Knowing Thyself: the Evolutionary Psychology of Moral Reasoning and Moral Sentiments

“Ought” cannot be derived from “is,” so why should facts about human nature be of interest to business ethicists? In this article, we discuss why the nature of human nature is relevant to anyone wishing to create a more just and humane workplace and society. We begin by presenting evolutionary psychology as a research framework, and then present three examples of research that illuminate various evolved cognitive programs. The first involves the cognitive foundations of trade, including a neurocognitive mechanism specialized for a form of moral reasoning: cheater detection. The second involves the moral sentiments triggered by participating in collective actions, which are relevant to organizational behavior. The third involves the evolved programs whereby our minds socially construct groups, and how these can be harnessed to reduce racism and foster true diversity in the workplace. In each case, we discuss how what has been learned about these evolved programs might inform the study and practice of business ethics. Introduction: Human Nature and Ethics Human beings have moral intuitions. Assume, for a moment, that some of these reflect the operation of reliably developing neural circuits, which implement programs that are species-typical and therefore cross-culturally universal. That is, assume that some forms of moral reasoning and moral sentiment are produced by elements of a universal human nature. Does this justify them ethically? Of course not. Natural selection favors designs on the basis of how well they promote their own reproduction, not on how well they promote ethical behavior. If this is not obvious, consider the fate of a mutation that alters the development of a neural circuit, changing its design away from the species standard. This new circuit design implements a decision rule that produces a radically different ethical choice in a particular type of situation: help rather than hurt, cooperate rather than free ride. Will this new decision rule, initially present in one or a few individuals, be eliminated from the population? Or will 92 / Business, Science, and Ethics it be retained, increasing in frequency over the generations until it replaces the old design, eventually becoming the new species standard? The fate of the mutant decision rule will be jointly determined by two ethically blind processes: chance and natural selection. Chance is blind not only to ethics, but to design: it cannot retain or eliminate circuit designs based on their consequences. Natural selection, however, is not blind to design. The mutant design and the standard design produce different ethical choices; these choices produce different consequences for the choosers, which can enhance or reduce the average rate at which they produce offspring (who carry the same design). If the mutant decision rule better promotes its own reproduction (through promoting the reproduction of its bearers), it will be favored by selection. Eventually, over the generations, it will become the new species-standard. The decisions it produces—ethical or otherwise—will become the “common sense” of that species. This is the process that, over eons, constructed our human nature. As a result, human nature is comprised of programs that were selected for merely because they outreproduced alternative programs in the past. There is nothing in this process to ensure the production of decision rules or moral sentiments that track the desiderata of an ethically justifiable moral system. So why should ethicists care about human nature? Human nature matters for three reasons. First, outcomes matter. Many ethicists are concerned with how to create a more just and humane society, starting in the workplace. But what policies are capable of achieving this? Whereas some moral philosophers argue that an outcome is ethical if the procedure that produced it was ethical (e.g., Nozick, 1975), others argue that certain outcomes are ethically better than others and that policies and rules of interaction should be chosen—at least in part—according to how well they achieve ethical outcomes (e.g., Bentham, 1789; Rawls, 1971; Sen, 1999). When outcomes matter, policy choices need to be made in light of human nature. What incentives encourage people to contribute to a public good, such as clean air? If people are starving and need to be fed, will collective incentive systems succeed in feeding them? If racial equality in the workplace is the goal, will this be best achieved by seminars designed to ferret out negative stereotypes in the attitudes of participants? Or will this increase hostility, making matters worse? The nature of human nature matters for a second reason: It may place constraints on what can be considered a moral imperative. An action cannot be morally required unless it is possible to perform. But when it comes to human behavior, the meaning of possible is complicated (see Conclusions). Consider the following example. Corporations have many internal rules regulating procedures, a (large) subset of which are not safety rules. Yet violations of these rules can produce cascades of consequences that end up being ethically catastrophic (think Homer Simpson at the nuclear plant). Perhaps people should be alert to such violations; perhaps this should be a moral imperative, in the same way that monitoring the safety of one’s child is. The mind is designed to moniTHE EVOLUTIONARY PSYCHOLOGY OF MORAL REASONING / 93 tor for breaches of safety rules (Fiddick, Cosmides, and Tooby, 2000; Stone et al. 2002), and