In this thesis, I discuss the aggregation problem for T. M. Scanlon’s “contractualism”. I argue that Scanlonian contractualists have the following two options when it comes to the aggregation problem. First, they can choose to limit aggregation directly via a specific version of the Relevance View, “Sequential Claims-Matching”. Second, Scanlonian contractualists can adopt a so-called “mixed solution” of which I propose a specific version. My mixed solution does not limit aggregation. Rather, it either avoids some of the counterintuitive results in (...) certain cases, or at least makes these same results look a lot less counterintuitive by putting them into perspective thanks to a plausible plurality of precisely specified values. The stakes between these two options are as follows. The first option justifies Scanlon’s intuition in one vs. many cases of which his “World Cup Case” is one example, but it comes at the cost of a seemingly quite limited range of application: any version of the Relevance View only works in cases in which we have no more than two groups of competing claimants. The second option has the exact opposite implications: my mixed solution cannot justify Scanlon’s intuition in one vs. many cases, but it could be applied to any case with any number of groups of competing claimants. In this choice between pre-theoretical intuition and feasibility, I would urge Scanlonian contractualists to choose feasibility. (shrink)

First, we argue that the appeal of effective altruism (henceforth, EA) depends significantly on a certain empirical premise we call the Heavy Tail Hypothesis (HTH), which characterizes the probability distribution of opportunities for doing good. Roughly, the HTH implies that the best causes, interventions, or charities produce orders of magnitude greater good than the average ones, constituting a substantial portion of the total amount of good caused by altruistic interventions. Next, we canvass arguments EAs have given for the existence of (...) a positive (or “right”) heavy tail and argue that they can also apply in support of a negative (or “left”) heavy tail where counterproductive interventions do orders of magnitude more harm than ineffective or moderately harmful ones. Incorporating the other heavy tail of the distribution has important implications for the core activities of EA: effectiveness research, cause prioritization, and the assessment of altruistic interventions. It also informs the debate surrounding the institutional critique of EA. (shrink)

Deontic constraints prohibit an agent performing acts of a certain type even when doing so will prevent more instances of that act being performed by others. In this article I show how deontic constraints can be interpreted as either maximizing or non-maximizing rules. I then argue that they should be interpreted as maximizing rules because interpreting them as non-maximizing rules results in a problem with moral advice. Given this conclusion, a strong case can be made that consequentialism provides the best (...) account of deontic constraints. (shrink)

A problem of the many Fs arises in cases where intuitively there is precisely one F (in the region you are talking about), but when you look closely you find many candidates for being that F, each one apparently as well-qualified as the next. Imagine an apparently solitary cloud in an otherwise blue sky. Look closer, and you'll see lots of water vapor molecules, with no one collection of them more eligible than the others to count as the cloud. Many (...) things are like this when you look closely enough. The problem arises for mundane things like rocks, houses and coins. It also arises for entities that present special philosophical challenges, like persons and experiencers. In this essay, I present a new argument that the problem of the many experiencers is an especially hard problem of the many, and property dualism—the view that properties that there is something it is like to instantiate are irreducible—may be the best way to solve it. (shrink)