By Karl Arunski
Any licensed professional – whether in engineering, law, or medicine – is required to adhere to their profession’s standards of ethics and must likely participate in annual ethics training. These sessions typically advise participants of the governing rules and the consequences of not following them. That is the accepted standard for corporate ethics. But what happens when there are conflicts, either among the rules themselves, or between the rules and our personal values? To resolve these tricky situations, both professionally and ethically, requires an understanding of moral reasoning (1).
Useful insights into moral reasoning are provided by various authors, notably Lawrence Kohlberg, Robert Kegan, and Rushworth Kidder. Rather than lecturing us on right and wrong, each author provides insight into how human thinking develops and where we might stand in that process ourselves.
Kohlberg (1958) (4) posits that we progress through moral reasoning stages that he characterizes as pre-conventional, conventional, and post-conventional. Children are typically pre-conventional. They learn to distinguish between right and wrong through systems of reward and punishment. By adulthood, most people reside at the conventional level at which they not only adhere to the rules and norms of society because they understand their purpose and value, but also teach and enforce those customs. A conundrum arises when breaking the rules might offer better alternatives. Think, speeding in an emergency or, for engineers, “pushing the envelope” of a technology, or employing artificial intelligence (AI) to make sensitive decisions. These situations epitomize post-conventional reasoning. Kohlberg cautions that you cannot legitimately operate at the post-conventional stage without acknowledgement and respect of society’s rules and conventional reasoning.
Similarly, Robert Kegan (1982) (2) outlines how our sense of self evolves as we interact with difficult situations. We toggle between internal and external foci as we learn to balance our personal needs and perspectives with those of others. Like Kohlberg, Kegan observes that we grow from our childhood’s impulsive stage through adulthood where we understand our institutions and their roles in society. Eventually for some, there is a stage where we comprehend the tensions the lie at intersection of interpersonal and interinstitutional norms.
While Kohlberg and Kegan provide insight for self-reflection in ethically ambiguous situations, Rushworth Kidder (1996) (3) provides a useful algorithm that might appeal to the logical minds of technical professionals. Kidder identifies ethical dilemmas where the choice is not between right and wrong, but between right and right: Justice vs. mercy (think the plight of refugees), individual vs. community (think, rights of marginalized communities), truth vs. loyalty (think, do I inform my team of a pending lay off), and short-term vs. long-term (think, business investment). His approach is straightforward: Act after looking at the situation through three lenses. First, what do the rules tell me to do? Secondly and counter-intuitively, what would I do if there were no rules to either guide or constrain me? Finally, regardless of the rules, what approach embodies the greatest care for those involved?
At the heart of this discussion is not a delineation of right and wrong or the consequences of unethical behavior. Rather, the takeaway for technology and engineering managers is introspection: What will guide us as we demonstrate leadership and make decisions that enable us and our teams to sleep well at night?
Digging Deeper:
(1) “Moral Reasoning”, Stanford Encyclopedia of Philosophy, https://plato.stanford.edu/entries/reasoning-moral/.
(2) Kegan, R. (1982). The Evolving Self: The Problem and Process in Human Development. Harvard University Press.
(3) Kidder, R. (1996). How Good People Make Tough Choices: Resolving the Dilemmas of Ethical Living. Fireside, Simon and Schuster.
(4) Kohlberg, L. (1958). The Development of Modes of Thinking and Choices in Years 10 to 16. Ph. D. Dissertation, University of Chicago.
About the author
Karl Arunski is a life senior member of IEEE and serves as the Vice President of Education for the IEEE Technology and Engineering Management Society. He retired after a career in systems engineering, engineering management and mission assurance during which he concurrently developed and taught graduate level courses as an adjunct at Southern Methodist University. He is a graduate of the United States Military Academy at West Point and holds a MS-EE from Washington University in St. Louis.