certain conditions, such as impending parenthood, seem to hyperactivate this system (Leckman and Mayes, 1998, 1999). But what if the human mind lacks cognitive mechanisms that spontaneously monitor for violations of procedural rules when these are not, in any obvious way, about safety? If this were true, could a person be held ethically responsible for not noticing such a breach? As we will see, this example is not as science-fictional as it may seem. There is yet a third reason that ethicists should care about human nature: Ethicists are human beings. If the human cognitive architecture contains programs that generate moral intuitions in humans, then it generates moral intuitions in humans who are ethicists. These evolved programs cause certain moral intuitions to be triggered by particular situations. Yet this in no way justifies those moral intuitions—see above. Indeed, on reflection, some of these moral intuitions may be found wanting (yes, the ability to reflect is also made possible by evolved programs; see Leslie, 1987; Frith, 1992; Baron-Cohen, 1995; Cosmides and Tooby, 2000a). If outcomes matter to ethical judgments, then ethicists need to focus on the real world consequences of alternative policies, and not have their judgment unduly affected by moral sentiments that are nothing more than read-outs of evolved programs that were generated by an amoral process. Justified or not, people’s moral sentiments are a fact of life that anyone in business will need to accommodate. Far more needs to be known about the evolutionary psychology of moral reasoning and moral sentiments, but a start has been made. Below we present a brief overview of where evolutionary psychology fits in the intellectual landscape. Then we present empirical findings from evolutionary psychology relevant to three different topics: social exchange, collective action, and the social construction of groups. Some findings, like the results about social exchange, rest on a large evidentiary base that also includes cross-cultural tests. Others are newer, and more tentative. We offer these findings not as the last word on each topic, but as food for thought. For each topic, we briefly discuss possible implications for business ethics. Our intention is not to present well-worked out ethical theories in these sections. Instead, they are offered in the spirit of brain storming, as an exercise in how research in evolutionary psychology might eventually inform ethical theory and practice. What is Evolutionary Psychology? In the final pages of the Origin of Species, after Darwin had presented the theory of evolution by natural selection, he made a bold prediction: “In the distant future I see open fields for far more important researches. Psychology will be based on a new foundation, that of the necessary acquirement of each mental power and capacity by gradation.” More than a century later, a group of scientists—Martin Daly, Margo Wilson, Don Symons, John Tooby, Leda Cosmides, David Buss, Steve Pinker, Gerd Gigerenzer—began to work out exactly how Darwin’s fundamental insights could be used as a foundation on which to build 94 / Business, Science, and Ethics a more systematic approach to psychology (for review, see Tooby and Cosmides, 1992; see also Symons, 1979; Cosmides and Tooby, 1987; Daly and Wilson, 1988; Buss, 1989; Pinker, 1997; Gigerenzer, 2000). We were motivated by new developments from a series of different fields: Advance #1. The cognitive revolution was providing, for the first time in human history, a precise language for describing mental mechanisms, as programs that process information. Advance #2. Advances in paleoanthropology, hunter-gatherer studies and primatology were providing data about the adaptive problems our ancestors had to solve to survive and reproduce and the environments in which they did so. Advance #3. Research in animal behavior, linguistics, and neuropsychology was showing that the mind is not a blank slate, passively recording the world. Organisms come factory-equipped with knowledge about the world, which allows them to learn some relationships easily, and others only with great effort, if at all. Skinner’s hypothesis—that learning is a simple process governed by reward and punishment—was simply wrong. Advance #4. Evolutionary game theory was revolutionizing evolutionary biology, placing it on a more rigorous, formal foundation of replicator dynamics. This clarified how natural selection works, what counts as an adaptive function, and what the criteria are for calling a trait an adaptation. We thought that, if one were careful about the causal connections between these disciplines, these new developments could be pieced together into a single integrated research framework, in a way that had not been exploited before because the connections ran between fields rather than cleanly within them. We called this framework evolutionary psychology. The goal of research in evolutionary psychology is to discover, understand, and map in detail the design of the human mind, as well as to explore the implications of these new discoveries for other fields. The eventual aim is to map human nature—that is, the species-typical information-processing architecture of the human brain. Like all cognitive scientists, when evolutionary psychologists refer to “the mind,” they mean the set of information-processing devices, embodied in neural tissue, that are responsible for all conscious and nonconscious mental activity, and that generate all behavior. And like other psychologists, evolutionary psychologists test hypotheses about the design of these information-processing