The decrease in soil-animal-years is proportional to the increase in agricultural-land-years, which is the increase in human population times the agricultural land per capita. I think both of these factors decrease over time, and therefore so does the decrease in soil-animal-years.
The agricultural land per capita in low income countries (LICs) has been decreasing.
Figuring out the increase in human population across time is tricky. The people whose lives were extended will tend to have more children as a result, but decreasing mortality also decreases fertility. From the paper The Impact of Life-Saving Interventions on Fertility by David Roodman:
[...] In places where lifetime births/woman has been converging to 2 or lower, saving one child’s life should lead parents to avert a birth they would otherwise have. The impact of mortality drops on fertility will be nearly 1:1, so population growth will hardly change. In the increasingly exceptional locales where couples appear not to limit fertility much, such as Niger and Mali, the impact of saving a life on total births will be smaller, and may come about mainly through the biological channel of lactational amenorrhea. Here, mortality-drop-fertility-drop ratios of 1:0.5 and 1:0.33 appear more plausible. But in the long-term, it would be surprising if these few countries do not join the rest of the world in the transition to lower and more intentionally controlled fertility.
Nothing special happens in 100 years. This is just a rough guess for when the future impact becomes smaller than 10 % of the past impact.
1. In ~100 years, some sort of (almost) unavoidable population equilibrium will be reached no matter how many human lives we (don’t) save today. (Ofc, nothing very special in exactly 2125, as you say, and it’s not that binary, but you get the point.)
Saving human lives today changes the human population curve between 2025 and ~2125 (multiple possible paths represented by dotted curves). But in ~2125 , our impact (no matter in which direction it was) is canceled out.
2. Even if 1 is a bit false (such that what the above black curve looks like after 2125 actually depends on how many human lives we save today), this won’t translate into a difference in terms of agricultural land use (and hence in terms of soil nematode populations).
Almost no matter how many humans there are after ~2125, total agricultural land remains roughly the same.
Is that a fair summary of your view? If yes, what do you make of, say, the climate change implications of changing the total number of humans in the next 100 years? Climate change seems substantially affected by total human population (and therefore by how many human lives we save today). And the total number of soil nematodes seems substantially affected by climate change (e.g., could make a significant difference in whether there will ever be soil nematodes in current dead zones close to the poles), including long after ~2125 (nothing similar to your above points #1 and #2 applies here; climate-change effects last). Given the above + the simple fact that the next 100 years constitute a tiny chunk of time in the scheme of things, the impact we have on soil nematodes counterfactually affected by climate change between ~2125 and the end of time seems to, at least plausibly, dwarf our impact on soil nematodes affected by agricultural land use between now and ~2125.[1] What part of this reasoning goes wrong, exactly, in your view, if any?
We might have no clue about the sign of our impact on the former such that some would suggest we should ignore it in practice (see, e.g., Clifton 2025; Kollin et al. 2025), but it’s a very different thing from assuming this impact almost certainly is negliglble relative to short-term impact.
Yes, that is a fair summary, with the caveat that I do not think the global population or agricultural land will stabilise after a certain date. I just believe they will be roughly the same longterm with or without intervention.
There is nothing in particular which is wrong about what you said. However, evidence from randomized controlled trials (RCTs), which are the best way to empirically assess causal effects, still shows these decrease over time.
Figure 4: Posterior expected value from forecast signal with expected value 1 and linearly increasing noise over time, 1,000,000 years, log-log scale
[...]
Figure 6: Posterior expected value from forecast signal with expected value 1 and non-linearly increasing noise over time, 1,000,000 years, log-log scale
[...]
Table 4: How long it takes until posterior expected value is some fraction of signal expected value
Years until posterior expected value is x% of signal
x%
Central fixed effects
Upper bound, fixed effects
Central, no fixed effects
Upper bound, no fixed effects
Increasing rate of increase
Decreasing rate of increase
10%
561
158
187
84
68
13,276
1%
6,168
1,735
2,047
923
337
484,318
0.1%
62,233
17,507
20,651
9,307
1,571
15.5 million
0.01%
622,886
175,218
206,690
93,144
7,294
491 million
We can see that under the preferred central fixed effects estimate, signals of the value produced with a horizon of 561 years produce a posterior expected value that is 10% of the expected value of the signal. Every order of magnitude increase in forecast horizon after that results in a posterior expected value roughly an order of magnitude smaller.
For the possibilities considered in David Bernard’s post, 90 % of the effects materialise in 68 to 13.3 k years. I think the timelines above are too long because David assumed “the variance of the prior was the same for each time horizon whereas the variance of the signal increases with time horizon for simplicity”. Without any information, I would guess my actions can have a much greater effect in 10 years that in 10 M years. So I would assume the variance of the prior decreases over time, in which case the signal would be more heavily discounted than in David’s analysis, and therefore the time until 90 % of the effects materialising would be shorter.
