The Economy of Nature: A Brief Introduction

all organic beings are striving to seize on each place in the economy of nature

(Darwin, [1859] 2003, p. 90)

Needless to say, Darwin’s theory of descent with modification was a true conceptual revolution[1]. It provides a general mechanism that explains the diversity and adaptivity of living beings—natural selection—and a guiding principle for organizing the mass of facts about them, the tree of life [2]. In recalling how this idea had come to his mind, Darwin wrote that he was trying to solve one problem: how is it that plants and animals sharing a common ancestry end up to be so different?

“The solution, as I believe, is that the modified offspring of all dominant and increasing forms tend to become adapted to many and highly diversified places in the economy of nature”[3].

Darwin repeatedly uses the expression “economy of nature” in The Origin of Species and other writings. He was not the first to conceive nature as an economy, although he was among the first to suggest an explicit similarity between natural and political economy. Before Darwin, the idea of nature as an economy had no particular ramification with human economic practices. In The Sacred Theory of the Earth, theologian Thomas Burnet referred to the “Oeconomy of nature” as the “well ordering of the great Family of living Creatures”[4] an order of divine origin. Swedish naturalist Carl Linnaeus, in his Specimen Academicum de Oeconomia Naturae, construed this divine order has being self-organized, exhibiting a balance of births and deaths, a complementarity between the function and purpose of life forms[5]. Adam Smith recognized the unity of this economy, where all living forms strive for “self-preservation, and the propagation of the species” but are limited in their problem-solving capacities, and hence must often rely on intuition instead of reasoning[6]. Lyell, in his Principle of Geology, describes how the involuntary agency of human and other animals “

contribute to extend or limit the geographical range and numbers of certain species, in obedience to general rules in the economy of nature, which are for most the part out of our control”[7].

Where Linnaeus saw a clockwork organization, Lyell’s representation of the world was more that of a dynamic equilibrium.

Thus, from natural theology to geology, the economy of nature referred to the complex organization of the universe[8]. What was new with Darwin is that the economy of nature began to be understood with conceptual tools borrowed from political economy. The division of labor, competition (“struggle” in Darwin’s words), trading, cost, the accumulation of innovations, the emergence of complex order from unintentional individual actions, the scarcity of resources and the geometric growth of populations are ideas borrowed from Adam Smith, Thomas Malthus, David Hume and other founders of modern economics. Thus, the “economy of nature” ceased to be an abstract representation of the universe and became a depiction of the complex web of interactions between biological individuals, species and their environment. The beginning of evolutionary biology coincided also with the beginning of ecology. The founder of ecology, Ernst Haeckel, defined this science as

“the body of knowledge concerning the economy of nature (…) the study of all those complex interrelationships referred to by Darwin as the condition of the struggle for existence”[9].

Consequently, Darwin’s main contributions are its transforming biology into a historical science (like geology) and an economic science[10]. From evolutionary game theory to biological markets, this approach is now flourishing.



Notes and References

[1] (Charles Darwin, 1859)
[2] (see Dennett, 1995; Gayon, 2003; Thagard, 1992, chapter 6)
[3] (C. Darwin, 1887, p. 84)
[4] (Burnet, [ca. 1692]1965, II, x),
[5] (Hestmark, 2000; Linnaeus, 1751).
[6] (Smith, [1759] 2002, p. 90)
[7] (Lyell, [1830-33]1853, p. 664)
[8] (Bowler, 1976; Ghiselin, 1978, 1995, 1999; Hammerstein & Hagen, 2005; Hodgson, 2001; Schabas, 2005)
[9] in “Morphology of Organisms” (1866); see (Stauffer, 1960).
[10] (Ghiselin, 1999, p. 7).

• Bowler, P. J. (1976). Malthus, Darwin, and the Concept of Struggle. Journal of the History of Ideas, 37(4), 631-650.
• Burnet, T. ([ca. 1692]1965). The sacred theory of the earth. Carbondale,: Southern Illinois University Press.
• Darwin, C. (1859). On the origin of species by means of natural selection. London,: J. Murray.
• Darwin, C. (1887). Autobiography. In F. Darwin (Ed.), The life and letters of Charles Darwin, including an autobiographical chapter (Vol. 1, pp. 26-106). London: John Murray.
• Dennett, D. C. (1995). Darwin's dangerous idea : evolution and the meanings of life. New York: Simon & Schuster.
• Gayon, J. (2003). From Darwin to Today in Evolutionary Biology. In J. Hodge & G. Radick (Eds.), The Cambridge Companion to Darwin (pp. 240-264). Cambridge: Cambridge University Press.
• Ghiselin, M. T. (1978). The Economy of the body The America Economic Review, 68 (2), 233-237.
• Ghiselin, M. T. (1995). Perspective: Darwin, progress and economic principle. Evolution, 49(6), 1029-1037.
• Ghiselin, M. T. (1999). Darwinian monism: the economy of nature. In P. Koslowski (Ed.), Sociobiology and bioeconomics : the theory of evolution in biological and economic theory (pp. x, 341 p.). Berlin ; New York: Springer.
• Hammerstein, P., & Hagen, E. H. (2005). The second wave of evolutionary economics in biology. Trends in Ecology & Evolution, 20(11), 604.
• Hestmark, G. (2000). Oeconomia Naturae L. Nature, 405(6782), 19.
• Hodgson, G. M. (2001). Bioeconomics. In P. A. O'Hara (Ed.), Encyclopedia of Political Economy (pp. 37-41). London ; New York: Routledge/Taylor & Francis Group.
• Linnaeus, C. (1751). Specimen Academicum de Oeconomia Naturae. Amoenitas Academicae, 2, 1-58.
• Lyell, C. ([1830-33]1853). Principles of geology; or, The modern changes of the earth and its inhabitants considered as illustrative of geology (9th and entirely rev. ed.). London,: J. Murray.
• Schabas, M. (2005). The natural origins of economics. Chicago: University of Chicago Press.
• Smith, A. ([1759] 2002). The theory of moral sentiments. Cambridge, U.K. ; New York: Cambridge University Press.
• Stauffer, R. C. (1960). Ecology in the Long Manuscript Version of Darwin's" Origin of Species" and Linnaeus'" Oeconomy of Nature". Proceedings of the American Philosophical Society, 104(2), 235-241.
• Thagard, P. (1992). Conceptual revolutions. Princeton, N.J.: Princeton University Press.

The Complete Work of Charles Darwin Online

This site contains Darwin's complete publications and many of his handwritten manuscripts. There are over 50,000 searchable text pages and 40,000 images. There is also the largest Darwin bibliography and manuscript catalogue ever published. More than 150 ancillary texts are included, ranging from reference works to reviews, obituaries, descriptions of the Beagle specimens and related works for understanding Darwin's context. Free audio mp3 versions of his works are also available.

FEATURES (click to see what is special about this site)

Most of the works on this site appear online for the first time such as the first editions of Journal of Researches, Descent of Man, Zoology and all six editions of the Origin of species (1st, 2nd, 3rd, 4th, 5th & 6th). There are many never before published manuscripts such as Darwin's Beagle field notebooks and complete images of his early theoretical notebooks.

Darwin's evolutionary social psychology

While reading the chapter 5 of Darwin's The Descent of Man, I noticed that Darwin reconstruct Human evolutionary history as--forgive the anachronism--a gene-culture co-evolution. Of course, there was no concept of gene in Darwin's time, so the correct label would be "nature-culture co-evolution", but I was amazed to see how his intuitions are closed to current theories. Basically, he described our evolution as an evolutionary arms race (another anachronism) between social life and intelligence. The process goes trough 3 phases: social instinct, social intelligence, and social reasoning:

1. Social instincts: learning and sympathy

General intelligence

• It deserves notice that, as soon as the progenitors of man became social (and this probably occurred at a very early period), the principle of imitation, and reason, and experience would have increased, and much modified the intellectual powers in a way, of which we see only traces in the lower animals.

Social instincts: sympathy, fidelity, and courage

• In order that primeval men, or the apelike progenitors of man, should become social, they must have acquired the same instinctive feelings, which impel other animals to live in a body; and they no doubt exhibited the same general disposition. They would have felt uneasy when separated from their comrades, for whom they would have felt some degree of love; they would have warned each other of danger, and have given mutual aid in attack or defence. All this implies some degree of sympathy, fidelity, and courage.

