A critique of EA's focus on longtermism

By Remus Rimbu @ 2025-10-23T18:16 (+9)

Hello everyone, 

A couple of days ago I had to present a critique of EA for an in-depth course and to try to steelman the argument as much as possible. I was encouraged to post it here as well, perhaps it can spawn some interesting discussion. It is not necessarily a terribly new critique, nor is it very original; nevertheless, I believe the arguments are pretty solid and the critique might convince some within EA to shift focus on some of its cause areas. 

The summary of my critique of EA runs as follows: EA has placed too large of an emphasis on longtermism as a central (though broad) cause area; EA would benefit from a return to its roots in the form of less-uncertain global health/poverty, animal welfare and (arguably) climate change interventions. 

For people who are not so familiar with longtermism, one common definition is that longtermism entails believing that positively influencing the long-term future is a (or the) key moral priority of our time. 

Some of the theoretical/philosophical basis for longtermism can be found in books by influent EA figures. For example, in What We Owe the Future, Will MacAskill illustrates the moral equality of future and present people through a simple thought experiment. Suppose you leave a broken bottle in a forest. If someone cuts their hand on it tomorrow, you would rightly feel responsible for their injury. But if, instead, the bottle remains there for a hundred years and someone then gets hurt, the moral situation is unchanged: the harm is the same, and your causal role is identical. The time delay does not diminish the victim’s suffering or your moral responsibility. MacAskill’s point is that temporal distance alone cannot justify discounting the interests of future individuals. A person’s location in time, like their location in space, is morally irrelevant.

I do agree with this framing and with the proposition that, in principle, the lives of future, potential people count equally with those of present, actual people. The key element is the „in principle” part, which might become different in practice given the uncertainties involved. I am also open to theories whereby we apply an discount rate on the value of future people that grows with the time separating us from them, as long as the discount rate is not too steep. I am genuinly agnostic on which of these approaches is better or „more true”; however, I am quite confidently opposed to any moral theories that assigns zero moral worth to future, potential people. The arguments of my critique of EA makes no use of such assumptions. 

To summarize, I would like to make it perfectly clear what I am not claiming here: I am not claiming that the lives of future people count for less than that of actual people. Instead, I am simply claiming that there is more uncertainty about both the probabilities of the individual causes affecting the survival of humanity, and uncertainty about whether we can be effective in doing something about it. Because longtermist interventions have extremely high variance and weak feedback loops, their expected-value estimates are often dominated by speculative assumptions rather than empirical validation. I am also not claiming that longtermism should stop being a focus inside EA altogether. I am simply arguing for a shift in focus in EA on other issues. 

My argument can be broken down into three parts: 

1. Epistemic uncertainty: We have low confidence in estimates of the likelihood of specific existential risks. Toby Ord’s The Precipice explicitly acknowledges that uncertainty in probability estimates of extinction risk is vast. At the same time, Ord admits some estimates (like AI extinction risk) are based more on expert judgment than hard empirical data. The epistemologist Christian Tarsney and the Global Priorities Institute have noted that longtermist decision-making involves deep uncertainty. All of these considerations should give us more epistemic humility regarding our understanding of the risks involved.
2. Tractability: Even if such risks are real, interventions may not be effective given their geopolitical or technical nature. I am going to focus on three popular causes within EA’s longtermist approach: extinction risk from nuclear war, man-made pandemics or artificial superintelligence. 

Disclaimer: I am not an expert in any of the fields I am going to talk about, so I might be wrong about technical details. If you know more about these fields than I do and think my arguments break down somewhere, please let me know!  

Nuclear war: it seems to me that any money donated to NGOs that aim to reduce nuclear proliferation can achieve little in a world where currently the vast majority(about 90%[1]) of nuclear weapons are in the hands of two arguably mentally unstable sociopaths: I am talking of course about Vladimir Putin and Donald Trump. Since they have some veto power over the use of these weapons, and anyway the circle of people making such decisions is small, the average EA can do very little to reduce probability of extinction via nuclear war. Historical research shows that most “near-miss” nuclear incidents in history were prevented by luck or individual restraint (e.g., Vasili Arkhipov, Stanislav Petrov), not by NGO intervention.

Man-made pandemic risk: this is also an area where the danger can arguably come from a small team of individuals that are hard to be controlled or regulated by the average EA donor. That is because risks arise from small, uncontrolled actors (e.g., rogue labs, state bioweapons programs). I actually happen to think it is probably a very good idea to regulate gain-of-function research. Gain-of-function research involves deliberately enhancing the transmissibility or virulence of pathogens in laboratory settings to study how dangerous variants might evolve. While scientifically informative, it carries the risk that an engineered strain could escape containment, potentially causing a pandemic. Laboratory leaks have occurred multiple times in the past: for example, smallpox escaped from a UK laboratory in 1978, killing a medical photographer, and SARS-CoV leaked from research facilities in Beijing in 2004, infecting several laboratory workers.

