My cause prioritization


The search for the most important causes is essential for an effective altruist who wants to do the most good. Here I present my cause prioritization, starting from a moral theory that deals with problems in population ethics (involving future generations). Given our current knowledge in welfare biology, I argue that healthy humans might have the best lives worth living. However, most humans consume animal products and therefore contribute to the existence of exploited animals with lives not worth living. As a result, promoting veganism, animal rights and antispeciesism is a first cause area with top priority. The moral theory of maximizing relative preferences also gives a strong priority to reducing catastrophic risks, in particular S-risks (suffering risks) where futures are created that contain huge numbers of sentient beings with lives not worth living. Artificial intelligence is unique in the sense that it can create the biggest S-risks. Therefore, a second cause area with top priority is AI-safety research, in particular solving the value alignment problem such that AI-machines have the correct values to avoid S-risks.


Population ethics

For effective altruists who want to do the most good, cause prioritization is crucial. To find the most important causes, we first have to deal with population ethics that studies the goodness of moral choices when our choices determine who will exist in the future. This is important, because we must also be concerned about people in the far future who do not yet exist and may never exist when we make other choices.

My starting point is the maximum self-determined relative preferences principle. Suppose we choose a specific situation S. In that situation, there are a number of individuals who exist or will exist in the future. Each of those individuals has his or her own relative preference: the preferences for situation S relative to a reference preference that the individual has in situation S. This preference can be a complex function of everything the individual values, such as well-being or happiness. For example: if everyone’s preference function is a concave function of well-being, we get a prioritarian theory that says that we should improve everyone’s well-being, giving priority to the worst-off people who have the lowest levels of well-being.

Suppose an individual exists in situation S and in this situation, he or she strongly prefers situation S with a preference or utility equal to 100 utility units. This individual can also choose his or her own reference preference (hence the self-determination), which can be (but need not be) the preference for another situation, such as the most preferred situation M. That individual in situation S might have a preference for his or her most preferred situation equal to 1000 utility units. The self-determined relative preference of that individual in situation S equals -900 utility units. In this case, the relative preference is negative, which means it measures a kind of complaint: in situation S the individual is complaining with a strength of 900 utility units that situation M was not chosen. Similarly, the individual can choose the empty situation E where no-one exists as a reference, for which he or she has a preference of 0 utility units. The relative preference now equals 100 utility units. This value is now positive, which means it measures a kind of gratitude: in situation S the individual is grateful with a strength of 100 utility units that situation S instead of E was chosen.

The maximum relative preferences principle states that we should choose the situation where the sum of everyone’s relative preferences, measured in utility units, is maximum. This principle unifies different theories or views in population ethics. The reference preferences of most people gravitate towards two important possibilities (or combinations of them): 0 or a conditional maximum. All the individuals can determine their own reference preferences, but what are the implications if everyone had the same reference preference?

First, suppose everyone’s reference preference is 0, which corresponds with the empty situation where no-one exists. In this case, the maximum relative preferences principle becomes a kind of sum utilitarianism, also known as the total view, where we simply maximize the total of preference satisfaction. Suppose in situation 1 a number of maximally happy people exist, with a total gratitude of 1000 utility units. In situation 2, those people have maximally miserable lives, with a total complaint of -1000 utility units (which means their lives are not worth living), but there is a huge population of extra people, each with a small gratitude of 1 utility unit. If the size of this second population is large enough, the total relative preferences in situation 2 becomes higher than in situation 1, which means situation 2 should be selected. The sum of the small gratitudes of the extra people can trump the complaints of the miserable people. For some people, this seems counter-intuitive, a kind of sadistic conclusion that prefers a situation where some people have miserable lives.

Second, suppose everyone’s reference preference is their conditional maximum. That means that everyone has a complaint, and our maximum relative preferences principle becomes a minimum complaint theory where we have to choose the situation that minimizes the total complaint. This is a kind of negative utilitarianism, also known as a person affecting view. It is closely related, but not exactly similar, to suffering-focused ethics, antifrustrationism and critical level utilitarianism in population ethics. The important difference with those related theories lies in the conditionality of the maximum reference preference. Suppose you have a preference of 100 utility units for situation S, and 1000 utility units for situation M, and I have the reverse preferences: 100 for M and 1000 for S. Both situations S and M contain a complaint of at least one person. The only situation that minimizes complaints, is the empty situation E where we don’t exist. However, we both have positive preferences in situations S and M. So I can decide not to complain in situation M. It is as if in situation M, I take that situation for my reference preference, which means my self-determined relative preference becomes 0 instead of -900, and situation M can be chosen.

The total view and the person affecting view are the two most dominant views in population ethics. The first theory roughly says that we have to make happy people and the second says that we have to make people happy. This difference is important when we face existential risks. Suppose in one possible future, there will be thousands of generations with billions of people. In the second future there will be a global catastrophe that kills everyone who currently exists. In that second situation, there will be no-one in the future. In that situation, there is of course a harm done to the current generation of people who die. But is the non-existence of the possible future people also a harm? According to the total view, the harm is immensely big, because if the people in the future would have positive preferences (lives worth living), their total gratitude would be enormous; much higher than all the possible complaints and gratitudes of the current generation.

So according to the total view, avoiding this existential risk has by far the highest priority (at least if the possible people in the future have positive preferences for their existence). But according to the person affecting view, the non-existing people in the second future are not harmed and do not complain. For a person who does not exist, the relative preference is always 0, so there is no complaint (and no gratitude). The future where people do not exist is neither bad nor good for those non-existing people, because those non-existing people are not affected. That is why this theory is called the person affecting view. Hence, the person affecting view gives a higher priority to the preferences of the existing population (the people who can be affected because they exist or will exist in all the situations that we can choose). For the person affecting view, the top priority is avoiding negative relative preferences. In particular this means avoiding the existence of individuals who have lives not worth living.

As each individual can determine his or her own reference preference, which basically means that each individual can determine which population ethics theory should be applied to him or her, we will have a complex combination of the total view and the person affecting view. The gratitudes of the existing people in the future will have some weight. (There may be individuals who are indifferent between the population ethical views or who do not have a clear reference preference. In that case, we are allowed to determine their reference preferences.)

Welfare biology

Because at least some people choose a conditional maximum as their reference preference, we have to give some weight to the person affecting view in population ethics. In that case, we have a priority to avoid the existence of individuals with lives not worth living. Here we face the problem of wild animal suffering. It is possible that some animals in nature have lives not worth living, because their lives are full of negative experiences due to hunger, diseases, injuries, parasites and predators. Especially the animals with an r-selection reproductive strategy have a problem: these animals have a lot of offspring (the population has a high rate of reproduction, hence the name ‘r-selection’), and only a few of them survive long enough to reproduce themselves. Most lives of those animals are very short and probably miserable. We are not likely to see the majority of those animals, because they will die and be eaten quickly.