2. Social intelligence--reciprocity and approbation

Reciprocity:

• as the reasoning powers and foresight of the members became improved, each man would soon learn that if he aided his fellow-men, he would commonly receive aid in return. From this low motive he might acquire the habit of aiding his fellows; and the habit of performing benevolent actions certainly strengthens the feeling of sympathy which gives the first impulse to benevolent actions. Habits, moreover, followed during many generations probably tend to be inherited.

Approbation

• [a] powerful stimulus to the development of the social virtues, is afforded by the praise and the blame of our fellow-men. primeval man, at a very remote period, was influenced by the praise and blame of his fellows. It is obvious, that the members of the same tribe would approve of conduct which appeared to them to be for the general good, and would reprobate that which appeared evil.

3. Social reasoning--norms, rules and morality

• With increased experience and reason, man perceives the more remote consequences of his actions, and the self-regarding virtues, such as temperance, chastity, &c., which during early times are, as we have before seen, utterly disregarded, come to be highly esteemed or even held sacred.

Evolution, cooperation and kinds of altruism

[Another clarification attempt; as ususal, comments welcome!]

Perhaps the most remarkable aspect of evolution is its ability to generate cooperation in a competitive world. Thus, we might add "natural cooperation" as a third fundamental principle of evolution beside mutation and natural selection (Nowak, 2006, p. 1563)

In a first approximation, a cooperative behavior i) benefits the recipient and ii) is beneficent or costly to the actor. Thus cooperation has two components: altruism (costly,) and mutual benefits (beneficent).

Following Sober and Wilson (1998), one may distinguishes evolutionary (or biological) altruism from psychological altruism. Psychological altruism is a psychological motivation that take another agent’s well-being (or utility) as a ultimate ends, i.e., the other agent’s well-being is “is desired for its own sake, rather than because the agent thinks that satisfying the desire will lead to the satisfaction of some other desire” (Stich, 2007, p. 268). Evolutionary altruism refers to behavior by which an organism engages in a costly behavior that benefits another organism, the cost and benefits being evaluated in terms of fitness consequences. Biologists, since Darwin, wondered why an individual would invest time and resources to help another: “He who was ready to sacrifice his life, […] rather than betray his comrades, would often leave no offspring to inherit his noble nature” (Darwin, 1871/2000, p. 130). They came up with two types of explanation: cooperation has either direct or indirect fitness consequences.

As demonstrated by Grafen, population genetics entails that natural selection favors individuals that maximize their fitness (Grafen, 1999, 2002, 2006). It does not mean that biological agents are optimal or perfect, but rather that they optimize their fitness: they tend to behave in such a way that their genes get replicated. This tendency is statistical, not teleological: on average, they do better than chance. For at least three situations (There are others, but I will discuss only the most salient in the literature), gene propagation and fitness optimization may be facilitated by others organisms and requires cooperation.

Fig. 1, based on West et al, 2007.

Cooperation can have direct or indirect fitness benefit, i.e., cooperating can contribute to one’s own survival and reproduction (direct) or it can contrbute to genetically related organisms’ survival and reproduction (indirect). Since relatives share genes with the actor, helping them is a way to maximize indirect fitness (Hamilton, 1964a, 1964b). Cooperative individuals can also maximize direct fitness if they reciprocate in repeated encounters (Trivers, 1971). A’s helping B is fitness-enhancing if A can expect B to help him in the future (direct reciprocity, or “tit-for-tat” altruism (Axelrod, 1984)). Indirect reciprocity brings a third individual: A helps B even if A never encountered B in the past because helping B contribute to building a good reputation and may result in being helped by another individual C (Nowak & Sigmund, 2005). Cooperative individuals are thus more likely to be helped (see Fig.2).

From Nowak (2006)

Direct reciprocity can be compared to “a barter economy based on the immediate exchange of goods, whereas indirect reciprocity resembles the invention of money. The money that fuels the engines of indirect reciprocity is reputation. (Nowak, 2006, p. 1561)”. Indirect reciprocity also explains evolutionary altruism as costly signaling (Zahavi & Zahavi, 1997). Evolutionarily speaking, the peacock’s tail is not the most useful body part: it makes movement difficult and is far from being discreet. However, this handicap is a costly signal since it is, for peacocks, a sign of fitness: offspring of peacocks with elaborate tails “grow and survive better under nearly natural conditions”(Petrie, 1994, p. 598). Hence the tail becomes a hard-to-fake signal directed at female peacocks. A behavior can be a costly signal if it is easily observable, costly to the actor, reliably associated with of some desirable characteristic (resources, power, skills, etc.) and lead to some evolutionary advantage such as mates, food, etc. (Smith & Bird, 2000). Costly signal theory can thus explains altruism as a behavioral costly signal: in helping unknown and unrelated individuals (when it is a perceptible and perceptibly costly behavior), the altruist individuals are in fact building social capital by hard-to-fake signals (Smith & Bird, 2004; Zahavi, 2000).

Evolutionary and psychological altruism contrast sharply. The former is a fitness-maximizing behavioral pattern whereby individuals cooperate because it promotes gene propagation and it was selected for its fitness-enhancing consequences. Biological organisms cooperate in order to maximize their inclusive fitness (the conjunction of direct and indirect fitness). Evolutionary altruisms can be found in microbes and plants as well as in birds and human (although indirect reciprocity seems to be uniquely human). Psychological altruism, most probably a capacity reserved to higher mammals or primates, is a motivation that has nothing to do with fitness (Sober & Wilson, 1998). A behavior can be evolutionary altruistic without being psychologically altruistic and vice-versa (vervet monkeys predator alarm calls). It is nonetheless possible that a psychologically altruistic behavior has fitness-enhancing consequences or that an evolutionary altruistic behavior be motivated by psychological altruism (child care for instance). One might possibly resist using the term altruism for kin discrimination, direct and indirect reciprocity, since it seems that helping another individuals so as to maximize your inclusive fitness does not sound like altruistic at all. Remember Haldane remarks, that he would give his life to save two brothers or eight cousins, since the shared genetic material is identical (quoted in McElreath & Boyd, 2007, p. 82). It seems that in the end, any kind of altruistic behavior turns out to be un-altruistic:

To extend Haldane’s famous remark, kinship can explain rescuing drowning people if they are relatives (…); reciprocal altruism if they return the favor (…); indirect reciprocity if a third party returns the favor (…) and signaling if the rescuer is judged more attractive (Farrelly et al., 2007, p. 314)

Yet if we reserve altruism solely for psychological (‘real’) altruism, it is impossible to look for an evolutionary account of altruism. “If by ‘real’ altruism we mean altruism done with the conscious intention to help, then the vast majority of living creatures are not capable of ‘real’ altruism nor therefore of ‘real’ selfishness either” (Okasha, 2005, §4).

Although psychological and evolutionary altruism are well-defined concepts they leave aside important characteristics of altruism. Take the costs and benefits, for instance. Psychological altruism, construed as a motivation, has no explicit cost or benefits. Evolutionary altruism has cost and benefits: copies of genes in the gene pool. But how can we measure whether organism X helping organism Y increases the number of X’s (or Y’s) offspring? Of course, evolutionary theory is “population thinking” (Mayr, 1959), and do not deal with single individuals in isolation. Yet, behavioral ecology (the study of animal behavior), psychology, and experimental economics do deal with individuals and need to quantify altruistic behavior. Behavioral ecologists, remark White and Crawford, “almost always ignore the number of offspring produced and study, instead, how a particular adaptation contributes to some fitness proxy, for example, net energy intake rate” (White et al., 2007, p. 276). Most of the research on cooperation deals with fitness proxies such as money, food, status: when someone donates to humanitarian organizations, it is possible to quantify how much money is donated, but not—or more difficulty—how this act increases fitness through reputation (indirect reciprocity). Similarly, cooperating in a repeated prisoner’s dilemma is direct-reciprocal, but it is not clear how it promotes genes propagation; it could be fitness-enhancing, but this is not how experimental game theory measures cooperation. Hence between evolutionary and psychological altruism I suggest we add another type of altruism: economic altruism. A behavior is economically altruistic if it benefits the recipient and it is costly to the actor; the cost and benefits are not fitness consequences, but commodities or resources (food, money, information etc.). An economically altruistic behavior could be fitness-enhancing, but need not to; it could be motivated by psychological altruism, but need not to. Economic altruism can therefore be ‘pure’ (disinterested, in which case it overlap with psychological altruism) or ‘impure” when it is motivated by a warm-glow feeling (Andreoni, 1990).

