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Computational and neurobiological foundations of leadership decisions


Edelson, Micah G; Polania, Rafael; Ruff, Christian C; Fehr, Ernst; Hare, Todd A (2018). Computational and neurobiological foundations of leadership decisions. Science, 361(6401):online.

Abstract

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.

Abstract

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.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Uncontrolled Keywords:Multidisciplinary
Language:English
Date:August 2018
Deposited On:14 Aug 2018 13:31
Last Modified:12 Apr 2019 07:03
Publisher:American Association for the Advancement of Science
ISSN:0036-8075
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1126/science.aat0036
Official URL:http://science.sciencemag.org/content/361/6401/eaat0036
Project Information:
  • : FunderSNSF
  • : Grant ID100014_140277
  • : Project TitleInteractions between social signals, stress, and self-control
  • : FunderSNSF
  • : Grant IDCRSII3_141965
  • : Project TitleNeuroeconomics of value-based decision making

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