In his 2009 book, The Life You Can Save, Nobel Laureate moral philosopher (and current professor at the University of Melbourne) Peter Singer, put forward the following thought experiment:
“On your way to work, you pass a small pond. On hot days, children sometimes play in the pond, which is only about knee-deep. The weather’s cool today, though, and the hour is early, so you are surprised to see a child splashing about in the pond. As you get closer, you see that it is a very young child, just a toddler, who is flailing about, unable to stay upright or walk out of the pond. You look for the parents or babysitter, but there is no one else around. The child is unable to keep her head above the water for more than a few seconds at a time. If you don’t wade in and pull her out, she seems likely to drown. Wading in is easy and safe, but you will ruin the new shoes you bought only a few days ago, and get your suit wet and muddy. By the time you hand the child over to someone responsible for her, and change your clothes, you’ll be late for work. What should you do?”[i]
By default, the answer of many to this question is a belief unreservedly that we would save the child in these circumstances – for a lost pair of shoes and missed hour of work pales in comparison to the lost life of a young child. Equally, we would regard the decision of leaving the child to drown as not only selfish, but psychopathic and morally repulsive. While such attitudes about the drowning child in this rare hypothetical situation may seem uncontroversial, the responsibilities one feels to other moral causes with less proximity to immediate, everyday life, are more ambiguous.
According to UNICEF, today there are approximately 376 million children who live in ‘extreme poverty’, meaning they lack access to basic necessities such as shelter and sanitation[ii]. Common causes of death for such malnourished children are often easily preventable and unheard of in wealthier countries, such as diarrhea and malaria, which could be easily avoided with cheap bed nets. In fact, not-for-profit charity evaluator Give Well estimates that for every $3,000-5,000 donated to an effective charity such as the Against Malaria Foundation, a life is expected to be saved[iii]. At the same time, if you are reading this article in a wealthy area such as Melbourne, you likely purchase items that you don’t really need. Whether it be new clothes, a bottle of water that could be freely substituted from a tap, or a luxury car, the vast majority of people clearly do not factor in the prospect of giving to effective charities as an opportunity cost in their consumption decisions. Of course, there are philosophical objections to be made against the ethics underpinning a responsibility of giving to others abroad, which will not be discussed here (though if you are interested THIS is an excellent article on the matter authored by Singer).
Taking the goal of helping others in need seriously gives rise to the effective altruism (EA) movement. As described by pioneer William MacAskill, EA is the task of using evidence and reason to figure out how to benefit others as much as possible, and taking action on that basis[iv]. As such, many EA’s give a substantial portion of their income to charities that are particularly effective, and strive to maximise their income in order to make the greatest positive impact on the world. As this movement has developed, it has become clear that there are many gains to be made in coordination across the EA community, rather than each individual trying to maximise their impact separately. In the proceeding discussion, I will highlight some coordination problems that arise in deciding which charity to donate to, and consider some tools from mechanism design which could be implemented for better decision-making.
Mechanism Design and Effective Altruism:
Much like what we learn about firms in microeconomics classes, charities are only able to increase their number of staff and scale up their operations to a limited degree in the short-run before diminishing their cost-effectiveness, and they therefore can only have limited room for more funding (RFMF). Charity-evaluator Give Well investigates the RFMF of many of the world’s most effective charities. For example, it estimates that the Against Malaria Foundation could only productively use an additional $37.8 million of funding between now and early 2022, in order to support their distribution of bed nets across eight countries[v].
The short run diminishing marginal product associated with charities arises problems in donor coordination, as individual donors will allocate their funds to a charity that is believed to be most effective such as the Against Malaria Foundation, resulting in an overallocation where the charity cannot productively use the additional funds. Such a situation often occurs following natural disasters, where there is a surge in donations to a small subsection of charities. In this case, we would expect a rational effective altruist to give to what is believed to be the second most effective charity, as the RFMF of the best charity has been exhausted. However, this becomes problematic when different donors hold converging preferences about the next-best charity. This situation has been coined the Givers’ Dilemma[vi], and can be illustrated in the following example:
Two effective altruists, Peter and William, wish to give to Charity A, as they believe it to be the most effective and has an RFMF of $X. Both of them are willing to fill this gap for more funding. However, Peter and William disagree on the merits of the second-best charity, such that Peter prefers Charity B and William prefers Charity C. If Peter discovers William’s plans, his incentive is to give nothing to charity A, as he knows William will fill its funding gap. On the other hand, if William discovers Peter’s funding plans, his incentive is to give nothing to charity A so he can effectively fund his second preference, Charity C . This creates a problematic situation in which neither Peter nor William has the incentive to be honest with the other about his giving plans and preferences – and each has the incentive to try to wait out the other’s decision.
A solution to this ‘donor’s dilemma’ would have to be a system that prevents (or at least minimises) strategic behaviour to produce effective donation allocations. This could be in the form of a ‘donation clearinghouse’, to which donors communicate their preferences over charitable organisations as well as their budgets, and the clearinghouse then decides how their budgets are ultimately allocated[vii]. If a successful system akin to a ‘donation clearing house’ is to be designed, there are several challenges it must overcome. For instance, it is unclear how donors should report their preferences and which optimisation objection the system should use. Considering potential solutions to such challenges involves a high level of technical complexity that is beyond the scope of this article, though it is an area where further research breakthroughs could have a high impact and improve many lives. It will be interesting to follow how concepts from mechanism design are applied to EA in the future.
[ii] UNICEF. Child Poverty. (2021). Retrieved March 17 2021, from https://www.unicef.org/social-policy/child-poverty#:~:text=Across%20the%20world%2C%20about%201,children%20live%20in%20extreme%20poverty
[iv] McCaskill. Effective Altruism: Introduction. Essays in Philosophy. (2017). Retrieved March 17 2021, from https://static1.squarespace.com/static/5506078de4b02d88372eee4e/t/5bc7205d104c7bf5cc8f1dca/1539776611190/Effective+Altruism+-+Introduction.pdf
[v] Give Well. Room For More Funds. (2020). Retrieved March 17 2021, from https://www.givewell.org/charities/amf#Roomformorefunds
[vi] Karnofsky, H. The value of coordination. (2014). The GiveWell Blog. Retrieved March 17 2021, from https://blog.givewell.org/2014/12/02/donor-coordination-and-the-givers-dilemma/