Economic altruism is therefore another category of altruistic behavior, irreducible to—but not completely independent of—psychological and biological altruism. It is the proximate, immediate, visible face of altruism and cooperation (and deeper, of morality), while evolutionary altruism is ultimate and psychological altruism is not directly observable (although neural imaging technology are now making it observable yet imprecise). Therefore, when experimental economists study how much money a subject is ready share a lab experiment, they study economic altruism (e.g. Guth & van Damme, 1998); when social psychologists study readiness to help, they study psychological altruism (e.g. Batson, 1991); and when biologists study kin recognition and nepotism in social animals, they study evolutionary altruism (e.g. Silk, 2002).

References

• Andreoni, J. (1990). Impure Altruism and Donations to Public Goods: A Theory of Warm-Glow Giving. The Economic Journal, 100(401), 464-477.
• Axelrod, R. M. (1984). The Evolution of Cooperation. New York: Basic Books.
• Batson, C. D. (1991). The Altruism Question : Toward a Social Psychological Answer. Hillsdale, N.J.: L. Erlbaum, Associates.
• Darwin, C. (1871/2000). The Descent of Man, and Selection in Relation to Sex: Adamant Media.
• Dawkins, R. (1976). The Selfish Gene. New York: Oxford University Press.
• Farrelly, D., Lazarus, J., & Roberts, G. (2007). Altruists Attract. Evolutionary Psychology, 5(2), 313-329.
• Grafen, A. (1999). Formal Darwinism, the Individual-as-Maximising-Agent Analogy, and Bet-Hedging. Proc. Roy. Soc. Ser. B, 266, 799–803.
• Grafen, A. (2002). A First Formal Link between the Price Equation and an Optimization Program. Journal of Theoretical Biology, 217(1), 75.
• Grafen, A. (2006). Optimization of Inclusive Fitness. J Theor Biol, 238(3), 541-563.
• Guth, W., & van Damme, E. (1998). Information, Strategic Behavior, and Fairness in Ultimatum Bargaining: An Experimental Study. J Math Psychol, 42(2/3), 227-247.
• Hamilton, W. D. (1964a). The Genetical Evolution of Social Behaviour. I. Journal of Theoretical Biology, 7(1), 1-16.
• Hamilton, W. D. (1964b). The Genetical Evolution of Social Behaviour. Ii. Journal of Theoretical Biology, 7(1), 17-52.
• Mayr, E. (1959). Darwin and the Evolutionary Theory in Biology. In Evolution and Anthropology: A Centennial Appraisal (pp. 409–412). Washington, D.C.: Anthropological Society of Washington.
• McElreath, R., & Boyd, R. (2007). Mathematical Models of Social Evolution : A Guide for the Perplexed. Chicago ; London: University of Chicago Press.
• Nowak, M. A. (2006). Five Rules for the Evolution of Cooperation. Science, 314(5805), 1560-1563.
• Nowak, M. A., & Sigmund, K. (2005). Evolution of Indirect Reciprocity. Nature, 437(7063), 1291-1298.
• Okasha, S. (2005). Biological Altruism. The Stanford Encyclopedia of Philosophy, Edward N. Zalta (ed.), http://plato.stanford.edu/archives/sum2005/entries/altruism-biological.
• Petrie, M. (1994). Improved Growth and Survival of Offspring of Peacocks with More Elaborate Trains. Nature, 371(6498), 598-599.
• Silk, J. B. (2002). Kin Selection in Primate Groups. International Journal of Primatology, 23(4), 849-875.
• Smith, E. A., & Bird, R. B. (2004). Costly Signaling and Cooperative Behavior. In H. Gintis, S. Bowles, R. Boyd & E. Ferh (Eds.), Moral Sentiments and Material Interests : The Foundations of Cooperation in Economic Life (pp. 115-148). Cambridge, Mass.: MIT Press.
• Smith, E. A., & Bird, R. L. B. (2000). Turtle Hunting and Tombstone Opening: Public Generosity as Costly Signaling. Evolution and Human Behavior, 21(4), 245-261.
• Sober, E., & Wilson, D. S. (1998). Unto Others : The Evolution and Psychology of Unselfish Behavior. Cambridge, Mass.: Harvard University Press.
• Stich, S. (2007). Evolution, Altruism and Cognitive Architecture: A Critique of Sober and Wilson’s Argument for Psychological Altruism. Biology and Philosophy, 22(2), 267-281.
• Trivers, R. L. (1971). The Evolution of Reciprocal Altruism. Quarterly Review of Biology, 46(1), 35.
• West, S. A., Griffin, A. S., & Gardner, A. (2007). Social Semantics: Altruism, Cooperation, Mutualism, Strong Reciprocity and Group Selection. Journal of Evolutionary Biology, 20(2), 415-432.
• White, D. W., Dill, L. M., & Crawford, C. B. (2007). A Common, Conceptual Framework for Behavioral Ecology and Evolutionary Psychology. Evolutionary Psychology,, 5(2), 275-288.
• Zahavi, A. (2000). Altruism: The Unrecognized Selfish Traits. Journal of Consciousness Studies, 7, 253-256.
• Zahavi, A., & Zahavi, A. (1997). The Handicap Principle : A Missing Piece of Darwin's Puzzle. New York: Oxford University Press.

Altruism: a research program

Phoebe: I just found a selfless good deed; I went to the park and let a bee sting me.
Joey: How is that a good deed?
Phoebe: Because now the bee gets to look tough in front of his bee friends. The bee is happy and I am not.
Joey: Now you know the bee probably died when he stung you?
Phoebe: Dammit!
- [From Friends, episode 101]

Altruism is a lively research topic. The evolutionary foundations, neural substrates, psychological mechanisms, behavioral manifestations, formal modeling and philosophical analyses of cooperation constitute a coherent—although not unified—field of inquiry. See for instance how neuroscience, game theory, economic, philosophy, psychology and evolutionary theory interact in Penner et al. 2005; Hauser 2006; Fehr and Fischbacher 2002; Fehr and Fischbacher 2003. The nature of prosocial behavior, from kin selection to animal cooperation to human morality can be considered as a progressive Lakatosian research programs. Altruism has a great conceptual "sex-appeal" because it is mystery for two types of theoreticians: biologists and economists. They both wonder why an animal or an economic agent would help another: since these agents maximize fitness/utility, altruistic behavior is suboptimal. Altruims (help, trust, fairness, etc.) seems intuitively incoherent with economic rationality and biological adaptation, with markets and natural selection. Or is it?

In the 60's, biologists challenged the idea that natural selection is incompatible with altruism. Hamilton (1964a, 1964b) and Trivers (1971) showed that biological altruism makes sense. An animal X might behave altruistically toward another Y because they are genetically related: in doing so, X maximize the copying of its gene, since many of its genes will be hosted in Y. Thus the more X and Y are genetically related, the more X will be ready to help Y. This is kin altruism. Altruism can also be reciprocal: scratch my back and I'll scratch yours. Tit-for-tat, or reciprocal altruism also makes sense because by being altruistic, one may augments its payoff. X helps Y, but the next time Y will help X; thus it is better to help than not to help. In both cases, the idea is that altruism is a mean not an end. Others argue that more complex types of altruisms exists. For instance, X can help Y because Y already helped Z (indirect reciprocity). In this case, the tit-for-tat logic is extended to agents that the helper did not meet in the past. Generalized reciprocity (see this previous post) is another type of altruism: helping someone because someone helped you in the past. This altruism does not require memory or personal identification. X helps someone because someone else helped X. Finally, Strong reciprocity is the idea that humans display genuine altruism: strong reciprocators cooperate with cooperators, do not cooperate with cheaters, and are ready to punish cheaters even at a cost to themselves. Their proponents argue that it evolved through group selection.

