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This chapter introduces and briefly evaluates several arguments commonly thought to support the moral importance of the distinction between statistical and identified lives in the context of saving lives in health care, many of which frequently appear in the literature. It argues that none of them succeeds in doing that. It concludes that when, but only when, a morally important principle like priority to the worse off maps onto the identified/statistical difference, then the identified/statistical difference is morally important—but that is because of the other principle—in this case, priority to the worse off—not the difference between identified and statistical lives

For years, debates about the best way to combat the AIDS pandemic have pitted proponents of scaling up antiretroviral treatment for people suffering from AIDS against those advocating for more cost-effective prevention measures. In an important recent article, Dan Brock and Daniel Wikler argue that there is no sound moral basis to privilege the saving of identified lives through antiretroviral treatment, if preventive methods could save more (statistical) lives. This chapter takes issue with Brock and Wikler’s argument. In so doing, it develops a novel account of how the choice between “treatment” and “prevention” intersects the problem of identified versus statistical lives. The chapter concludes with a postscript on “treatment-as-prevention” (TasP), a new avenue of HIV/AIDS research that stresses the preventive benefits of early antiretroviral treatment. It argues that, despite its medical promise, TasP does not transcend the ethical dichotomy between treatment and prevention explored in this chapter.

This chapter introduces the central topic of the book. The identified lives effect refers to the greater inclination to assist (and avoid harming) persons and groups identified as those at high risk of great harm rather than to assist (and avoid harming) persons and groups who will suffer (or already suffer) similar harm but are not identified (as yet). It then demarcates and explains the three central groups of questions covered by this book: (1) When precisely does the identified person bias arise? And what exactly does it consist in? (2) What, if anything, might normatively justify giving priority to identified persons at risk? (3) What would be the practical implications for law, public health, medicine, and the environment of accepting the priority given to identified persons, or of forsaking it—if we could successfully do so? Finally, it introduces each of the chapters.

Environmental law focuses on coming probabilities, spread across human populations, rather than on past events, visited upon individuals, and thus it fixes attention on statistical rather than identified lives. The major US environmental laws, as written, offer exceedingly strong protections for human health. In reality, however, environmental law often does not live up to its protective promise. In defending decisions to allow people to die, the government often deploys arguments that, implicitly or explicitly, take advantage of the generally lower status of the statistical life. The effect is to move us away from solicitude and toward nonchalance in our relationship to the statistical life.

When experts write guidelines for patient care for a health condition, they speak about a certain population of patients from a statistical perspective. When clinicians care for patients who have these conditions, they deal with identified persons. The distinction between statistical and identified lives is thought to make it more acceptable for policymakers to say no to certain treatments for a population of prospective patients than for clinicians to prioritize care for their individual patients. But such a view involves too simplistic an understanding of the statistical/identified distinction. This chapter puts forth the argument that in clinical contexts, it is often not known whether an individual patient would actually benefit from treatment. At the point of treatment patient beneficiaries also remain “statistical.” Clinical treatment cannot therefore simply be associated with identified lives while prevention and policymaking are associated with statistical lives. The confusion in doing so is compounded by speaking of ‘rationing’ instead of ‘prioritizing.’

In this chapter, Andreas Mogensen discusses the suggestion that one might be morally obligated to let the child drown in Singer’s infamous “Shallow Pond” case, so that one can save a greater number of lives through donations. Intuitively, there would be something morally horrendous about doing this. Yet a moral requirement to let the child drown seems to be the conclusion of reasoning very similar to that used by Singer and his allies to argue for demanding duties to donate on the basis of cases like “Shallow Pond”; what should we make of this? Mogensen attempts to capture both the intuition that our obligations to donate to effective life-saving organizations are as strong as our obligations to save the child in “Shallow Pond” and the intuition that one should not allow the child to drown even if by doing so one could save a greater number of lives through donations.