Not only states but traits — Humans can identify permanent altruistic dispositions in 20 s

Humans behave altruistically in one-shot interactions under total anonymity. In search of explanations for such behavior, it has been argued that at least some individuals have a general tendency to behave altruistically independent of profitability. In fact, a stable altruistic trait would be adaptive if it were recognizable. Then, altruists could choose each other in order to retain benefits through mutual cooperation. Previous research has shown that individuals can predict the degree of altruistic behavior of strangers by reading signs of emotions evoked in significant social decisions. However, the identification of benevolent emotional states is no guarantee of the existence of permanent altruistic traits, though permanent traits are the preferable criterion for selection of good interaction partners. In this study, we tested whether individuals are able to identify altruistic traits. Judges watched 20-s silent video clips of unacquainted target persons and were asked to estimate the behavior of these target persons in a money-sharing task. As the videotapes of the target persons had been recorded in a setting unrelated to altruistic behavior, the judges could not base their estimates on situational cues related to the money-sharing task but instead had to draw on stable signals of altruism. Estimates were significantly better than chance, indicating that individuals can identify permanent altruistic traits in others. As this mechanism raises opportunities for selective interactions between altruists, our findings are discussed with respect to their relevance for explaining the evolution of altruism through assortment.     

The spatial spread of altruism versus the evolutionary response of egoists

Several recent models have shown that altruism can spread in viscous populations, i.e. in spatially structured populations within which individuals interact only with their immediate neighbours and disperse only over short distances. I first confirm this result with an individual-based model of a viscous population, where an individual can vary its level of investment into a behaviour that is beneficial to its neighbours but costly to itself. Two distinct classes of individuals emerge: egoists with no or very little investment into altruism, and altruists with a high level of investment; intermediate levels of altruism are not maintained. I then extend the model to investigate the consequences of letting interaction and dispersal distances evolve along with altruism. Altruists maintain short distances, while the egoists respond to the spread of altruism by increasing their interaction and dispersal distances. This allows the egoistic individuals to be maintained in the population at a high frequency. Furthermore, the coevolution of investment into altruism and interaction distance can lead to a stable spatial pattern, where stripes of altruists (with local interactions) alternate with stripes of egoists (with far-reaching interactions). Perhaps most importantly, this approach shows that the ease with which altruism spreads in viscous populations is maintained despite countermeasures evolved by egoists.     

WHEN HAWKS GIVE RISE TO DOVES: THE EVOLUTION AND TRANSITION OF ENFORCEMENT STRATEGIES

The question of how altruism can evolve despite its local disadvantage to selfishness has produced a wealth of theoretical and empirical research capturing the attention of scientists across disciplines for decades. One feature that has remained consistent through this outpouring of knowledge has been that researchers have looked to the altruists themselves for mechanisms by which altruism can curtail selfishness. An alternative perspective may be that just as altruists want to limit selfishness in the population, so may the selfish individuals themselves. These alternative perspectives have been most evident in the fairly recent development of enforcement strategies. Punishment can effectively limit selfishness in the population, but it is not free. Thus, when punishment evolves among altruists, the double costs of exploitation from cheaters and punishment make the evolution of punishment problematic. Here we show that punishment can more readily invade selfish populations when associated with selfishness, whereas altruistic punishers cannot. Thereafter, the establishment of altruism because of enforcement by selfish punishers provides the ideal invasion conditions for altruistic punishment, effectively creating a transition of punishment from selfishness to altruistic. Thus, from chaotic beginnings, a little hypocrisy may go a long way in the evolution and maintenance of altruism.     

Altruists Proliferate Even at a Selective Disadvantage within Their Own Niche

The evolutionary origin of altruism is a long-standing puzzle. Numerous explanations have been proposed, most prominently based on inclusive fitness or group selection. One possibility that has not yet been considered is that new niches will be created disproportionately often when altruism appears, perhaps by chance, causing altruists to be over-represented in such new niches. This effect is a novel variant of group selection in which altruistic groups benefit by discovering unoccupied niches instead of by competing for the limited resources within a single niche. Both an analytical population genetics model and computational simulations support that altruism systematically arises due to this side effect of increased carrying capacity even when it is strongly selected against within any given niche. In fact, even when selection is very strongly negative and altruism does not develop in most populations, it can still be expected to be observed in a consistent fraction of species. The ecological structure provided by niches thereby may be sufficient for altruists to proliferate even if they are always at a disadvantage within each niche considered individually.     

