Exploiting the cognitive biases of altruists

How to become an effective altruist? The answer is easy: by exploiting the cognitive biases of altruists. Learn about cognitive biases, see how altruists are susceptible to these biases by making ineffective choices, and do what those biased altruists don’t do: make the altruistic choices that avoid those biases. People perform many altruistic deeds, but due to those biases, we miss so many opportunities to do more good. So here is a list of the most important biases that make altruists less effective.

Arbitrary categorization. We can categorize a set into a hierarchy of subsets, subsubsets of those subsets, subsubsubsets, and so on. For example the set of all problems can be divided in subproblems, subsubproblems and so on. The group of all suffering patients can be divided in subgroups, subsubgroups and so on. In their cause prioritization, looking for the problem to focus on or the patients to help, altruists have a tendency to arbitrarily (without giving good reasons or following a rule) pick a level in the hierarchy of categories (e.g. the subsubsets) and arbitrarily pick a specific element (e.g. a specific subsubset) at this level. That way of prioritization results in choices of problems and groups of patients where one can have less impact. For example altruists tend to focus on countries and prefer helping people in their own country. Or they tend to focus on groups of patients with a specific disease, or individuals belonging to a specific species.

Advice to become more effective: perform your cause prioritization by first looking at the total set of all suffering (including all diseases, all causes of suffering), or the total group of everyone (including foreigners, non-human animals, future generations,…). Then categorize this total set in subsets and pick the subset where you can have the biggest positive impact. That choice of subset is no longer arbitrary, because it follows the rule of maximizing impact.


Ingroup bias. As a result of arbitrary categorization, people have a tendency to prefer helping individuals of their own subgroup: people in their own country, of their own species, with the same interests (e.g. the same disease).

Advice to become more effective: help those individuals who are not considered as ingroup members by other altruists. The problems faced by those individuals are more neglected.


Zero risk bias (related to pseudocertainty effect and Allais paradox). People have a stronger incentive to eliminate a small risk compared to slightly reducing a bigger risk, even if reducing that bigger risk makes the world safer overall (in terms of reducing the aggregate of all risks). This zero risk bias is also a consequence of arbitrary categorization, because one can divide the total set (aggregate) of all risks into subsets of subrisks, subsubrisks,… and then focus on eliminating a specific subrisk.

Advice to become more effective: perform your cause prioritization by first looking at the total set of all risks. Then categorize this total set in subsets (subrisks) and pick the subset where you can have the biggest impact in the sense of the strongest reduction of the aggregate of all risks.


Risk aversion (related to certainty effect). People prefer safer bets with lower expected rewards compared to high risk high reward bets. This means the value function is not linear in gains. Winning one extra dollar is worth less when you already gained a lot of money. But when it comes to helping others, the value function should be linear in gains: saving an extra life is equally valuable, no matter how many lives are already saved. As a result of risk aversion, altruists prefer safe but low impact actions with certain but small positive results, above high risk high impact actions that have a higher expected impact. When a group of effective altruists choose high risk high impact actions, most of those altruists have bad luck and will cause no impact, but a minority is extremely lucky and will cause a lot of positive impact. This group as a whole does more good than a group of risk averse altruists where each member is sure to cause a little bit of good. For the effective altruists, it does not matter who are the lucky winners in the group; they only care about the strategy that results in the most good overall.

Advice to become more effective: be risk neutral when it comes to doing good and go for the high risk high impact actions because these are more neglected by other, risk averse altruists.


Loss aversion (related to reflection effect and framing effect). People have a stronger incentive to avoid losses than to obtain gains. Losses and gains are measured relative to a reference situation. If one considers as a reference the situation where everyone dies, every life saved is a gain. But if one considers the situation where everyone lives, everyone not saved is a loss. When being loss averse, your value function depends on a reference situation and the absolute value of the value function is not symmetric in gains and losses. The positive value of gaining one unit of goodness is in absolute terms smaller than the negative value of losing one unit of goodness. This is irrational, because it depends on the framing of the problem, i.e. the arbitrary choice of the reference situation. When N lives are at stake, framing a situation in terms of saving M of those lives (i.e. a guaranteed gain of M) should be considered the same as letting N-M people die (i.e. a guaranteed loss of N-M people).

Advice to become more effective: be gain-loss neutral when it comes to doing good and consider actions that can cause losses, when the expected net-benefits (gains minus losses) is positive. For example don’t be too extreme in applying the precautionary principle when introducing new technologies that have an expected net positive impact.


Status quo bias. People tend to be conservative and prefer the status quo. They are reluctant towards e.g. human cognitive enhancement, life extension or interventions in nature to improve wild animal welfare, because they prefer the current situation (the current cognitive level, life expectancy, natural processes,…).

Advice to become more effective: do the reversal test to check whether your preference for (in)action depends on a status quo bias. Be less reluctant against e.g. genetic cognitive enhancement, life extension (fighting aging) and nature intervention for wild animal welfare.


Scope neglect. In their cause prioritization, altruists are not often considering the size of the problem they focus on. On the contrary, there is often a positive correlation between the scope of a problem and the neglectedness of that problem (even for problems that are equally tractable in terms of feasibility to reduce them). The bigger the problem, the less attention it gets. Local relative poverty in rich countries gets more attention than global, extreme poverty. Shelter animal suffering gets more attention than livestock animal suffering, which gets more attention than wild animal suffering.

Advice to become more effective: consider the scope of the problem and choose the biggest problems.


Identifiable victim effect. People prefer to help patients they know personally or victims they can identify. They choose to support a campaign that helps a specific patient, become a foster parent of a specific child, or adopt a specific dog.

Advice to become more effective: choose supporting campaigns and actions where you cannot identify or know the patients or victims who benefit from your help. Those actions are often more neglected.


Identifiable problem effect. People have a stronger incentive to take preventive or precautionary measures when the potential problem is more clearly identifiable (e.g. in terms of place and time). This could result in taking too much preventive measures in one area (to prevent a small, identifiable risk) and not enough preventive measures in another area (to prevent a big, unidentifiable risk). Unidentifiable risks are risks where you cannot know whether your preventive measures resulted in decreasing or avoiding that risk. This lack of identification or knowledge means that those risks are more neglected.

Advice to become more effective: choose to invest in preventive measures against unidentifiable risks, even if we will never know that the preventive measures made a difference.


Availability heuristic. People focus on problems that easily come to mind, e.g. because of media attention (e.g. terrorism, natural disasters).

Advice to become more effective: focus on problems that get less media attention, donate to less known organizations (instead of e.g. disaster relief).


Groupthink (group conformity bias, bandwagon effect). People often follow other group members and adopt their beliefs. This can sometimes result in collective beliefs that are less accurate. For example most people on the left of the political spectrum are in favor of organic food and fair trade; most people in the environmental movement are against GMOs and nuclear power, even if those positions are not effective in terms of doing good.

Advice to become more effective: be less concerned about what other altruists believe. Use critical thinking and scientific evidence instead.


A/B effect (anti-experimentation bias). People are reluctant to consider interventions as experiments where data of the intervened group (group A) is compared to data of the non-intervened (control) group (group B).

Advice to become more effective: do more experiments (e.g. randomized controlled trials) to estimate the effectiveness of interventions. Such scientific research of effectiveness is often neglected.


Hyperbolic discounting. People are often inconsistent in discounting the well-being and suffering in the future. For example the difference between helping someone now versus the same kind of help next year is considered greater than the difference between helping someone in 100 years versus the same kind of help a year later (i.e. in 101 years). In general, this results in too much discounting of the future.

Advice to become more effective: consider the far future (longtermism).


Confirmation bias (related to overconfidence). People often have more confidence in a belief than what can be justified by evidence or reason, and they consider new information selectively in a way that affirms their prior beliefs. A confirmation bias is at play when altruists are not willing to accept negative evidence against their project or idea. As a result, altruists can have beliefs that are not always accurate, resulting in selection of ineffective means to help others.

Advice to become more effective: consider all new information in an impartial way, avoid strong feelings about your beliefs, update your confidence levels according to new evidence.


Commitment bias (sunk cost fallacy). People have a tendency to keep on investing in a project when they have already put a lot of effort in that project, even if new evidence shows that the project is much less effective than other opportunities.

Advice to become more effective: dare to quit projects, change jobs, do something else, be flexible, consider projects as learning experiences. Avoid too strong emotional attachments to current projects.

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Asymmetry in ethical principles

In general, we have to avoid unwanted arbitrariness in ethics. Arbitrariness is closely related to the notion of asymmetry. Symmetry means that an object looks the same after performing a transformation. Consider a perfect sphere with a uniform color. This object has rotational symmetry: if you close your eyes, I rotate the sphere, and you open your eyes again, you are not able to tell whether I rotated the sphere. No point on the sphere is special. Now you can randomly select a point on this sphere and draw a small line there. Suddenly, all rotational symmetry is gone. You can see when the sphere is rotated. In drawing the line that breaks the symmetry, there is arbitrariness, because you did not follow a rule when selecting the points and the direction of the line. The points on the line are special points of the sphere.

