Aggregating Small Risks of Serious Harms
Tomi Francis (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 21-2024
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.
Other working papers
Crying wolf: Warning about societal risks can be reputationally risky – Lucius Caviola (Global Priorities Institute, University of Oxford) et al.
Society relies on expert warnings about large-scale risks like pandemics and natural disasters. Across ten studies (N = 5,342), we demonstrate people’s reluctance to warn about unlikely but large-scale risks because they are concerned about being blamed for being wrong. In particular, warners anticipate that if the risk doesn’t occur, they will be perceived as overly alarmist and responsible for wasting societal resources. This phenomenon appears in the context of natural, technological, and financial risks…
Quadratic Funding with Incomplete Information – Luis M. V. Freitas (Global Priorities Institute, University of Oxford) and Wilfredo L. Maldonado (University of Sao Paulo)
Quadratic funding is a public good provision mechanism that satisfies desirable theoretical properties, such as efficiency under complete information, and has been gaining popularity in practical applications. We evaluate this mechanism in a setting of incomplete information regarding individual preferences, and show that this result only holds under knife-edge conditions. We also estimate the inefficiency of the mechanism in a variety of settings and show, in particular, that inefficiency increases…
Doomsday and objective chance – Teruji Thomas (Global Priorities Institute, Oxford University)
Lewis’s Principal Principle says that one should usually align one’s credences with the known chances. In this paper I develop a version of the Principal Principle that deals well with some exceptional cases related to the distinction between metaphysical and epistemic modality. I explain how this principle gives a unified account of the Sleeping Beauty problem and chance-based principles of anthropic reasoning…