Mistakes in the moral mathematics of existential risk (Part 5: Implications)

What are the philanthropic causes that should be prioritized if one adopts the longtermist perspective of giving equal weight to the welfare of current and future generations? Many have argued that, because human extinction would result in a permanent loss of all future lives, extinction risk mitigation should be the top priority. In this paper, we provide a challenge to this argument. We first introduce a theoretical framework for quantifying cost-effectiveness from a longtermist perspective. We then show that standard population models imply the existence of interventions that produce social benefits that are permanent and large enough to render these interventions at least as cost-effective as extinction risk mitigation from a longtermist perspective.

Maya Eden and Gustav Alexandrie, “Is Extinction Risk Prevention the Unique Longtermist Priority? Not in Standard Population Models”, forthcoming in Essays on longtermism (OUP).
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1. Recap

This is Part 5 in my series “Mistakes in moral mathematics” based on a paper of the same name. In this series, I discuss three mistakes that are often made in calculating the value of existential risk mitigation. I show how these mistakes have led the value of existential risk mitigation efforts to be overestimated, and how they have mislocated debates about the value of existential risk mitigation.

Part 1 introduced the series and discussed the first mistake: focusing on cumulative rather than per-unit risk. When existential risk mitigation is framed as an intervention on risk in our own century, rather than risk across many distant centuries, the value of existential risk mitigation drops dramatically. We saw how a leading paper by Nick Bostrom makes the first mistake.

Part 2 discussed a second mistake: ignoring background risks which are not affected by our intervention. We saw how a leading estimate of the cost-effectiveness of biosecurity interventions by Piers Millett and Andrew Snyder-Beattie falls once background risk is incorporated. We also saw how the second mistake compounds with the first in Millett and Snyder-Beattie’s discussion, leading to a larger overestimate.

Part 3 introduced a third mistake: neglecting population dynamics. We saw how standard population models threaten to push the expected number of future lives far below longtermist projections. And we saw that standard models are robust against a number of objections that might be raised against them. Part 4 showed how the third mistake continues to be impactful even under highly optimistic assumptions about technological and population growth.

Today’s post concludes by drawing five lessons from this discussion.

2. Beyond existential risk mitigation

There is something which I very much wish I had stressed in my paper “Existential risk pessimism and the time of perils” and which I must not forget to stress in this paper. That is: this isn’t really a paper about the value of existential risk mitigation. The mistakes in this paper will tend to artificially inflate the value of nearly all longtermist interventions.

Most obviously, the third mistake (ignoring population dynamics), makes longtermist interventions look better by inflating the number of people who are likely to be around to enjoy the future we have left for them. Plausible estimates of the future human population reduce the value of longtermist interventions by reducing the number of people who will benefit from those interventions.

Likewise, the second mistake (ignoring background risk) makes longtermist interventions look better by inflating the likelihood that humanity will be around to reap the benefits of longtermist interventions. On many assumptions about background risk, it is no longer so likely that humanity will be around for billions of years to enjoy what we have left for them.

The first mistake (focusing on cumulative risk) may make longtermist interventions look better in the same way as the first, by making it look relatively less difficult for humanity to live a very long time.

If this is right, then the upshot of this paper is not just that the case for existential risk mitigation has been inflated, but rather that the case for longtermism has been inflated across the board.

3. Demographic policy matters

Suppose that standard demographic models are right, and the future human population is on a course to be depressingly small. This means that demographic policy interventions may be even more important than efforts to mitigate existential risk if they can lead to stable increases in the long-term size of the human population.

This is far from a sure thing. Demographers are currently struggling to find any demographic policies that can bring humanity back even to the replacement fertility level required to avoid a collapse in the size of the future human population.

However, if effective altruists are already willing to bet on highly speculative efforts to mitigate existential risk, then perhaps they should also be willing to bet on less speculative, if less glamorous, demographic research aimed at identifying and implementing feasible strategies for stably increasing the size of the future human population.