Experimental economics and neuroeconomics also challenged the idea of rational, greedy, selfish actor (the Ayn Rand hero). Experimental game theory showed that, contrarily to orthodox game theory, subjects cooperate massively in prisoner’s dilemma (Ledyard, 1995; Sally, 1995). Rilling et al. showed that players enjoy cooperating. Players who initiate and players who experience mutual cooperation display activation in nucleus accumbens and other reward-related areas such as the caudate nucleus, ventromedial frontal/orbitofrontal cortex, and rostral anterior cingulate cortex (Rilling et al., 2002). In another experiment, the presentation of faces of intentional cooperators caused increased activity in reward-related areas (Singer et al. 2004). In the ultimatum game, proposers make ‘fair’ offers, about 50% of the amount, responders tend to accept these offers and reject most of the ‘unfair’ offers (less than 20%;Oosterbeek et al., 2004). Brain scans of people playing the ultimatum game indicate that unfair offers trigger, in the responders’ brain, a ‘moral disgust’: the anterior insula (associated with negative emotional states like disgust or anger) is more active when unfair offers are proposed (Sanfey, Rilling, Aronson, Nystrom, & Cohen, 2003). Subjects experiment this affective reaction to unfairness only when the proposer is a human being: the activation is significantly lower when the proposer is a computer. Moreover, the anterior insula activation is proportional to the degree of unfairness and correlated with the decision to reject unfair offers (Sanfey et al., 2003: 1756). Fehr and Fischbacher (2002) suggested that economic agents are inequity-averse and have prosocial preferences. Thus they modified the utility functions to account for behavioral (and now neural) data. In Moral Markets: The Critical Role of Values in the Economy, Paul Zak proposes a radically different conception of morality in economics:

The research reported in this book revealed that most economic exchange, whether with a stranger or a known individual, relies on character values such as honesty, trust, reliability, and fairness. Such values, we argue, arise in the normal course of human interactions, without overt enforcement—lawyers, judges or the
police are present in a paucity of economic transactions (...). Markets are moral in two senses. Moral behavior is necessary for exchange in moderately regulated markets, for example, to reduce cheating without exorbitant transactions costs. In addition, market exchange itself can lead to an understanding of fair-play that can build social capital in nonmarket settings. (Zak, forthcoming)

See how this claim is similar to :

The two fundamental principles of evolution are mutation and natural selection. But evolution is constructive because of cooperation. New levels of organization evolve when the competing units on the lower level begin to cooperate. Cooperation allows specialization and thereby promotes biological diversity. Cooperation is the secret behind the open-endedness of the evolutionary process. Perhaps the most remarkable aspect of evolution is its ability to generate cooperation in a competitive world. Thus, we might add "natural cooperation" as a third fundamental principle of evolution beside mutation and natural selection. (Nowak, 2006)

Hence, biological and economic theorizing followed a similar path: they started first with the assumption that agents value only their own payoff; evidence suggested then that agents behave altruistically and, finally, theoretical models were amended and now incorporate different kinds of reciprocity.

So is it good news? Are we genuinely altruistic? First a precision: there is a difference between biological and psychological altruism, and the former does not entail the latter; biological altruism is about fitness consequencences (survival and reproduction), while psychological altruism is about motivation and intentions:

Where human behaviour is concerned, the distinction between biological altruism, defined in terms of fitness consequences, and ‘real’ altruism, defined in terms of the agent's conscious intentions to help others, does make sense. (Sometimes the label ‘psychological altruism’ is used instead of ‘real’ altruism.) What is the relationship between these two concepts? They appear to be independent in both directions (...). An action performed with the conscious intention of helping another human being may not affect their biological fitness at all, so would not count as altruistic in the biological sense. Conversely, an action undertaken for purely self-interested reasons, i.e. without the conscious intention of helping another, may boost their biological fitness tremendously (Biological Altruism, Stanford Encyclopedia of Philosophy; see also a forthcoming paper by Stephen Stich and the classic Sober & Wilson 1998).

The interesting question, for many researchers, is then: what is the link between biological and psychological altruism? A common view suggests non-human animals are biological altruists, while humans are also psychological atruists. I would like argue against this sharp divide and briefly suggest three things:

1. Non-humans also display psychological altruism
2. Human altruism is strongly influenced by biological motives
3. Prosocial behavior in human and non-human animals should be understood as a single phenomena: cooperation in the economy of nature

1. Non-humans also display psychological altruism


A discussed in a previous post, a recent research paper showed that rats exhibit generalized reciprocity: rats who had previously been helped were more likely (20%) to help unknown partner than rats who had not been helped. Although the authors of the paper take a more prudent stance, I consider generalized reciprocity as psychological altruism (remember, it can be both): rats cooperate because they "feel good", and that feeling is induced by cooperation, not by a particular agent. Hence their brain value cooperation (probably thanks to hormonal mechanisms similar to ours) in itself, even if there is no direct tit-for-tat. In the same edition of PLoS biology, primatologist Frans de Waal (2007) also argue that animals show signs of psychological altruism; it it particularly clear in an experiment (Warneken et al, again, in the same journal) that show that chimpanzees are ready to help unknown humans and conspecifics (hence ruling out kin and tit-for-tat altruism), even at a cost to themselves. Here is the description of the experiments:

In the first experiment, the chimpanzee saw a person unsuccessfully reach through the bars for a stick on the other side, too far away for the person, but within reach of the ape. The chimpanzees spontaneously helped the reaching person regardless of whether this yielded a reward, or not. A similar experiment with 18-month-old children gave exactly the same outcome. Obviously, both apes and young children are willing to help, especially when they see someone struggling to reach a goal. The second experiment increased the cost of helping. The chimpanzees were still willing to help, however, even though now they had to climb up a couple of meters, and the children still helped even after obstacles had been put in their way. Rewards had been eliminated altogether this time, but this hardly seemed to matter. One could, of course, argue that chimpanzees living in a sanctuary help humans because they depend on them for food and shelter. How familiar they are with the person in question may be secondary if they simply have learned to be nice to the bipedal species that takes care of them. The third and final experiment therefore tested the apes' willingness to help each other, which, from an evolutionary perspective, is also the only situation that matters. The set-up was slightly more complex. One chimpanzee, the Observer, would watch another, its Partner, try to enter a closed room with food. The only way for the Partner to enter this room would be if a chain blocking the door were removed. This chain was beyond the Partner's control—only the Observer could untie it. Admittedly, the outcome of this particular experiment surprised even me—and I am probably the biggest believer in primate empathy and altruism. I would not have been sure what to predict given that all of the food would go to the Partner, thus creating potential envy in the Observer. Yet, the results were unequivocal: Observers removed the peg holding the chain, thus yielding their Partner access to the room with food (de Waal)

(image from Warneken et al video)

2. Human altruism is strongly influenced by biological motives

In many cases, human altruism appear as a complex version of biological altruism (see Burnham & Johnson, 2005. The Biological and Evolutionary Logic of Human Cooperation for a review). For instance, Madsen et al. (2007) showed that humans behave more altruistically toward their own kin when there is a significant genuine cost (such as muscular pain), an attitude also mirrored in study with questionnaires (Stewart-Williams 2007): when the cost of helping augments, subjects are more ready to help siblings than friends. Other studies showed that facial similarity enhances trust (DeBruine 2002). In each cases, there is a mechanism whose function is to negotiate personal investments in relationships in order to promote the copying of genes housed either in people of—or people who seems to be of—our kin.

Many of these so called altruistic behavior can be explained only by the operations of hyper-active agency detectors and a bias toward fearing other people’s judgement. When they are not being or feeling watched, peoples behave less altruistically. Many studies show that in the dictator game, a version of the ultimatum game where the responder has to accept the offer, subjects always make lower offers than in the ultimatum (Bolton, Katok, and Zwick 1998). Offers are even lower in the dictator game when donation is fully anonymous (Hoffman et al. 1994). When subjects feel watched, or think of agents, even supernatural ones, they tend to be much more altruistic. When a pair of eyes is displayed in a computer screen, almost twice as many participants transfer money in the dictator game (Haley and Fessler 2005), and people contribute 3 times more in an honesty box for coffee' when there is a pair of eyes than when there is pictures of a flower (Bateson, Nettle, and Roberts 2006). The sole fact of speaking of ghosts enchances honest behavior in a competitive taks (Bering, McLeod, and Shackelford 2005), while priming subjects with the God concept in the anonymous dictator game (Shariff and Norenzayan in press).