If we see an asymmetry in ethical principles, we have to be cautious, because it might involve unwanted arbitrariness. Therefore, most ethical principles should not have an asymmetry. There are however two fundamental principles that do have an asymmetry, one principle in population ethics, and one in rights ethics. For those two principles, we have to check whether they involve unwanted arbitrariness. In particular, as there is arbitrariness, we have to check whether there is something unwanted with those principles.

The first asymmetry is present in population ethics. Consider the phrase: “it is always bad to bring a person into the world who has a negative welfare, but it is not always good to bring a person into the world who has a positive welfare.” This phrase contains an asymmetry, because switching the words “bad” and “negative” with the words “good” and “positive” does not give the same meaning. According to this ‘procreation asymmetry’ in population ethics, adding an extra person with a negative utility (negative preference) always lowers the aggregate utility (total welfare), but adding an extra person with a positive utility does not always increase aggregate utility.

This asymmetry is derived from one of the most basic ethical principles: the maximum self-determined relative preferences principle or variable critical level utilitarianism (and all its variations and special cases). In such theories, the aggregate utility or total welfare consists of the sum of everyone’s relative utilities, where a person’s relative utility is his or her utility (e.g. individual welfare) minus a (self-chosen) critical level. The asymmetry kicks in when we condition that the critical levels may not be negative: they should always be zero or positive. The justification for a non-negative critical level, is that if a person chooses a critical level, that person should be willing to accept a life with a utility equal to that chosen critical level. No-one is willing to accept a life with negative utility. Everyone prefers a higher utility (higher welfare, higher preference) above a lower utility, so there is an asymmetry: increasing welfare is wanted, decreasing welfare is not wanted. This asymmetry is based on what is wanted, so as a result the arbitrariness is not unwanted.

The second asymmetry is present in rights ethics. Consider the phrase: “Harming you always violates your rights, but not helping you not always violates your rights.” This phrase contains an asymmetry, because switching the words “harming” with “not helping” does not give the same meaning. According to this asymmetry in rights ethics, negative rights (not to be harmed by others, or to not help others) trump positive rights (to be helped by others or to harm others). When there is a conflict, the right not to be treated by others in some way is more important than the right to treat others in some way.

Similarly, there is an asymmetry between active and passive rights. Consider the phrase: “You have the right not to be harmed by others, but not the right to harm others.” Switching “not to be harmed by others” with “to harm others” changes the meaning. According to this asymmetry in rights ethics, passive rights (to be treated by others in some way) trump active rights (to treat others in some way).

These two asymmetries are derived from another one of the most basic ethical principles: the mere means principle or basic right not to be used against one’s will as a means to someone else’s ends. Consider four rights: the positive, active right to kill others against their will, the positive, active right to use others as means against their will, and their negative, passive counterparts: the right not to be killed by others against one’s will and the right not to be used as means by others against one’s will. I will argue that only the latter (the negative, passive right not to be used) is special. This exclusiveness breaks the symmetry with its positive, active counterpart. (We do not need to consider the more trivial positive, passive right to be killed by others, nor the negative, active right to not kill others.)

This negative, passive right not to be used against one’s will, is related to the mere means principle. It can be explained using the trolley problem. In the first trolley dilemma, called ‘the switch’, a runaway trolley is about to kill five people on the main track. The only way to save themselves, is if one of the five people pulls a switch that directs the trolley to the side track, killing one person. In the second trolley dilemma, ‘the bridge’, there is no side track, but the five people on the main track can save themselves by pulling a heavy person from a bridge (suppose they can pull a lever that topples the bridge). The heavy person falls in front of the trolley, the trolley is blocked and the person is killed.

Consider everyone having the negative, passive right not to be killed by others, even when being killed by others minimizes the number of people dying. In that case, pulling the switch and pulling the heavy person from the bridge are not allowed, because the persons on the side track and the bridge have the right not to be killed by others. (If the trolley kills the five people, they are not killed by the persons on the side track or on the bridge, because if those persons were absent, the five people would still die.) Now consider the positive, active version of this right: everyone has the right to kill others. In this case, pulling the switch and pulling the heavy person are allowed. Which of those two rights is most important?

The issue with these rights to kill and not be killed, is that there is always at least someone who prefers the absence of other people. If the one person on the side track has the negative right not to be killed, the five people on the main track prefer the absence of the one person, because then they are allowed to pull the switch. Similarly, if the five people have the positive right to kill the one person, the one person prefers the absence of the five people, because in their presence the five people could choose to kill the one person. There is a symmetry between the positive and negative rights: either A wants B to be absent, or B wants A to be absent. In other words: both the rights to kill and not be killed have costs for others: adding people who have this right might limit the freedom of other people. When the side track is empty, the five people can save themselves by pulling the switch. But adding a person with the negative right not to be killed on this side track harms the five people on the main track: they can no longer save themselves.

Every decision in the switch case is always costly or harmful to at least someone. The only option we have, is to minimize costs. So we can either choose the positive right to kill or the negative right not to be killed, depending on the situation. When harms are minimized by the positive right to kill, as in the switch dilemma, we can choose the positive right. In the switch dilemma, with the positive right only one person prefers the absence of other people, whereas with the negative right not to be killed, five people prefer the absence of only one person. So in the switch case, the positive right prevails. But due to the symmetry, if there were five people on the side track and only one person on the main track, the negative right not to be killed prevails and the one person on the main track is not allowed to pull the switch.

Now consider the positive, active right to use other people against their will as means to one’s own ends. In the switch case, this right is never violated, because even when the person on the side track is killed, that person was not used as a means. In the absence of the person, the five people could still pull the switch and be saved, so the presence of the person on the side track is not necessary. The right to use others does not determine the permissibility of pulling the switch.

The right to use others becomes non-trivial in the bridge dilemma. The presence of the heavy person on the bridge is required to save the five people. Without the person, the trolley cannot be blocked, so the heavy person is used as a means (as a trolley blocker). When the five people have the right to use others, the heavy person prefers the absence of the five people on the main track, because their presence endangers the heavy person on the bridge: they can exercise their right to use the heavy person. The five people on the other hand, prefer the presence of the heavy person: without that person, they cannot pull anyone in front of the trolley so they cannot save themselves. So again, this positive, active right to use others is harmful: if there are people who have this right, the freedom of other people shrinks.

So we are left with one right: the negative, passive right not to be used by others as means against one’s will. This right is very special, because it harms no-one. If the heavy person on the bridge has this right, the five people on the main track are not made worse off compared to the situation where the heavy person was absent. In the switch dilemma, the right not to be used by others does not determine the permissibility of pulling the switch. Even if the one person on the side track has this right, the five people on the main track do not violate this right when they pull the switch, because they do not use the person on the side track as a means.

In summary: there is a symmetry between the positive, active right to kill others and the negative, passive right not to be killed. But there is an asymmetry between the positive, active right to use others and the negative, passive right not to be used. The latter asymmetry is the result of preferences of individuals: what individuals want. We can choose the negative and passive instead of the positive and active version of the right about usage, but this choice is arbitrary. However, due to the asymmetry in preferences, this arbitrariness is not unwanted: it fits with what people can want about absence or presence of other people. In this sense, the choice for the negative right is not arbitrary: we followed to rule to choose the right that best fits people’s preferences.

Hence  we select the basic right not to be used by others against one’s will as a means to someone else’s ends. This basic right underlies the asymmetries that we see in rights ethics. First, we have the asymmetry that negative rights trump positive rights. Consider the positive right to be helped by others. This right means that others have a duty to help you. However, if you force others to help you, those persons are used against their will: their presence is necessary in order to help you, and they do not want to help you (for example because they want to help someone else instead). So their basic right is violated. The fact that you cannot force someone to help you, but you can force someone not to use you, means that your positive right to be helped by others is weak. Second, we have the asymmetry that some passive rights can trump active rights. The right not to be harmed by others is stronger than the right to harm others, when ‘harming others’ is interpreted as ‘using others as means against their will’.

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The identifiable problem effect

The identifiable victim effect is a cognitive bias (or moral illusion) where an incentive to help someone is higher when the person in need can be identified by the helper. For example, people donate more money to a charity if the donors know the identity (e.g. name) of the person that is helped, compared to a charity that helps anonymous victims (such that the donors do not know who they help).

Here I hypothesize that there is a similar cognitive bias when it comes to preventing or solving problems: the identifiable problem effect. For example, if you drive extremely fast and reckless, you know that you will risk an accident. You can have a good guess about the place and time of the accident: the more busy the place or slippery the road, the more likely the accident. The faster you drive, the sooner the accident. Being able to guess where and when an accident can occur gives you a strong incentive to drive more slowly and safely.

However, this is different in the case of a preventive car engine check. If you don’t check the engine, you cannot guess where and when an accident could occur. It is even possible that the engine is fine and you will never get an accident. In that case, checking the engine would become superfluous. If you check the engine, and you do not have an accident, you will never know whether checking the engine caused the avoidance of an accident. You cannot identify the avoided accident, you cannot tell when and where the accident could have taken place, because perhaps there was no accident.