Selection for altruism through random drift in variable size populations

ABSTRACT: BACKGROUND: Altruistic behavior is defined as helping others at a cost to oneself and a lowered fitness. The lower fitness implies that altruists should be selected against, which is in contradiction with their widespread presence is nature. Present models of selection for altruism (kin or multilevel) show that altruistic behaviors can have 'hidden' advantages if the 'common good' produced by altruists is restricted to some related or unrelated groups. These models are mostly deterministic, or assume a frequency dependent fitness. RESULTS: Evolutionary dynamics is a competition between deterministic selection pressure and stochastic events due to random sampling from one generation to the next. We show here that an altruistic allele extending the carrying capacity of the habitat can win by increasing the random drift of "selfish" alleles. In other terms, the fixation probability of altruistic genes can be higher than those of a selfish ones, even though altruists have a smaller fitness. Moreover when populations are geographically structured, the altruists advantage can be highly amplified and the fixation probability of selfish genes can tend toward zero. The above results are obtained both by numerical and analytical calculations. Analytical results are obtained in the limit of large populations. CONCLUSIONS: The theory we present does not involve kin or multilevel selection, but is based on the existence of random drift in variable size populations. The model is a generalization of the original Fisher-Wright and Moran models where the carrying capacity depends on the number of altruists.     

Conditions for the evolution of altruism under darwinian selection

A model of population structure is discussed which under certain circumstances allows for evolution of altruistic traits, beyond the classical restrictions imposed by kin selection theory and related concepts such as reciprocal altruism. Essentially, the model sees a large population as socially subdivided into small groups without any barriers, however, to free random mating. An altruistic trait is defined as lowering, locally, the fitness of a carrier below that of noncarriers within the same group; but the local fitness of an individual randomly chosen in a group increases with the number of altruists. It is shown that altruism can evolve even if the groups are randomly formed. The conditions for such evolution are contrasted with those prevailing when the groups are formed either with some phenotypic assortment between the members or on the basis of kinship. It is shown that any possibility of evolution tends to rapidly disappear as groups become large, unless there is complete positive assortment or individuals in the groups are kin. The example of alarm calls is also considered, and the two extremes of random and sib-groups are contrasted, using a model by Maynard Smith. It is shown that alarm calls can evolve in small groups of unrelated individuals under conditions qualitatively similar but quantitatively more rigorous than those prevailing for sib-groups.     

Multilevel selection and human altruism

Views on the evolution of altruism based upon multilevel selection on structured populations pay little attention to the difference between fortuitous and deliberate processes leading to assortative grouping. Altruism may evolve when assortative grouping is fortuitously produced by forces external to the organism. But when it is deliberately produced by the same proximate mechanism that controls altruistic responses, as in humans, exploitation of altruists by selfish individuals is unlikely and altruism evolves as an individually advantageous trait. Groups formed with altruists of this sort are special, because they are not affected by subversion from within. A synergistic process where altruism is selected both at the individual and at the group level can take place.     

"Runaway" social evolution: reinforcing selection for inbreeding and altruism.

