Here’s a framing which I think captures some (certainly not all) of what you’re saying. Imagine graphing out percentiles for your credence distribution over values the entire future can take. We can consider the effect that extinction mitigation has on the overall distribution, and the change in expected value which the mitigation has. In the diagrams below, the shaded area represents the difference made by extinction migitation.
The closest thing to a ‘classic’ story in my head looks like below: on which (i) the long-run future is basically biomodal, between ruin and near-best futures, and (ii) the main effect of extinction mitigation is to make near-best futures more likely.
A rough analogy: you are a healthy and othrewise cautious 22-year old, but you find yourself trapped on a desert island. You know the only means of survival is a perilous week-long journey on your life raft to the nearest port, but you think there is a good chance you don’t survive the journey. Supposing you make the journey alive, then your distribution over your expected lifespan from this point (ignoring the possibility of natural lifespan enhancement) basically just shifts to the left as above (though with negligible weight on living <1 year from now).
A possibility you raise is that the main effect of preventing extinction is only to make worlds more likely which are already close to zero value, as below.
A variant on this possibility is that, if you knew some option to prevent human extinction were to be taken, your new distribution would place less weight on near-zero futures, but less weight on the best futures also. So your intervention affects many percentiles of your distribution, in a way which could make the net effect unclear.
One reason might be causal: the means required to prevent extinction might themselves seal off the best futures. In a variant of the shipwreck example, you could imagine facing the choice between making the perilous week-long journey, or waiting it out for a ship to find you in 2 months. Suppose you were confident that, if you wait it out, you will be found alive, but at the cost of reducing your overall life expectancy (maybe because of long-run health effects).
The above possibilities (i) assume that your distribution over the value of the future is roughly bimodal, and (ii) ignore worse-than-zero outcomes. If we instead assume a smooth distribution, and include some possibility of worse-than-zero worlds, we can ask what effect mitigating extinction has.
Here’s one possibility: the fraction of your distribution that effectively zero value worlds gets is ‘pinched’, giving more weight both to better-than-zero worlds, and worse-than-zero worlds. Here you’d need to explain why this is a good thing to do.
So an obvious question here is how likely it is that extinction mitigation is more like the ‘knife-edge’ scenario of a healthy person trapped in a survive-or-die predicament. I agree that the ‘classic’ picture of the value of extinction mitigation can mislead about how obvious this is for a bunch of reasons. Though (as other commenters seem to have pointed out) it’s unclear how much to rely on relatively uninformed priors, versus the predicament we seem to find ourselves in when we look at the world.
I’ll also add that, in the case of AI risk, I think that framing literal human extinction as the main test of whether the future will be good seems like a mistake, in particular because I think literal human extinction is much less likely than worlds where things go badly for other reasons.
Curious for thoughts, and caveat that I read this post quickly and mostly haven’t read the comments.
Imagine graphing out percentiles for your credence distribution over values the entire future can take.
I personally find it more intuitive to plot the PDF of the value of the future, instead of its cumulative distribution function as you did, but I like your graphs too!
The closest thing to a ‘classic’ story in my head looks like below: on which (i) the long-run future is basically biomodal, between ruin and near-best futures, and (ii) the main effect of extinction mitigation is to make near-best futures more likely.
I do not know whether the value of the future is bimodal. However, even if so, I would guess reducing the nearterm risk of human extinction only infinitesimaly increases the probability of astronomically valuable worlds. Below is an illustration. The normal and dashed lines are the PDFs of the value of the future before and after the intervention. I suppose the neutral worlds would be made slightly less likely (dashed line below the normal line), and the slightly negative and positive worlds would me made slightly more likely (dashed line above the normal line), but the astronomically negative and positive worlds would only be made infinitesimaly more likely (basically no difference between the normal and dashed line).
Are there any interventions whose estimates of (posterior) counterfactual impact, in terms of expected total hedonistic utility (not e.g. preventing the extinction of a random species), do not decay to 0 in at most a few centuries? From my perspective, their absence establishes a strong prior against persistent longterm effects.
I’ll also add that, in the case of AI risk, I think that framing literal human extinction as the main test of whether the future will be good seems like a mistake, in particular because I think literal human extinction is much less likely than worlds where things go badly for other reasons.
I wonder whether the probability of things going badly is proportional to the nearterm risk of human extinction. In any case, I am not sure the size of the risk affects the possibility of some interventions having astronomical cost-effectiveness. I guess this mainly depends on how fast the (posterior) counterfactual impact decreases with the value of the future. If exponentially, based on my Fermi estimate in the post, the counterfactual impact linked to making astronomically valuable worlds more likely will arguably be negligible.