A better reproductive strategy in terms of well-being, is K-selection: having few offspring with long lives and high survival rates. If a life is long, it is more likely to be positive because it has proportionally fewer negative experiences of hunger or deadly diseases. Only humans are very close to a perfect K-selection: the average fertility rate of a woman is 2,5 children, and this rate is decreasing and expected to reach 2 children in the second halve of this century. When it reaches 2 children per woman, and when all children survive till they reproduce, the human population becomes stable. Every human can have a full live. (As lifespan increases, the fertility rate can drop below 2 children per woman.)

According to the person affecting view, we have to give priority to avoiding r-selection and promoting K-selection. Perhaps with genetic manipulation (e.g. gene drives), we can turn every population into K-selection (where female animals have on average two offspring) and make sure that all animals have long healthy lives. But for the moment, only humans are about to reach the ideal K-selection reproduction.

Healthy humans have other advantages: they have complex preferences and strong personal identities over time, which means they can have potentially high levels of lifetime well-being when their preferences are satisfied. So it is possible that humans can have larger relative preferences than non-human animals. Most humans can also clearly communicate their preferences: it is easier to determine the levels of well-being of humans who can self-consciously think and speak than the levels of well-being of non-human animals who can only communicate their preferences in very indirect ways through behavior. Estimating the well-being or relative preferences of wild animals is very difficult and may require accurate brain scans. We can be very confident that the lives of healthy humans are worth living, but not confident at all that the life of an average wild animal is worth living.

The above implies that we can give a priority to saving and helping humans. This preference for healthy humans (increasing the relative number of healthy humans) is not speciesism, because the basic criteria to derive this preference (e.g. the level of personal identity over time, the level of communication and the level of K-selection) did not refer to species membership. The above discussion did not use the word ‘species’ at all. Given our current state of knowledge, a preference for healthy humans is most likely to satisfy the maximum relative preferences principle.

Pros and cons of human population growth

As explained above, helping humans means increasing K-selection in the world. The more individuals who belong to a K-selection population, the better. However, there are also problems with human population growth. More humans means more competition for scarce resources, more people who can invent dangerous technologies, more greenhouse gas emissions, higher likelihood of spreading of dangerous viruses. These things increase existential risks. But it can also mean more mutually beneficial situations through trade and cooperation, more inventions of good technologies, higher likelihood of resistance against dangerous viruses.

However, there is one very big disadvantage of giving priority to humans: most humans consume animal products. Buying animal products gives an incentive to breed animals who have lives not worth living in e.g. factory farms. Fighting poverty and promoting economic development might increase animal suffering: a $1,000 increase in per capita GDP in the poorest countries implies an increased consumption of 1.7 kg of meat per person per year. Saving the life of a human omnivore means a consumption of about 30 kg of meat.

It is difficult to estimate the total costs and benefits of further human population growth. Give the consumption of animal products, I tend towards the conclusion that decreasing human population growth is valuable, but only if it is done in a way that has other cobenefits. Avoiding unwanted pregnancies through family planning is the only strategy that has a lot of cobenefits in terms of women’s rights, health of newborn children, environmental impact reduction and poverty reduction. The benefit-cost ratio of family planning is high. This means that family planning may also be consistent with the total view in population ethics, even if fewer happy people might come into existence. Finally by reducing the fertility rate, family planning is a means to reach perfect K-selection. Therefore, I give a low priority to family planning by supporting organizations such as Marie Stopes International.

Cause area: veganism and antidiscrimination

As helping humans involves a risk of increasing animal suffering, I give a high priority to promoting veganism, animal rights and antispeciesism. According to some thought experiments, we can conclude that most animals in agriculture and aquaculture have lives not worth living, so creating those lives violates both the person affecting view and the total view in population ethics. Promoting veganism is a more neglected area than improving human health and well-being.

Furthermore, veganism also has many cobenefits in terms of improved human health: less chronic diseases due to healthier diets, less health impact from climate change due to lower greenhouse gas emissions, less malnutrition due to lower food prices for the poorest people, and less health risks from pollution, zoonotic viruses and antibiotic resistant bacteria.

Veganism also facilitates spreading the value of antidiscrimination. Speciesism is an example of discrimination. If people consume animal products, a cognitive dissonance prevents them from valuing animals as equal to humans. When they eat vegan, this cognitive dissonance diminishes and they are more open to the value of antispeciesism. The interspecies model of prejudice predicts that a decrease in speciesism results in a decrease in racism, i.e. a decrease of prejudice against other groups of people. Antispeciesism is also necessary to start scientific research about wild animal suffering and to find safe and effective means to intervene in nature to improve wild animal well-being. And finally, antispeciesism becomes important when it comes to the development of artificial general intelligence and superintelligence. If we create superintelligent AI machines and implement them with our own speciesist goals, even more animals can be exploited by AI machines for many years in the future.

The cause area of veganism is also relatively neglected and tractable, which means effective altruists have a lot of high impact opportunities in this area. Effective vegan advocacy, perhaps with deep canvassing, is promising. But clean meat, and more generally tissue engineering, appear to be very promising as well. With these technologies, we can create animal products without using animals. It might also be a crucial technology for wild animal suffering reduction, as it can provide a food alternative for predators. The tissue engineering technology can also be used to extend life and replace a lot of animal experimentation. Therefore, I support the Good Food Institute and to a lesser degree the Methuselah Foundation.

Catastrophic risks

There are several possible extinction risks (X-risks) where everyone dies: asteroid impacts, supervolcano eruptions, pandemic viruses, runaway global warming, global nuclear war, dangerous nanotechnology. According to the total view of population ethics, extinction of sentient and intelligent life is a tragedy, because it means a lot of future preference satisfaction (well-being, happiness) is lost. Hence, extinction prevention (X-risk reduction) gets a top priority.

From a person affecting view, extinction is less bad, because with extinction, non-existent future beings cannot complain and wild animals with lives not worth living will no longer be born, so future complaints will be avoided. Extinction is only bad for those of the current generations who value a continued existence in the far future, and especially for the last generation, because most extinction scenarios involve suffering when everyone dies.

But there is a class of catastrophic risks that is even worse than X-risks: S-risks or suffering risks, where the future contains huge populations of sentient beings with lives full of misery. This is worse than extinction, because an S-risk is terrible both from a total view as well as from a person affecting view.

