Super-additive cooperation.

Repeated interactions provide an evolutionary explanation for one-shot human cooperation that is counterintuitive but orthodox1-3. Intergroup competition4-7 provides an explanation that is intuitive but heterodox. Here, using models and a behavioural experiment, we show that neither mechanism reliably supports cooperation. Ambiguous reciprocity, a class of strategies that is generally ignored in models of reciprocal altruism, undermines cooperation under repeated interactions. This finding challenges repeated interactions as an evolutionary explanation for cooperation in general, which further challenges the claim that repeated interactions in the past can explain one-shot cooperation in the present. Intergroup competitions also do not reliably support cooperation because groups quickly become extremely similar, which limits scope for group selection. Moreover, even if groups vary, group competitions may generate little group selection for multiple reasons. Cooperative groups, for example, may tend to compete against each other8. Whereas repeated interactions and group competitions do not support cooperation by themselves, combining them triggers powerful synergies because group competitions constrain the corrosive effect of ambiguous reciprocity. Evolved strategies often consist of cooperative reciprocity with ingroup partners and uncooperative reciprocity with outgroup partners. Results from a behavioural experiment in Papua New Guinea fit exactly this pattern. They thus suggest neither an evolutionary history of repeated interactions without group competition nor a history of group competition without repeated interactions. Instead, our results suggest social motives that evolved under the joint influence of both mechanisms.

A Turing test of whether AI chatbots are behaviorally similar to humans.

We administer a Turing test to AI chatbots. We examine how chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairness, risk-aversion, cooperation, etc., as well as how they respond to a traditional Big-5 psychological survey that measures personality traits. ChatGPT-4 exhibits behavioral and personality traits that are statistically indistinguishable from a random human from tens of thousands of human subjects from more than 50 countries. Chatbots also modify their behavior based on previous experience and contexts "as if" they were learning from the interactions and change their behavior in response to different framings of the same strategic situation. Their behaviors are often distinct from average and modal human behaviors, in which case they tend to behave on the more altruistic and cooperative end of the distribution. We estimate that they act as if they are maximizing an average of their own and partner's payoffs.

Altruism and natural selection in a variable environment.

Hamilton's rule provides the cornerstone for our understanding of the evolution of all forms of social behavior, from altruism to spite, across all organisms, from viruses to humans. In contrast to the standard prediction from Hamilton's rule, recent studies have suggested that altruistic helping can be favored even if it does not benefit relatives, as long as it decreases the environmentally induced variance of their reproductive success ("altruistic bet-hedging"). However, previous predictions both rely on an approximation and focus on variance-reducing helping behaviors. We derived a version of Hamilton's rule that fully captures environmental variability. This shows that decreasing (or increasing) the variance in the absolute reproductive success of relatives does not have a consistent effect-it can either favor or disfavor the evolution of helping. We then empirically quantified the effect of helping on the variance in reproductive success across 15 species of cooperatively breeding birds. We found that a) helping did not consistently decrease the variance of reproductive success and often increased it, and b) the mean benefits of helping across environments consistently outweighed other variability components of reproductive success. Altogether, our theoretical and empirical results suggest that the effects of helping on the variability components of reproductive success have not played a consistent or strong role in favoring helping.

Is in-kind kinder than cash? The impact of money vs. food aid on social emotions and aid take-up.

Over the past decade, there has been a shift in the way charities deliver humanitarian aid. Historically, the most prevalent way to help the global poor was by providing in-kind asset transfers. Recently, alternatives to in-kind aid, such as cash aid, have been increasing in prevalence. Although there has been widespread endorsement from the academic community and the public on the popularizing model of giving cash aid, one perspective remains untouched: the recipient's perspective. Thus, the present research explores how food-insecure individuals feel when receiving money vs. in-kind food aid to help meet their hunger and nutrition needs. Specifically, we explore the degree of positive (e.g., feeling cared for) and negative (e.g., feeling ashamed) social emotions felt when receiving the aid opportunity and how willing recipients are to accept monetary (vs. food) aid. Results from five preregistered experiments (N = 3,110)-a field experiment in Kenya and four online experiments in the United States-find that monetary (vs. food) aid elicits comparatively more of a market-pricing relationship and less of a communal sharing relationship and, hence, makes people feel less positive and more negative social emotions when receiving the help. Subsequently, recipients are less likely to take up monetary (vs. food) aid from a charity. However, we find that this effect does not persist when receiving government aid: Recipients are similarly willing to accept money and in-kind food aid from the government. This research suggests that future scholarship ought to examine ways to improve psychological experiences when receiving money from charity.