Nice, thanks. To the extent that, indeed, noise generally washes out our impact over time, my impression is that the effects of increasing human population in the next 100 years on long-term climate change may be a good counterexample to this general tendency.
Not all long-term effects are equal in terms of how significant they are (relative to near-term effects). A ripple on a pond barely lasts, but current science gives us good indications that i) releasing carbon into the atmosphere lingers for tens of thousands of years, and ii) increased carbon in the atmosphere plausibly hugely affects the total soil nematode population (see, e.g., Tomasik’s writings on climate change and wild animals)[1]. It is not effects like (i) and (ii) Bernard’s post studies, afaict. I don’t see why we should extrapolate from his post that there has to be something that makes us mistaken about (i) and/or (ii), even if we can’t say exactly what.
I forgot to comment on your example about climate change. The question is not whether carbon dioxide (CO2) will remain in the atmosphere, but whether emitting 1 kg more today means there will be 1 kg more in e.g. 1 k years.
As an analogy, I think banning caged hens in a country may well imply there will be no caged hens there forever, but I still think the difference between the expected number of caged hens there without and with the ban still decreases over time. Animal welfare corporate campaigns have resulted in fewer hens in cages, and, more longterm, I believe technological development will lead to alternative proteins which decrease the consumption of eggs, or new systems which displace cages. In addition, economic growth means greater willingness to pay for animal welfare.
Likewise, blocking the construction of a farm which produces 10 t/year of chicken meat per year does not mean the global production of chicken meat will be 10 t/year lower forever. Existing farms can increase their production, and additional new farms be built to offset the initial drop in production.
The chance of the end goal being achieved via other means can be modelled with an annual discount rate. Any cost-effectiveness analysis estimating finite benefits necessarily assumes the benefits decrease over time. Otherwise, they would be infinite.
hey sorry for reopening but very curious to get your take on this:
Say you have been asked to evaluate the overall[1] utilitarian impact of the very first Christianity-spreaders during the first century AD (like Paul the Apostle) on the world until now (independently of their intention ofc). You have perfect information on what’s causally counterfactually related to their actions. How much of their impact (whether good or bad) is on beings between 0 and 200 VS. on beings between 200 and now? (making your usual assumptions you specifically make about nematodes and stuff; don’t take anyone else’s perspective.)
If mostly the former, how do you explain that?
If mostly the latter, what’s the difference between their ex post impact and yours? Why is most of their ex post impact longtermist-ish while yours would be neartermist? Why would, e.g., most of the people helping nematodes, thanks to you (including very indirectly through your influence on others before them) be concentrated within the next hundred years?
No worries, Jim! Feel free to ask questions like this any time.
I would model the impact of the very 1st Christianity-spreaders as speeding up some changes that would happen anyway a few decades to a century later. I guess most of their impact was before the year 200. The answer for me does not depend on whether one accounts for only humans, or all potential beings, or whether Christianity lasts 3 k or 3 M years. The theory of relativity could remain relevant for centuries (even if as an approximation), but I guess Albert Einstein still only accelerated the knowledge about it by a few years to decades. Both the 2008 financial crisis and COVID-19 only affected real gross world product (GWP) for 3 years or so (approximate time until returning to the original trajectory).
You may be interested in my chat with Matthew Adelstein. We discussed my scepticism about longtermism.
The decrease in soil-animal-years is proportional to the increase in agricultural-land-years, which is the increase in human population times the agricultural land per capita. I think both of these factors decrease over time, and therefore so does the decrease in soil-animal-years.
The agricultural land per capita in low income countries (LICs) has been decreasing.
Figuring out the increase in human population across time is tricky. The people whose lives were extended will tend to have more children as a result, but decreasing mortality also decreases fertility. From the paper The Impact of Life-Saving Interventions on Fertility by David Roodman:
Nothing special happens in 100 years. This is just a rough guess for when the future impact becomes smaller than 10 % of the past impact.
Oh ok so you’re saying that:
1. In ~100 years, some sort of (almost) unavoidable population equilibrium will be reached no matter how many human lives we (don’t) save today. (Ofc, nothing very special in exactly 2125, as you say, and it’s not that binary, but you get the point.)
Saving human lives today changes the human population curve between 2025 and ~2125 (multiple possible paths represented by dotted curves). But in ~2125 , our impact (no matter in which direction it was) is canceled out.
2. Even if 1 is a bit false (such that what the above black curve looks like after 2125 actually depends on how many human lives we save today), this won’t translate into a difference in terms of agricultural land use (and hence in terms of soil nematode populations).
Almost no matter how many humans there are after ~2125, total agricultural land remains roughly the same.
Is that a fair summary of your view? If yes, what do you make of, say, the climate change implications of changing the total number of humans in the next 100 years? Climate change seems substantially affected by total human population (and therefore by how many human lives we save today). And the total number of soil nematodes seems substantially affected by climate change (e.g., could make a significant difference in whether there will ever be soil nematodes in current dead zones close to the poles), including long after ~2125 (nothing similar to your above points #1 and #2 applies here; climate-change effects last). Given the above + the simple fact that the next 100 years constitute a tiny chunk of time in the scheme of things, the impact we have on soil nematodes counterfactually affected by climate change between ~2125 and the end of time seems to, at least plausibly, dwarf our impact on soil nematodes affected by agricultural land use between now and ~2125.[1] What part of this reasoning goes wrong, exactly, in your view, if any?