These reflections also applies to altruistic punishment. First, it is enhanced by an audience. (Kurzban, DeScioli, and O'Brien 2007) showed that with a dozen participants, punishment expenditure tripled. Again, appareant altruism is instrumental in personal satisfaction. Other research suggest that altruism is also an advantage in sexual selection: "people preferentially direct cooperative behavior towards more attractive members of the opposite sex. Furthermore, cooperative behavior increases the perceived attractiveness of the cooperator" (Farrelly et al., 2007).

An interesting framework to understand altruims is Hardy (no relation with me) & Van Vugt (2006) theory of competitive altruism: "individuals attempt to outcompete each other in terms of generosity. It emerges because altruism enhances the status and reputation of the giver. Status, in turn, yields benefits that would be otherwise unattainable." We need, however, a more general perspective.


3. Prosocial behavior in human and non-human animals should be understood as a single phenomena: cooperation in the economy of nature

All organic beings are striving to seize on each place in the economy of nature - (Darwin, [1859] 2003, p. 90)

With Darwin, natural economy began to be understood with the conceptual tools of political economy. The division of labor, competition (“struggle” in Darwin’s words), trading, cost, the accumulation of innovations, the emergence of complex order from unintentional individual actions, the scarcity of resources and the geometric growth of populations are ideas borrowed from Adam Smith, Thomas Malthus, David Hume and other founders of modern economics. Thus, the economy of nature ceased to be an abstract representation of the universe and became a depiction of the complex web of interactions between biological individuals, species and their environment—the subject matter of ecology. Consequently, Darwin’s main contributions are his transforming biology into a historical science—like geology—and into an economic science.

I take the economy-of-nature principle to be a refinement of the natural selection principle: while it describes general features of the biosphere, it puts emphasis on the intersection between individual biographies and natural selection, and especially on decision-making. On the one hand, the decisions biological individuals make increase or decrease their fitness, and thus good decision-makers are more likely to propagate their genes. On the other hand, natural selection is likely to favor good decision-makers and to get rid of bad decision-makers. Thus, if our best descriptive theories of animal and human economic behavior indicate that all these agents have prosocial preferences and make altruistic decisions, then these preferences and decisions are not maladaptive and irrational. They must have an evolutionary and an economic payoff. Markets and natural selections requires cooperation, even if the deep motivations are partly selfish. Fairness, equity and honesty are social goods in the economy of nature, human and non-human.

• Bateson, M., D. Nettle, and G. Roberts. 2006. Cues of being watched enhance cooperation in a real-world setting. Biology Letters 12:412-414.
• Bering, J. M., K. McLeod, and T. K. Shackelford. 2005. Reasoning about Dead Agents Reveals Possible Adaptive Trends. Human Nature 16 (4):360-381.
• Bolton, G. E., E. Katok, and R. Zwick. 1998. Dictator Game Giving: Rules of Fairness versus Acts of Kindness International Journal of Game Theory 27 269-299
• Burnham, T. C., and D. D. P. Johnson. 2005. The Biological and Evolutionary Logic of Human Cooperation. Analyse & Kritik 27:113-135.
• DeBruine, L. M. 2002. Facial resemblance enhances trust. Proc Biol Sci 269 (1498):1307-12.
• de Waal FBM (2007) With a Little Help from a Friend. PLoS Biol 5(7): e190 doi:10.1371/journal.pbio.0050190
• Farrelly, D., J. Lazarus, and G. Roberts. 2007. Altruists attract. Evolutionary Psychology 5 (2):313-329.
• Fehr, E., and U. Fischbacher. 2002. Why social preferences matter: The impact of non-selfish motives on competition, cooperation and incentives. Economic Journal 112:C1-C33.
• Fehr, Ernst, and Urs Fischbacher. 2003. The nature of human altruism. Nature 425 (6960):785-791.
• Hamilton, W. D. 1964a. The genetical evolution of social behaviour. I. J Theor Biol 7 (1):1-16.
• ———. 1964b. The genetical evolution of social behaviour. II. J Theor Biol 7 (1):17-52.
• Hauser, Marc D. 2006. Moral minds : how nature designed our universal sense of right and wrong. New York: Ecco.
• Ledyard, J. O. 1995. Public goods: A survey of experimental research. In Handbook of experimental economics, edited by J. H. Kagel and A. E. Roth: Princeton University Press.
• Haley, K., and D. Fessler. 2005. Nobody’s watching? Subtle cues affect generosity in an anonymous economic game. Evolution and Human Behavior 26 (3):245-56.
• Hoffman, E., K. Mc Cabe, K. Shachat, and V. Smith. 1994. Preferences, Property Rights, and Anonymity in Bargaining Experiments. Games and Economic Behavior 7:346–380.
• Kurzban, Robert, Peter DeScioli, and Erin O'Brien. 2007. Audience effects on moralistic punishment. Evolution and Human Behavior 28 (2):75-84.
• Madsen, Elainie A., Richard J. Tunney, George Fieldman, Henry C. Plotkin, Robin I. M. Dunbar, Jean-Marie Richardson, and David McFarland. 2007. Kinship and altruism: A cross-cultural experimental study. British Journal of Psychology 98:339-359.
• Penner, Louis A., John F. Dovidio, Jane A. Piliavin, and David A. Schroeder. 2005. Prosocial behavior: Multilevel Perspectives. Annual Review of Psychology 56 (1):365-392.
• Okasha, Samir, "Biological Altruism", The Stanford Encyclopedia of Philosophy (Summer 2005 Edition), Edward N. Zalta (ed.), URL = http://plato.stanford.edu/archives/sum2005/entries/altruism-biological/.
• Stewart-Williams, Steve. 2007. Altruism among kin vs. nonkin: effects of cost of help and reciprocal exchange. Evolution and Human Behavior 28 (3):193-198.
• Nowak, M. A. 2006. Five Rules for the Evolution of Cooperation. Science 314 (5805):1560-1563.
• Oosterbeek, H., Randolph S., and G. van de Kuilen. 2004. Differences in Ultimatum Game Experiments: Evidence from a Meta-Analysis. Experimental Economics 7:171-188.
• Rilling, J., D. Gutman, T. Zeh, G. Pagnoni, G. Berns, and C. Kilts. 2002. A neural basis for social cooperation. Neuron 35 (2):395-405.
• Rutte C, Taborsky M (2007) Generalized Reciprocity in Rats. PLoS Biol 5(7): e196 doi:10.1371/journal.pbio.0050196
• Sally, D. 1995. Conversations and cooperation in social dilemmas: a meta-analysis of experiments from 1958 to 1992. Rationality and Society 7:58 – 92
• Sanfey, A. G., J. K. Rilling, J. A. Aronson, L. E. Nystrom, and J. D. Cohen. 2003. The neural basis of economic decision-making in the Ultimatum Game. Science 300 (5626):1755-8.
• Shariff, A.F. , and A. Norenzayan. in press. God is watching you: Supernatural agent concepts increase prosocial behavior in an anonymous economic game. Psychological Science.
• Singer, T., S. J. Kiebel, J. S. Winston, R. J. Dolan, and C. D. Frith. 2004. Brain responses to the acquired moral status of faces. Neuron 41 (4):653-62.
• Sober, Elliott, and David Sloan Wilson. 1998. Unto others : the evolution and psychology of unselfish behavior. Cambridge, Mass.: Harvard University Press.
• Stich, S. (forthcoming). Evolution, Altruism and Cognitive Architecture: A Critique of Sober and Wilson's Argument for Psychological Altruism, to appear in Biology and Philosophy.
• Trivers, R. L. 1971. The Evolution of Reciprocal Altruism. Quarterly Review of Biology 46 (1):35.
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• Zak, P. J., ed. forthcoming. Moral Markets: The Critical Role of Values in the Economy. Princeton, N.J.: Princeton University Press.

Natural Rationality for Newbies

Decision-making, as I routinely argue in this blog, must be understood as entrenched in a richer theoretical framework: Darwin’s economy-of-nature. According to this principle, animals could be modeled as economic agents and their control systems could be modeled as economic devices. All living beings are thus deciders, strategists or traders in the economy of reproduction and survival.