Emergence and collapse of reciprocity in semiautomatic driving coordination experiments with humans.

Forms of both simple and complex machine intelligence are increasingly acting within human groups in order to affect collective outcomes. Considering the nature of collective action problems, however, such involvement could paradoxically and unintentionally suppress existing beneficial social norms in humans, such as those involving cooperation. Here, we test theoretical predictions about such an effect using a unique cyber-physical lab experiment where online participants (N = 300 in 150 dyads) drive robotic vehicles remotely in a coordination game. We show that autobraking assistance increases human altruism, such as giving way to others, and that communication helps people to make mutual concessions. On the other hand, autosteering assistance completely inhibits the emergence of reciprocity between people in favor of self-interest maximization. The negative social repercussions persist even after the assistance system is deactivated. Furthermore, adding communication capabilities does not relieve this inhibition of reciprocity because people rarely communicate in the presence of autosteering assistance. Our findings suggest that active safety assistance (a form of simple AI support) can alter the dynamics of social coordination between people, including by affecting the trade-off between individual safety and social reciprocity. The difference between autobraking and autosteering assistance appears to relate to whether the assistive technology supports or replaces human agency in social coordination dilemmas. Humans have developed norms of reciprocity to address collective challenges, but such tacit understandings could break down in situations where machine intelligence is involved in human decision-making without having any normative commitments.

Parasite effects on receivers in animal communication: Hidden impacts on behavior, ecology, and evolution.

Parasites exert a profound effect on biological processes. In animal communication, parasite effects on signalers are well-known drivers of the evolution of communication systems. Receiver behavior is also likely to be altered when they are parasitized or at risk of parasitism, but these effects have received much less attention. Here, we present a broad framework for understanding the consequences of parasitism on receivers for behavioral, ecological, and evolutionary processes. First, we outline the different kinds of effects parasites can have on receivers, including effects on signal processing from the many parasites that inhabit, occlude, or damage the sensory periphery and the central nervous system or that affect physiological processes that support these organs, and effects on receiver response strategies. We then demonstrate how understanding parasite effects on receivers could answer important questions about the mechanistic causes and functional consequences of variation in animal communication systems. Variation in parasitism levels is a likely source of among-individual differences in response to signals, which can affect receiver fitness and, through effects on signaler fitness, impact population levels of signal variability. The prevalence of parasitic effects on specific sensory organs may be an important selective force for the evolution of elaborate and multimodal signals. Finally, host-parasite coevolution across heterogeneous landscapes will generate geographic variation in communication systems, which could ultimately lead to evolutionary divergence. We discuss applications of experimental techniques to manipulate parasitism levels and point the way forward by calling for integrative research collaborations between parasitologists, neurobiologists, and behavioral and evolutionary ecologists.

Lifetime inclusive fitness effects of cooperative polygamy in the acorn woodpecker.

Although over 50 y have passed since W. D. Hamilton articulated kin selection and inclusive fitness as evolutionary explanations for altruistic behavior, quantifying inclusive fitness continues to be challenging. Here, using 30 y of data and two alternative methods, we outline an approach to measure lifetime inclusive fitness effects of cooperative polygamy (mate-sharing or cobreeding) in the cooperatively breeding acorn woodpecker Melanerpes formicivorus. For both sexes, the number of offspring (observed direct fitness) declined while the number of young parented by related cobreeders (observed indirect fitness effect) increased with cobreeding coalition size. Combining these two factors, the observed inclusive fitness effect of cobreeding was greater than breeding singly for males, while the pattern for females depended on whether fitness was age-weighted, as females breeding singly accrued greater fitness at younger ages than cobreeding females. Accounting for the fitness birds would have obtained by breeding singly, however, lifetime inclusive fitness effects declined with coalition size for males, but were greater for females breeding as duos compared to breeding singly, due largely to indirect fitness effects of kin. Our analyses provide a road map for, and demonstrate the importance of, quantifying indirect fitness as a powerful evolutionary force contributing to the costs and benefits of social behaviors.