Kin selection theory predicts that altruistic behaviors, those that decrease the fitness of the individual performing the behavior but increase the fitness of the recipient, can increase in frequency if the individuals interacting are closely related. Several studies have shown that inbreeding therefore generally increases the effectiveness of kin selection when fitnesses are linear, additive functions of the number of altruists in the family, although with extreme forms of altruism, inbreeding can actually retard the evolution of altruism. These models assume that a constant proportion of the population mates at random and a constant proportion practices some form of inbreeding. In order to investigate the effect of inbreeding on the evolution of altruistic behavior when the mating structure is allowed to evolve, we examined a two-locus model by computer simulation of a diploid case and illustrated the important qualitative features by mathematical analysis of a haploid case. One locus determines an individual's propensity to perform altruistic social behavior and the second locus determines the probability that an individual will mate within its sibship. We assumed positive selection for altruism and no direct selection at the inbreeding locus. We observed that the altruistic allele and the inbreeding allele become positively associated, even when the initial conditions of the model assume independence between these loci. This linkage disequilibrium becomes established, because the altruistic allele increases more rapidly in the inbreeding segment of the population. This association subsequently results in indirect selection on the inbreeding locus. However, the dynamics of this model go beyond a simple "hitch-hiking" effect, because high levels of altruism lead to increased inbreeding, and high degrees of inbreeding accelerate the rate of change of the altruistic allele in the entire population. Thus, the dynamics of this model are similar to those of "runaway" sexual selection, with gene frequency change at the two loci interactively causing rapid evolutionary change.     

The financial cost of status signaling: Expansive postural displays are associated with a reduction in the receipt of altruistic donations

Models of human altruism suggest that decisions to help are influenced by assessments of both potential recipients' need state and their competence, as high need increases the value of gifts received, and competent recipients can most effectively use and repay gifts. Need and competence are often inversely related, however, raising the question of how altruists weigh these competing sources of information. We examined the impact of a nonverbal display (expansive posture) that, by signaling high status, simultaneously cues both low need and high competence, on actual altruistic behaviors: donations of financial aid to needy individuals. Across three studies using ecologically valid data drawn from a micro-lending charity website, men who displayed expansive posture while requesting aid faced a substantial reduction in the amount of aid they received; this effect held controlling for a range of relevant covariates. These findings demonstrate that: (a) altruists bias their giving toward those in greater need rather those who may be more competent, and (b) subtle nonverbal cues of status influence altruistic decision-making.     

Pro-community altruism and social status in a Shuar village

Reciprocity theory (RT) and costly signaling theory (CST) provide different explanations for the high status of pro-community altruists: RT proposes that altruists are positively and negatively sanctioned by others, whereas CST proposes that altruists are attractive to others. Only RT, however, is beset by first- and higher-order free rider problems, which must be solved in order for RT to explain status allocations. In this paper, several solutions to RT’s free rider problems are proposed, and data about status allocations to Ecuadorian Shuar pro-community altruists are analyzed in light of RT and CST. These data confirm that perceived pro-community altruists are indeed high status and suggest that (1) community residents skillfully monitor the altruism of coresidents, (2) residents who engage in opportunities to broadcast desirable qualities are high status only to the extent that they are considered altruistic, and (3) individuals who sanction coresidents based on coresidents’ contributions to the community are themselves relatively high status. To a greater extent than CST, RT straightforwardly predicts all of these results.     

Competitive altruism: from reciprocity to the handicap principle

Current work on cooperation is focused on the theory of reciprocal altruism. However, reciprocity is just one way of getting a return on an investment in altruism and is difficult to apply to many examples. Reciprocity theory addresses how animals respond dynamically to others so as to cooperate without being exploited. I discuss how introducing differences in individual generosity together with partner choice into models of reciprocity can lead to an escalation in altruistic behaviour. Individuals may compete for the most altruistic partners and non-altruists may become ostracized. I refer to this phenomenon as competitive altruism and propose that it can represent a move away from the dynamic responsiveness of reciprocity. Altruism may be rewarded in kind, but rewards may be indirectly accrued or may not involve the return of altruism at all, for example if altruists tend to be chosen as mates. This variety makes the idea of competitive altruism relevant to behaviours which cannot be explained by reciprocity. I consider whether altruism might act as a signal of quality, as proposed by the handicap principle. I suggest that altruistic acts could make particularly effective signals because of the inherent benefits to receivers. I consider how reciprocity and competitive altruism are related and how they may be distinguished.     