An example of an S-risk is space colonization where we export wild animal suffering and livestock farming: the number of animals with lives not worth living will multiply when other planets are colonized. Before we start with space colonization, we should first adopt veganism and antispeciesist values such that we will not export and multiply animal suffering.

Pros and cons of AI-development

Next to tissue engineering – creating organic bodies – another breakthrough technology of this century is artificial intelligence – creating intelligent minds. With further developments in artificial intelligence, we can better solve the problems of wild animal suffering and human suffering. The potential positive impact of AI is huge. But this technology is also uniquely risky.

First, AI generates an X-risk. Superintelligent AI-machines are more powerful than humans. If the values of these AI-machines are not aligned with the values of humans, AI machines may outcompete humans. This is the important value alignment problem in AI safety research. Developing safe AI is crucial, because we will never be smart enough to control the first superintelligent machines that are smarter than us.

But AI is unique because it also creates S-risks. AI might speed up space colonization, exporting the exploitation of sentient beings to other planets. AI might use humans and animals as slaves, keeping newborn sentient beings in misery. And worse of all: AI might perform virtual reality simulations containing lots of sentient beings in the simulated worlds. The number of sentient beings who suffer in those simulated worlds can be huge.

Just like intelligent humans could dominate sentient animals, superintelligent AI-machines can dominate intelligent sentient beings both in the real world as well as in simulated worlds. Just like the domination of sentient animals by intelligent humans led to a vast increase of the number of exploited animals with lives not worth living, the domination of real and simulated intelligent people by superintelligent AI-machines can result in a vast increase of the number of exploited people with lives not worth living. The S-risk of AI might be the exponent of the S-risk of a perpetual livestock farming. For the animals, livestock farming is an Eternal Treblinka. But for the future generations, AI-machines might create a new, bigger Eternal Treblinka. Both from a total view, but especially from a person affecting view (a downside focused ethics), such S-risks from AI are the worst possible outcomes and we have a top priority to avoid such risks.

Cause area: AI-safety and value alignment

The above brings us to the second cause area: AI-safety. A first strategy is to slow down AI-development research. This involves improving international cooperation and improving institutions to better regulate AI research. However, AI has potential huge benefits and really slowing down research on a global scale is difficult. There is a collective action problem: if we slow down our AI-research, we have to make sure that everyone else also slows down their research, otherwise other AI-researchers can gain a dangerous advantage. Hence, slowing down research is less feasible or tractable. Therefore, I give a lower priority to this strategy.

A second strategy therefore might be to speed up AI-safety research, in particular solving the value alignment problem: how can we implement good values in AI-algorithms? This gets a top priority, because this area is also highly neglected compared to other cause areas. This strategy doesn’t suffer from a collective action problem: if we learn from our research how to make AI safer, everyone else can learn from us and adopt our safety measures.

Here we also see a link with the abovementioned cause area: promoting values such as antidiscrimination. We should not implement discrimination such as speciesism or substratism in AI-machines. Substratism is a kind of discrimination where beings with one type of substrate (e.g. electronic computers) are considered more important than beings with other substrates (e.g. organic brains). AI-machines should not discriminate organic life forms or simulated beings. If we keep discriminating animals and we develop AI-machines, what chance do we have that those machines do not discriminate others?

To improve AI-safety research, I support MIRI and the Future of Humanity Institute.

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Thought experiment: which dream do you prefer?

Imagine, before you go to sleep, I offer you a choice between different pills. If you take the black pill, you will not have a dream tonight. You will remain in a deep, unconscious sleep without experiences. There are no further side effects.

If you take the blue pill, you will dream that you are an animal in the livestock industry. As most livestock animals are chickens, you will experience a random 15 minutes of the life of a chicken, such as being on a factory farm or slaughtered in a slaughterhouse. You will experience everything the chicken can experience, such as fear or pain. You will most likely not experience things that chickens are most likely not able to experience, such as higher levels of self-consciousness, rational thought, the concept of death, the feeling of getting married or preferences for a distant future. The mental capacities you have in that dream will likely be at the level of a typical dream. When someone tries to kill you, you will feel fear, but you don’t have an abstract notion of death.

If you take the yellow pill, you will have a very lucid dream about a random experience that could happen in your life, such as watching a new movie, having lunch or meeting a friend. In this dream, you will experience everything at the same level of lucidity or consciousness as when you are fully awake and self-conscious. Or similarly, taking this pill is equivalent to having 15 minutes less sleep without feeling more tired.

If you take the green pill, you will have a random 15 minutes experience of a randomly selected wild vertebrate animal such as a bird. The level of experience will be the same as what that animal can experience. You might feel hungry, feel the fear of a predator attacking you, feel the joy of playing,…

If you take the brown pill, you will have a random 15 minutes experience of a randomly selected wild invertebrate animal such as an insect. The level of experience will be the same as what that animal can experience.

Now the question is: how much are you willing to pay or receive to take one of those pills, if you are maximally informed about the lives of livestock animals and wild animals? The amount of money for taking the black pill will be your reference point. It will be close or at 0 dollars. If you want to pay more than this reference point for taking the yellow pill, it means that an average experience of your life is positive, which is an indicator that your life is worth living. Similarly, if you want to pay less than the reference point for taking the blue pill, it means that most livestock animals have lives dominated by negative experiences, which is an indicator that their lives are not worth living. You would rather not be born than being born as a chicken on a factory farm.

At my current level of knowledge and understanding of factory farms, wild nature and animal sentience, my personal preferences in terms of willingness to pay are as follows: 0$ for the black pill, 0,5$ for the yellow pill, -50$ for the blue pill (i.e. I would take the blue pill if I receive 50$), -5$ for the green pill and -0,1$ for the brown pill. This means that I consider my life as worth living, but the life of a livestock chicken as very negative, and the lives of wild animals on average as slightly not worth living. I am doubtful about the subjective experiences of insects, so that is why I am willing to receive a small amount of money for taking the brown pill.

Who will pay more for the blue pill than the black pill? My guess is almost no-one who is informed about livestock farming. If we do not want to pay more, that means we should not bring factory farm chickens into existence. And I guess even the light blue pill, having an experience of e.g. a free range chicken, will be worth less than the black pill.

Who will pay more for the green and brown pills than the black pill? My guess is almost no-one who studied the welfare of wild animals.  If we do not want to pay more, that means we should do scientific research how to safely and effectively intervene in nature to improve wild animal well-being.

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One day car free

One day car freeIn a previous post I wrote about the benefits of eating vegan for one day. Here I discuss the benefits of living car free for one day. In particular: what if an average person in Belgium replaces car transport by public transport (train and bus) for all distances longer than 10 km and car by bike for all distances shorter than 10 km? How much harm is caused by just those few minutes a day that one uses a car? What is avoided each day by being car free?

