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Veil-of-ignorance reasoning mitigates self-serving bias in resource allocation during the COVID-19 crisis

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2021-01

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Cambridge University Press (CUP)
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Huang, Karen, Regan Bernhard, Netta Barak-Corren, Max Bazerman, and Joshua D. Greene. "Veil-of-Ignorance Reasoning Mitigates Self-Serving Bias in Resource Allocation During the COVID-19 Crisis." Judgment and Decision Making 16, no. 1 (January 2021): 1–19.

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Abstract

The COVID-19 crisis has forced healthcare professionals to make tragic decisions concerning which patients to save. Furthermore, The COVID-19 crisis has foregrounded the influence of self-serving bias in debates on how to allocate scarce resources. A utilitarian principle favors allocating scarce resources such as ventilators toward younger patients, as this is expected to save more years of life. Some view this as ageist, instead favoring age-neutral principles, such as “first come, first served”. Which approach is fairer? The “veil of ignorance” is a moral reasoning device designed to promote impartial decision-making by reducing decision-makers’ use of potentially biasing information about who will benefit most or least from the available options. Veil-of-ignorance reasoning was originally applied by philosophers and economists to foundational questions concerning the overall organization of society. Here we apply veil-of-ignorance reasoning to the COVID-19 ventilator dilemma, asking participants which policy they would prefer if they did not know whether they were younger or older. Two studies (pre-registered; online samples; Study 1, N=414; Study 2 replication, N=1,276) show that veil-of-ignorance reasoning shifts preferences toward saving younger patients. The effect on older participants is dramatic, reversing their opposition toward favoring the young, thereby eliminating self-serving bias. These findings provide guidance on how to remove self-serving biases to healthcare policymakers and frontline personnel charged with allocating scarce medical resources during times of crisis.

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Economics and Econometrics, Applied Psychology, General Decision Sciences

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