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Nicholas Humphrey Introduction: Science Looks at Fairness IT FALLS TO ME, IN INTRODUCING THE FIRST SECTION OF THIS ISSUE, to make the obvious—but all important—point that the word “fair”has a double meaning. On the one hand, we say a situation is fair when we can see that it is well balanced in an objective sense—when, for example, things are distributed evenly, symmetrically, or in a stable configura­ tion. On the other hand, we say a situation is fair when we judge it to be well balanced in a moral sense—when things are distributed in ways we ourselves consider good, beautiful, or just. As it happens, we typically judge a situation to be morally fair when we can see it is as a matter of fact objectively fair. We say indeed that “fair is fair.” But this connection between moral and objective fair­ ness is presumably a contingent and not a necessary one. There would be nothing—in logic—to stop someone considering an objectively unfair situation to be a morally fair one. It would not be illogical, but—as the papers that follow show—it would be deeply inhuman. These papers, by pioneers in the new field of scientific ethics, bring the perspectives of ethology, anthropology, and experimental economics to bear on people’s (and monkeys’) sense of fair play as a psychological trait. And they combine to show how deep it goes: how human beings—following closely in the steps of their animal ancestors—universally equate objective fairness with moral fairness. Sure, there are local individual and cultural variations. But the lesson is clear that it is in the nature of human beings to value objective fair­ ness—to work for it when they have the chance to do so and to expect social research Vol 73 : No 2 : Summer 200 6 345 others to work for it too. The fairness trait is in effect a “moral instinct”: fair play is in our genes. However, in that case, we have to ask, as scientists, what evolu­ tionary cost-benefit calculation can have put it there? What adaptive function is the sense of fairness serving? Moral philosophers have long relied on analytic arguments to establish what the rules should be: seeking to define what fairness must be on a priori grounds. But asking the evolutionary question brings into sharp focus the question-begging nature of the classical arguments. Kant’s “categorical imperative,” Bentham’s “Golden Rule of do as you would be done by,” Mill’s “greatest happiness principle,” Rawls’s “origi­ nal position behind a veil of ignorance”—presumably none of these cut much ice with natural selection. Natural selection can only act a posteriori. If there has indeed been selection for the sense of fairness, then it must have been the consequences of individuals behaving in objectively fair or unfair ways that counted toward evolutionary success. As scientists, then, we have to tryto discoverjust what those conse­ quences are (or were). It is revealing to see how the different papers in this section address this issue. But there is certainly a common theme in what they find: namely, that when an individual behaves unfairly— or, at any rate, when he is seen to behave unfairly—he runs a high risk of being punished, albeit at some cost to the punishers. Going against what I just said, this may be just the place where evolutionary science does after all have something to learn from philos­ ophy—and especially from Rawls (though see what de Waal has to say). For evolutionary theory continues to have a problem with explaining behaviors whose benefits are spread indifferently across the group— and “altruistic punishment” of unfair behavior would seem to be just a case in point. True, pace Rawls, there is no point in pretending that in real life individual human beings start behind a veil of ignorance as to where they will be placed in the social order (nor individual monkeys for that matter). However, it can plausibly be argued that individual genes do 346 social research start behind just such a veil, because individual genes cannot possibly predict what kind of body they will end up...

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Additional Information

ISSN
1944-768X
Print ISSN
0037-783X
Pages
pp. 345-347
Launched on MUSE
2014-04-30
Open Access
No
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