The identifiable problem effect is the hypothesis that people have a stronger incentive to take preventive measures when the potential problem is more clearly identifiable (e.g. in terms of place and time). This effect is a cognitive bias, because it could result in taking too much preventive measures in one area or not enough preventive measures in another area.

This identifiable problem effect can have serious consequences, for examples in the area of existential risks. These are risks that could derail society, kill (almost) everyone or simply wipe out humanity. Some existential risks are identifiable. For example climate change: if greenhouse gas emissions keep rising, we can estimate when temperatures will increase to such a high level that life becomes endangered. We already see an increase in temperatures, and we have computer simulations to estimate what will happen when and where.

Compare climate change with other existential risks such as a global pandemic, a nuclear war or new technologies such as unsafe artificial superintelligence. We can invest in preventive measures, just like the car engine check, but in doing so, we will never know whether we actually prevented such a catastrophe, let alone when the catastrophe would have happened. The potential problem of a future pandemic supervirus is an unidentifiable problem: we have no idea whether, when and where that virus will strike us and kill us all. It could be the case that the problem never occurs. Therefore, it can seem that preventive measures are futile or superfluous. We will not know whether we made progress in solving the problem, because the problem is unidentifiable.

So we have two types of existential risks: the identifiable and the unidentifiable risks. Due to the identifiable problem effect, people tend to underinvest in preventive measures against the second type of existential risks. Research in artificial intelligence safety or global coordination to prevent pandemics and nuclear wars, are more neglected than e.g. climate change. This neglectedness could be very dangerous. It also means that investments in preventive measures against unidentifiable existential risks are highly valuable, even if we will never know that the preventive measures made a difference.

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My mistakes and failures

To do good in the world, I think it is crucial to learn from mistakes. In the past I made a lot of mistakes and also this website contained (and most likely still contains) mistakes. Here I present an overview of my most important mistakes and failures. The writing of this article was inspired by this Global Optimum podcast.

As I keep continue making and discovering mistakes, this overview is updated regularly. It already contains more than 20 mistakes.


Bias blind spot. I underestimated my cognitive biases, moral illusions and irrational beliefs. This is a meta-mistake: I made a mistake about how many mistakes I make.

Antidote: to correct for this mistake, I study a lot about rationality and critical thinking, I actively look for other mistakes I made, and I promote the importance of changing our minds based on good arguments and evidence.

Moral philosophy

Intrinsic value of biodiversity. This is probably my biggest moral mistake: I’ve put too much emphasis on an intrinsic value of biodiversity, integrity or naturalness of ecosystems. Related to this, I defended a deep ecological biocentric-ecocentric ethic for more than ten years. This is a kind of egocentrically imposing my own projected values of integrity and naturalness (comparable to esthetic preferences for the beauty of nature) on all sentient beings in nature, instead of prioritizing what the animals want (or can consistently want if they were well-informed).

Antidote: to correct for this mistake, I focus more on the well-being of animals, including wild animals. I intrinsically value well-being of individuals (including animals), because those individuals themselves value their own well-being, whereas nature itself does not value biodiversity, integrity or naturalness. Instead of conservation biology, I promote welfare biology: supporting scientific research for safe and effective interventions in nature to improve wild animal welfare. Hence, I support Wild Animal Initiative.

Average utilitarianism in population ethics. In my PhD-thesis in moral philosophy, I defended a kind of average utilitarianism. This population ethical theory faces a sadistic conclusion: Situation S contains N people with extreme happiness and 1 person with extreme suffering. Situation S’ contains the same N people with extreme happiness, the same 1 person, but with extreme happiness, plus extra M people with lives close to but slightly lower than extreme happiness. According to average utilitarianism, S’ is better and should be preferred, because S’ contains the highest level of average happiness. This is counterintuitive to me.

Antidote: to correct for this mistake, a formulated a variable critical level utilitarianism.


Anticapitalism. I participated in anticapitalistic actions, although there is much evidence that currently known socialist/communist systems are worse than many capitalist economies, and evidence is lacking that transforming capitalism into a new kind of good socialism is more feasible than improving capitalistic systems. Revolutions to destroy capitalism are also dangerous, with possibly many negative side effects.

Antidote: instead of criticizing capitalism, I criticize privatized economic rent (monopoly power, privatized excessive scarcity benefits) and propose fair and efficient economic market mechanisms that are compatible with capitalism.

Degrowth. I supported the degrowth movement, although degrowth cannot sufficiently reduce our environmental footprint, can be harmful (in terms of decreasing economic welfare, employment, scientific research and resilience against natural disasters, and increasing poverty and inequality) and distracts from more effective environmental solutions (in particular market mechanisms and technology).

Antidote: I focus on effective market mechanisms such as a carbon tax and funding research and development of clean energy technologies.

Interest-free money. I was very critical about the money system, stock markets and financial speculation, and supported alternative interest-free money systems. This was targeting the wrong enemy. I now see more benefits in financial markets.

Antidote: instead of promoting interest-free money, I focus on the real problem: privatized economic rent (e.g. fractional reserve banking that only allows for big banks, increasing monopoly power of banks). Positive Money promotes the idea of capturing the monopoly rent of commercial banks, by criticizing the system of fractional reserve banking.


Organic food. I promoted and bought organic food, although there are no clear health and environmental benefits but it costs much more than non-organic. Organic food has lower yields and hence a higher ecological footprint compared to conventional food. It can also have slightly higher eutrophication levels and an Environmental Impact Quotient of more toxic and less effective organic pesticides.

Antidote: instead of buying organic food, I buy the cheapest food and donate the saved money to effective charities that promote vegan food. Veganism has all the benefits that organic food incorrectly claims to have, plus many more, and with much stronger evidence.

Anti-GMO. I protested against the use of genetically modified organisms, although GMOs have many environmental and health benefits and there is a strong scientific consensus on its safety.

Antidote: instead of opposing GMOs, I support developments in new agricultural technologies, including GMOs, but also cellular agriculture, precision agriculture and vertical agriculture.

Antinuclear. I did many actions against nuclear energy, although nuclear energy has a carbon footprint and a death footprint (deaths from accidents and pollution per kWh electricity) comparable to renewable energy and much lower than fossil fuels. Eliminating nuclear power could increase the use of fossil fuels a little bit, causing more harm from climate change, accidents and pollution, and it could prevent research and development of new generations of nuclear power plants that are safer, able to treat nuclear waste and limit monopoly power of electricity producers.

Antidote: instead of criticizing nuclear energy, I focus on effective market mechanisms such as a carbon tax and funding research and development of clean energy technologies.

Human overpopulation. In my environmental activism, I spoke a lot about the problem of human overpopulation, although there is no strong scientific consensus that human overpopulation is a real risk that requires strong population control measures. Rather than a human overpopulation, we can speak of a non-human animal overpopulation problem, because basically all animal populations (with humans as a rare exception) use a high fertility reproductive strategy, which means that every new generation, a huge percentage of newborn animals die from hunger, diseases, parasites, predation and other harms that could be associated with the harms from overpopulation.

Antidote: instead of focusing on human overpopulation, I focus on wild animal welfare, promoting safe and effective means to control wild animal populations (e.g. immunocontraception or gene drives) in order to improve the welfare of all newborn animals.

Glyphosate ban. I did actions to ban the herbicide glyphosate, although glyphosate is perhaps the least toxic herbicide and a ban could increase the use of worse pesticides. For example, one study indicates that a global ban on glyphosate could result in a loss of farmers’ income and global welfare worth $7 billion a year, an increase of 12% of the Environmental impact Quotient of herbicides, an increase of 2.6 million tons of CO2 emitted per year and an extra use of 760,000 hectares of agricultural land (hence extra deforestation).

Antidote. Instead of banning glyphosate, I focus on livestock reduction, because livestock agriculture has huge environmental and health costs.

Social justice

Feminism and identity politics. I strongly believed and emphasized the notion of patriarchy, although there are many reasons to doubt the existence of a consistent patriarchal system in most Western, developed countries. I became more worried that the focus on patriarchy distracts from other, more important root causes of sexism, that the notion of male privilege is too often used as an ad hominem against men, that identity politics (and some elements of feminism) results in group discrimination such as sexism and racism.

Antidote: instead of calling myself a feminist, I feel more comfortable with calling myself an equal rights activist or an antisexist. I focus on all kinds of sexism and discrimination of both women and men.

Fair trade. I bought a lot of fair trade products, even though only a small fraction of the fair trade premium price reaches the farmers, those farmers are not the poorest of the poor, and the fair trade system could incentivize overproduction resulting in lower incomes of non-fair trade farmers.

Antidote: instead of buying fair trade, I buy the cheapest products and donate the saved money to effective development organizations recommended by GiveWell, such as GiveDirectly. Their unconditional cash transfers target the poorest of the poor, have maximum efficiency and do not create overproduction.

Boycott sweatshops. I did campaigns to boycott products made in sweatshops, although such consumerist actions have negligible impact and worsen the situation of poor people. When boycotts result in the closure of sweatshops, workers are often made worse off (becoming unemployed or having to work in worse conditions elsewhere).