How large of a demographic shock is needed? The jury is out, but an excellent forthcoming paper by Gustav Alexandrie (of GPI) and Maya Eden (of Brandeis) sheds some light on the matter. The paper, entitled “Is extinction risk prevention the unique longtermist priority? Not in standard population models” is forthcoming in Essays on longtermism, which should be available (open access) through Oxford University Press in a year or so. Stay tuned!

4. The demographics of digital minds

Now for the wacky bit. Suppose you agree that it is unlikely for humans to spend our days expanding throughout the galaxy as fast as our limited resources will allow. And suppose you think that is a bad thing, for it means that the galaxy will support far fewer future lives than it could support.

Here is one solution: create digital minds instead. We might imagine that a population of digital minds would be constrained primarily by the availability of resources, such as energy and raw materials. And we might imagine that digital minds, or the computers that simulated them, could be endowed with an overriding desire to increase their own population as far as resources allow.

One question is whether the population dynamics of digital minds would indeed follow this path. As far as I know, the population dynamics of digital minds has not been well-studied. Perhaps it is time for that to change.

A second question is whether, if digital minds would really be subject to significantly more growth-oriented population dynamics than future human populations are likely to show, that might not generate pressure to create digital minds, or even to replace ourselves with digital minds.

That’s an uncomfortable thought. I’m not exactly sure what to say about it. I rather dislike the direction that this thought leads us, but I suppose that one must follow an argument where it leads. Is that where this paper leads? I hope not!

5. Intergenerational coordination

Our analysis of the first mistake revealed two things. First, realizing astronomical future value requires reducing cumulative existential risk by an appreciable amount. Second, reducing cumulative risk by an appreciable amount requires massive and consistent reductions in per-century risk. If we want, for example, a mere one-millionth of one percent chance of surviving for a billion years, then we need to drive per-century risk down to about one in a million, and we need to do this consistently, nearly without fail, in every single century.

This means that existential risk reduction is best understood as an intergeneration coordination problem in which all generations must come together to coordinate on a policy of keeping risk very low. This is a terribly difficult coordination problem for any number of reasons.

First, the required level of risk is very low. If effective altruists are right that current generations are running a 10-20% chance of existential catastrophe, then the demanded sacrifice is perhaps five orders of magnitude of risk. How much must each generation give up to reach this level of risk? Perhaps quite a lot.

Second, coordination must be nearly exceptionless. Even a few free-riding generations (such as, perhaps, our own) can scuttle the entire enterprise.

Third, enforcement mechanisms are few and far between. How do you punish past generations for the risk that they exposed you to? What about future generations? What is to stop them from taking on a bit more risk, given that fourth, externalities are high? Each generation bears only a tiny fraction of the total cost of human extinction, so an extreme degree of altruism or else highly effective coordination mechanisms are likely to be needed to bring free-riding generations into line. But there may not be effective coordination mechanisms, and people are not that altruistic.

Can the intergenerational coordination problem be solved? Perhaps. Framing the problem this way tends to incline one towards pessimism. But I am not usually so pessimistic about the chance of existential catastrophe. Perhaps there is a natural way of solving this coordination problem. Or perhaps the risks were never so high to begin with.

6. Fool me once, shame on you. Fool me thrice …

My paper “Existential risk pessimism and the time of perils” brought out a mistake that is made in many estimates of the value of existential risk mitigation: ignoring background risk. I showed how incorporating background risk may significantly lower the value of existential risk mitigation.

This paper grouped the second mistake into a larger pattern. Many authors also make the first mistake (focusing on cumulative rather than per-century risk) and the third mistake (ignoring population dynamics). We saw that each mistake substantially lowers the value of existential risk mitigation.

There comes a point where readers lose confidence in a class of projections and in the authors propounding them. Effective altruists repeatedly, and en masse, offer astoundingly high estimates of the value of existential risk mitigation. We have seen that many of these estimates are inflated by many orders of magnitude, and that they became inflated by making some of the same mistakes across many papers.