When he suggested that nature is an economy, Darwin paved the way for a stronger interaction between biology and economics. One of the consequences of a bio-economic approach is that decision-making becomes an increasingly important topic. The usual, commonsense construal of decision-making suggests that it is inherently tied to human characteristics, language in particular. If that is the case, then talk of animal decisions is merely metaphorical. However, behavioral ecology showed that animals and human behavior is constrained by economic parameters and coherent with the economy-of-nature principle. Neuroeconomics suggest that the neural processing follow the same logic. Dopaminergic systems drive animals to achieve certain goals while affective mechanisms place goals and action in value spaces. These systems, although they were extensively studied in humans, are not peculiar to them: humans display a unique complexity of goals and values, but this complexity relies partly on neural systems shared with many other animals: the nucleus accumbens and the amygdala, for instance are common in mammals. Brainy animals evolved an economic decision-making organ that allows them to cope with complex situations. As Gintis remarks, the complexity and the metabolic cost of central nervous systems co-evolved in vertebrates, which suggests that despite their cost, brains are designed to make adaptive decision[i].

Hence decision-making should be analyzed similarly as, and occupies an intellectual niche analogous to, the concept of cooperation. Nowadays, the evolutionary foundations, neural substrates, psychological mechanisms, formal modeling and philosophical analyses of cooperation constitutes a coherent—although not unified—field of inquiry [ii]. The nature of prosocial behavior, from kin selection to animal cooperation to human morality, is best understood by adopting a naturalistic stances that highlights both the continuity of the phenomenon and the human specificity. Biological decision-making deserves the same eclecticism.

Talking about biological decision-making comes at a certain conceptual price. As many philosophers pointed out, whenever one is describing actions and decisions, one is also presupposing the rationality of the agent[iii]. When we say that agent A chose X, we suppose that A had reasons, preferences, and so on. The default assumption is that preferences and actions are coherent: the firsts caused the seconds, and the seconds are justified by the firsts. The rationality philosophers are referring to, however, is a complex cognitive faculty, that requires language and propositional attitudes such as beliefs and desires. When animals forage their environment, select preys, patches, or mates, no one presupposes that they entertain beliefs or desires. There is nonetheless a presupposition that “much of the structure of the internal mental operations that inform decisions can be viewed as the product of evolution and natural selection”.[iv] Thus, to a certain degree, the neuronal processes concerned with the use of information are effective and efficient, otherwise natural selection would have discarded them. I shall label these presuppositions, and the mechanisms it might reveal, “natural rationality”. Natural rationality is a possibility condition for the concept of biological decision-making and the economy-of-nature principle. One needs to presuppose that there is a natural excellence in the biosphere before studying decisions and constraints.

More than a logical prerequisite, natural rationality concerns the descriptive and normative properties of the mechanisms by which humans and other animals make decisions. Most concepts of rationality take only the descriptive or the normative side, and hence tend to describe cognitive/neuronal processes without concern for their optimality, or state ideal conditions for rational behavior. For instance, while classical economics considers rational-choice theory either as a normative theory or a useful fiction, proponents of bounded rationality or ecological rationality refuse to characterize decision-making as optimization.[v] Others advocate a strong division of labor between normative and descriptive project: Tversky and Kahneman, for instance, concluded from their studies of human bounded rationality that the normative and descriptive accounts of decision-making are two separate projects that “cannot be reconciled”[vi]

The perspective I suggest here is that we should expect an overlap between normative and descriptive theories, and that the existence of this overlap is warranted by natural selection. On the normative side, we should ask what procedures and mechanisms biological agents should follow in order to make effective and efficient decision given all their constraints in the economy of nature. On the descriptive side, we must assess whether a procedure succeeds in achieving goals or, conversely, what goals could a procedure aim at achieving. If there is no overlap between norms and facts, then either norms should be reconceptualized or facts should be scrutinized: it might be the case that norms are unrealistic or that we did not identify the right goal or value.

This accounts contrasts with philosophers (e.g. Dennett or Davidson) who construe rationality as an idealization and researchers who preach the elimination of this concept because of its idealized status (evolutionary psychologists, for instance[vii]). Thus, rationality can be conceived not as an a priori postulate in economy and philosophy, but as an empirical and multidisciplinary research program. Quine once said that “creatures inveterately wrong in their inductions have a pathetic but praiseworthy tendency to die out before reproducing their kind”[viii]. Whether it is true for inductions is still open to debate, but I suggest that it clearly applies to decisions.

Related posts

• Decision-making and the economy of nature
• The Economy of Nature: A Brief Introduction
• Rational performance and behavioral ecology

Notes and references

• [i] (Gintis, 2007, p. 3)
• [ii] See for instance how neuroscience, game theory, economic, philosophy, psychology and evolutionary theory interact in (E. Fehr & Fischbacher, 2002; Ernst Fehr & Fischbacher, 2003; Hauser, 2006; Penner et al., 2005).
• [iii] (Davidson, 1980; Dennett, 1987; Popper, 1994).
• [iv] (Real, 1994, p. 4)
• [v] (Chase et al., 1998; Gigerenzer, 2004; Selten, 2001)
• [vi] (Tversky & Kahneman, 1986, p. s272)
• [vii][vii] (Cosmides & Tooby, 1994)
• [viii] (Quine, 1969, p. 126)
  

References

• Chase, V. M., Hertwig, R., & Gigerenzer, G. (1998). Visions of Rationality. Trends in Cognitive Science, 2(6), 206-214.
• Cosmides, L., & Tooby, J. (1994). Better Than Rational: Evolutionary Psychology and the Invisible Hand. The American Economic Review, 84(2), 327-332.
• Davidson, D. (1980). Essays on Actions and Events. Oxford: Oxford University Press.
• Dennett, D. C. (1987). The Intentional Stance. Cambridge, Mass.: MIT Press.
• Fehr, E., & Fischbacher, U. (2002). Why Social Preferences Matter: The Impact of Non-Selfish Motives on Competition, Cooperation and Incentives. Economic Journal, 112, C1-C33.
• Fehr, E., & Fischbacher, U. (2003). The Nature of Human Altruism. Nature, 425(6960), 785-791.
• Gigerenzer, G. (2004). Fast and Frugal Heuristics: The Tools of Bounded Rationality. In D. Koehler & N. Harvey (Eds.), Blackwell Handbook of Judgment and Decision Making (pp. 62–88). Oxford: Blackwell.
• Gintis, H. (2007). A Framework for the Unification of the Behavioral Sciences. Behavioral and Brain Sciences, 30(01), 1-16.
• Hauser, M. D. (2006). Moral Minds : How Nature Designed Our Universal Sense of Right and Wrong. New York: Ecco.
• Penner, L. A., Dovidio, J. F., Piliavin, J. A., & Schroeder, D. A. (2005). Prosocial Behavior: Multilevel Perspectives. Annual Review of Psychology, 56(1), 365-392.
• Popper, K. R. (1994). Models, Instruments, and Truth: The Status of the Rationality Principle in the Social Sciences. In The Myth of the Framework. In Defence of Science and Rationality
• Quine, W. V. O. (1969). Ontological Relativity, and Other Essays. New York,: Columbia University Press.
• Real, L. A. (1994). Behavioral Mechanisms in Evolutionary Ecology: University of Chicago Press.
• Selten, R. (2001). What Is Bounded Rationality ? . In G. Gigerenzer & R. Selten (Eds.), Bounded Rationality: The Adaptive Toolbox (pp. 13-36). MIT Press: Cambridge, MA.
• Tversky, A., & Kahneman, D. (1986). Rational Choice and the Framing of Decisions. The Journal of Business, 59(4), S251-S278.

Smith vs. Darwin

Smith vs. Darwin

n today's great God-versus-Science debate, both sides maneuver for the middle ground. Though he's otherwise tolerant of nothing, George W. Bush calls for evolution and Intelligent Design to be taught together in the science classes of public schools. Meanwhile, our great gray citadel of secular humanism, the New York Times, finds it comforting to tell us (on the front page on August 23) that there really are good Christian scientists out there who do evolution on weekdays and church on Sunday. So what's the problem?

A neuroecomic picture of valuation

Values are everywhere: ethics, politics, economics, law, for instance, all deal with values. They all involve socially situated decision-makers compelled to make evaluative judgment and act upon them. These spheres of human activity constitute three aspects of the same problem, that is, guessing how 'good' is something. This means that value 'runs' on valuation mechanisms. I suggest here a framework to understand valuation.