devices—these programs—using laboratory methods from experimental cognitive and social psychology, as well as methods drawn from experimental economics, neuropsychology, and cross-cultural field work. What allows evolutionary psychologists to go beyond traditional approaches in studying the mind is that they make active use in their research of an often overlooked fact: That the programs comprising the human mind were designed by natural selection to solve the adaptive problems faced by our huntergatherer ancestors—problems like finding a mate, cooperating with others, THE EVOLUTIONARY PSYCHOLOGY OF MORAL REASONING / 95 hunting, gathering, protecting children, avoiding predators, and so on. Natural selection tends to produce programs that solve problems like these reliably, quickly, and efficiently. Knowing this allows one to approach the study of the mind like an engineer. You start with a good specification of an adaptive information-processing problem, then you do a task analysis of that problem. This allows you to see what properties a program would have to have in order to solve that problem well. This approach allows you to generate testable hypotheses about the structure of the programs that comprise the mind. From this point of view, there are precise causal connections that link the four developments above into a coherent framework for thinking about human nature and human society (Tooby and Cosmides, 1992). These connections (C1 through C-6) are as follows: C-1. Each organ in the body evolved to serve a function: the intestines digest, the heart pumps blood, the liver detoxifies poisons. The brain is also an organ, and its evolved function is to extract information from the environment and use that information to generate behavior and regulate physiology. From this perspective, the brain is a computer, that is, a physical system that was designed to process information (Advance #1). Its programs were designed not by an engineer, but by natural selection, a causal process that retains and discards design features on the basis of how well they solved problems that affect reproduction (Advance #4). The fact that the brain processes information is not an accidental sideeffect of some metabolic process: The brain was designed by natural selection to be a computer. Therefore, if you want to describe its operation in a way that captures its evolved function, you need to think of it as composed of programs that process information. The question then becomes, what programs are to be found in the human brain? What are the reliably developing, species-typical programs that, taken together, comprise the human mind? C-2. Individual behavior is generated by this evolved computer, in response to information that it extracts from the internal and external environment (including the social environment) (Advance #1). To understand an individual’s behavior, therefore, you need to know both the information that the person registered and the structure of the programs that generated his or her behavior. C-3. The programs that comprise the human brain were sculpted over evolutionary time by the ancestral environments and selection pressures experienced by the hunter-gatherers from whom we are descended (Advances #2 and #4). Each evolved program exists because it produced behavior that promoted the survival and reproduction of our ancestors better than alternative programs that arose during human evolutionary history. Evolutionary psychologists emphasize hunter-gatherer life because the evolutionary process is slow—it takes tens of thousands of years to build a program of any complexity. The industrial revolution—even the agricultural revolution—are mere eyeblinks in evolutionary time, too short to have selected for new cognitive programs. 96 / Business, Science, and Ethics C-4. Although the behavior our evolved programs generate would, on average, have been adaptive (reproduction-promoting) in ancestral environments, there is no guarantee that it will be so now. Modern environments differ importantly from ancestral ones—particularly when it comes to social behavior. We no longer live in small, face-to-face societies, in semi-nomadic bands of 50100 people, many of whom were close relatives. Yet our cognitive programs were designed for that social world. C-5. Perhaps most importantly, the brain must be comprised of many different programs, each specialized for solving a different adaptive problem our ancestors faced—i.e., the mind cannot be a blank slate (Advance #3). In fact, the same is true of any computationally powerful, multi-tasking computer. Consider the computer in your office. So many people analyze data and write prose that most computers come factory-equipped with a spreadsheet and a text-editor. These are two separate programs, each with different computational properties. This is because number-crunching and writing prose are very different problems: the design features that make a program good at data analysis are not well-suited to writing and editing articles, and vice versa. To accomplish both tasks well, the computer has two programs, each well-designed for a specific task. The more functionally specialized programs it has, the more intelligent your computer is: the more things it can do. The same is true for people. Our hunter-gatherer ancestors were, in effect, on a camping trip that lasted a lifetime, and they had to solve many different kinds of problems well to survive and reproduce under those conditions. Design features that make a program good at choosing nutritious foods, for example, will be ill-suited for finding