The right thing to conclude is not: there are three, and only three mistakes, in existing estimates of the value of existential risk mitigation, and the value of existential risk mitigation can be correctly determined by correcting them.

A better inference is that there are very likely further mistakes in these estimates, and that correcting these mistakes may lead to still more dramatic reductions in the value of existential risk reduction.

How sharp might the drop be? I am not sure. Perhaps I will write further papers chasing down other ways in which estimates become inflated. But at a certain point, one simply begins to lose confidence in the reliability of published figures. How many mistakes are leading estimates allowed to make until we stop believing them? Surely not many more than three.

I would encourage readers to go home, look up some leading estimates, and scratch out the reasoning behind them on their own. What exactly does it take to make these estimates tick? Do you believe them? Are there, perhaps, other systematic errors to be found? Let me know what you find. For my own part, my trust is waning.

Comments

6 responses to “Mistakes in the moral mathematics of existential risk (Part 5: Implications)”

  1. Michael St. Jules Avatar
    Michael St. Jules

    Do you find the models, especially fast expansion with digital minds, so wrong that you assign ~0 credence to them being decent approximations (e.g. within a few orders of magnitude)? If you assign the models even a very small chance of being right, say 1 in a million, the payoffs could still be large enough to compensate.

    1. David Thorstad Avatar

      Thanks Michael!

      One of the most common reactions to my work by effective altruists is that surely their claims have some small probability of being true, and if that’s right, it’s enough to get longtermism to be true. In general, I want to say a few things about this reaction.

      First, this move looks a lot better when we pull it once than it does when we pull it repeatedly. If one single criticism costs the longtermist 3-4 orders of magnitude in their expected value estimates, they might be able to handle the loss. But if every criticism costs the longtermist 3-4 orders of magnitude in their expected value estimates, then they’re going to run out of zeroes quite quickly.

      Second, effective altruists are very good at stressing that numbers can be extremely high, but less good at stressing that numbers can be extremely low. One in a million (shedding *six* orders of magnitude in one go!) is still not such a small chance: probabilities can go much lower than this. For example, my chance of being struck by lightning this morning is about one in a billion, and the chance that they’re going to find the Loch Ness monster is … well, vanishingly small. Extreme claims such as strong versions of the time of perils hypothesis are, at first glance, highly implausible, and most of what I’ve seen since looking into the evidence for them has tended to hurt as much as to help. I tend to think that such claims should be assigned very low probability.

      Third, even low probabilities need arguments. It’s very well to propose that claims should be assigned small, but not vanishingly small probabilities. But this proposal needs to be supported by arguments, since if we don’t have much reason in favor of extreme scenarios, it may well be appropriate to assign them vanishingly small probabilities.

      In my book, I am going to call the general strategy of argument above the “shedding zeroes strategy”. Roughly, the effective altruist begins by claiming that the expected value of longtermist interventions exceeds that of competing interventions by many orders of magnitude. I’m not sure that’s right, but I’ll accept that for the sake of argument. Then I will illustrate a series of problems, such as the three problems in this paper, that tend to take orders of magnitude off of expected value estimates, “shedding zeroes” from the case for longtermism. Rinsing and repeating may cost the longtermist more zeroes than she has to spend.

  2. James Brobin Avatar
    James Brobin

    It seems like there’s two primary ways to attack longtermism.

    One is to argue that, if we model the future accurately, the value of existential risk mitigation no longer appears astronomical.

    To support this view, you’ve argued, variously that:
    – We need to take into account background risk.
    – We need to focus on cumulative risk over period risk.
    – We need to accept the time of perils hypothesis, but it’s likely false since you’re not persuaded by arguments related to space settlement, the Kuznets curve, humanity gaining wisdom, and ASI.