Antidote: instead of boycotting sweatshops, I donate to effective antipoverty charities (recommended by GiveWell), and I support more effective economic measures to fight poverty and poor working conditions (e.g. freer migration, antitrust law to decrease the monopsony power of large companies on the labor market).

Anti-trade agreements. I demonstrated against international trade agreements, although international trade is overall beneficial in terms of economic growth and development, and trade agreements can improve the efficiency of global markets. Free trade is a net gain for society, according to an economic consensus.

Antidote: instead of limiting free trade, I support efficient trade (with corrections for market failures, such as a tax on carbon emissions) and free migration (open borders). Free migration offers many benefits, especially for immigrant workers (and workers in poor countries).

Animal welfare

Red meat reduction and ovo-vegetarian products. In lectures and writings, I focused a lot on the environmental impact of meat (which is highest for red meat) and the health risks of excessive meat consumption (which are highest for red and processed meat). I also participated in campaigns against animal suffering of cows and pigs. This could potentially result in a shift from red meat consumption to chicken meat and eggs. However, the number of animals killed and the hours of animal suffering is roughly ten times higher for chicken meat and eggs compared to beef and pig meat. Also vegetarian (non-vegan) meat substitutes that contain only a small percentage of egg-protein quickly has twice as much animal suffering than an equal-sized portion of red meat. In other words, if a reduction of red meat consumption is accompanied with only a small increase of chicken meat or eggs, or a shift to ovo-vegetarian meat substitutes, animal suffering increases.

Antidote: next to focusing on environmental and health problems of meat consumption, I prioritize reducing the consumption of chicken meat and eggs, and I’m involved with vegan corporate outreach to ask producers of vegetarian products to veganize those products. I avoid promoting ovo-vegetarian products.

Idealistic animal activism. In my early days of animal activism, I mostly had an idealistic approach, focusing on strict veganism and rigid (deontological) rules, although such an approach could easily backfire (offering bad publicity for veganism). I now moved more towards a consequentialist instead of a deontological approach of activism, focusing on the results of our actions.

Antidote: I developed a method of ‘deep canvassing for animal rights’ that is more positive towards the not-yet-vegans.

Helping predator animals. I helped as a volunteer in a wildlife rescue center, helping predator animals (birds of prey). I petitioned against shark fining, protested against tuna fishing and promoted the reintroduction of predator animals in natural parks. However, it is far from clear whether these actions improved overall wild animal welfare, because one adult predator harms and kills many other animals.

Antidote: before intervening in nature to help predators, I first support scientific research to estimate the costs and benefits (the positive and negative impact) of having more predators in nature. I focus on all wild animal suffering (including suffering of prey animals), by supporting organizations like Wild Animal Initiative.

Activism and volunteerism

Alarmism. In my environmental and climate activism, I often used pessimistic, alarmistic messages (with doom scenarios), although such messages could backfire (e.g. making people more skeptical about climate change and less motivated to engage in environmentally friendly behavior). Looking at scientific and human progress, I became more optimistic.

Antidote: instead of alarmism, I prefer effectivism, promoting effective environmentalism.

Small problem focus. I did many actions about small problems, such as actions against the use of ponies at funfairs, the cutting of trees at city streets, and advocating for bicycle lanes, city gardens, consumer boycotts of Israeli products, selling locally grown grains, local sharing initiatives,…

Antidote: instead of diving into small problem activism, I engage in effective altruism and spend much time doing cause prioritization.

Vague demands. I did a lot of actions with vague demands (e.g. anticapitalist protests, actions for sustainable agriculture).

Antidote: I became more specific in setting my objectives.

Individual behavior change. I focused a lot on individual behavior change (e.g. campaigns to drive less, recycle more, buy local, replace light bulbs, turn off stand-by,…), instead of focusing on institutional change (system change) and technologies. Spending time and money on clean energy technology developments or market mechanism campaigns (e.g. carbon taxes) can be far more effective than spending time and money on individual behavior change campaigns. Veganism is the exception: a reduction of the consumption of animal products is likely the most effective behavior change that benefits human health, the environment and the animals.

Antidote: except for vegan consumption, I no longer spend much time promoting behavior change. As for veganism, I invest in developments of animal-free products (e.g. vegan burgers, clean meat), to facilitate behavior change. I keep sustainable behavior in my personal life, because there is no cost in convincing myself to live more sustainable.


Donation spreading. I supported too many organizations a little bit, instead of a few highly effective organizations a lot. This increased the relative overhead costs of my donations.

Antidote: I focus on a few organizations and funds, e.g. Effective Altruism Funds, GiveWell, Wild Animal Initiative.

Low effective organizations. Of the many organizations I supported, I estimate that more than 2/3 are low effective, and a few are even counterproductive (e.g. anarchist and communist organizations).

Antidote: I focus on highly effective organizations. e.g. Effective Altruism Funds.

Risk aversion. In my donations, I preferred low risk, low impact organizations and projects above high risk high impact projects. This made me less effective. Most altruists are risk averse, which means that high risk high impact projects are more neglected. Therefore, it is easier to find highly effective opportunities among the high risk high impact projects. Also, pure, impartial altruism requires one to be risk neutral when it comes to helping others and saving lives, because there is no decreasing marginal utility in helping others. And when a group of altruists invest in many high risk high impact projects, many of which will fail, it does not matter which of those altruists is the lucky winner who realizes the high impact.

Antidote: I look for high risk high impact projects.

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Drie ethische basisprincipes en hun belangrijkste implicaties

Met drie ethische basisprincipes kunnen we zowat elk moreel probleem in kaart brengen en nagaan wat de beste keuzes zijn. Om de drie basisprincipes te verduidelijken, bespreek ik kort de belangrijkste implicaties: antispeciesisme, de welzijnsbevordering van wilde dieren in de natuur, en veganisme.

1.     Ongewenste willekeur vermijden

Formulering: voor elke keuze die we maken moeten we een rechtvaardigende regel kunnen geven waarvan we consistent kunnen willen dat iedereen die regel volgt in alle denkbare situaties.

Verduidelijking: als we een keuze maken (bv. de keuze voor een handeling of voor een formulering van een morele wet), dan selecteren we een optie uit een verzameling van opties. Er is sprake van willekeur wanneer we een element of deelverzameling uit een verzameling van opties kiezen zonder daarbij een selectieregel te volgen. Die willekeur is ongewenst wanneer er minstens een persoon (wezen met een eigen wil) die willekeur niet consistent kan willen, dus wanneer die willekeur niet verenigbaar is met de belangrijkste dingen die een persoon wil.

Rechtvaardiging: deze regel is een veralgemening en verfijning van de gulden regel: behandel anderen (niet) zoals je zelf (niet) behandeld wil worden. Als ik ongewenste willekeur mag hebben in mijn keuzes en mijn ethiek, dus als ik keuzes mag maken zonder rechtvaardigende regel die iedereen mag volgen, dan mag iedereen ongewenste willekeur toelaten. Dan mogen anderen willekeurige keuzes maken die ik niet consistent kan willen. Ik kan mezelf selecteren uit de verzameling van alle wezens en daarmee zeggen dat enkel ik wel dergelijk recht heb om ongewenst willekeurige keuzes te maken. Maar ik ben niet in staat een rechtvaardigende regel te geven voor deze keuze dat ik de enige zou zijn die ongewenste willekeur mag toelaten. Daarom mag ik geen ongewenste willekeur hebben in mijn ethiek.

Belangrijkste implicatie: antispeciesisme. Speciesisme is discriminatie op basis van soort en is in onze huidige samenleving de grootste vorm van discriminatie. Discriminatie van B ten opzichte van A is het slechter behandelen van B dan A op een manier die B niet kan willen, zonder het kunnen geven van een rechtvaardigende regel (dus op basis van willekeurige criteria) en zonder het tolereren van het verwisselen van posities (A behandelen zoals B en B zoals A). In geval van speciesisme formuleert men een ethisch principe (bv. dat men wezens die behoren tot de mensensoort niet mag schaden en andere wezens wel), selecteert men daarbij een bepaalde biologische categorie (namelijk de soort) uit een verzameling van biologische categorieën (die naast de soort onder andere populatie, genus, orde, klasse en stam bevat), en selecteert men een bepaalde soort (namelijk mensen) uit de verzameling van alle soorten, zonder dat men daarvoor rechtvaardigende selectieregels kan geven.

Meer lezen:

Over het antiwillekeurprincipe:






Over antidiscriminatie en antispeciesisme:



2.     Relatieve voorkeuren verhogen

Formulering: we moeten de situatie (toekomst) verkiezen waarbij de som van relatieve voorkeuren van alle personen die bestaan en gaan bestaan maximaal is.