I define here valuation as the process by which a system maps an object, property or event X to a value space, and a valuation mechanism as the device implementing the matching between X and the value space. I do not suggest that values need to be explicitly represented as a space: by valuation space, I mean an artifact that accounts for the similarity between values by plotting each of them as a point in a multidimensional coordinate system. Color spaces, for instance, are not conscious representation of colors, but spatial depiction of color similarity along several dimensions such as hue, saturation brightness.

The simplest, and most common across the phylogenetic spectrum, value space has two dimensions: valence (positive or negative) and magnitude. Valence distinguishes between things that are liked and things that are not. Thus if X has a negative valence, it does not implies that X will be avoided, but only that it is disliked. Magnitude encodes the level of liking vs. disliking. Other dimensions might be added—temporality (whether X is located in the present, past of future), other- vs. self-regarding, excitatory vs. inhibitory, basic vs. complex, for instance—but the core of any value system is valence and magnitude, because these two parameters are required to establish rankings. To prefer Heaven to Hell, Democrats to Republicans, salad to meat, or sweet to bitter involves valence and magnitude.

Nature endowed many animals (mostly vertebrates) with fast and intuitive valuation mechanisms: emotions.[1] Although it is a truism in psychology and philosophy of mind and that there is no crisp definition of what emotions are[2], I will consider here that an emotion is any kind of neural process whose function is to attribute a valence and a magnitude to something else and whose operative mode are somatic markers. Somatic markers[3] are bodily states that ‘mark’ options as advantageous/disadvantageous, such as skin-conductance, cardiac rhythm, etc. Through learning, bodily states become linked to neural representations of the stimuli that brought these states. These neural structures may later reactivate the bodily states or a simulation of these states and thereby indicate the valence and magnitude of stimuli. These states may or may not account for many legitimate uses of the word “emotions”, but they constitute meaningful categories that could identify natural kinds[4]. In order to avoid confusion between folk-psychological and scientific categories, I will rather talk of affects and affective states, not emotions.

More than irrational passions, affectives states are phylogenetically ancient valuation mechanisms. Since Darwin,[5] many biologists, philosophers and psychologists[6] have argued that they have adaptive functions such as focusing attention and facilitating communication. As Antonio Damasio and his colleagues discovered, subjects impaired in affective processing are unable to cope with everyday tasks, such as planning meetings[7]. They lose money, family and social status. However, they were completely functional in reasoning or problem-solving tasks. Moreover, they did not felt sad for their situation, even if they perfectly understood what “sad” means, and seemed unable to learn from bad experiences. They were unable to use affect to aid in decision-making, a hypothesis that entails that in normal subjects, affect do aid in decision-making. These findings suggest that decision-making needs affect, not as a set of convenient heuristics, but as central evaluative mechanisms. Without affects, it is possible to think efficiently, but not to decide efficiently (affective areas, however, are solicited in subjects who learn to recognize logical errors[8]).

Affects, and specially the so-called ‘basic’ or ‘core’ ones such as anger, disgust, liking and fear[9] are prominent explanatory concepts in neuroeconomics. The study of valuation mechanisms reveals how the brain values certain objects (e.g. money), situations (e.g. investment, bargaining) or parameter (risk, ambiguity) of an economic nature. Three kinds of mechanisms are typically involved in neuroeconomic explanations:

1. Core affect mechanisms, such as fear (amygdala), disgust (anterior insula) and pleasure (nucleus accumbens), encode the magnitude and valence of stimuli.
2. Monitoring and integration mechanisms (ventromedial/mesial prefrontal, orbitofrontal cortex, anterior cingulate cortex) combine different values and memories of values together
3. Modulation and control mechanisms (prefrontal areas, especially the dorsolateral prefrontal cortex), modulate or even override other affect mechanisms.

Of course, there is no simple mapping between psychological functions and neural structures, but cognitive and affective neuroscience assume a dominance and a certain regularity in functions. Disgust does not reduce to insular activation, but anterior insula is significantly involved in the physiological, cognitive and behavioral expressions of disgust. There is a bit of simplification here—due to the actual state of science—but enough to do justice to our best theories of brain functioning. I will here review two cases of individual and strategic decision-making, and will show how affective mechanisms are involved in valuation[10].

In a study by Knutson et al.,[11] subjects had to choose whether or not they would purchase a product (visually presented), and then whether or not they would buy it at a certain price. While desirable products caused activation in the nucleus accumbens, activity is detected in the insula when the price is seen as exaggerated. If the price is perceived as acceptable, a lower insular activation is detected, but mesial prefrontal structures are more solicited. The activation in these areas was a reliable predictor of whether or not subjects would buy the product: prefrontal activation predicted purchasing, while insular activation predicted the decision of not purchasing. Thus purchasing decision involves a tradeoff, mediated by prefrontal areas, between the pleasure of acquiring (elicited in the nucleus accumbens) and the pain of purchasing (elicited in the insula). A chocolate box—a stimulus presented to the subjects—is located in the high-magnitude, positive-valence regions of the value space, while the same chocolate box priced at $80 is located in the high-magnitude, negative-valence regions of the space.

In the ultimatum game, a ‘proposer’ makes an offer to a ‘responder’ that can either accept or refuse the offer. The offer is a split of an amount of money. If the responder accepts, she keeps the offered amount while the proposer keeps the difference. If she rejects it, however, both players get nothing. Orthodox game theory recommends that proposers offer the smallest possible amount, while responder should accept every proposition, but all studies confirm that subjects make fair offer (about 40% of the amount) and reject unfair ones (less than 20%)[12]. Brain scans of people playing the ultimatum game indicate that unfair offers trigger, in the responders’ brain, a ‘moral disgust’: the anterior insula is more active when unfair offers are proposed,[13] and insular activation is proportional to the degree of unfairness and correlated with the decision to reject unfair offers[14]. Moreover, unfair offers are associated with greater skin conductance[15]. Visceral and insular responses occur only when the proposer is a human: a computer does not elicit those reaction. Beside the anterior insula, two other areas are recruited in ultimatum decisions: the dorsolateral prefrontal cortex (DLPFC). When there is more activity in the anterior insula than in the DLPFC, unfair offers tend to be rejected, while they tend to be accepted when DLPFC activation is greater than anterior insula.

These two experiments illustrate how neuroeconomics begin to decipher the value spaces and how valuation relies on affective mechanisms. Although human valuation is more complex than the simple valence-magnitude space, this ‘neuro-utilitarist’ framework is useful for interpreting imaging and behavioral data: for instance, we need an explanation for insular activation in purchasing and ultimatum decision, and the most simple and informative, as of today, is that it trigger a simulated disgust. More generally, it also reveals that the human value space is profoundly social: humans value fairness and reciprocity. Cooperation[16] and altruistic punishment[17] (punishing cheaters at a personal cost when the probability of future interactions is null), for instance, activate the nucleus accumbens and other pleasure-related areas. People like to cooperate and make fair offers.

Neuroeconomic experiments also indicate how value spaces can be similar across species. It is known for instance that in humans, losses[18] elicit activity in fear-related areas such as amygdala. Since capuchin monkey’s behavior also exhibit loss-aversion[19] (i.e., a greater sensitivity to losses than to equivalent gains), behavioral evidence and neural data suggests that the neural implementation of loss-aversion in primates shares common valuation mechanisms and processing. The primate—and maybe the mammal or even the vertebrate—value space locate loss in a particular region.