a fertile mate. Different problems require different evolved solutions. This can be most clearly seen by using results from evolutionary game theory (Advance #4) and data about ancestral environments (Advance #2) to define adaptive problems, and then carefully dissecting the computational requirements of any program capable of solving those problems. So, for example, programs designed for logical reasoning would be poorly-designed for detecting cheaters in social exchange, and vice versa; as we will show, it appears that we have programs that are functionally specialized for reasoning about reciprocity and exchange. C-6. Lastly, if you want to understand human culture and society, you need to understand these domain-specific programs. The mind is not like a video camera, passively recording the world but imparting no content of its own. Domain-specific programs organize our experiences, create our inferences, inject certain recurrent concepts and motivations into our mental life, give us our passions, and provide cross-culturally universal frames of meaning that allow us to understand the actions and intentions of others. They cause us to think certain very specific thoughts; they make certain ideas, feelings, and reactions seem reasonable, interesting, and memorable. Consequently, they play a key role in determining which ideas and customs will easily spread from mind to mind, and which will not. That is, they play a crucial role in shaping human culture. THE EVOLUTIONARY PSYCHOLOGY OF MORAL REASONING / 97 Instincts are often thought of as the diametric opposite of reasoning. But the reasoning programs that evolutionary psychologists have been discovering (i) are complexly specialized for solving an adaptive problem; (ii) they reliably develop in all normal human beings; (iii) they develop without any conscious effort and in the absence of formal instruction; (iv) they are applied without any awareness of their underlying logic, and (v) they are distinct from more general abilities to process information or behave intelligently. In other words, they have all the hallmarks of what we usually think of as an instinct (Pinker, 1994). In fact, one can think of these specialized circuits as reasoning instincts. They make certain kinds of inferences just as easy, effortless and “natural” to us as humans, as spinning a web is to a spider or building a dam is to a beaver. Consider this example from the work of Simon Baron-Cohen (1995), using the Charlie task. A child is shown a schematic face (“Charlie”) surrounded by four different kinds of candy. Charlie’s eyes are pointed toward the Milky Way bar (for example). The child is then asked, “Which candy does Charlie want?” Like you and I, a normal 4 year old will say that Charlie wants the Milky Way— the candy Charlie is looking at. In contrast, children with autism fail the Charlie task, producing random responses. However—and this is important—when asked which candy Charlie is looking at, children with autism answer correctly. That is, children with this developmental disorder can compute eye direction correctly, but they cannot use that information to infer what someone wants. We know, spontaneously and with no mental effort, that Charlie wants the candy he is looking at. This is so obvious to us that it hardly seems to require an inference at all. It is just common sense. But “common sense” is caused: it is produced by cognitive mechanisms. To infer a mental state (wanting) from information about eye direction requires a computation. There is a little inference circuit—a reasoning instinct—that produces this inference. When the circuit that does this computation is broken or fails to develop, the inference cannot be made. Those with autism fail the Charlie task because they lack this reasoning instinct. As a species, we have been blind to the existence of these instincts—not because we lack them, but precisely because they work so well. Because they process information so effortlessly and automatically, their operation disappears unnoticed into the background. These instincts structure our thought so powerfully that it can be difficult to imagine how things could be otherwise. As a result, we take normal behavior for granted: We do not realize that normal behavior needs to be explained at all. For example, at a business school, all aspects of trade are studied. Business school scholars and students take for granted the fact that, by exchanging goods and services, people can make each other better off. But this kind of cooperation for mutual benefit—known in evolutionary biology as reciprocity, reciprocal altruism, or social exchange—is not common in the animal kingdom. Some species—humans, vampire bats, chimpanzees, baboons—engage in this very useful form of mutual help, whereas others do not (Cashdan, 1989; Isaac, 1978; Packer, 1977; de Waal, 1989; Wilkinson, 1988). 