Verduidelijking: een persoon is een voelend of willend wezen met persoonlijke ervaringen en voorkeuren. Een voorkeur meet hoe sterk die persoon een situatie verkiest. Die voorkeur is een functie van onder andere het levenswelzijn van die persoon (de som van alle positieve min alle negatieve ervaringen in diens leven), maar kan ook andere waarden bevatten die de persoon belangrijk vindt, zoals rechtvaardigheid en het respecteren van rechten van zichzelf of anderen. Een voorkeur is positief als de persoon die situatie verkiest boven een gelijkaardige situatie waarin die persoon zelf niets ervaart en wilt (of bv. niet bestaat). Een voorkeur is negatief als de persoon in die situatie liever niet had bestaan. Een relatieve voorkeur meet de eigen voorkeur ten opzichte van een vrijwillig zelf gekozen kritisch niveau. Het kritisch niveau is nooit negatief. Als de eigen voorkeur hoger is dan dat kritisch niveau, dan is de relatieve voorkeur positief en dan draagt die persoon positief bij aan de toestand van de wereld: de wereld is er beter aan toe als een persoon met een positieve relatieve voorkeur aanwezig is, en er slechter aan toe als een persoon met een negatieve relatieve voorkeur aanwezig is.

Rechtvaardiging: het maximaliseren van het totaal van ieders relatieve voorkeuren is een ethisch systeem waar men het minste tegen kan protesteren. In vergelijking met andere mogelijke ethische principes, zijn de klachten tegen dit basisprincipe minimaal, want die klachten worden gemeten als negatieve relatieve voorkeuren. Deze theorie staat bekend als het variabele kritisch niveau utilitarisme, waarbij de utiliteit van een persoon in een bepaalde situatie gelijk is aan de voorkeur van die persoon voor die situatie. Het variabel kritisch niveau utilitarisme is in staat om de meest contra-intuïtieve implicaties in de populatie-ethiek te vermijden. De populatie-ethiek houdt zich bezig met het beoordelen van situaties waarbij onze keuzes bepalen wie en hoeveel personen er in de toekomst gaan bestaan.

Belangrijkste implicatie: welzijn van wilde dieren. Hoogstwaarschijnlijk zijn veel wilde dieren in de natuur voelende wezens (personen met eigen persoonlijke ervaringen), en de kans is groot dat de meeste dieren die geboren worden een negatief leven hebben (dus eerder een voorkeur hebben om niet te bestaan, omdat hun bestaan gedomineerd wordt door negatieve ervaringen van ziekte, honger, angst, stress en lichamelijke verwondingen). Omdat er zoveel wilde dieren zijn en gaan geboren worden in de toekomst (in tegenstelling tot het toenemende welzijn bij mensen), vormen hun negatieve ervaringen waarschijnlijk het grootste leed op aarde, en dat grote probleem wordt sterk verwaarloosd. Het beste wat we nu kunnen doen, is beginnen met wetenschappelijk onderzoek naar veilige en effectieve maatregelen om het welzijn van wilde dieren in de toekomst te verhogen.

Meer lezen:

Over het variabel kritisch niveau utilitarisme en populatie-ethiek




Over dierenleed in de natuur:





3.     Lichamelijke zelfbeschikking respecteren

Formulering: we mogen niet het lichaam van een voelend (willend) wezen tegen diens wil in gebruiken als middel voor de doelen van anderen.

Verduidelijking: het basisrecht op lichamelijke zelfbeschikking is het recht om niet gebruikt te worden als louter middel. De twee woorden “louter middel” duiden op twee voorwaarden, respectievelijk: 1) een voelend wezen wordt aangezet of gedwongen iets te doen of ondergaan tegen diens wil in om een doel van iemand anders te bereiken (dat niet gedeeld wordt door het wezen zelf), en 2) het lichaam van dat voelend wezen moet noodzakelijk aanwezig zijn als middel om het doel te bereiken. Een voelend en willend wezen is een wezen dat een besef heeft van het eigen lichaam, dat via positieve en negatieve gevoelens iets wel of niet kan willen, en dat dergelijk voelend en willend vermogen nog niet definitief verloren heeft. Het basisrecht is niet noodzakelijk absoluut: als er gigantisch veel welzijn van anderen op het spel staat, kan het gerechtvaardigd zijn om het basisrecht van een persoon te schenden. Als een persoon dat wil, kan die persoon het basisrecht mee opnemen in diens relatieve voorkeur, waardoor dit derde basisprincipe opgenomen wordt in het tweede ethische basisprincipe.

Rechtvaardiging: het basisrecht op lichamelijke zelfbeschikking is een negatief recht om niet op een bepaalde manier behandeld te worden. Dat staat tegenover positieve rechten: rechten om wel iets te mogen doen, zoals het recht op vrije meningsuiting. Dit basisrecht is het enige negatieve recht dat geen kosten oplegt voor anderen: de introductie van een extra persoon met dit basisrecht belemmert niet de mogelijkheden of vrijheden van anderen om hun doelen te bereiken. Andere rechten zijn wel kostelijk voor derden. Zo kan in een moreel dilemma de loutere aanwezigheid van een persoon die het recht op leven heeft (het recht om niet gedood te worden), verhinderen dat andere personen gered kunnen worden. De loutere aanwezigheid van een persoon die enkel het basisrecht heeft (het recht om niet gebruikt te worden), is daarentegen nooit nadelig voor anderen. Het basisrecht is ook in overeenstemming met sterk gevoelde morele intuïties in talrijke morele dilemma’s, en het rechtvaardigt een vorm van partijdigheid: bij het helpen van anderen mogen we partijdig zijn ten voordele van onze dierbaren. We zijn niet gedwongen om tegen onze wil in hulp te bieden aan een derde partij ten koste van onze dierbaren in nood (zelfs niet als die hulp aan derden het totale welzijn in de wereld zou verhogen), want in dergelijk geval zouden wij gebruikt worden als louter middel. Maar we moeten wel tolereren dat iemand anders wel die derde partij (in plaats van onze dierbaren) zou helpen. Als we die hulp aan derden niet zouden tolereren, dan discrimineren we die derde partij ten opzichte van onze dierbaren (cfr. het eerste basisprincipe).

Belangrijkste implicatie: veganisme. Bij de productie en consumptie van dierlijke producten worden de lichamen van dieren tegen hun wil in gebruikt als middel voor onze doelen (met name voor voeding, kleding, vermaak,…). Gezien het zeer grote aantal betrokken dieren en het ernstige dierenleed, vormen veeteelt en visserij de grootste groep van basisrechtschendingen in de wereld. Het beste wat we kunnen doen, is veganistisch eten en veganisme promoten, onder andere via steun voor de ontwikkeling van nieuwe diervrije alternatieven voor vlees, vis, zuivel, ei, leder, bont en wol.

Meer lezen:

Over het basisrecht:



Over veganisme:




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Reducing existential risks or wild animal suffering? Part II: expected value estimate

In a previous article (part I), I wrote about two top priorities for effective altruists who are concerned about far future human and animal welfare: the reduction of existential risks (X-risks) and the reduction of wild animal suffering. Elsewhere, I gave a personal probability estimate that wild animal welfare gets priority. However, in that article I argued that the two cause areas (reduction of existential risks and wild animal suffering) are interconnected: reducing X-risks can help reduce wild animal suffering in the far future. Here I present a highly simplified model to prioritize between those two cause areas, assuming that reducing wild animal suffering is the prime objective for the far future (i.e. assuming that if humans survive the far future, and keeping in mind progress in human welfare improving technologies and institutions, human suffering would be almost eliminated).

The model is based on an expected value estimation, assuming an asymmetric suffering focused population ethic (as explained here). In other words, the prime objective is to minimize suffering, and more precisely minimize the total negative welfare (negative utility) of all wild animals who have net-negative lives (i.e. lives not worth living, with more negative than positive experiences). Hence, total suffering is defined as the total negative welfare of all animals with net-negative lives. The expected (dis)value of suffering is the total suffering times the probability that this suffering occurs in the future.

Suppose we have the choice between two options. Option 1 means we start doing research about wild animal suffering right now, such that we can sooner intervene in nature with safe and effective technologies to eliminate wild animal suffering. Option 2 means we first do research about prevention of existential risks, and wait t years (e.g. 100 years) before we switch to research about wild animal suffering (at least if we are still alive by then).

Assume that if humans go extinct and wild animals survive, those animals have to wait T years (e.g. 100 million years) before new intelligent life forms arise who are able and willing to eliminate wild animal suffering. Assume that the amount of wild animal suffering is linearly proportional to the number of years, i.e. X/x is proportional to T/t, with X and x being the amounts of wild animal suffering in T years and t years respectively.

