Tomi Francis

This paper concerns the difficulty of avoiding an additive version of the Very Repugnant Conclusion. An impossibility theorem is provided which shows that we cannot avoid this version of the Repugnant Conclusion even if we deny the Mere Addition Principle and closely related principles which place limits on the badness of adding happy people, such as “Dominance Addition” and additive “Non-Sadism” conditions. I argue that the impossibility theorem shows that the additive version of the Very Repugnant Conclusion cannot reasonably be avoided by population-ethical means alone. One must instead either deny structural conditions such as acyclicity, adopt a radically unorthodox fixed-population axiology, or accept this version of the Very Repugnant Conclusion.

According to Stochastic Dominance, it is rationally obligatory to prefer one gamble to another if it gives you the same chances of getting final outcomes you prefer. According to Statewise Maximality, it is rationally permissible not to disprefer a gamble if it is guaranteed not to result in a final outcome you disprefer. These principles conflict in cases involving incomplete preferences, known as Opaque Sweetening cases. In this paper, we argue for Stochastic Dominance and against Statewise Maximality in Opaque Sweetening cases. First, we rebut two standard arguments for statewise maximality, which we call the Argument from Full Information and the Argument from the Primacy of Final Outcomes. We then provide an argument for the verdict of Stochastic Dominance in Opaque Sweetening cases. This argument appeals to the principle of Transitivity, the Sure-Thing Principle, and the claim that stochastic reasoning is appropriate at least for choices which do not involve incomparability.

Autonomous systems are machines that can alter their behavior without direct human oversight or control. How ought we to program them to behave? A plausible starting point is given by the Reduction to Acts Thesis, according to which we ought to program autonomous systems to do whatever a human agent ought to do in the same circumstances. Although the Reduction to Acts Thesis is initially appealing, we argue that it is false: it is sometimes permissible to program a machine to do something that it would be wrong for a human to do. We advance two main arguments for this claim. First, the way an autonomous system will behave can be known in advance. This knowledge can indirectly affect the behavior of other agents, while the same may not be true at the time the system actually executes its programming. Second, a lack of knowledge of the identities of the victims and beneficiaries can provide a justification during the programming phase that would be unavailable to an agent at the time the autonomous system executes its programming.

According to Partial Aggregation, a serious harm can be outweighed by a large number of somewhat less serious harms, but can outweigh any number of trivial harms. In this paper, I address the question of how we should extend Partial Aggregation to cases of risk, and especially to cases involving small risks of serious harms. I argue that, contrary to the most popular versions of the ex ante and ex post views, we should sometimes prevent a small risk that a large number of people will suffer serious harms rather than prevent a small number of people from certainly suffering the same harms. Along the way, I object to the ex ante view on the grounds that it gives an implausible degree of priority to preventing identified over statistical harms, and to the ex post view on the grounds that it fails to respect the separateness of persons. An insight about the nature of claims emerges from these arguments: there are three conceptually distinct senses in which a person’s claim can be said to have a certain degree of strength. I make use of the distinction between these three senses in which a claim can be said to have strength in order to set out a new, more plausible, view about the aggregation of people’s claims under risk.

In “An Intrapersonal Addition Paradox,” Jacob Nebel provides a novel intrapersonal argument for the Repugnant Conclusion. The most controversial premise of Nebel’s argument is the “Probable Addition Principle,” on which it is better for individuals to receive additional chances of existence with a life worth living. I provide an alternative intrapersonal argument for the Repugnant Conclusion which does not assume the Probable Addition Principle. I also show that Pareto principles alone, when conjoined with very minimal principles of prudence, imply a version of the Repugnant Conclusion.

According to the Welfare Diffusion Objection, we should reject Prioritarianism because it implies the ‘desirability of welfare diffusion’: the claim that it can be better for there to be less total wellbeing spread thinly between a larger total number of people, rather than for there to be more total wellbeing, spread more generously between a smaller total number of people. I argue that while Prioritarianism does not directly imply the desirability of welfare diffusion, Prioritarians are nevertheless implicitly committed to certain principles for comparing different-number populations which, together with the Prioritarian same-person axiology, imply the desirability of welfare diffusion.

I argue for the principle of Anonymity, according to which two populations are equally good whenever they have the same anonymous distribution of wellbeing. I first show that, given transitivity of the at-least-as-good-as relation, Anonymity is entailed by the ``Non-Identity Principle'', according to which the consequence of bringing better rather than worse lives into existence is, all else equal, better. I then argue for the Non-Identity Principle on the basis that if it were false, it would follow that we fail to improve the world when we make existing people better off, while at the same time replacing worse-off future people with different better-off future people. Since this is implausible, we should accept the Non-Identity Principle, and therefore Anonymity as well.