Human Prosocial Preferences Are Related to Slow-Wave Activity in Sleep.

Prosocial behavior is crucial for the smooth functioning of the society. Yet, individuals differ vastly in the propensity to behave prosocially. Here, we try to explain these individual differences under normal sleep conditions without any experimental modulation of sleep. Using a portable high-density EEG, we measured the sleep data in 54 healthy adults (28 females) during a normal night's sleep at the participants' homes. To capture prosocial preferences, participants played an incentivized public goods game in which they faced real monetary consequences. The whole-brain analyses showed that a higher relative slow-wave activity (SWA, an indicator of sleep depth) in a cluster of electrodes over the right temporoparietal junction (TPJ) was associated with increased prosocial preferences. Source localization and current source density analyses further support these findings. Recent sleep deprivation studies imply that sleeping enough makes us more prosocial; the present findings suggest that it is not only sleep duration, but particularly sufficient sleep depth in the TPJ that is positively related to prosociality. Because the TPJ plays a central role in social cognitive functions, we speculate that sleep depth in the TPJ, as reflected by relative SWA, might serve as a dispositional indicator of social cognition ability, which is reflected in prosocial preferences. These findings contribute to the emerging framework explaining the link between sleep and prosocial behavior by shedding light on the underlying mechanisms.

Sleep loss leads to the withdrawal of human helping across individuals, groups, and large-scale societies.

Humans help each other. This fundamental feature of homo sapiens has been one of the most powerful forces sculpting the advent of modern civilizations. But what determines whether humans choose to help one another? Across 3 replicating studies, here, we demonstrate that sleep loss represents one previously unrecognized factor dictating whether humans choose to help each other, observed at 3 different scales (within individuals, across individuals, and across societies). First, at an individual level, 1 night of sleep loss triggers the withdrawal of help from one individual to another. Moreover, fMRI findings revealed that the withdrawal of human helping is associated with deactivation of key nodes within the social cognition brain network that facilitates prosociality. Second, at a group level, ecological night-to-night reductions in sleep across several nights predict corresponding next-day reductions in the choice to help others during day-to-day interactions. Third, at a large-scale national level, we demonstrate that 1 h of lost sleep opportunity, inflicted by the transition to Daylight Saving Time, reduces real-world altruistic helping through the act of donation giving, established through the analysis of over 3 million charitable donations. Therefore, inadequate sleep represents a significant influential force determining whether humans choose to help one another, observable across micro- and macroscopic levels of civilized interaction. The implications of this effect may be non-trivial when considering the essentiality of human helping in the maintenance of cooperative, civil society, combined with the reported decline in sufficient sleep in many first-world nations.

When do stereotypes undermine indirect reciprocity?

Social reputations provide a powerful mechanism to stimulate human cooperation, but observing individual reputations can be cognitively costly. To ease this burden, people may rely on proxies such as stereotypes, or generalized reputations assigned to groups. Such stereotypes are less accurate than individual reputations, and so they could disrupt the positive feedback between altruistic behavior and social standing, undermining cooperation. How do stereotypes impact cooperation by indirect reciprocity? We develop a theoretical model of group-structured populations in which individuals are assigned either individual reputations based on their own actions or stereotyped reputations based on their groups' behavior. We find that using stereotypes can produce either more or less cooperation than using individual reputations, depending on how widely reputations are shared. Deleterious outcomes can arise when individuals adapt their propensity to stereotype. Stereotyping behavior can spread and can be difficult to displace, even when it compromises collective cooperation and even though it makes a population vulnerable to invasion by defectors. We discuss the implications of our results for the prevalence of stereotyping and for reputation-based cooperation in structured populations.