Assume there is a critical period in the near future (e.g. 100 years), such that if humans survive that period, the probability that they will go extinct after that period is negligible. The end of that period could for example be an intelligence explosion: if the artificial superintelligence does not kill us, it is sufficiently value aligned with us such that it can effectively help us avoiding all future existential risks. The probability that humans will not go extinct and that we will invent effective technologies to eliminate wild animal suffering, is P (e.g. 90%). The probability that if we do not invest in X-risk reduction research (but we invest in wild animal suffering reduction research instead), humans will go extinct and animals will not go extinct, and if we do invest in that X-risk research, humans will not go extinct, is p. This probability is the product of the probability that there will be a potential extinction event (e.g. 10%), the probability that, given such an event, the extra research in X-risk reduction (with the resources that would otherwise have gone to wild animal suffering research) to avoid that extinction event is both necessary and sufficient to avoid human extinction (e.g. 1%) and the probability that animals will survive the extinction event even if humans do not (e.g. 1%). Hence, p is likely to be very low, because with increasing human survival capacity, it becomes less likely that an extinction event will eliminate all humans but not also all wild animals. If something powerful is able to kill all humans, it will likely also kill all animals. So the total probability p could be 0,001%.

With these assumptions, we can conclude that option 2 (doing t years of research to prevent existential risks) is better in terms of expected value of wild animal suffering reduction, if X/x>P/p. Both X and P are much larger than x and p respectively, but it is not clear whether X/x is larger than P/p. With the above estimates, for t equal to 100 years, X/x is 1 million, and P/p is 100.000, so existential risk reduction research should get priority if elimination of wild animal suffering is primarily important. However, the period that we should prioritize existential risk reduction (i.e. the number of years t) should not exceed 1000 years in this example (assuming the same probability p), because that would delay elimination of wild animal suffering with too many years.

Whether the expected value of X-risk reduction is bigger or smaller than wild animal suffering reduction, depends on many crucial considerations. Hence, it is not clear whether wild animal suffering is a smaller or bigger problem than X-risks. It is also unclear to me whether wild animal suffering is more or less tractable (solveable) than X-risks. But what we do know, is that wild animal suffering is much much more neglected than X-risks. This latter aspect favors wild animal suffering prioritization.

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Probability estimate for wild animal welfare prioritization

In this article I calculate my subjective probability estimate that the problem of wild animal suffering is the most important cause area in effective altruism. I will use a Fermi estimate to calculate lower and upper bounds of the probability that research about interventions to improve wild animal welfare should be given top priority. A Fermi estimate breaks the probability up into several factors such that the estimate of the total probability is the product of the estimates of the factors. This method is known in superforecasting to increase accuracy or predictive power.

With the lower and upper bound estimates, and a discussion of interconnectedness of cause areas, I estimate probabilities for the four major effective altruism cause areas. These probabilities can serve as allocation percentages for a donation portfolio.

(This article extends the discussion about prioritizing the reduction of existential risks versus the reduction of wild animal suffering. See here for part I and part II).

Major cause areas

Effective altruism has four major cause areas, which is also reflected in the four effective altruism funds. First, there is the meta-level cause area: community building, prioritization research and awareness raising about effective altruism. Next, there are three object-level cause areas: human welfare, animal welfare and the long-term future. Those three object-level cause areas can be better split into four, based on two considerations: time (short-term versus long-term) and target subject (human versus non-human animal).

With these two dimensions, we can create four object-level cause areas. The short-term human cause area involves increasing current generation human welfare, primarily by improving global health and human development and reducing extreme poverty. The long-term human cause area involves guaranteeing far-future human welfare, primarily by avoiding existential risks (X-risks) that could end human civilization. The short-term animal cause area involves increasing animal welfare, primarily by decreasing animal suffering in factory farming. Finally, the long-term animal cause area deals with wild animal welfare, primarily by doing research about safe and effective interventions in nature to improve far future wild animal welfare. Due to lack of effective interventions and knowledge, short-term wild animal welfare improvements are unfeasible (intractable).

There are other cause areas, such as effective environmentalism, and other target subjects, such ecosystems, plants, digital sentient entities or aliens, but these are less important: ecosystems and plants are most likely not sentient (have no subjective interests), digital sentience does not yet exist and aliens have not yet made contact with us.

Based on our beliefs and preferences, we can choose our preferred cause areas.

You should choose short-term cause areas in particular when:

  • you prefer a person-affecting population ethic (making existing people happy instead of making extra happy people),
  • you believe the population of target subjects (e.g. humans) might definitely and unavoidably go extinct in the not so far future, so attempts to improve far future welfare will be pointless,
  • you believe that increasing or maximizing happiness becomes unavoidable in the far future (for example you believe we will unavoidably develop artificial superintelligent machines that automatically solve all problems of future sentient beings), so attempts to improve far future welfare will be unnecessary, or
  • you prefer an agent-relative ethic: a moral agent is allowed to be partial towards those individuals who are known to exist by the agent (e.g. towards those individuals who exist at the time when the agent makes a choice to help).

You should choose long-term cause areas in particular when:

  • you prefer a population ethic that strongly values positive outcomes (e.g. total utilitarianism that maximizes total future happiness or preference satisfaction), and you believe that a future state with positive aggregate welfare is possible, such that you prioritize avoiding X-risks (avoiding future non-existence of many happy individuals), or
  • you prefer a population ethic with a procreation asymmetry that strongly disvalues negative outcomes (e.g. suffering focused ethics, some kinds of negative utilitarianism or variable critical level utilitarianism), and you believe that without proper interventions we get a future state with many suffering entities (with net-negative welfare), such that you prioritize avoiding S-risks (avoiding future existence of many suffering individuals).

You should choose human cause areas in particular when:

  • you prefer to be maximally sure about the level of sentience (by selecting target subjects who most strongly look like you at a neurobiological level or who can talk and clearly communicate their feelings to you),
  • you prefer the most efficient welfare improving solutions that require some minimum level of intelligence (e.g. economic market solutions that require an understanding of money, prices, property rights, incentives,…),
  • you prefer to help those who can most effectively help others (e.g. development of poor countries will increase the number of people who can do scientific research, humans have highly developed skills of cooperation, humans can design economic mechanisms that effectively create mutually beneficial situations), or
  • you believe that most humans can reach higher levels of happiness (or suffering) than non-human animals.

You should choose animal cause areas in particular when:

  • you believe sentience is more important than e.g. rationality or intelligence and you believe animals are likely to be sentient and their potential welfare levels are not extremely smaller than those of humans.

Lower bound probability estimate

In this section I perform a Fermi estimate of the lower bound of the probability that wild animal welfare (the far-future animal cause area) gets priority. The total lower bound probability is the product of the probabilities of 14 conditions. I present my personal lower bound estimates for the moral validity or factual truth of each moral and factual condition. The probability estimate of each condition is conditional on the truth or validity of all the previous conditions (e.g. given that condition 1 is valid, how likely is condition 2 valid?).

  1. No unwanted arbitrariness

Ethical systems should not contain unwanted arbitrariness such as discrimination on the basis of time, place or species. When someone exists, where someone exists and to which biological category (race, species, genus, order,…) someone belongs, is morally irrelevant.

My probability estimate (normative certainty) of this condition is >99%, which means I’m highly confident about the moral validity of this principle to avoid unwanted arbitrariness. This estimate is based on my moral intuitions about fundamental moral reasons. For example: if I am allowed to include unwanted arbitrariness in my ethic, everyone else is allowed to do so as well, even if I do not want their kinds of arbitrariness, so I cannot rationally want this.

If this condition turns out to be invalid, we are allowed to prioritize current generations or humans (the short-term human cause area).

If ethical systems have to avoid unwanted arbitrariness, animals and the far future matter, but we do not yet know in what sense or how much they matter. To solve that question, we need to know our moral values.

  1. Consequentialist ethic

Moral individualism and consequentialism are valid moral theories. This means that individual outcomes exist and are the only things that matter. An individual outcome not necessarily only includes the level of happiness, preference satisfaction or welfare of an individual, but can also include the strength of an individual rights violation or the level of autonomy and freedom of that individual. Individual outcomes include everything that the individual cares about.

My probability estimate (normative certainty) of this condition is >99%. This estimate is based on a personal preference for autonomy and avoiding arbitrariness: if I may impose my values on others, then someone else may also impose his values on me, and I cannot want that. Hence, the only things that I should morally value, are the things that are valued by others. For example I may value the well-being of a sentient individual, because that individual also cares about her own well-being. But I may not intrinsically value e.g. the naturalness of an ecosystems, the beauty of a painting or the integrity of a culture, because the ecosystem, the painting and the culture themselves do not care about anything. Similarly, a homophobic person may not value the sexual purity of a homosexual person (when he believes that homosexuality is impure), because that value is not shared by the homosexual.

If this condition turns out to be invalid, we are allowed to prioritize environmental issues, the protection of cultural traditions, and we are allowed to impose our own values on others who cannot want that. For example it allows for ecocentric values, where our (esthetic) values of naturalness and integrity of ecosystems are considered more important than the welfare of sentient wild animals. This ecocentrism results in a hands-off policy where we should not intervene in nature to increase everyone’s welfare.

If we choose a consequentialist ethic, we still have to figure out how to compare the outcomes between different individuals. If the welfare of a wild animal is incomparable to the welfare of a human, we cannot yet decide whether to prioritize wild animal welfare.

  1. Interpersonal comparability of outcomes

Outcomes (goodness or badness) of individuals can be measured and interpersonally compared to a sufficient degree that makes comparisons useful. This means that an aggregate (total) outcome exists (by aggregating individual outcomes).

