How should risk and ambiguity affect our charitable giving?

Lara Buchak (Princeton University)

GPI Working Paper No. 8 - 2022, published in Utilitas

Suppose we want to do the most good we can with a particular sum of money, but we cannot be certain of the consequences of different ways of making use of it. This paper explores how our attitudes towards risk and ambiguity bear on what we should do. It shows that risk-avoidance and ambiguity-aversion can each provide good reason to divide our money between various charitable organizations rather than to give it all to the most promising one. It also shows on how different attitudes towards risk and ambiguity affect whether we should give to an organization which does a small amount of good for certain or to one which does a large amount of good with some small, unknown probability.

Other working papers

Social Beneficence – Jacob Barrett (Global Priorities Institute, University of Oxford)

A background assumption in much contemporary political philosophy is that justice is the first virtue of social institutions, taking priority over other values such as beneficence. This assumption is typically treated as a methodological starting point, rather than as following from any particular moral or political theory. In this paper, I challenge this assumption.

The case for strong longtermism – Hilary Greaves and William MacAskill (Global Priorities Institute, University of Oxford)

A striking fact about the history of civilisation is just how early we are in it. There are 5000 years of recorded history behind us, but how many years are still to come? If we merely last as long as the typical mammalian species…

Quadratic Funding with Incomplete Information – Luis M. V. Freitas (Global Priorities Institute, University of Oxford) and Wilfredo L. Maldonado (University of Sao Paulo)

Quadratic funding is a public good provision mechanism that satisfies desirable theoretical properties, such as efficiency under complete information, and has been gaining popularity in practical applications. We evaluate this mechanism in a setting of incomplete information regarding individual preferences, and show that this result only holds under knife-edge conditions. We also estimate the inefficiency of the mechanism in a variety of settings and show, in particular, that inefficiency increases…