Short summary: a car free day saves 20 hours of the life of a vertebrate animal due to less road kill, almost 50 minutes of your own life due to less chronic diseases and car accidents and more than 20 minutes of someone else’s life due to less health impact from global warming, air pollution and car accidents.

Note 1: I exclude the environmental impacts of production of the cars and construction of the roads.

Note 2: for each result I also give my epistemic status, i.e. my level of confidence in the results.

Note 3: the results are expectation values.

Note 4: unless otherwise stated, the values below correspond to the harm done by 1 car user per day, who travels 30 km by car per day.


Harm to the animals

The death of 2 vertebrate animals per 1000 car users per day [Epistemic status: moderate]. For one car user, this corresponds with the loss of 20 hours of the life of a vertebrate wild animal (toad, bird, fox,…) [Epistemic status: low]


Harm to the environment

The emissions of 5 kg CO2. [Epistemic status: high] These emissions contribute to climate change and generate a health cost on future generations (diarrhea, malnutrition due to harvesting loss, cardiovascular disease due to heat waves, malaria due to the spread of mosquitoes by higher temperatures and floods due to extreme weather events and sea level rise), resulting in an expected 10 minutes shortening of someone else’s life in the near future. [Epistemic status: very low]


Harm to the human population

The emissions of 2 gram particulate matter of which almost 50% is PM2,5. [Epistemic status: high] Together with other forms of air pollution, this corresponds with a 10 minutes shortening of someone’s life due to human toxicity of pollutants (e.g. respiratory diseases). [Epistemic status: very low]

The death of 37 non-motorized road users per billion car users due to car accidents. [Epistemic status: high] For 1 car user, this corresponds with a 1 minute shortening of the life of a pedestrian or cyclist. [Epistemic status: low]


Harm to your health (as a car user)

The loss of 0,25 hours of physical activity (cycling). [Epistemic status: high] This lack of activity results in a higher risk for chronic diseases (e.g. cardiovascular diseases), corresponding with an expected 45 minutes shortening of your life. [Epistemic status: low]

The death of 80 passengers (including car drivers) per billion car users per day [Epistemic status: high]. This corresponds with an expected 2 minutes shortening of your life. [Epistemic status: low]


Calculations and sources

Average distance travelled by car in Belgium is 30 km per person per day, of which 5 km for short distances less than 10 km. (Mobiel Vlaanderen, Onderzoek Verplaatsingsgedrag Vlaanderen 5.1 (2015-2016) This means a car free day involves 5 km extra cycling and 25 km extra public transport.


For the animals

Road kill in Belgium involves 24000 animals per day. Assuming all these deaths comes from passenger cars, this equals 0,00007 animals killed per km car use. An animal killed by a car is assumed to lose 1 year of life.


For the environment

Total emissions for passenger car transport in Flanders is 2,2 ton CO2e per person per year. (Vercalsteren A., Boonen K., Christis M., Dams Y., Dils E., Geerken T. & Van der Linden A. (VITO), Vander Putten E. (VMM) (2017), Koolstofvoetafdruk van de Vlaamse consumptie, studie uitgevoerd in opdracht van de Vlaamse Milieumaatschappij, MIRA, MIRA/2017/03, VITO, VITO/2017/SMAT/R.) CO2 emissions from public transport per passengerkilometer are assumed to be 1/3 of the car emissions.

The health cost due to climate change, per unit CO2 emitted is 3,5 DALYs (disability adjusted life years) per 1000 ton CO2 according to the egalitarian perspective in the ReCiPe-model (Goedkoop M. e.a. (2009). ReCiPe 2008. A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level. Report I: Characterisation. Ministry of Housing, Spatial Planning and Environment, the Netherlands.) This corresponds with the loss of 1,8 healthy life years per kg CO2e.


For the human population

Particulate matter emissions from road traffic in Flanders are 2100 ton PM2,5 and 3000 ton PM10, for a population of 6,3 million car users. (VMM (2016). Lozingen in de lucht 2000-2016).

Loss of healthy life years due to particulate matter and human toxicity of air pollution from 1 km driving by average car, is 0,0000009 DALY/km, which equals 0,5 minutes/km. Emissions from public transport per passengerkilometer are assumed to be 1/3 of the car emissions.

There are 640 human deaths by road accidents in Belgium in 2016, of which 23% pedestrian and cyclists. I assume all deaths come from car accidents (i.e. no truck accidents). That is 4×10^-8 pedestrians and cyclists killed per car user per day. Death by accidents results in an average of 40 years of life lost.


For your health

Physical activity for 20 minutes saves 2 microlives, which equals a 1 hour longer life. (Spiegelhalter D. (2012). Using speed of ageing and “microlives” to communicate the effects of lifetime habits and environment, Britisch Medical Journal, 345:e8676). 5 km cycling at 20 km/hour equals 0,25 hours physical activity.

There are 640 deaths by road accidents in Belgium in 2016, of which 50% drivers and passengers. That is 8×10^-8 pedestrians and cyclists killed per car user per day. Death by accidents results in an average of 40 years of life lost.


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Wolvin Naya toont wispelturigheid van ons moreel kompas

Opiniestuk verschenen in De Morgen, 26-01-18.

De tijd van Roodkapje en de boze wolf is voorbij. Vroeger werden wolven verafschuwd, nu zijn ze beschermd en staat er een celstraf van 5 jaar op het doodschieten van wolvin Naya. Toch roept de aanwezigheid van een wolf in Vlaanderen veel vragen op voor moraalfilosofen. Onze houding ten opzichte van dieren is behoorlijk wispelturig en inconsistent.

Welke morele waarden spelen hier mee? Allereerst is er het dierenwelzijn. Kogels afvuren naar Naya, dat is voor haar zeer pijnlijk. Maar Naya veroorzaakt zelf leed door schapen te doden. Is het leven van een wolf dan meer waard dan dat van meerdere schapen? Is het leed van een schaap minder erg? Een psychologisch mechanisme zaait nog meer verwarring in ons moreel denken: naamgeving. Omdat we Naya een naam gaven, beschouwen we haar sneller als een persoon. Waarom lezen we nergens de namen van de schapen die doodgebeten werden? Enkele jaren geleden werd in Afrika Cecil de leeuw doodgeschoten, waarna de jager moest onderduiken. Hoe heetten de zebra’s die door Cecil gedood werden? Waarom zou het ene dier wel en het andere geen naam mogen hebben?