Is it selfish to be filamentous in biofilms? Individual-based modeling links microbial growth strategies with morphology using the new and modular iDynoMiCS 2.0.

Microbial communities are found in all habitable environments and often occur in assemblages with self-organized spatial structures developing over time. This complexity can only be understood, predicted, and managed by combining experiments with mathematical modeling. Individual-based models are particularly suited if individual heterogeneity, local interactions, and adaptive behavior are of interest. Here we present the completely overhauled software platform, the individual-based Dynamics of Microbial Communities Simulator, iDynoMiCS 2.0, which enables researchers to specify a range of different models without having to program. Key new features and improvements are: (1) Substantially enhanced ease of use (graphical user interface, editor for model specification, unit conversions, data analysis and visualization and more). (2) Increased performance and scalability enabling simulations of up to 10 million agents in 3D biofilms. (3) Kinetics can be specified with any arithmetic function. (4) Agent properties can be assembled from orthogonal modules for pick and mix flexibility. (5) Force-based mechanical interaction framework enabling attractive forces and non-spherical agent morphologies as an alternative to the shoving algorithm. The new iDynoMiCS 2.0 has undergone intensive testing, from unit tests to a suite of increasingly complex numerical tests and the standard Benchmark 3 based on nitrifying biofilms. A second test case was based on the "biofilms promote altruism" study previously implemented in BacSim because competition outcomes are highly sensitive to the developing spatial structures due to positive feedback between cooperative individuals. We extended this case study by adding morphology to find that (i) filamentous bacteria outcompete spherical bacteria regardless of growth strategy and (ii) non-cooperating filaments outcompete cooperating filaments because filaments can escape the stronger competition between themselves. In conclusion, the new substantially improved iDynoMiCS 2.0 joins a growing number of platforms for individual-based modeling of microbial communities with specific advantages and disadvantages that we discuss, giving users a wider choice.

Reinforcement learning of altruistic punishment differs between cultures and across the lifespan.

Altruistic punishment is key to establishing cooperation and maintaining social order, yet its developmental trends across cultures remain unclear. Using computational reinforcement learning models, we provided the first evidence of how social feedback dynamically influences group-biased altruistic punishment across cultures and the lifespan. Study 1 (n = 371) found that Chinese participants exhibited higher learning rates than Americans when socially incentivized to punish unfair allocations. Additionally, Chinese adults showed slower learning and less exploration when punishing ingroups than outgroups, a pattern absent in American counterparts, potentially reflecting a tendency towards ingroup favoritism that may contribute to reinforcing collectivist values. Study 2 (n = 430, aged 12-52) further showed that such ingroup favoritism develops with age. Chinese participants' learning rates for ingroup punishment decreased from adolescence into adulthood, while outgroup rates stayed constant, implying a process of cultural learning. Our findings highlight cultural and age-related variations in altruistic punishment learning, with implications for social reinforcement learning and culturally sensitive educational practices promoting fairness and altruism.

The links between physical activity and prosocial behavior: an fNIRS hyperscanning study.

The prevalence of physically inactive lifestyles in modern society raises concerns about the potential association with poor brain health, particularly in the lateral prefrontal cortex, which is crucial for human prosocial behavior. Here, we explored the relationship between physical activity and prosocial behavior, focusing on potential neural markers, including intra-brain functional connectivity and inter-brain synchrony in the lateral prefrontal cortex. Forty participants, each paired with a stranger, completed two experimental conditions in a randomized order: (i) face-to-face and (ii) face stimulus (eye-to-eye contact with a face stimulus of a fictitious person displayed on the screen). Following each condition, participants played economic games with either their partner or an assumed person displayed on the screen. Neural activity in the lateral prefrontal cortex was recorded by functional near-infrared spectroscopy hyperscanning. Sparse multiset canonical correlation analysis showed that a physically inactive lifestyle was covaried with poorer reciprocity, greater trust, shorter decision-making time, and weaker intra-brain connectivity in the dorsal lateral prefrontal cortex and poorer inter-brain synchrony in the ventral lateral prefrontal cortex. These associations were observed exclusively in the face-to-face condition. Our findings suggest that a physically inactive lifestyle may alter human prosocial behavior by impairing adaptable prosocial decision-making in response to social factors through altered intra-brain functional connectivity and inter-brain synchrony.