    To me, it seems like this approach is unlikely to lead to a convincing argument against longtermism to the ears of most longtermists given that we know so little about the far future that people can easily come to wide ranging views about very important questions such as:
    -How technological progress will affect existential risk over the long-term
    -Whether space settlement vastly reduces existential risk
    -Whether humanity will eventually be able to collaborate sufficiently to reduce existential risk
    -Whether ASI will be able to safeguard humanity from existential risks

    As such, it seems to me like a better approach to criticizing longtermism is to, instead, argue that we are unable make accurate predictions about the far future so we should expect the effects of our actions to be neutral in relation to it. Some reasons to think this are:
    1. Historically, we’ve been bad at making predictions about the future. By induction, we should expect this to continue to be true.
    2. There is an extraordinarily vast possibility space for what the future of humanity could look like, but we only have a paucity of information on which to guess where within this possibility space humanity will navigate.
    3. Human history thus far has been very chaotic. By induction, we should expect this to continue to be true, which undermines our abilities to make accurate predictions about the future.
    4. There have been many black swan events historically. If there are too many going forwards, we should not expect to be able to make accurate predictions about the far future.

    I’m curious. Do you still think that the modelling approach is a good way to argue against longtermism? Do you think that an epistemic challenge to longtermism alone is sufficient to argue against it? Also, are you still working on Beyond Longtermism or did you move on from that?

    1. James Brobin Avatar
      James Brobin

      Also, to be clear, I’m not against the approach of assessing longtermism from multiple angles as you have been doing.

    2. David Thorstad Avatar

      Thanks James!

      I’m highly sympathetic to your concern that it is hard to predict the future, and that given this uncertainty, we should be hesitant to update too strongly on longtermist arguments. I agree with many of your grounds for this concern as well. I address this most clearly in my paper and blog series, “The scope of longtermism.” I think it is also very excellently addressed by Eva Vivalt’s chapter in Essays on longtermism. Eva is an economist who has done a good deal of work on forecasting (and previously directed GPI), so she really knows what she is talking about and makes a good, accessible case for forecasting concerns that connects well to the issues faced by longtermists.

      I think that those sympathetic to these concerns probably don’t need any more of the medicine that I’m peddling. In that sense, if you wanted to just ignore the rest of my papers and call it a day, I wouldn’t blame you.

      Those who still want more medicine might agree that, in general, it is difficult to predict the long-term future but take themselves to be in possession of considerations so strong, either in plausibility or in potential magnitude, that they are worth taking seriously even given general concerns about predicting the future. Papers and blog series like this one are geared towards the latter audience.

      I do agree that it is a bit awkward to keep track of the multiple overlapping, and not always perfectly compatible, argumentative threads running through different concerns about longtermism. I am, oddly, a bit happy that the literature has reached the state where this is a problem. Most developed academic discussions evolve into rich literatures with a patchwork of overlapping findings and concerns that need to be pieced together with some care. Piecing them together can be exhausting, but it’s also a sign that we’ve reached a state of some maturity when the exhaustion comes to set in. In the early stages of a literature, so little of the relevant conceptual space has been explored that there isn’t much difficulty in piecing together the various perspectives, approaches and issues. And that is just a sign that there is more work to be done.

      Thanks for asking about Beyond longtermism. I hope it will be out soon (in academic timescales). I’ve had a full manuscript under review with Oxford University Press since late last year. They’re promising me that the reviews will be in any day now, which hopefully puts us around 12-18 months from publication, but academic publishing can be a bit slow and unpredictable. Sorry for the delay here. I’ll start posting more about the book when I get closer to the final version. I really appreciate your interest. (I’ll also try to keep fundraising to make the book open access, so more people can read it).

      1. James Brobin Avatar

        That makes a lot of sense! I understand your approach a lot better now.

        Since you started on the book a while ago, I assumed that it would come out any day now so I’m glad to hear that I shouldn’t be holding my breath!

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