Naast dierenwelzijn zijn er nog andere waarden die zoals de flippers in een flipperkast ons moreel denken verstoren. Bijvoorbeeld zeldzaamheid: de wolf is zeldzaam en daarom beschermd. Eigenlijk is dat hetzelfde als zeggen: “Naya, zorg maar dat je zeldzaam blijft. En schapen, pech voor jullie dat jullie met zovelen zijn.” En wat als Naya mensen had gedood, die nog talrijker zijn dan schapen?

Een derde waarde is het respect voor de natuurlijke orde. Omdat roofdieren bovenaan in de voedselketen staan, zijn we sneller geneigd hen een hogere morele status toe te dichten. Maar dit respect voor een natuurlijke orde wringt langs alle kanten met ons rechtvaardigheidsgevoel. Als Naya mensen had gedood, dan hechten we plots geen belang meer aan die natuurlijke orde. Moraalfilosofen zijn er nog steeds niet in geslaagd om een duidelijk en consistent verhaal te maken van het idee om natuurlijke orde te respecteren.

Als een schapenboer zijn schapen zou doden zoals Naya doet, dan is dat strafbaar. Dat doodbijten is niet bepaald volgens de regels van verdoofd slachten. We hebben dan de morele intuïtie dat dierenleed veroorzaakt door een mens erger is dan dierenleed veroorzaakt door een wild dier. Maar deze morele intuïtie is eigenlijk een morele illusie, want leed is leed voor het schaap. Zeggen dat gedood worden door een mens erger is dan gedood worden door een wolf, is willekeur.

Waarschijnlijk zijn het waarderen van zeldzaamheid en natuurlijke orde ook morele illusies. Ik kan zowel het welzijn van een dier als de orde van de natuur belangrijk vinden, maar er is een verschil: naast mij is er altijd nog iemand anders, namelijk dat dier zelf, dat diens welzijn belangrijk vindt. Maar van de natuur kunnen we niet zeggen dat die een bepaalde orde belangrijk vindt. De natuur zelf waardeert niets. Als ik waarde toeken aan de natuur, dan is dat niets meer dan een projectie van mijn eigen waarden. Vergelijk het met een schilderij: ik kan dat mooi vinden, maar het schilderij zelf interesseert zich niet in schoonheid.

We mogen geen overhaaste conclusies trekken. Wie in bovenstaande een pleidooi leest om Naya te doden, wordt gebuisd op het examen moraalfilosofie. Moraalfilosofen hebben een belangrijke taak om onze morele illusies te doorprikken en om samenhangende en consistente morele regels te formuleren. Ik vermoed dat waarden zoals welzijn en universele rechten gaan domineren omdat voelende wezens die waarden zelf waarderen en ze dus niet louter onze projecties zijn. Wolvin Naya is een interessante case study om na te denken over het welzijn en de rechten van wilde dieren.

Stijn Bruers is moraalfilosoof en auteur van Morele Illusies


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Rational democracy and futarchy

This article explains how rational democracy and futarchy, summarized as “voting on values, betting on beliefs”, is a promising solution to the central problem in politics and ethics: moral and empirical uncertainty.

Rational ethics can be summarized with the slogan: “accurate in beliefs, effective in means, coherent in ends”. We start with the ends: our moral values. These values can be expressed in ethical rules or principles, such as the principle to maximize well-being. Our ends are coherent if they do not contain unwanted arbitrariness. Unwanted arbitrariness means making a choice whereby the consequences are unwanted by at least one individual (i.e. they cannot be consistently preferred by everyone) and the justification of that choice is not based on a rule. The latter condition means the choice is arbitrary. Examples of unwanted arbitrariness are discrimination between individuals, inconsistencies between ethical principles and ambiguities in moral values.

After determining the ends, we need effective means to reach those ends, and in order to find those means, we need accurate beliefs about the world. Now we face the central problem in ethics and politics: how to deal with moral and empirical uncertainty? Moral uncertainty is uncertainty about moral values: which ends or values are the correct ones? Empirical uncertainty is uncertainty about empirical facts: which beliefs about the world are the correct ones? The solution to this problem of moral and empirical uncertainty in politics is rational democracy.

In our current democratic system, political parties are characterized by political ideologies which contain a mixture of moral values and beliefs about empirical facts. This makes the choice or vote for most preferred moral values, most effective means and most reliable beliefs almost impossible, and it increases the risk of politicians being irrational and biased due to their identification with ideologies that distort their judgments about policies. So we first have to disentangle the moral values from the empirical facts.


Voting on values (the parliamentary model for moral uncertainty)

There are many possible coherent ethical systems, such as a deontological rights ethic, a consequentialist utilitarian welfare ethic, a libertarian ethic or pluralist ethics that combine several ethical principles (see this example). We have a moral uncertainty about which ethical system is correct. In a sense, all coherent systems are equally valid: I cannot give reasons why my coherent ethical system would be better than yours.

Nick Bostrom proposed a Parliamentary Model to deal with this kind of moral uncertainty. Here I take this idea literally: political parties should be primarily defined by their ethical systems. A political party corresponds with a cluster of similar ethical principles. For example, a consequentialist utilitarian party clusters consequentialist utilitarian ethical systems. A party member or eligible candidate can have his or her own preferred ethical system that is broadly in line with the position of the party.

An ethical committee, consisting of experts in moral philosophy, controls the coherence of the ethical systems held by all parties and party members. People who have incoherent ethical systems (i.e. with inconsistencies or unwanted arbitrariness) are not allowed to participate during election. For example: a party with a racist ideology is not allowed, because racism is a kind of unwanted arbitrariness.

Each voting citizen has 10 demivotes to vote on parties or eligible candidates. For example: if you have 90% confidence in a prioritarian welfare ethic and 10% confidence in a libertarian rights ethic, you can give 9 demivotes for the candidate who is closest to your prioritarian ethic and 1 demivote for the candidate of the libertarian party.

All the elected officials debate in the parliament about the most preferred mixture of moral values. The resulting consensus view is a kind of weighted average of all ethical systems, weighted according to preference or credence. The most important task of the members of parliament is the determination of measurable indicators for the following legislature. Analogous to life cycle impact assessments, we can make a distinction between midpoint and endpoint indicators. Possible example of midpoint indicators are: GDP, the Gini index for income inequality, lifespan, life satisfaction, depression rates, crime rates, the level of greenhouse gas emissions, measures of progress in scientific research,… These midpoint indicators can be aggregated into a limited number of endpoint indicators such as the human development index. These endpoints measure for example economic prosperity, environmental sustainability or general happiness. During the election, each eligible candidate can present his or her preferred midpoint and endpoint indicators, so all voters can have a clear picture of what the candidates find important.