We might have no clue about the sign of our impact on the former such that some would suggest we should ignore it in practice (see, e.g., Clifton 2025; Kollin et al. 2025), but it’s a very different thing from assuming this impact almost certainly is negliglble relative to short-term impact.
Thanks, Jim.
Yes, that is a fair summary, with the caveat that I do not think the global population or agricultural land will stabilise after a certain date. I just believe they will be roughly the same longterm with or without intervention.
There is nothing in particular which is wrong about what you said. However, evidence from randomized controlled trials (RCTs), which are the best way to empirically assess causal effects, still shows these decrease over time.
For the possibilities considered in David Bernard’s post, 90 % of the effects materialise in 68 to 13.3 k years. I think the timelines above are too long because David assumed “the variance of the prior was the same for each time horizon whereas the variance of the signal increases with time horizon for simplicity”. Without any information, I would guess my actions can have a much greater effect in 10 years that in 10 M years. So I would assume the variance of the prior decreases over time, in which case the signal would be more heavily discounted than in David’s analysis, and therefore the time until 90 % of the effects materialising would be shorter.
Nice, thanks. To the extent that, indeed, noise generally washes out our impact over time, my impression is that the effects of increasing human population in the next 100 years on long-term climate change may be a good counterexample to this general tendency.
Not all long-term effects are equal in terms of how significant they are (relative to near-term effects). A ripple on a pond barely lasts, but current science gives us good indications that i) releasing carbon into the atmosphere lingers for tens of thousands of years, and ii) increased carbon in the atmosphere plausibly hugely affects the total soil nematode population (see, e.g., Tomasik’s writings on climate change and wild animals)[1]. It is not effects like (i) and (ii) Bernard’s post studies, afaict. I don’t see why we should extrapolate from his post that there has to be something that makes us mistaken about (i) and/or (ii), even if we can’t say exactly what.
Again, we might have no clue in which direction, but it still does.
I forgot to comment on your example about climate change. The question is not whether carbon dioxide (CO2) will remain in the atmosphere, but whether emitting 1 kg more today means there will be 1 kg more in e.g. 1 k years.
As an analogy, I think banning caged hens in a country may well imply there will be no caged hens there forever, but I still think the difference between the expected number of caged hens there without and with the ban still decreases over time. Animal welfare corporate campaigns have resulted in fewer hens in cages, and, more longterm, I believe technological development will lead to alternative proteins which decrease the consumption of eggs, or new systems which displace cages. In addition, economic growth means greater willingness to pay for animal welfare.
Likewise, blocking the construction of a farm which produces 10 t/year of chicken meat per year does not mean the global production of chicken meat will be 10 t/year lower forever. Existing farms can increase their production, and additional new farms be built to offset the initial drop in production.
The chance of the end goal being achieved via other means can be modelled with an annual discount rate. Any cost-effectiveness analysis estimating finite benefits necessarily assumes the benefits decrease over time. Otherwise, they would be infinite.
Interesting. Thanks for taking the time to explain all that :)
Thanks for the interesting questions too, Jim!
hey sorry for reopening but very curious to get your take on this:
Say you have been asked to evaluate the overall[1] utilitarian impact of the very first Christianity-spreaders during the first century AD (like Paul the Apostle) on the world until now (independently of their intention ofc). You have perfect information on what’s causally counterfactually related to their actions. How much of their impact (whether good or bad) is on beings between 0 and 200 VS. on beings between 200 and now? (making your usual assumptions you specifically make about nematodes and stuff; don’t take anyone else’s perspective.)
If mostly the former, how do you explain that?
If mostly the latter, what’s the difference between their ex post impact and yours? Why is most of their ex post impact longtermist-ish while yours would be neartermist? Why would, e.g., most of the people helping nematodes, thanks to you (including very indirectly through your influence on others before them) be concentrated within the next hundred years?
I.e., factoring in nematodes and stuff.
No worries, Jim! Feel free to ask questions like this any time.
I would model the impact of the very 1st Christianity-spreaders as speeding up some changes that would happen anyway a few decades to a century later. I guess most of their impact was before the year 200. The answer for me does not depend on whether one accounts for only humans, or all potential beings, or whether Christianity lasts 3 k or 3 M years. The theory of relativity could remain relevant for centuries (even if as an approximation), but I guess Albert Einstein still only accelerated the knowledge about it by a few years to decades. Both the 2008 financial crisis and COVID-19 only affected real gross world product (GWP) for 3 years or so (approximate time until returning to the original trajectory).
You may be interested in my chat with Matthew Adelstein. We discussed my scepticism about longtermism.