98 / Business, Science, and Ethics This rarity is itself telling: It means that social exchange is not generated by a simple general learning mechanism, such as classical or operant conditioning. All organisms can be classically and operantly conditioned, yet few engage in exchange. This strongly suggests that engaging in social exchange requires specific cognitive machinery, which some species have and others lack. That is, there are good reasons to think we humans have cognitive machinery that is functionally specialized for reasoning about social exchange—reasoning instincts that make thinking about and engaging in social exchange as easy and automatic for humans as stalking prey is for a lion or building a nest is for a bird. But what, exactly, are these programs like? The research we have been conducting with our colleagues on the cognitive foundations of social exchange—of trade—suggests that the programs that allow social exchange to proceed in humans are specialized for that function, and include a subroutine that one can think of as an instinct that causes a certain kind of moral reasoning: the detection of cheaters. The Cognitive Foundations of Trade Selection pressures favoring social exchange exist whenever one organism (the provisioner) can change the behavior of a target organism to the provisioner’s advantage by making the target’s receipt of a provisioned benefit conditional on the target acting in a required manner. This mutual provisioning of benefits, each conditional on the others’ compliance, is what is meant by social exchange or reciprocation (Cosmides, 1985; Cosmides and Tooby, 1989; Tooby and Cosmides, 1996). Social exchange is an “I’ll scratch your back if you scratch mine” principle: X provides a benefit to Y conditional on Y doing something that X wants. Robert Trivers, W. D. Hamilton, Robert Axelrod, and other evolutionary researchers used game theory to understand the conditions under which social exchange can and cannot evolve (Trivers, 1971; Axelrod and Hamilton, 1981; Boyd, 1988). For adaptations causing this form of cooperation to evolve and persist—that is, for reciprocation to be an evolutionarily stable strategy (ESS)— the behavior of cooperators must be generated by programs that perform certain specific tasks well. For example these programs would need design features that would (i) allow cooperators to detect cheaters (i.e., those who do not comply or reciprocate), and (ii) cause cooperators to channel future benefits to reciprocators, not cheaters (Trivers, 1971; Axelrod and Hamilton, 1981; Axelrod, 1984). In other words, reciprocation cannot evolve if the organism lacks reasoning procedures that can effectively detect cheaters (i.e., those who take conditionally offered benefits without providing the promised return). Such individuals would be open to exploitation, and hence selected out. Based on such analyses, Cosmides and Tooby hypothesized that the human neurocognitive architecture includes social contract algorithms: a set of programs that were specialized by natural selection for solving the intricate computational problems inherent in adaptively engaging in social exchange behavior, including a subroutine for cheater detection. THE EVOLUTIONARY PSYCHOLOGY OF MORAL REASONING / 99 Conditional Reasoning Reciprocation is, by definition, social behavior that is conditional: you agree to deliver a benefit conditionally (conditional on the other person doing what you required in return). Understanding it therefore requires conditional reasoning. Indeed, an agreement to exchange—a social contract—can be expressed as a conditional rule: If A provides a requested benefit to or meets the requirement of B, then B will provide a rationed benefit to A. A cheater is someone who illicitly takes the benefit specified in the social contract; that is, someone who violates the social contract by taking the benefit without meeting the provisioner’s requirement. Because engaging in social exchange requires conditional reasoning, investigations of conditional reasoning can be used to test for the presence of social contract algorithms. The hypothesis that the brain contains social contract algorithms predicts a sharply enhanced ability to reason adaptively about conditional rules when those rules specify a social exchange. The null hypothesis is that there is nothing specialized in the brain for social exchange: This predicts no enhanced conditional reasoning performance specifically triggered by social exchanges as compared to other contents. A standard tool for investigating conditional reasoning is Wason’s 4-Card Selection Task (Wason, 1966, 1983; Wason and Johnson-Laird, 1972). Using this task, Cosmides, Tooby, and their colleagues conducted an extensive series of experiments to address the following questions: 1. Do our minds include cognitive machinery that is specialized for reasoning about social exchange? (alongside some other domain-specific mechanisms, each specialized for reasoning about a different adaptive domain involving conditional behavior?) Or, 2. Is the cognitive machinery that causes good conditional reasoning general—does it operate well regardless of content? (a blank slate-type theory; Pinker, 2002). This second, blank-slate view was in trouble before we even started our investigations. If the human brain had cognitive machinery that causes good conditional reasoning regardless of content, then people should be good at tasks requiring conditional reasoning. For example, they should be good at detecting violations of conditional rules. Yet studies with the Wason selection task had already shown that they are not. The Wason task asks you to look for potential violations of a conditional rule (If P then Q), such as “If a person has Ebbinghaus disease, then that person is forgetful” (see Figure 1 [p. 100], panel a). The rule is accompanied by pictures of four cards, each representing one person— a patient in this case. For each card, one side tells whether the patient in question has Ebbinghaus disease, and the other side tells whether that patient is forgetful. However, you can see only one side of each card, so your information about each patient is incomplete. The question: Which card(s) would you need to turn over to find out if there are patients whose situation violates the rule? 100 / Business, Science, and Ethics