The ethical committee checks if the resulting parliamentary consensus and chosen indicators do not contain unwanted arbitrariness. An independent bureau of statistics has the task to collect all the data to calculate the chosen indicators.


Betting on beliefs (the prediction market model for empirical uncertainty)

After determining the moral values or ends measured by the chosen midpoint and endpoint indicators, we now have to find the most effective means to reach those ends. These means are the policies and laws. To find those means, we need accurate beliefs. However, most people are biased and a lot of politicians have hidden agendas or personal (e.g. financial) interests. These biases generate inaccurate beliefs, resulting in ineffective means.

The question becomes: what is the best institution to find the most effective means? No institution is perfect: we do not have a completely unbiased, impartial institution with perfect scientific knowledge about economics and other relevant disciplines, that can determine the most effective policies. But this does not mean we cannot look for the least bad institution.

One interesting proposal that deserves more research, is Robin Hanson’s futarchy, which he describes with the slogan: “voting on values, betting on beliefs.” Voting on values was a least bad solution to moral uncertainty, and perhaps betting on beliefs is the least bad solution to empirical uncertainty. In a futarchy, prediction markets (speculative markets trading in idea futures) are used to determine the most effective policies. A prediction market is probably one of the most reliable and effective institutions to gain crucial information about e.g. the likelihood that a certain policy has a positive effect (measured as increases in the chosen indicators).

In a prediction market, people can trade in conditional bets. For example, if the chosen indicator is GDP and the proposed policy is a certain trade agreement, I can sell you a conditional bet that pays you $1 if the policy is adopted and GDP increases after a certain amount of time and $0 if the policy is adopted and GDP decreases. The bet is annulled if the policy is not adopted. If you have 70% confidence that GDP will increase if the policy is adopted, you (as a rational agent) are willing to pay at most $0.7. The maximum price you are willing to pay corresponds with your subjective degree of confidence (your subjective probability). Similarly, the minimum price I am willing to sell this bet corresponds with my degree of confidence. According to some research mentioned by Hanson, if there are many speculators, chances increase that the market prices of those conditional bets become reliable estimates of the probabilities of the effectiveness of the policies.

Prediction markets cannot only give probability estimates for the effectiveness of policies, but also probability estimates for future indicators chosen by future governments. This is important, because taking our moral uncertainty into consideration means taking into account that our future moral values might be different. So we have to be aware that in the future people might have other preferences for their moral values, or that new insights and technologies allow for the adoption of other, better indicators in the future.

In futarchy, a policy is adopted (and competing policies are rejected) if two conditions are met: 1) the price of the conditional bet for that policy and for the currently chosen indicator (i.e. conditional on that policy being adopted and the indicator being chosen) is clearly higher than the prices of the conditional bets for the competing policies (i.e. conditional on the other policies being adopted), and 2) the price of the conditional bet for that policy and for the most likely future indicator (i.e. conditional on that policy being adopted and the future indicator chosen) is not clearly lower than the prices of the conditional bets for the competing policies with that future indicator. The second condition guarantees that we will not regret our policy decision when our moral values (and the corresponding indicators) change in the future. For example, if chances are high that in the future another indicator than GDP will be chosen, and if the prediction market clearly predicts that the proposed trade agreement worsens that future indicator, the proposed agreement does not become law.

For a lot of policy choices, reliable information about empirical facts is highly important, and prediction markets are a good source of information (they can effectively aggregate information). Such information has a lot of value, because a lot is at stake. Therefore, prediction markets that predict the effectiveness of promising policies should be subsidized in order to attract enough speculators. This subsidy reflects the financial value of the information. The details of futarchy, as well as the rebuttals of some criticism, are discussed in Hanson’s paper.

Futarchy is just one promising proposal. There are many other possible solutions to the problem of moral and empirical uncertainty in politics. We cannot tell in advance whether futarchy or another proposal works well, but these promising proposals deserve more research and experimentation.


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Ineffective actions and campaigns that can backfire

Effective altruism is not only about looking for actions that do the most good, but also about avoiding ineffective actions. Here I will give four examples of campaigns or actions that can backfire in the sense that they can do more harm than good. I cover three areas – environmental pollution, animal suffering and social injustice – and one general strategy – fundraising. The objective of this article is to let us think more critically about helping others and become more effective in doing good.

Environmental pollution

A recent ineffective campaign from the environmental movement was the campaign to ban the herbicide glyphosate, which is primarily based on the World Health Organization International Agency for Research on Cancer (WHO IARC) 2015 evaluation that in terms of hazard (i.e. whether the substance is capable of causing an effect), glyphosate is probably carcinogenic. First of all, there does not seem to be a scientific consensus on the carcinogenicity of glyphosate. For example, the European Chemical Agency (ECHA) says available scientific evidence did not meet the criteria to classify glyphosate as a carcinogen. Second, even if glyphosate may be a carcinogenic hazard, there seems to be a scientific consensus that it poses no carcinogenic risk (i.e. the actual exposure to the substance – for example through diet – is too low to show a significant effect). The European Food Safety Authority (EFSA), the UN Food and Agriculture Organization (FAO) and the WHO agree that glyphosate is unlikely to be genotoxic at anticipated dietary exposures and unlikely to pose a carcinogenic risk to humans from exposure through the diet.

It happens that glyphosate is one of the safest herbicides. The Environmental Impact Quotient (EIQ) of glyphosate is 15, lower than many other herbicides that were used instead of glyphosate, such as imazethapyr (EIQ 20), trifluralin (EIQ 19) and pendimethalin (EIQ 30). The human toxicity potential of glyphosate is 0,7 gram 1,4-DCB-equivalent per kg substance, almost 40.000 times lower than the average herbicide. The soil ecotoxicity and freshwater ecotoxicity potentials of glyphosate (per kg substance) are respectively 800 and 300 times lower than the average herbicide. For individuals, using acetic acid, salt or liquid bleach (sodium hypochlorite), or other common herbicides such as dicamba, is probably more polluting than using glyphosate. And they are more toxic for mammals. The LD50 lethal dose of glyphosate (for rats) is 5 grams per kg body weight, compared to 3 g/kg for acetic acid and salt, 1 g/kg for dicamba and 0,2 g/kg for sodium hypochlorite.

So what would happen if glyphosate were banned? It is not clear if that would lower the environmental impact overall. If other herbicides are not banned, farmers and individuals might switch to more toxic herbicides. It is also not clear that the alternatives for herbicides, such as ploughing, are better for the environment: they can decrease soil quality and increase fuel consumption and soil erosion. Evidence that herbicide-free organic farming is better for the environment, is lacking.

