title: Underprotection of Unpredictable Statistical Lives Compared to Predictable Ones.
abstract: Existing ethical discussion considers the differences in care for identified versus statistical lives. However, there has been little attention to the different degrees of care that are taken for different kinds of statistical lives. Here we argue that for a given number of statistical lives at stake, there will sometimes be different, and usually greater, care taken to protect predictable statistical lives, in which the number of lives that will be lost can be predicted fairly accurately, than for unpredictable statistical lives, where the lives are at stake because of a low-probability event, such that most likely no one will be affected by the decision but with low probability some lives will be at stake. One reason for this difference is the statistical challenge of estimating low probabilities, and in particular the tendency of common approaches to underestimate these probabilities. Another is the existence of rational incentives to treat unpredictable risks as if the probabilities were lower than they are. Some of these factors apply outside the pure economic context, to institutions, individuals, and governments. We argue that there is no ethical reason to treat unpredictable statistical lives differently from predictable statistical lives. Moreover, lives that are unpredictable from the perspective of an individual agent may become predictable when aggregated to the level of a societal decision. Underprotection of unpredictable statistical lives is a form of market failure that may need to be corrected by altering regulation, introducing compulsory liability insurance, or other social policies.
authors.affiliation: Center for Communicable Disease Dynamics, Department of Epidemiology and Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
authors.forename: Marc
authors.initials: M
authors.lastname: Lipsitch
authors.affiliation: Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Nicholas G
authors.initials: NG
authors.lastname: Evans
authors.affiliation: Future of Humanity Institute, Oxford Martin School, University of Oxford, Oxford, UK.
authors.forename: Owen
authors.initials: O
authors.lastname: Cotton-Barratt
mesh_terms: D003132:Commerce; D017281:Cost of Illness; D003657:Decision Making; D004785:Environmental Pollutants / Q000191:economics; D004992:Ethics, Medical; D006291:Health Policy; D006801:Humans; D007351:Insurance, Liability; D018803:Models, Economic; D015233:Models, Statistical; D011336:Probability; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods*; D012308:Risk Management; D013223:Statistics as Topic
chemical_list: D004785:Environmental Pollutants
keywords: Competition; incentives; limited liability; market failure; rare events; statistical lives; tragedy of the commons