The weight of suffering
Andreas Mogensen (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 4-2022, forthcoming in The Journal of Philosophy
How should we weigh suffering against happiness? This paper highlights the existence of an argument from intuitively plausible axiological principles to the striking conclusion that in comparing different populations, there exists some depth of suffering that cannot be compensated for by any measure of well-being. In addition to a number of structural principles, the argument relies on two key premises. The first is the contrary of the so-called Reverse Repugnant Conclusion. The second is a principle according to which the addition of any population of lives with positive welfare levels makes the outcome worse if accompanied by sufficiently many lives that are not worth living. I consider whether we should accept the conclusion of the argument and what we may end up committed to if we do not, illustrating the implications of the conclusions for the question of whether suffering in aggregate outweighs happiness among human and non-human animals, now and in future.
Other working papers
Longtermism in an Infinite World – Christian J. Tarsney (Population Wellbeing Initiative, University of Texas at Austin) and Hayden Wilkinson (Global Priorities Institute, University of Oxford)
The case for longtermism depends on the vast potential scale of the future. But that same vastness also threatens to undermine the case for longtermism: If the future contains infinite value, then many theories of value that support longtermism (e.g., risk-neutral total utilitarianism) seem to imply that no available action is better than any other. And some strategies for avoiding this conclusion (e.g., exponential time discounting) yield views that…
Exceeding expectations: stochastic dominance as a general decision theory – Christian Tarsney (Global Priorities Institute, Oxford University)
The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk (like Pascal’s Mugging), and intolerably paradoxical in cases like the St. Petersburg and Pasadena games. In this paper I show that, under certain conditions, stochastic dominance reasoning can capture most of the plausible implications of expectational reasoning while avoiding most of its pitfalls…
On two arguments for Fanaticism – Jeffrey Sanford Russell (University of Southern California)
Should we make significant sacrifices to ever-so-slightly lower the chance of extremely bad outcomes, or to ever-so-slightly raise the chance of extremely good outcomes? Fanaticism says yes: for every bad outcome, there is a tiny chance of of extreme disaster that is even worse, and for every good outcome, there is a tiny chance of an enormous good that is even better.