This paper argues that the philosophy of explanation can help inform core debates in value theory. Specifically, it argues that there is a consistent parallelism between the properties of explanation and the properties of justification such that one can reasonably infer that any property of explanation has a counterpart property of justification. Thus, by appealing to facts about the nature of explanation, one can derive various conclusions about the justifications offered by normative theorists. The paper illustrates this point by considering (...) a debate within political philosophy over whether inequality requires justification in a way that equality does not. Egalitarians typically presume an affirmative answer to this question. However, libertarian critics note that this justificatory asymmetry cannot be simply assumed without argument. This paper argues that, by appealing to the explanation-justification parallelism, one can resolve this debate in favor of the egalitarians, as there are two properties of explanation, the justificatory analogs of which vindicate the egalitarian presumption. (shrink)

Egalitarians think that equality in the distribution of goods somehow matters. But what exactly is egalitarianism? This article argues for a characterization based on novel principles essentially involving risk. The characterization is then used to resolve disputed questions about egalitarianism. These include: the way egalitarianism is concerned with patterns, in particular its relationship to strong separability; the relationship between egalitarianism and other distributive views, such as concerns with fairness and with giving priority to the worse off; and the relationship between (...) egalitarianism and evaluative measurement. But egalitarianism is subject to a particularly severe form of the levelling-down objection, and is claimed to be false. (shrink)

Principles of distributive justice are normative principles designed to guide the allocation of the benefits and burdens of economic activity.

Luck egalitarianism is an approach within current distributive justice theory which aims to focus redistributive efforts solely upon disadvantages that ensue from bad luck. This article considers how central assumptions and themes of both luck egalitarianism and its critics parallel those of providence theology and share some of their concerns. These relate to problems such as the basis of equality, the extent and nature of our knowledge, and of course, the paternalism that assessing people’s responsibility over their own disadvantages involves. (...) I highlight the similarity of luck egalitarianism to the role of providence and providence theory thinking, and particularly the tension between egalitarianism as a theological concept and the condescension inherent to imitatio Dei ethics. I approach these issues by analyzing standard criticisms of the luck egalitarian project, espoused by Susan Hurley and Elizabeth Anderson. I then proceed to assess the values of luck egalitarianism itself and consider different models of providence, and the meaning of this analysis for normative ethics. The subject matter of this article is part of a wider comparison of distributive justice and providence theory, within which luck egalitarianism affords a very fruitful and highly relevant case study. (shrink)

The arrival of “big data” promises new degrees of precision in understanding human behavior. Could it also allow drawing a finer line between “choice” and “circumstances”? In a culture in which individual responsibility continues to be celebrated, this raises questions about new opportunities for institutional design with a stronger focus on individual responsibility. But what is it that can be learned from big data? In this paper I argue that we should not expect a “god’s eye view” on choice versus (...) circumstances from big data. “Responsibility” is a social construct that depends on the logic of different social situations, as well as our epistemic access to certain counterfactuals (e.g., whether an agent “could have acted differently”). It is this epistemic dimension that changes with the arrival of big data. But while this might help overcome some epistemic barriers, it might also create new problems, e.g., because of polluted and hence biased data. This is not just a theoretical problem; it is directly connected to the regulation of insurance. The new developments force us to directly confront questions about mutualist versus solidaristic forms of insurance, and more generally about how much weight to ascribe to individual responsibility, given all we know about unequal background circumstances. (shrink)