Decisions as diverse as committing soldiers to the battlefield or picking a school for your child share a basic attribute: assuming responsibility for the outcome of others. This responsibility is inherent in the roles of prime ministers and generals, as well as in the more quotidian roles of firmmanagers, schoolteachers, and parents. Here we identify the underlying behavioral, computational, and neurobiologicalmechanisms that determine the choice to assume responsibility over others. Leaders must take responsibility for others and affect the well-being of individuals, organizations, and nations. We identify the effects of responsibility on leaders' choices at the behavioral and neurobiological level and document the widespread existence of responsibility aversion, i.e., a reduced willingness to make decisions if the welfare of others is at stake. In mechanistic terms, basic preferences towards risk, losses and ambiguity do not explain responsibility aversion which, instead, is driven by a second-order cognitive process reflecting an increased demand for certainty about the best choice when others' welfare is affected. Finally, models estimating levels of information flow between brain regions processing separate choice components, provide the first step in understanding the neurobiological basis of individual variability in responsibility aversion and leadership scores. We identify and characterize the computations and neural mechanisms underlying choices to lead.
This file includes:Hyperlinked Table of Contents Materials and Methods
Supplementary ResultsFigs. S1 to S8 Tables S1 to S7 References and notes Appendix S1Appendix S22
Participants and sample size determination.We conducted the experiment with two separate samples of participants -marked throughout the manuscript as original and fMRI replication groups. The difference between the groups was that the latter performed the delegation task in the MRI scanner. Previous laboratory experiments on individual versus group decision making have typically used between 30-50 participants (37-39).Power calculations (40) based on the aforementioned studies average effect sizes suggested a stopping criterion of 40 participants as a reasonable estimate to ensure a statistical power of 0.8 (with an alpha level of 0.05). We thus recruited 40 participants for the original group (21 females; age 25.7 ± 0.66 standard error of the mean). In the fMRI replication group, we added, a priori, four additional participants (constituting one unit of participants, see below, resulting in 44 participants; 25 females; age 23.5 ± 0.43). This was done in anticipation of some minor data loss due to issues such as excessive head movement in the scanner, and because the minimum experimental session size could not be under eight participants (see task design below). The data for three participants were not fully collected (two participants failed the test quiz assessing comprehension of the instructions and one participant did not show up for the second stage), resulting in a fi...