Reasoning under Rawls' veil-of-ignorance mitigates self-serving bias in resource allocation during the COVID-19 crisis

Veil-of-ignorance reasoning mitigates self-serving bias in resource allocation during the COVID-19 crisis. Karen Huanga   Regan M. Bernhardb   Netta Barak-Correnc   Max H. Bazermand   Joshua D. Greenee. Judgment and Decision Making, Vol. 16, No. 1, January 2021, pp. 1-19. http://journal.sjdm.org/20/201205/jdm201205.html

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.

Keywords: fairness; self-serving bias; procedural justice; bioethics; COVID-19

4  General Discussion

In two pre-registered studies, we show that veil-of-ignorance reasoning favors allocating scarce medical resources to younger patients in response to the COVID-19 ventilator dilemma. Participants who first engaged in veil-of-ignorance reasoning, compared to participants who did not engage in veil-of-ignorance reasoning, were subsequently more likely to approve of a utilitarian policy that maximizes the number of life-years saved. These findings, predicted based on prior research (Huang, Greene & Bazerman, 2019), make three further contributions.

First, and most straightforwardly, these results apply directly to an ongoing crisis in which competing claims to fairness must be resolved. While the ventilator shortage in the developed world is currently less acute than many feared, it is likely that the COVID-19 crisis will continue to generate moral dilemmas of a similar form. These may be due to limited resources of other kinds such as medical personnel (Bernstein, 2020), the further spread of the disease in the developing world (Woodyatt, 2020), or structurally similar dilemmas arising from the distribution of vaccines (Emanuel, 2020b; Sun, 2020b; Ahuja, 2020). Moreover, it is likely that bioethical dilemmas of this general form will arise in future public health crises. The present research indicates that VOI reasoning can be a useful tool, grounded in a principle of impartiality, for decision-makers confronting difficult decisions during such crises.

Second, the present results underscore the power of VOI reasoning to eliminate self-serving bias. Self-serving bias is pervasive, and few interventions have been shown to effectively mitigate it. We demonstrate an effective intervention to mitigate self-serving bias in moral dilemmas. In Study 2, few older participants (33%) in the control condition favored prioritizing younger patients. But after engaging in veil-of-ignorance reasoning, most older participants (62%) favored doing so, just like younger participants. Indeed, the VOI manipulation completely eliminated self-serving bias among older participants, despite a sizable effect in the control condition.

Third, the present results demonstrate that VOI reasoning can be applied not only to dilemmas varying numbers of lives saved (Huang, Greene & Bazerman, 2019), but also to dilemmas varying numbers of life-years saved. As noted previously, this is important for bioethical decision-making, in which QALYs are commonly – but controversially – regarded as a legitimate factor in the allocation of medical resources (Cropper, Aydede & Portney, 1994; Johannesson & Johansson, 1997; Rodriguez & Pinto, 2000; Busschbach, Hessing & Charro, 1993; Tsuchiya, Dolan & Shaw, 2003; Lewis & Charny, 1989). Likewise, age may also prove to be an important and contentious factor for decisions involving new technologies, such as AVs (Awad et. al., 2018), which may access information about age in new ways. Of course, the “quality” in QALYs depends on who makes those judgments, for what purposes, and under what circumstances (e.g., Ubel, Loewenstein & Jepson, 2003; Loewenstein & Ubel, 2008; Ne’eman, 2020).

The present experiments use a simple control condition, as in Experiments 1–3 of Huang, Greene and Bazerman (2019). In that prior work, Experiments 4–7 employed more sophisticated controls aimed at distinguishing the distinctive effects of veil-of-ignorance reasoning from component factors such as perspective taking, numerical reasoning, and anchoring. That work showed that the veil-of-ignorance effect depends critically on assigning probabilities that align with principles of impartiality. Here we employ a simple control because our aim is to assess the net effect of veil-of-ignorance reasoning, not to distinguish it from its components. For present purposes, we assume that the mechanisms behind the present results are comparable to those responsible for our prior results, which were the bases for our pre-registered hypotheses.

The empirical findings, of course, cannot provide definite answers for the normative questions raised by this dilemma. Nevertheless, healthcare professionals confronting distributional dilemmas must adjudicate between competing claims of fairness in the absence of definitive answers. Our starting point is neither that policies should favor the young over the old, nor that physicians should generalize freely from our findings to prioritize patients based on specific features such as identity, ability, or socioeconomic status (Ne’eman, 2020). Rather, we show that veil-of-ignorance reasoning could provide a widely respected and transparent standard for adjudicating claims of fairness. This procedure will result in different policies — some of those policies may favor the young, while other policies may favor others — depending on the specific context and circumstances of the dilemma involved. Insofar as one respects the veil-of-ignorance standard for impartiality, our findings provide concrete guidance on how to remove self-serving biases from decisions made by policy-makers and front-line professionals charged with allocating scarce resources during this crisis, and others that may follow.