My probability estimate (factual certainty) of this condition is >75%. This estimate is based on my moral judgment that considerations about fairness or equality are important and sensible, as well as on factual neurobiological (and evolutionary) similarities between sentient beings, the existence of just noticeable differences in experiences and other considerations explained here and here.

If this condition turns out to be wrong, we can choose a very narrow contractualist ethic and a welfare economics restricted to mere Pareto efficiency. Such contractualism and Pareto efficiency is usually restricted to (a subgroup of) humans, and avoids issues of equality, which means that the scope is very narrow. The contractualism can be extended to include equality of opportunity. And under slightly more general conditions, a welfare economics with a principle of fair division of resources is possible, including both Pareto efficiency and essentially envy-freeness. This means we could focus on efficient markets, equality of opportunity, fair property rights allocations, and basic rights and liberties. This is the area of short-term human welfare. However, if animals are included in the fair division of resources and basic liberties, wild animal welfare can become very important as well.

If outcomes are interpersonally comparable, we have to determine how they contribute to the aggregate outcome of all future individuals.

  1. Positive and negative outcomes

Outcomes of individuals can be positive or negative. When a situation is chosen such that the overall lifetime outcome of an individual (over the course of its life) is net-positive (e.g. more positive than negative experiences), the individual has a life worth living.

My probability estimate (factual certainty) of this condition is >99%. This estimate is based on my personal experience: I can imagine a life with so much suffering, that I would prefer non-existence (i.e. not being born), which means such a life is not worth living.

If this condition turns out to be wrong, we can exclude many population ethical theories. We do not have to worry about creating lives not worth living, so antinatalist conclusions are automatically avoided. This means avoiding X-risks becomes much more important, although improving wild animal welfare might still be important due to the large number of animals in the future.

If future individual outcomes can be negative, we have to determine whether we can avoid the existence of individuals with a negative welfare.

  1. Positivity of future total outcome

A future with a total (aggregate) negative outcome or a majority of lives not worth living, is avoidable. That means total future outcome can be made positive by our choices. When total future outcome is positive, positive experiences trump negative experiences (or lives with net-positive welfare trump lives with net-negative welfare), and most lives are worth living.

My probability estimate (factual certainty) of this condition is >95%. This estimate is based on my confidence in technological progress. If new technologies do not unavoidably result in extinction, it is not impossible that they will be used for the good, to decrease negative outcomes.

If this condition turns out to be wrong, there is one conclusion: choose for total extinction (e.g. antinatalism). If we cannot avoid a future dominated by suffering, the more future generations will be born, the more the total outcome of the future will be negative. Hence the avoidance of all future generations gets top priority.

If we can avoid aggregate negative outcomes, we have to determine how positive individual outcomes compare to negative outcomes.

  1. Validity of asymmetric, suffering focused population ethics

Some asymmetric, suffering focused population ethic is much more valid than total utilitarianism that maximizes the sum of everyone’s welfare. A suffering focused ethic is characterized by an asymmetry: when someone has a net-negative life (i.e. a negative lifetime outcome), this always implies a negative contribution to the total aggregate outcome, but when someone has a net-positive life, this does not always imply a positive contribution to the total outcome. Total utilitarianism does not have such an asymmetry. Examples of asymmetric, suffering focused ethics are some versions of negative utilitarianism, critical level utilitarianism, person-affecting views, or most generally variable critical level utilitarianism.

Total utilitarianism is susceptible to the repugnant sadistic conclusion, which is probably the most counterintuitive implication of total utilitarianism. Consider the choice between two situations. In situation A, a number of extremely happy people exist. In situation B, the same people exist and have extreme suffering (maximal misery), and a huge number of extra people exist, all with lives barely worth living (slight positive welfare). If the extra population in B is large enough, the total welfare in B becomes larger than the total welfare in A. Hence, total utilitarianism would prefer situation B, which is sadistic (there are people with extreme suffering) and repugnant (a huge number of people have lives barely worth living and no-one is very happy).

The most simple suffering focused ethic is vulnerable to the extinction conclusion: if the only objective is to minimize suffering, the best future state is the one where no-one will be born (because it may be impossible to avoid the birth of a life not worth living or a life with suffering). More nuanced suffering focused ethics do not necessarily imply this conclusion because of boundary constraints to the objective of minimizing suffering. So the condition states that there exist consistent suffering focused ethics that avoid both the repugnant sadistic conclusion of total utilitarianism and the extinction conclusion, as well as other very counterintuitive conclusions.

My probability estimate (normative certainty) of this condition is >90%. This estimate is based on the strength of my moral intuition about the sadistic repugnant conclusion, and the flexibility of variable critical level utilitarianism to avoid very counterintuitive conclusions.

If this condition turns out to be wrong, total utilitarianism can be the preferred population ethic, which means we should strongly prioritize decreasing X-risks (if that guarantees a future with more positive than negative individual outcomes), although wild animal welfare might still be important due to the large number of future wild animals.

If a suffering focused ethic is valid, we have to determine whether human or animal suffering in the future will decrease or increase.

  1. Increasing human flourishing

Human flourishing will increase and suffering will decrease in the future (if humanity does not go extinct). The number of future human lives with net-negative welfare will be small and decrease to become negligible.

My probability estimate (factual certainty) of this condition is >80%. This estimate is based on the past human trajectory: the evidence of human progress, economic growth, decrease (in absolute terms) of extreme poverty, mortality rates and violence, increase of human health, life expectancy and cooperation, welfare improving technologies,…

If this condition turns out to be wrong, we could focus on human development, anti-poverty, human health, especially if we prefer a person-affecting population ethic. However, even with increasing human suffering (decreasing flourishing), it could still be possible that the problem of wild animal suffering is bigger and hence more important.

If human flourishing will increase, we are left with animal suffering. From all anthropogenic (human-caused) animal suffering, livestock farming is the biggest problem due to the high number of livestock animals. So how does the welfare of livestock animals compare to wild animals?

  1. Livestock elimination

Livestock farming and livestock animal suffering will be eliminated in the near future (e.g. this century).

My probability estimate (factual certainty) of this condition is >90%. This estimate is based on developments in animal free food technologies (plant-based and cultivated meat) as well as increases of farm animal welfare concerns and decreases of meat consumption in many highly developed countries.

If this condition turns out to be wrong, we probably should focus more on veganism and the development of alternative foods. However, it is possible that veganism indirectly increases wild animal suffering, for example when livestock farms (e.g. grasslands) are replaced by forests and natural habitats. This means that wild animal suffering could remain important.[i]

The investments in animal free food technologies (billions of dollars by large food companies), and the campaigning by vegan organizations, means that the problem of livestock animal suffering is less neglected than the problem of wild animal suffering. If livestock farming gets eliminated, wild animal suffering becomes the biggest remaining problem of animal suffering, especially if many wild animals have net-negative welfare.

  1. Net-negative lives of wild animals

Many wild animals have lives not worth living, i.e. with a net-negative lifetime welfare.

My probability estimate (factual certainty) of this condition is >80%. This estimate is based on the high reproduction rates (r-selection population dynamics), the short lifespans of most animals, and the abundance of causes of suffering (diseases, injuries, parasitism, starvation, predation,…)

If this condition turns out to be wrong, we could focus on the welfare of the current generation (of humans or animals) or X-risk reduction. However, even if they have net-positive lives, wild animals could still have the lowest welfare levels (compared to humans), such that wild animal welfare improvements remain important.

If animals have net-negative welfare, their welfare levels can still be very small compared to humans.

  1. Non-negligible welfare of wild animals

Wild animals have sufficiently high sentience levels such that wild animal suffering is a big problem.

My probability estimate (factual certainty) of this condition is >90%. This estimate is based on e.g. brain sizes and the fact that there are orders of magnitude more wild animals than humans. So even if a smaller brain implies a smaller welfare potential, the huge number of animals means that their total suffering can be huge.

If this condition turns out to be wrong, we could prioritize human welfare (or the development of supersentient artificial intelligence with an extremely high welfare potential).

If future wild animal suffering is not negligible, there still may be other, bigger causes of suffering.

  1. Dominance of wild animal suffering

Most far future lives with net-negative welfare will be wild animals, instead of e.g. plants, digital sentient entities or computer-simulated conscious beings.

My probability estimate (factual certainty) of this condition is >90%. This estimate is based on the lack of evidence that plants are conscious, my low confidence that we can and will create huge numbers of digital sentient entities with net-negative experiences and the high probability that we can easily improve the welfare of digital sentience once it exists.

If this condition turns out to be wrong, we should focus on digital sentience welfare, and especially avoid the related S-risks (e.g. the simulation of countless digital entities that suffer).

If there are no other bigger suffering problems next to wild animal suffering, it is still possible that all attempts to improve wild animal welfare will be futile, e.g. when we go extinct.