Is prospective altruist-detection an evolved solution to the adaptive problem of subtle cheating in cooperative ventures? Supportive evidence using the Wason selection task

Reciprocal altruism in humans may be made possible in part by the existence of information processing mechanisms for the detection of overt cheating. However, cheating may not always be readily detectable due to the division of labor. Subtle cheating poses a serious problem for the evolution of altruism. This article argues that subtle cheating may have exerted selective pressures on early hominids to be sensitive to information regarding the genuineness of an altruistic act. In two experiments, subjects were required to complete Wason selection tasks designed to allow for the detection of altruism. Performance on the altruist-detection tasks was compared to performance on control Wason selection tasks (Experiment 1) and to performance on control and cheater detection tasks (Experiment 2). Participants were significantly better at solving cheater-detection and altruist-detection versions compared to control versions of the problems, and there was no significant difference between altruist-detection and cheater-detection. Results are discussed in relation to recent conceptual models for the evolution of altruism. Specifically, it is argued that non-kin altruism may be an evolutionarily stable strategy if altruists can detect one another and form mutually beneficial social support networks.     

Evolution,altruism and cognitive architecture: a critique of Sober and Wilson’s argument for psychological altruism

Sober and Wilson have propose a cluster of arguments for the conclusion that “natural selection is unlikely to have given us purely egoistic motives” and thus that psychological altruism is true. I maintain that none of these arguments is convincing. However, the most powerful of their arguments raises deep issues about what egoists and altruists are claiming and about the assumptions they make concerning the cognitive architecture underlying human motivation.     

Altruism and mental disorders

Data suggest that the theories of kin selection and reciprocal altruism are viable working models to explain altruistic behavior. It remains to be demonstrated if these models can explain the behavior of persons with mentaL disorders for whom altruistic behavior is reported to be reduced. This paper addresses this issue. Part I reviews proximate factors that are thought to influence both altruistic decision making and interindividual variation in altruistic behavior. The focus is on trait signaling by potential beneficiaries and the evaluation of signals and altruistic decision making by potential altruists. In Part II, points developed in Part I are combined with clinical and empirical findings to analyze data on personality disorders and dysthymic disorder. The analysis leads to three causal hypotheses: Reduced altruistic behavior may be an evolved strategy, a consequence of dysfunctional recognition systems or algorithms, and/or a secondary response to an increase in symptoms. Different disorders and features of disorders are explained by each hypothesis.     

The evolution of generalized reciprocity on social interaction networks

Generalized reciprocity (help anyone, if helped by someone) is a minimal strategy capable of supporting cooperation between unrelated individuals. Its simplicity makes it an attractive model to explain the evolution of reciprocal altruism in animals that lack the information or cognitive skills needed for other types of reciprocity. Yet, generalized reciprocity is anonymous and thus defenseless against exploitation by defectors. Recognizing that animals hardly ever interact randomly, we investigate whether social network structure can mitigate this vulnerability. Our results show that heterogeneous interaction patterns strongly support the evolution of generalized reciprocity. The future probability of being rewarded for an altruistic act is inversely proportional to the average connectivity of the social network when cooperators are rare. Accordingly, sparse networks are conducive to the invasion of reciprocal altruism. Moreover, the evolutionary stability of cooperation is enhanced by a modular network structure. Communities of reciprocal altruists are protected against exploitation, because modularity increases the mean access time, that is, the average number of steps that it takes for a random walk on the network to reach a defector. Sparseness and community structure are characteristic properties of vertebrate social interaction patterns, as illustrated by network data from natural populations ranging from fish to primates.     