Hamilton's rule in economic decision-making.

Hamilton's rule [W. D. Hamilton, Am. Nat. 97, 354­356 (1963); W. D. Hamilton, J. Theor. Biol. 7, 17­52 (1964)] quantifies the central evolutionary ideas of inclusive fitness and kin selection into a simple algebraic relationship. Evidence consistent with Hamilton's rule is found in many animal species. A drawback of investigating Hamilton's rule in these species is that one can estimate whether a given behavior is consistent with the rule, but a direct examination of the exact cutoff for altruistic behavior predicted by Hamilton is almost impossible. However, to the degree that economic resources confer survival benefits in modern society, Hamilton's rule may be applicable to economic decision-making, in which case techniques from experimental economics offer a way to determine this cutoff. We employ these techniques to examine whether Hamilton's rule holds in human decision-making, by measuring the dependence between an experimental subject's maximal willingness to pay for a gift of $50 to be given to someone else and the genetic relatedness of the subject to the gift's recipient. We find good agreement with the predictions of Hamilton's rule. Moreover, regression analysis of the willingness to pay versus genetic relatedness, the number of years living in the same residence, age, and sex shows that almost all the variation is explained by genetic relatedness. Similar but weaker results are obtained from hypothetical questions regarding the maximal risk to her own life that the subject is willing to take in order to save the recipient's life.

Developmental constraints enforce altruism and avert the tragedy of the commons in a social microbe.

Organisms often cooperate through the production of freely available public goods. This can greatly benefit the group but is vulnerable to the "tragedy of the commons" if individuals lack the motivation to make the necessary investment into public goods production. Relatedness to groupmates can motivate individual investment because group success ultimately benefits their genes' own self-interests. However, systems often lack mechanisms that can reliably ensure that relatedness is high enough to promote cooperation. Consequently, groups face a persistent threat from the tragedy unless they have a mechanism to enforce investment when relatedness fails to provide adequate motivation. To understand the real threat posed by the tragedy and whether groups can avert its impact, we determine how the social amoeba Dictyostelium discoideum responds as relatedness decreases to levels that should induce the tragedy. We find that, while investment in public goods declines as overall within-group relatedness declines, groups avert the expected catastrophic collapse of the commons by continuing to invest, even when relatedness should be too low to incentivize any contribution. We show that this is due to a developmental buffering system that generates enforcement because insufficient cooperation perturbs the balance of a negative feedback system controlling multicellular development. This developmental constraint enforces investment under the conditions expected to be most tragic, allowing groups to avert a collapse in cooperation. These results help explain how mechanisms that suppress selfishness and enforce cooperation can arise inadvertently as a by-product of constraints imposed by selection on different traits.

The restart effect in social dilemmas shows humans are self-interested not altruistic.

Do economic games show evidence of altruistic or self-interested motivations in humans? A huge body of empirical work has found contrasting results. While many participants routinely make costly decisions that benefit strangers, consistent with the hypothesis that humans exhibit a biologically novel form of altruism (or "prosociality"), many participants also typically learn to pay fewer costs with experience, consistent with self-interested individuals adapting to an unfamiliar environment. Key to resolving this debate is explaining the famous "restart effect," a puzzling enigma whereby failing cooperation in public goods games can be briefly rescued by a surprise restart. Here we replicate this canonical result, often taken as evidence of uniquely human altruism, and show that it 1) disappears when cooperation is invisible, meaning individuals can no longer affect the behavior of their groupmates, consistent with strategically motivated, self-interested, cooperation; and 2) still occurs even when individuals are knowingly grouped with computer players programmed to replicate human decisions, consistent with confusion. These results show that the restart effect can be explained by a mixture of self-interest and irrational beliefs about the game's payoffs, and not altruism. Consequently, our results suggest that public goods games have often been measuring self-interested but confused behaviors and reject the idea that conventional theories of evolution cannot explain the results of economic games.