I would be curious to know how low would the risk of human extinction in the next 10 years (or other period) have to be for you to mostly:
Donate to animal welfare interventions (i.e. donate at least 50 % of your annual donations to animal welfare interventions).
Work on animal welfare (i.e. spend at least 50 % of your working time on animal welfare).
Here’s a framing which I think captures some (certainly not all) of what you’re saying. Imagine graphing out percentiles for your credence distribution over values the entire future can take. We can consider the effect that extinction mitigation has on the overall distribution, and the change in expected value which the mitigation has. In the diagrams below, the shaded area represents the difference made by extinction migitation.
The closest thing to a ‘classic’ story in my head looks like below: on which (i) the long-run future is basically biomodal, between ruin and near-best futures, and (ii) the main effect of extinction mitigation is to make near-best futures more likely.
A rough analogy: you are a healthy and othrewise cautious 22-year old, but you find yourself trapped on a desert island. You know the only means of survival is a perilous week-long journey on your life raft to the nearest port, but you think there is a good chance you don’t survive the journey. Supposing you make the journey alive, then your distribution over your expected lifespan from this point (ignoring the possibility of natural lifespan enhancement) basically just shifts to the left as above (though with negligible weight on living <1 year from now).
A possibility you raise is that the main effect of preventing extinction is only to make worlds more likely which are already close to zero value, as below.
A variant on this possibility is that, if you knew some option to prevent human extinction were to be taken, your new distribution would place less weight on near-zero futures, but less weight on the best futures also. So your intervention affects many percentiles of your distribution, in a way which could make the net effect unclear.
One reason might be causal: the means required to prevent extinction might themselves seal off the best futures. In a variant of the shipwreck example, you could imagine facing the choice between making the perilous week-long journey, or waiting it out for a ship to find you in 2 months. Suppose you were confident that, if you wait it out, you will be found alive, but at the cost of reducing your overall life expectancy (maybe because of long-run health effects).
The above possibilities (i) assume that your distribution over the value of the future is roughly bimodal, and (ii) ignore worse-than-zero outcomes. If we instead assume a smooth distribution, and include some possibility of worse-than-zero worlds, we can ask what effect mitigating extinction has.
Here’s one possibility: the fraction of your distribution that effectively zero value worlds gets is ‘pinched’, giving more weight both to better-than-zero worlds, and worse-than-zero worlds. Here you’d need to explain why this is a good thing to do.
So an obvious question here is how likely it is that extinction mitigation is more like the ‘knife-edge’ scenario of a healthy person trapped in a survive-or-die predicament. I agree that the ‘classic’ picture of the value of extinction mitigation can mislead about how obvious this is for a bunch of reasons. Though (as other commenters seem to have pointed out) it’s unclear how much to rely on relatively uninformed priors, versus the predicament we seem to find ourselves in when we look at the world.
I’ll also add that, in the case of AI risk, I think that framing literal human extinction as the main test of whether the future will be good seems like a mistake, in particular because I think literal human extinction is much less likely than worlds where things go badly for other reasons.
Curious for thoughts, and caveat that I read this post quickly and mostly haven’t read the comments.
Thanks for the comment, Fin! Strongly upvoted.
I personally find it more intuitive to plot the PDF of the value of the future, instead of its cumulative distribution function as you did, but I like your graphs too!
I do not know whether the value of the future is bimodal. However, even if so, I would guess reducing the nearterm risk of human extinction only infinitesimaly increases the probability of astronomically valuable worlds. Below is an illustration. The normal and dashed lines are the PDFs of the value of the future before and after the intervention. I suppose the neutral worlds would be made slightly less likely (dashed line below the normal line), and the slightly negative and positive worlds would me made slightly more likely (dashed line above the normal line), but the astronomically negative and positive worlds would only be made infinitesimaly more likely (basically no difference between the normal and dashed line).
Are there any interventions whose estimates of (posterior) counterfactual impact, in terms of expected total hedonistic utility (not e.g. preventing the extinction of a random species), do not decay to 0 in at most a few centuries? From my perspective, their absence establishes a strong prior against persistent longterm effects.
I wonder whether the probability of things going badly is proportional to the nearterm risk of human extinction. In any case, I am not sure the size of the risk affects the possibility of some interventions having astronomical cost-effectiveness. I guess this mainly depends on how fast the (posterior) counterfactual impact decreases with the value of the future. If exponentially, based on my Fermi estimate in the post, the counterfactual impact linked to making astronomically valuable worlds more likely will arguably be negligible.
I would be curious to know how low would the risk of human extinction in the next 10 years (or other period) have to be for you to mostly:
Donate to animal welfare interventions (i.e. donate at least 50 % of your annual donations to animal welfare interventions).
Work on animal welfare (i.e. spend at least 50 % of your working time on animal welfare).