Given this lack of evidence that alternatives to glyphosate use are substantially better for human and environmental health, urging for a ban on glyphosate might be too early. We first need to know the counterfactuals: what would be used if glyphosate was banned? And we need more scientific studies about the environmental impacts of those alternatives.

What are more effective campaigns at this moment? A first, more straightforward campaign would be the ban on the most dangerous pesticides on the market and the promotion of integrated pest management. But above all, the most effective campaign for the environment, is a decrease of animal production (e.g. a campaign for a high tax on animal products or for the promotion of animal-free products). The production of meat requires on average 4 times more cereals and soy (used for animal feed) than the production of plant-based protein-rich products. This means meat requires 4 times more herbicides than vegan alternatives. Animal-free, vegan food offers many other human, environmental and animal benefits as well. Besides, according to the IARC, red meat is like glyphosate probably carcinogenic (category 2A) and processed meat such as bacon is carcinogenic (category 1). However, pointing this out, results in another problem, as we will see next.

Animal suffering

Red meat has a higher environmental and health impact than other protein-rich foods. So a focus on the environmental and health consequences of diet might result in people eating more chicken meat and eggs as a replacement for red meat. The same goes for people who are concerned about animal welfare and are in favor of mammals. Campaigns that focus on the suffering of pigs and cows might increase the consumption of chicken meat, and vegetarians might increase their consumption of eggs and egg-containing products.

However, in terms of number of animals used and killed or hours of animal suffering per kilogram product, chicken meat and eggs are about 20 times worse than red meat. (Concerning eggs: male chicks and less productive layer hens are killed.)

Even a replacement of red meat by a vegetarian (non-vegan) alternative that contains egg-protein might be more harmful to animals. Suppose a vegetarian sausage contains 4% chicken egg protein. To produce 1 kg of egg protein, one needs 14 kg of eggs (i.e. 230 eggs). However, eggs not only contain protein but also other by-products with a market value, so we need to multiply the amount of eggs with an economic allocation factor of 0,45. That means 1 kg of vegetarian products containing egg-protein requires 0,25 kg eggs (i.e. 4 eggs). According to this calculation, egg-protein containing vegetarian products are 5 times worse than red meat in terms of animals killed and hours suffering. Reducetarians and flexitarians who replace red meat by such vegetarian alternatives, increase animal suffering.

What is a more effective strategy? First of all, we should avoid single issue campaigns that merely ask for a reduction of red meat consumption without mentioning chickens and eggs. Hence, we should promote vegan alternatives. In particular, red meat can be replaced with vegan protein-rich foods and chicken meat and eggs can be replaced with nuts, seeds and vegetables. Vegetables are better for the environment and human health than chicken meat and eggs, so this message is compatible with a concern for the environment and human health. Second, in terms of reducetarian or flexitarian campaigns, we should focus on reducing the consumption of chicken meat, eggs and farmed fish, because these animal products have the highest moral footprints. Finally, consumers can put pressure on producers of vegetarian products to eliminate eggs in their products.

Social injustice

A third example of an ineffective measure is a consumer boycott of products made with low wage labor or relatively bad working conditions (e.g. sweatshops). As long as there is no involuntary slavery involved, such boycotts might easily backfire: a boycott might result in those workers losing their jobs, and hence they often become worse off because they no longer generate an income or they move to another job that is less favored (i.e. with worse working conditions).

Buying Fairtrade is not always the answer either. The higher prices for Fairtrade gives the producers an incentive to produce more, which can result in overproduction and consequentially a decrease in price of the non-fairtrade products. The producers who were not able to get a Fairtrade certification can end up being worse off, with lower prices for their products and hence lower incomes.

So what is the answer? What is more effective to improve social justice? The general answer are campaigns against unearned income (income gained not through labor or entrepreneurship but through ownership of land and other monopoly), economic rent (a surplus profit above normal profit, received for non-produced inputs) or rent seeking (seeking to increase one’s share of existing wealth without creating new wealth). More specifically, a tax shift is possible: taxing economic rent (e.g. natural resources) instead of labor. Other related examples are a global resources dividend (an idea from Thomas Pogge) and a clean hands trust and clean trade in natural resources (an idea from Leif Wenar).

For individual consumers, a more effective alternative than boycotting sweatshops and buying fair trade is donating money to organizations that give unconditional cash transfers, such as GiveDirectly or Eight. In fact, one can argue that we have a duty to donate money to those charities.


If we measure the cost-effectiveness of measurable interventions (e.g. in terms of numbers of lives saved, loss of quality adjusted life years avoided, kilograms of toxics avoided, hours of animal suffering avoided, levels of income increased or levels of crime decreased per dollar invested), we see a very skewed (often log-normal or fat-tailed) distribution. A minority of interventions is far more effective than the vast majority, doing a lot more good per dollar. Most interventions have an effectiveness below the averages, because the small minority of highly effective interventions drives up this average. This is just like the global income or wealth distribution with a small number of very rich people. We can expect that the immeasurable interventions (whose cost-effectiveness we are not able to measure yet) have a similar skewed distribution.

This has important implications for fundraising. We can consider three types of organizations. First there are the big, multiple-issue organizations that do a lot of campaigns, projects and interventions (e.g. Greenpeace, Peta, Unicef). If their campaigns are randomly distributed, these large organizations have an average cost-effectiveness. Next, there are the single-issue organizations focusing on specific problems or specific interventions. Most of those single-issue organizations have an effectiveness below average, because most likely they focus on low cost-effective interventions. Examples are local environmental organizations, animal shelters and organizations that focus on minority groups, poverty and diseases in rich countries. A third group of organizations are the minority of highly effective single-issue organizations (e.g. the organizations recommended by GiveWell and Animal Charity Evaluators). They have an effectiveness above average.

Now suppose that you go fundraising for an organization. As a result, the number of donations and the amount of money that people donate might increase a bit. But we also see a shift between organizations: people start to donate more to your charity and less to other charities. This means there is a shift away from a group of charities with an average effectiveness. If your charity has an average effectiveness (e.g. it is a multiple-issue organization), this shift is neutral. But if your charity has an effectiveness below average, your fundraising might actually do more harm than good. The average effectiveness might be an order of magnitude (a power of ten) higher than the median effectiveness (i.e. than the effectiveness of most single-issue organizations). That means if your fundraising causes a shift towards a charity with below-average effectiveness, the amount of dollar donated would have to increase with an order of magnitude in order to compensate for the loss of effectiveness by the shift between charities. A world where you are not fundraising for that charity might be a world where more good is done. So even fundraising for a charity can sometimes be a harmful job.


