infinite addition is complete.
Regarding population ethics: I finished to write the first draft of the second post in the series, and it is exactly about this topic. Can I send the Google Doc to you so you can comment in advance on it? It’s around 2k words. I know you are a moral philosopher (I remember you writing so in your post about Hippo), so it would be great to have feedback.
If you want to look up the maths elsewhere, it may be helpful to know that a constant, independent chance of death (or survival) per year is modelled by a negative binomial distribution.
Yes, looking back at this, I should have just said that on average, if someone dies with a probability of 1/1000, then he will live 999 years and die in the 1000th. And then I should have linked him the “Expectation” section of the Wikipedia page of the negative binomial distribution.