Lower group productivity under kin-selected reproductive altruism

Abstract Hamilton's rule provides the foundation for understanding the genetic evolution of social behavior, showing that altruism is favored by increased relatedness and increased productivity of altruists. But how likely is it that a new altruistic mutation will satisfy Hamilton's rule by increasing the reproductive efficiency of the group? Altruism per se does not improve efficiency, and hence we would not expect a typical altruistic mutation to increase the mean productivity of the population. We examined the conditions under which a mutation causing reproductive altruism can spread when it does not increase productivity. We considered a population divided into temporary groups of genetically similar individuals (typically family groups). We show that the spread of altruism requires a pleiotropic link between altruism and enhanced productivity in diploid organisms, but not in haplodiploid organisms such as Hymenoptera. This result provides a novel biological understanding of the barrier to the spread of reproductive altruism in diploids. In haplodiploid organisms, altruism within families that lowers productivity may spread, provided daughters sacrifice their own reproduction to raise full‐sisters. We verified our results using three single‐locus genetic models that explore a range of the possible reproductive costs of helping. The advantage of female‐to‐female altruism in haplodiploids is a well‐known prediction of Hamilton's rule, but its importance in relaxing the linkage between altruism and efficiency has not been explored. We discuss the possible role of such unproductive altruism in the origins of sociality. We also note that each model predicts a large region of parameter space were polymorphism between altruism and selfishness is maintained, a pattern independent of dominance.     

Altruism Can Be Assessed Correctly Based on Impression

Detection of genuine altruists could be a solution to the problem of subtle cheating. Brown et al. (Evol Psychol 1:42–69, 2003) found that humans could detect altruists using nonverbal cues. However, their experiments can be improved upon in several ways, and further investigation is needed to determine whether altruist-detection abilities are human universals. In our experiment, we used video clips of natural conversations as the stimulus. We asked a sample of Japanese undergraduates to rate their own level of altruism and then to estimate the videotaped targets’ altruism using the same scale. The perceivers were able to estimate the targets’ altruism levels accurately. Perceivers’ altruism score did not affect their ability to discriminate between altruists and non-altruists. Perceivers’ impressions of the altruist and non-altruist targets were also found to be different. Coding of nonverbal behavior of the targets revealed that altruists exhibited more “felt smiles” than non-altruists, which also supports the results of the previous study.     

Partner choice creates competitive altruism in humans

Reciprocal altruism has been the backbone of research on the evolution of altruistic behaviour towards non-kin, but recent research has begun to apply costly signalling theory to this problem. In addition to signalling resources or abilities, public generosity could function as a costly signal of cooperative intent, benefiting altruists in terms of (i) better access to cooperative relationships and (ii) greater cooperation within those relationships. When future interaction partners can choose with whom they wish to interact, this could lead to competition to be more generous than others. Little empirical work has tested for the possible existence of this 'competitive altruism'. Using a cooperative monetary game with and without opportunities for partner choice and signalling cooperative intent, we show here that people actively compete to be more generous than others when they can benefit from being chosen for cooperative partnerships, and the most generous people are correspondingly chosen more often as cooperative partners. We also found evidence for increased scepticism of altruistic signals when the potential reputational benefits for dishonest signalling were high. Thus, this work supports the hypothesis that public generosity can be a signal of cooperative intent, which people sometimes 'fake' when conditions permit it.     

Altruism in networks: the effect of connections

Why are individuals altruistic to their friends? Theory suggests that individual, relationship and network factors will all influence the levels of altruism; but to date, the effects of social network structure have received relatively little attention. The present study uses a novel correlational design to test the prediction that an individual will be more altruistic to friends who are well-connected to the individual''s other friends. The result shows that, as predicted, even when controlling for a range of individual and relationship factors, the network factor (number of connections) makes a significant contribution to altruism, thus showing that individuals are more likely to be altruistic to better-connected members of their social networks. The implications of incorporating network structure into studies of altruism are discussed.     

Kin selection in human populations: theory reconsidered

Past considerations of kin selection have assumed a dyadic fitness exchange relationship between altruist and recipient. This approach does not account for all alleles affected by altruistic behavior. This can be corrected by focusing on matings rather than on individuals. I present a model that tries to account for fitness changes resulting from altruistic acts, not only for the altruist and recipient but also for their spouses, in an evolving population. Results from this model indicate that Hamilton's rule fails to predict when the altruism allele will increase in frequency and, more important, suggest that kin selection can, at most, account for low levels of a gene for altruism but only if fairly extreme conditions are met.