  1. No human extinction or knowledge loss

Humans will not go extinct before we can drastically improve far future wild animal welfare. It means we do not go extinct during the upcoming technology revolutions. For example, we will survive the transition towards a world with artificial superintelligence (machines that are more generally intelligent than humans). Once this superintelligence is created, it can help us in avoiding all other kinds of X-risks, so the transition towards superintelligence can be the last important barrier for human survival.

This condition also includes the non-extinction of human knowledge. A big human catastrophe that does not result in total extinction of humanity, could still result in the loss of all gained knowledge about wild animal welfare interventions. This would mean all current investments in wild animal welfare research would become futile and survived future human generations have to start research all the way from scratch.

My probability estimate (factual certainty) of this condition is >80%. This is based on expert surveys about existential risks. It means that the probability of extinction in the transition period could be as high as 20% if more resources are spend on wild animal suffering reduction instead of X-risk reduction.

If this condition turns out to be wrong, we should focus on current generation human welfare or X-risk reduction (short-term and long-term human welfare cause areas).

If humans do not go extinct, it is not guaranteed that we will develop and invent technologies that sufficiently improve wild animal welfare. The problem of wild animal suffering can simply be unsolvable.

  1. Tractability of wild animal suffering

Crucial problems of wild animal suffering are solvable, and it is possible to make progress in the research for technologies that improve wild animal welfare. It implies that the problem of wild animal suffering is tractable, including the possibly hardest subproblems of procreation (r-selection population dynamics) and predation.

My probability estimate (factual certainty) of this condition is >95%. This estimate is based on progress in environmental sciences, human health (vaccines), genetic manipulation (gene drives), cultivated meat, artificial intelligence,… Given the past track record of inventions to improve human welfare (e.g. eradicate diseases), it is unlikely that we will never find technologies that significantly improve wild animal welfare.

If this condition turns out to be wrong, we should focus on current generation human welfare or tractable X-risk reduction.

If the problem of wild animal suffering is large, neglected and tractable, which would give it a top priority, it is still possible that other cause areas or interventions (e.g. about climate change, veganism,…) will automatically sufficiently improve wild animal welfare.

  1. No indirect interventions

There will be no other (non-wild-animal-suffering related) interventions that automatically sufficiently solve the problem of wild animal suffering.

My probability estimate (factual certainty) of this condition is >95%. This estimate is based on the apparent complexity of the problem of wild animal suffering. It is unlikely that other interventions will have larger overall positive effects on wild animal welfare, because due to the complexity, those interventions have many spillover and flow-through positive and negative side-effects.

Overall estimate of lower bound

Multiplying the above probability estimates, the lower bound of wild animal welfare being a top priority is around 25%. This is the lowest bound, because even if some of the above conditions are not met, wild animal welfare might still be a top priority because of other reasons. My lower bound estimate, when one or more of the above conditions are not met, of the probability of wild animal suffering still being a top priority, is between 0% and 25%. Hence, the total lower bound is somewhere between ¼ and ½.

Upper bound probability estimate

I will also calculate an upper bound on the importance of wild animal welfare, by calculating lower bounds for the other major effective altruism cause areas.

Consider the reduction of X-risks (the long-term human welfare cause area). I will assume the same estimates for the first three conditions (no unwanted arbitrariness, consequentialism and interpersonal comparability of welfare) as above. Next, my estimate that total utilitarianism is valid will be 10% (the conjugate of the probability that it is invalid). The probability that the total future outcome will not unavoidably be negative, is 95% as above. Given a positive future outcome and the validity of total utilitarianism, the likelihood that an X-risk is the worst outcome is more than 99%, because by far the most net-positive lives will be in the far future, and the value of all those lives will be lost with an X-risk. The probability estimate of the tractability (solvability) of X-risk reduction is 95%. Finally, the probability estimate that humanity will not go extinct, even without any investments in X-risk reductions, is 20%. Hence the likelihood that X-risk interventions will not be futile (i.e. will be necessary and have some impact), is 80%. Together, the lowest bound on X-risk reduction priority is 5%. However, there are many other situations (with other conditions being met) where X-risk reduction is a top priority. My lower bound estimate, when one or more of the above conditions are not met, of the probability of X-risk reduction still being a top priority, is between 0 and 25%.

The other major effective altruism cause areas (short-term human and animal welfare) have lower probability estimates, but are not negligible. There is also a probability that there are yet unknown important cause areas. Together, the sum of the non-wild-animal-welfare (long-term animal) cause areas put an upper bound on the likelihood of wild animal welfare being the top priority. I estimate this upper bound to be between 50% and 90%.

Hence, the wild animal welfare priority has a wide-margins likelihood between 25%-90% and a narrow-margins likelihood around 50%.

Interconnections and indirect cause areas

Even if wild animal welfare is not the major cause area, there are several interconnections between the different cause areas. The other major cause areas have positive indirect effects for wild animal welfare. This means those other cause areas gain relative importance.

Short-term animal welfare

The most important problem for short-term animal welfare, is livestock animal suffering. Decreasing livestock farming (including fish farms), by promoting and developing animal free alternatives (e.g. plant-based egg substitutes and cultivated meat), directly reduces livestock animal suffering. But this veganism has beneficial side-effects for wild animal welfare. First, if humans decrease their animal meat consumption, the cognitive dissonance between meat consumption (behavior) and animal welfare (attitude) decreases, which means that the value of animal welfare becomes less suppressed. This facilitates a moral circle expansion, where animals are included in the moral circle. Animal welfare values can spread more easily in a vegan society, which means people become more interested in wild animal welfare. Also, the development of cultivated meat can eventually benefit wild predators, saving prey animals from unnecessary suffering.

Short-term human welfare

Economic development and poverty reduction could also increase wild animal welfare, by increasing research. If people are richer, they are more willing to spend some money on interventions that improve the welfare of others, including the welfare of wild animals. Therefore, GDP-growth is important. For example, if the poorest 4/5th of the world population becomes as rich as the richest 1/5th, the investments in wild animal welfare research could increase fivefold, because currently all research is done only in the richest part of the world.

Long-term human welfare

Avoiding existential risks that could wipe out humanity, is important, because if humans go extinct, wild animals have to wait another few million years before other intelligent lifeforms evolve that are able to develop technologies for effective wild animal welfare interventions, or they have to wait for extraterrestrial beings who care about animal welfare to arrive on earth.

Artificial superintelligence is probably the biggest X-risk, but also offers the best solutions against other X-risks as well as wild animal suffering. Therefore, research in AI-safety becomes important. We avoid unwanted artificial superintelligence (with value misalignment), and become able to develop superintelligent machines that follow our value of promoting both human and animal welfare. Safe and effective interventions in nature to improve wild animal welfare will drastically improve with safe artificial superintelligence.

Summary: probability estimates of major cause areas

With the above Fermi calculations and interconnectedness considerations of cause areas, I guesstimate the following probabilities for a major cause area to be top priority:

Long-term animal welfare (in particular reducing wild animal suffering): 1/3 or higher.

Long-term human welfare (in particular reducing existential risks): 1/4.

Short-term animal welfare (in particular reducing livestock farming and fishing/aquaculture): 1/4.

Short-term human welfare (in particular reducing extreme poverty): 1/6 or lower.

Reducing wild animal suffering is the most important cause area. Unfortunately it is also by far the most neglected in the effective altruism community. I estimate that the current total worldwide workforce involved in wild animal welfare research is less than 10 full-time equivalents (with only a few organizations: Wild Animal Initiative, Animal Ethics and to a lesser degree Rethink Priorities). This is orders of magnitudes smaller than the attention for X-risk reduction, veganism or human development.

The probability guesstimates can be used as allocation percentages for a donation portfolio (or for donation allocations at EA Funds).


[i] If insects are sentient, it is not yet clear whether grassland for livestock really has less animal suffering than, for example, a forest. Also on grassland there are birds of prey, wasps, insect parasites and other animals that cause suffering, as well as diseases, food shortages,… Forests could produce more food and offer more protection for animals, but can also increase animal abundance and hence the number of animals with lives not worth living. So with livestock farming we have a situation of directly visible harm and much much greater indirect, invisible harm. With vegan agriculture we have more nature, which means we do not have direct animal harm but we still have very large indirect, invisible harm. We do not know which of the two situations has the least indirect harm. We could then use a provisional rule of thumb to limit known, direct, visible harm and therefore opt for veganism. This is reasonable: we have four numbers: x (direct harm of livestock animals), X (suffering of wild animals in nature in a world with livestock farming), y (direct harm with veganism) and Y (suffering of wild animals in nature in a vegan world). We know for sure that y is 0 and x is bigger than y, but we do not know whether X is bigger than Y. With this knowledge, our subjective probability estimate that y+Y is less than  x+X is strictly greater than 50%. Even if it is 50,0001%, it is still reasonable to opt for the full 100% for y+Y (i.e. veganism). Suppose a coin has a chance of 50,0001% to be heads and you can guess a million times. Most people believe the best strategy is to alternately guess heads and tails with 500001 heads, but guessing heads a million times is better. In any case, the value of information about the relative sizes of X and Y is very high, so if we promote veganism, we should do much more research to estimate the indirect harms suffered by wild animals.

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