Notes

• [1] (Bechara & Damasio, 2005; Bechara et al., 1997; Damasio, 1994, 2003; LeDoux, 1996; Naqvi et al., 2006; Panksepp, 1998)
• [2] (Faucher & Tappolet, 2002; Griffiths, 2004; Russell, 2003)
• [3] (Bechara & Damasio, 2005; Damasio, 1994; Damasio et al., 1996)
• [4] (Griffiths, 1997)
• [5] (Darwin, 1896)
• [6] (Cosmides & Tooby, 2000; Paul Ekman, 1972; Griffiths, 1997)
• [7] (Damasio, 1994)
• [8] (Houde & Tzourio-Mazoyer, 2003)
• [9] (Berridge, 2003; P. Ekman, 1999; Griffiths, 1997; Russell, 2003; Zajonc, 1980)
• [10] The material for this part is partly drawn from (Hardy-Vallée, forthcoming)
• [11] (Knutson et al., 2007).
• [12] (Oosterbeek et al., 2004)
• [13] (Sanfey et al., 2003)
• [14] (Sanfey et al., 2003: 1756)
• [15] (van 't Wout et al., 2006)
• [16] (Rilling et al., 2002).
• [17] (de Quervain et al., 2004).
• [18] (Naqvi et al., 2006)
• [19] (Chen et al., 2006)

References

• Bechara, A., & Damasio, A. R. (2005). The somatic marker hypothesis: A neural theory of economic decision. Games and Economic Behavior, 52(2), 336.
• Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (1997). Deciding Advantageously Before Knowing the Advantageous Strategy. Science, 275(5304), 1293-1295.
• Berridge, K. C. (2003). Pleasures of the brain. Brain and Cognition, 52(1), 106.
• Chen, M. K., Lakshminarayanan, V., & Santos, L. (2006). How Basic Are Behavioral Biases? Evidence from Capuchin Monkey Trading Behavior. Journal of Political Economy, 114(3), 517-537.
• Cosmides, L., & Tooby, J. (2000). Evolutionary psychology and the emotions. Handbook of Emotions, 2, 91-115.
• Damasio, A. R. (1994). Descartes' error : emotion, reason, and the human brain. New York: Putnam.
• Damasio, A. R. (2003). Looking for Spinoza : joy, sorrow, and the feeling brain (1st ed.). Orlando, Fla. ; London: Harcourt.
• Damasio, A. R., Damasio, H., & Christen, Y. (1996). Neurobiology of decision-making. Berlin ; New York: Springer.
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Two New Papers on Natural Rationality

Hardy-Vallée, B. (forthcoming). Decision-Making in the Economy of Nature: Information as Value. In G. Terzis & R. Arp (Eds.), Information and Living Systems: Essays in Philosophy of Biology. Cambridge, MA: MIT Press.

This chapter analyzes and discusses one of the most important uses of information in the biological world: decision-making. I will first present a fundamental principle introduced by Darwin, the idea of an “economy of nature,” by which decision-making can be understood. Following this principle, I then argue that biological decision-making should be construed as goal-oriented, value-based information processing. I propose a value-based account of neural information, where information is primarily economic and relative to goal achievement. If living beings (I focus here on animals) are biological decision-makers, we may expect that their behavior would be coherent with the pursuit of certain goals (either ultimate or instrumental) and that their behavioral control mechanisms would be endowed with goal-directed and valuation mechanisms. These expectations, I argue, are supported by behavioral ecology and decision neuroscience. Together, they provide a rich, biological account of decision-making that should be integrated in a wider concept of ‘natural rationality’.

Hardy-Vallee B. (submitted) Natural Rationality and the Psychology of Decision: Beyond bounded and ecological rationality

Decision-making is usually a secondary topic in psychology, relegated to the last chapters of textbooks. It pictures decision-making mostly as a deliberative task and rationality as a matter of idealization. This conception also suggests that psychology should either document human failures to comply with rational-choice standards (bounded rationality) or detail how mental mechanisms are ecologically rational (ecological rationality). This conception, I argue, runs into many problems: descriptive (section 2), conceptual (section 3) and normative (section 4). I suggest that psychology and philosophy need another—wider—conception of rationality, that goes beyond bounded and ecological rationality (section 5).

Dennett in Montreal

At the opening conference of the Summer Institute on Social Cognition, Daniel Dennett, Austin B. Fletcher Professor of Philosophy and Co-Director of the Center for Cognitive Studies, Tufts University, will give a speech entitled "From Animal to Person: How Culture Makes Up our Minds".

This will be held on Friday 27th of June at 7pm in room JM-400. The address is UQAM, Pavillon Judith-Jasmin, studio théâtre Alfred-Laliberté, 405 rue Sainte-Catherine Est, (Berri-UQAM metro).

The poster of the event is available here.

Admission is free and the event is open to the general public. We highly recommend that you book your place in advance by sending an email to dennett.summer08.isc@gmail.com. Should places still be available on the event evening, places will be given on a first come first serve basis.

Daniel C. Dennett is one of today’s most important and productive philosophers of the mind. He is the author of over three hundred scholarly articles and 12 books, such as Consciousness Explained, Darwin’s Dangerous Idea, and Breaking the Spell: Religion as a Natural Phenomenon.

Why Evolutionary Psychology?

An undergrad recently contacted me and asked me how I got interested by evolutionary psychology. Here is my answer, if that can be of any use for anybody. The ideas my apply to academic research more generally.

As an undergrad philosophy student, my interest in evolutionary psychology was triggered by one of my teacher, a great scholar who was able to integrate biology, psychology, philosophy, neuroscience, anthropology, etc, in his reflexion. That is really what drove me in the field: someome who showed me how any question about the cognition and rationality can be approached in a darwinian perspective. Reading Dennett's "Darwin's dangerous ideas" also had the same effect on me. Hence to be honest, at first, it's because it was just so cool see things this way, and exciting to know that research may involve knowledge in many different fields. If that is cause, that is not, however, the reason. The reason, I think, was a deep commitment to materialism (the world is made of matter, period), naturalism (all facts are natural fact, there is no other realm of fact) and experimentalism in general (we should back any claim with scientific, experimental data). All that naturally leads to an evolutionary approach of anything. At your age (god I sound old when I say that! ), I was determined to do philosophy; to do my BA, MA, PhD, postodoc, and everything that was necessary to, one day, have a job in a university (I am not quite there, as I am still postdoc, but I hope one day I'll get one). So evolutionary psychology and other related fields appeared to me as a great opportunity to develop my "academic niche", to have my own speciality, and to do something interdisciplinary. So if I can give you an advice, it will be a very simple one: do something you really like. If just thinking about evolutionary psychology evokes a lot of ideas of questions, if you are thrilled by every paper or book you read about it, go ! It's easy to go through a thesis and all the other academic stuff when you like it. My second advice is that if you really like it, then read everything about it, from the classics to ongoing research to popular books; explore the connections between evolutionary psychology and other field (how it's related to economics? neuroscience? sociology?). Browse, dowload, print everything you can. Use RSS to syndicate important journals. Find those journals (Evolution and Human Behavior, Human Nature, etc.). Don't forget the holy trilogy: Nature, Science and PNAS. Be up-to-date and aware of the field's common knowledge.

If you like it, it will be easy for you to master the field. Try to find a supervisor that knows evolutionary psychology, who already published in the field. Make contact with other people, or students, interested by these topics. Try organizing reading groups, attend to conferences, become a member of scientific societies, etc. Don't miss encyclopedia entries.

What I like best about theis field? everything. What I like least? Nothing. Except maybe people who will try to show you that evolution is "just a theory", that evolutionary psychology is an evil attempt to eliminate "meanings" in our lives, blah blah blah, all that stuff is sometimes anoying. Don't take it too seriously, but you may consider sometimes trying to argue with them, it is always useful to test the foundations of your scientific conviction.

hope this will help,
B.

PRECIS OF: Evolution in Four Dimensions

PRECIS OF: Evolution in Four Dimensions

AUTHORS: Eva Jablonka* & Marion J. Lamb

*Cohn Institute for the History and Philosophy of Science and Ideas

ABSTRACT: In his theory of evolution, Darwin recognized that the conditions of life play a role in the generation of hereditary variations, as well as in their selection. However, as evolutionary theory was developed further, heredity became identified with genetics and variation was seen in terms of combinations of randomly generated gene mutations. We argue that this view is now changing, because it is clear that a notion of hereditary variation that is based solely on randomly varying genes that are unaffected by developmental conditions is an inadequate basis for evolutionary theories. Such a view not only fails to provide satisfying explanations of many evolutionary phenomena, it also makes assumptions that are not consistent with the data that are emerging from disciplines ranging from molecular biology to cultural studies. These data show that the genome is far more responsive to the environment than previously thought, and that not all transmissible variation is underlain by genetic differences. In Evolution in Four Dimensions we identify four types of inheritance (genetic, epigenetic, behavioural, and symbol-based), each of which can provide variations on which natural selection will act. Some of these variations arise in response to developmental conditions, so there are Lamarckian aspects to evolution. We argue that a better insight into evolutionary processes will result from recognizing that transmitted variations that are not based on DNA differences have played a role. This is particularly true for understanding the evolution of human behaviour, where all four dimensions of heredity have been important.