Ethical Leadership as a Balance Between Opposing Neural Networks

Abstract

In this article, we explore the implications of opposing domains theory for developing ethical leaders. Opposing domains theory highlights a neurological tension between analytic reasoning and socioemotional reasoning. Specifically, when we engage in analytic reasoning (the task positive network), we suppress our ability to engage in socioemotional reasoning (the default mode network) and vice versa. In this article, we bring together the domains of neuroscience, psychology, and ethics, to inform our theorizing around ethical leadership. We propose that a key issue for ethical leadership is achieving a healthy balance between analytic reasoning and socioemotional reasoning. We argue that organizational culture often encourages too heavy a reliance on nonemotional forms of reasoning to arrive at moral judgments (i.e., the TPN). As a result, leaders run the risk of suppressing their ability to pay attention to the human side of moral dilemmas and, in doing so, dehumanize colleagues, particularly subordinates, and clients.

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Fig. 1

Notes

  1. 1.

    A neural network consists of a group of distinct brain regions that (1) tend to be consistently activated by a class of cognitive tasks (Duncan and Owen 2000; Corbetta et al. 1998); or (2) demonstrate strong positive resting state connectivity with each other (Van Dijk et al. 2010; Vincent et al. 2008; Yeo et al. 2011); and/or (3) are consistently deactivated (i.e., less active than when the participant is at rest) by a class of cognitive tasks (Shulman et al. 1997).

  2. 2.

    The term ‘anticorrelated’ refers to a negative correlation in activity between the networks, i.e., when one is active the other tends to be less active, as compared to average activity at rest. For further clarification, please see Fox et al. (2009).

  3. 3.

    As indexed by either fMRI or PET, the only common methods commonly available which can provide a relatively unbiased estimate of neural activity across the entire brain.

  4. 4.

    Some caveats should be mentioned about this suppressive relationship: (i) it does not appear to be mediated by direct inhibitory connections between the networks, and (ii) it is not absolute, i.e., the two networks can both be active both at rest and during the performance of some tasks. The suppressive relationship between the two networks is nonetheless a highly robust emergent feature of the network connectivity of the brain (Buckner et al. 2008). The significance of coactivation of the two networks is discussed in detail later in the manuscript.

  5. 5.

    Following work characterizing this stance by the philosopher Daniel Dennett, we originally labeled it the ‘intentional stance.’ We are now adopting a different label because the ‘Intentional’ stance is often used and understood in the literature in a manner which extends beyond Dennett’s initial characterization and conflates it with the ‘Phenomenal’ stance. As Robbins and Jack (2006) explain, the distinction between these two aspects of social cognition is most poignantly illustrated by comparing individuals with social processing deficits characteristic of Autism, e.g., poor performance on theory of mind tasks, on the one hand, and individuals with the primary personality characteristic of Psychopathy, namely callous affect or lack of empathic concern, on the other hand. Psychopathic individuals often evidence excellent theory of mind ability; however, their social behavior is instrumental in nature (i.e., they use their social skills to predict and manipulate others for their own benefit).

  6. 6.

    The tension between self-interest and concern for other is discussed in detail by Jones et al. (2007). While not directly relevant to our article, Jones and colleagues provided a comprehensive overview of this tension across multiple literature themes including its ethical underpinnings and the impact of organizational culture on moral decision making in organizations.

  7. 7.

    While this framework provides a useful way to parse the literature for our purposes, we note that we are skeptical that a clear distinction can be made between moral motivation and the other components of the model. In other models (e.g., Robbins and Jack 2006), moral motivation was closely tied to moral awareness. This has been well borne out by subsequent research, which shows that moral motivation (in particular feelings of empathetic concern) powerfully influences moral awareness, moral judgment and moral behavior.

  8. 8.

    This finding only held for judgments/verdicts that an act was morally wrong. Borg et al (2011) suggest that it is possible that different neural networks may be used for negative moral verdicts compared to positive moral verdicts.

  9. 9.

    A priori ethical value is defined as “a person’s intrinsic value, feelings, and potential and actual contributions to larger society.”

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Rochford, K.C., Jack, A.I., Boyatzis, R.E. et al. Ethical Leadership as a Balance Between Opposing Neural Networks. J Bus Ethics 144, 755–770 (2017). https://doi.org/10.1007/s10551-016-3264-x

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Keywords

  • Ethical leadership
  • Neuroscience
  • Dehumanization
  • Leadership development