It probably is a good idea to regulate gain-of-function research; this however necessitates broad political action and international cooperation, both of which are hard to achieve using standard EA tools like donating to broad existential risk funds. The main levers are policy regulation and international treaties, both notoriously slow and resistant to small-scale donor influence. As you can notice, my arguments focus mostly on donations and earning to give; they might also apply to some degree to those EA members who try to help the world through their career. 

AI risk: some of our current most advanced models are LLMs like ChatGPT, which are based on deep learning neural networks. From a scientific, epistemic perspective, the problem with neural networks is that computer scientists themselves don't even understand how the black-box neural network arrives at its results. The decision processes within large neural networks are highly opaque and poorly understood in practice, making mechanistic interpretability a major open research challenge. This to me makes AI alignment research a very difficult endavour indeed. Moreover, there is as of now very little evidence of agentic AI having goals of its own. Current AI systems are non-agentic pattern predictors; no empirical evidence yet of goal-oriented autonomy. Even alignment researchers admit they are still defining what “misalignment” concretely means. Finally, the salaries of AI safety researchers tend to be very large, especially in labs such as Anthropic, OpenAI, or DeepMind, while the payoff is arguably very small: based on these reasons alone, giving to AI safety seems to me hardly cost effective. AI safety research often requires highly specialized technical expertise, making it relatively expensive compared with direct global health interventions. I am aware that longtermists attempt to make such donations cost-effective by using expected value calculations; any small and uncertain probability of averting extinction can yield great value if multiplied by a large enough benefit in terms of the future worth of humanity. Nevertheless, my understanding is that such calculations are highly speculative and can be made to show whatever one wants by simply manipulating the values inserted into the calculation: since such values are expert opinions at best (meaning an argument from authority) and subjective evaluations at worst, I do not think very highly of them. Such expected value calculations are also vulnerable to Pascal’s mugging, a deeply technical problem within decision theory that has, as far as I know, no non-controversial solution. 

3. Neglectedness reconsidered: EA has overcorrected toward longtermism, leaving its proven “roots” (global health, poverty reduction, animal welfare) underfunded. Funding data from Open Philanthropy show that global health and development programs receive a smaller fraction of EA-aligned grants today than existential risk mitigation, despite the former having far stronger empirical track records.[2]

Finally, my pragmatic approach is to say that average small-time EA donors should direct their money towards proven, cheap interventions into global health and poverty, animal welfare etc, rather than into speculative existential risk funds which are most likely not cost-effective. 

My conclusion is a portfolio diversification argument: Given extreme uncertainty and low tractability of existential risk mitigation, small donors should allocate primarily to global health, poverty, and animal welfare, while large donors/foundations can diversify into speculative, high-variance longtermist causes.

As you can see, I am mainly focusing on the day-to-day donation decisions of average EA small-time donors such as myself. I am someone who is not going to earn huge sums of money throughout my life, and therefore I am quite risk averse when it comes to where I want my charitable giving to go. If I were to win the lottery tomorrow, or be in a position to give advice to a billionaire or even millionaire, I would definitely change some of the focus of my critique and encourage them to speculatively donate to more uncertain existential risks areas. Nevertheless I think that the epistemic focus on longtermism from the EA community in the past couple of years, which perhaps stems from the fact that important figures like Will MacAskill, Toby Ord and Nick Bostrom have books on such topics, is not ideal. 

Notice that I have left out climate change from my criticisms of longtermist causes. There is one reason for that: the three cause areas I singled out (nuclear, biorisk, and AI) can be characterized as involving the potential for existential risk coming from a very small team of people. Such localized, agent-dependent threats are very difficult to prevent by the average EA donor without broad political intervention and international cooperation between countries. Climate change is an issue that also requires broad political intervention and international cooperation, but the threat is no longer coming from a small number of hard-to-control people, i.e. it is not agent-dependent. The solutions are also much clearer and more tractable in the case of climate change and other environmental concerns.[3] These are some of the reasons why I think tackling climate change should remain a core EA cause.

To close, in decision theory, when uncertainty overwhelms our ability to compare options, a cautious strategy favoring robustly good actions over speculative gambles becomes rational; especially for small donors.

Finally, I would argue that my criticisms places me in rather good company: in a Q&A, Peter Singer also expressed concern with some of EA’s focus on longtermism to the expense of present cause areas. 

[1] Federation of American Scientists (FAS), Nuclear Notebook 2024

[2] Open Philanthropy 2023 Annual Report

[3] Drawdown.org and 80,000 Hours both list climate change as moderately tractable and more tractable than AI or nuclear risk.