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De Heetste Week: kies je goede doelen goed

Onderstaand opiniestuk over effectief altruïsme, verschenen in De Tijd, werd geschreven naar aanleiding van De Warmste Week – Music for Life. Uit de lijst van Warmste Week goede doelen denk ik dat de volgende organisaties het meest effectief zijn:

Voor menselijk welzijn (armoedebestrijding, gezondheidszorg):

Eight: deze organisatie geeft mensen in Oeganda een onvoorwaardelijk basisinkomen en is vergelijkbaar met GiveDirectly, een topaanbeveling van GiveWell.

Unicef: deze organisatie doet onder andere preventiecampagnes tegen tropische infectieziektes. Dat zijn heel effectieve projecten volgens GiveWell. Maar omdat Unicef reeds een grote organisatie is (die reeds veel donaties krijgt), en veel verschillende projecten doet (waarvan er waarschijnlijk ook een groot deel minder effectief zijn), zijn de topaanbevelingen van GiveWell waarschijnlijk effectiever dan Unicef omdat die topaanbevelingen meer ruimte hebben voor extra financiering en focussen op de interventies met de hoogste impact.

Voor de dieren

Bite Back en Animal Rights: deze organisaties komen qua werking het best overeen met Animal Equality, een topaanbeveling van Animal Charity Evaluators.

EVA: deze organisatie promoot plantaardige voeding, een heel effectieve maatregel voor de dieren volgens Animal Charity Evaluators.

Kies je goede doelen goed

De meest zingevende gebeurtenis van het jaar

Vraag aan brandweerlieden die het afgelopen jaar een hond of een kind uit een brandend huis hebben gered: wat was uw meest zingevende ervaring van 2017? Iemand helpen of redden is zo’n fantastische ervaring, dat we bereid zijn er veel voor op te offeren. Stel je springt in een rivier om een drenkeling te redden, maar je verliest daarbij je portefeuille. Zou je dat erg vinden, of zou je blij zijn dat je een kind hebt gered? De meesten zijn bereid een paar duizend euro te verliezen als ze daarmee een leven kunnen redden. Iemand helpen is belangrijker dan een vakantie of een nieuwe smartphone.

Diegenen die zich inzetten voor een goed doel van De Warmste Week, zullen deze week waarschijnlijk de meest wezenlijke, zingevende keuze van het jaar maken. Misschien heb je niet hetzelfde euforische gevoel als die brandweerlieden, maar wat is voor jou het belangrijkste: een gevoel van euforie en trots, of het welzijn van de persoon die je hebt geholpen? Doe je het voor jezelf of de ander? Als je het voor de ander doet, zou je je inzet deze week dan niet maximaal zingevend willen maken? Wil je de effectiefste goede doelen steunen? Dan zijn onderstaande tips voor jou.

Denk als een investeerder

Net zoals een investeerder een maximaal financieel rendement wil, zo kun je bij je keuze van goed doel streven naar een maximaal sociaal rendement waarbij anderen zo goed mogelijk geholpen worden. Dan moet je wel je verstand gebruiken, kritisch denken en niet zomaar je buikgevoelens volgen. Investeerders luisteren ook niet zomaar naar mooie praatjes van bedrijven, dus wees waakzaam voor mooie verhaaltjes van goede doelen.

Verbreed je blik en kies waar, wanneer en wie je helpt

Drie factoren bepalen de effectiviteit van een goed doel. Ten eerste de ernst: hoe groot is het probleem waar het goede doel een oplossing voor wil bieden? Eén persoon met een verstuikte enkel of duizend kinderen met een dodelijke ziekte? Stel jezelf drie vragen.

Waar wil je helpen? Als de plaats niet uitmaakt: de armoede in het Zuiden is veel groter dan de armoede in je buurt. Verminder de extreemste armoede, vooral door de preventie van grote en verwaarloosde tropische ziektes.

Wie wil je helpen? Als het uiterlijk of de soort niet uitmaakt: het aantal dieren die lijden in stallen en slachthuizen is veel groter dan het aantal lijdende mensen. Verminder de veeteelt, vooral door de promotie van diervrije voeding.

Wanneer wil je resultaten van je hulp? Als dat eender is: in de verre toekomst staan veel meer levens op het spel dan vandaag. Verminder de extreemste bedreigingen die de hele samenleving kunnen uitroeien.

De effectiefste goede doelen helpen veel personen met weinig geld. Als je kunt weten welk individu je hebt geholpen met je gift, dan behoort dat goede doel waarschijnlijk tot de minder effectieve, omdat er dan meestal veel middelen geïnvesteerd worden in weinig personen.

Gebruik de wetenschap en kijk naar de opportuniteitskost van je gift

Een tweede factor is de reduceerbaarheid: hoe eenvoudig is het probleem aan te pakken en hoe sterk kan het goede doel het probleem verminderen? Met wetenschappelijk onderzoek kunnen we nagaan hoe doeltreffend een goed doel is. Als we met experimenten de effectiviteit van projecten meten, bijvoorbeeld in termen van geredde levens, gestegen inkomens, betere schoolresultaten, gedaalde criminaliteit of gezonder leefmilieu, dan zien we telkens dat de meeste projecten weinig of niet effectief zijn en een kleine minderheid supereffectief is. Waarschijnlijk is dus ook een kleine minderheid van Warmste Week goede doelen veel doeltreffender dan de meerderheid. Bijvoorbeeld: met het bedrag om een blindengeleidehond op te leiden om één blinde 10 jaar te helpen, kan men in arme landen oogontstekingen behandelen en zo voorkomen dat 1000 kinderen blind worden. Of het bedrag om een hond in een asiel te helpen kan het leed besparen van meer dan 1000 veedieren. De keuze voor het ene goede doel heeft een opportuniteitskost: er is geen geld meer om aan een ander project te geven dat mogelijks meer goeds realiseert.

Zoek de niche en kijk naar wat anderen niet doen

De derde factor meet de verwaarloosdheid: hoeveel andere personen doen al iets aan het probleem? Net zoals slimme investeerders rekening houden met wat andere investeerders doen en op zoek gaan naar het gat in de markt, zo kunnen we op zoek gaan naar goede doelen die een verwaarloosd probleem oplossen. Mediagenieke organisaties krijgen al veel geld, waardoor je eigen bijdrage minder impact heeft dan bij organisaties die weinig steun krijgen en ruimte hebben voor meer financiering.

Als we deze tips van het Effectief Altruïsme gebruiken, dan realiseren we een veel hoger sociaal rendement en wordt het de Heetste Week.

Stijn Bruers is auteur van Morele Illusies en mede-oprichter van Effectief Altruïsme Vlaanderen

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