Advancing convergence research: Renewable energy solutions for off-grid communities.

Millions of people across the world live off-grid not by choice but because they live in rural areas, have low income, and have no political clout. Delivering sustainable energy solutions to such a substantial amount of the world's population requires more than a technological fix; it requires leveraging the knowledge of underserved populations working together with a transdisciplinary team to find holistically derived solutions. Our original research has resulted in an innovative Convergence Framework integrating the fields of engineering, social sciences, and communication, and is based on working together with communities and other stakeholders to address the challenges posed by delivering clean energy solutions. In this paper, we discuss the evolution of this Framework and illustrate how this Framework is being operationalized in our on-going research project, cocreating hybrid renewable energy systems for off-grid communities in the Brazilian Amazon. The research shows how this Framework can address clean energy transitions, strengthen emerging industries at local level, and foster Global North-South scholarly collaborations. We do so by the integration of social science and engineering and by focusing on community engagement, energy justice, and governance for underserved communities. Further, this solution-driven Framework leads to the emergence of unique approaches that advance scientific knowledge, while at the same time addressing community needs.

Experimental evidence of physician social preferences.

Physicians' professional ethics require that they put patients' interests ahead of their own and that they should allocate limited medical resources efficiently. Understanding physicians' extent of adherence to these principles requires understanding the social preferences that lie behind them. These social preferences may be divided into two qualitatively different trade-offs: the trade-off between self and other (altruism) and the trade-off between reducing differences in payoffs (equality) and increasing total payoffs (efficiency). We experimentally measure social preferences among a nationwide sample of practicing physicians in the United States. Our design allows us to distinguish empirically between altruism and equality-efficiency orientation and to accurately measure both trade-offs at the level of the individual subject. We further compare the experimentally measured social preferences of physicians with those of a representative sample of Americans, an "elite" subsample of Americans, and a nationwide sample of medical students. We find that physicians' altruism stands out. Although most physicians place a greater weight on self than on other, the share of physicians who place a greater weight on other than on self is twice as large as for all other samples-32% as compared with 15 to 17%. Subjects in the general population are the closest to physicians in terms of altruism. The higher altruism among physicians compared with the other samples cannot be explained by income or age differences. By contrast, physicians' preferences regarding equality-efficiency orientation are not meaningfully different from those of the general sample and elite subsample and are less efficiency oriented than medical students.

COVID-19 infection induces higher trust in strangers.

How does the COVID-19 pandemic affect interpersonal trust? Most evidence shows that natural disasters reinforce trust and cooperation, but the COVID-19 virus differs from other calamities, since it spreads through contact with people, potentially increasing suspicion and distrust, as, according to contemporaneous writers' accounts, seems to have been the case with the Black Death, the London plague, and the Spanish influenza. We investigate the link between interpersonal trust and individuals exposed to COVID-19, either vicariously through their community or networks or directly by becoming infected. We rely on an original panel survey, including a survey experiment, with a representative sample of adults in Italy, one of the countries hardest struck by the pandemic. Our experimental findings reveal that priming people about the risk that the pandemic poses to their health leads to a substantial increase in their trust in strangers. Our panel data analysis of within-individual effects shows that those who become infected trust strangers more than those who are not infected. Our findings could be explained by people observing higher than expected altruistic behavior or becoming more dependent on other people's support, consistent with the "emancipation theory of trust." When people recover from COVID-19, however, they drop to trusting strangers as much as those who were not directly exposed to the virus, an indication that the positive effects on trust during the pandemic have an emotional source. Nonetheless, the evidence suggests that, in the aggregate, there has been a small but significant increase in trust among the general population relative to prepandemic levels.