Cooperation is essential to human life, from sharing resources and caring for vulnerable people to participating in institutions that benefit entire communities. Yet from an evolutionary perspective, cooperation is puzzling. Helping another person can be costly, while the immediate benefit may go to someone else. Researchers have therefore spent decades studying indirect reciprocity, the process through which people gain or lose reputations based on how they treat others. A person known to be helpful may receive help in the future, even from individuals they have never assisted directly. In this way, reputation can transform isolated acts of generosity into a stable social system.

Most mathematical models of indirect reciprocity focus on pairwise interactions. One person, known as the donor, decides whether to help another person, known as the recipient. Observers then evaluate the donor’s action and update the donor’s reputation. If the donor helps someone considered deserving, the donor may be judged “good.” If the donor refuses to help a deserving person, the donor may be viewed negatively. These judgments influence future decisions, creating a feedback loop in which reputations guide behavior and behavior reinforces reputations.

The problem becomes much more complicated as communities grow. In a small pair-based network, people may be able to keep track of who helped whom and why. In larger groups, however, individuals observe different encounters, interpret them differently, or rely on incomplete information. Two observers can therefore assign different reputations to the same person. Such private disagreements can destabilize cooperation: someone judged trustworthy by one observer may be denied help by another, while a person considered unworthy by one group may still receive support from someone else. Earlier models have often addressed this problem by adding mechanisms such as gossip, reputation-sharing systems, or public institutions that synchronize social judgments.

The Kobe University team, working with collaborators from RIKEN and the Interdisciplinary Transformation University, examined whether cooperation could remain stable through a simpler mechanism. Instead of allowing observers to update only the donor’s reputation, their model allowed them to update their view of both people involved in the interaction. When Alice observes Bob helping Charlie, for example, she does not merely decide whether Bob acted well. She also learns something about Charlie from the fact that Charlie was helped. Alice might conclude that Charlie is regarded as deserving, or she might simply use Bob’s action as evidence about Charlie’s social standing. The interaction thus becomes a source of information about the recipient as well as the donor.

This dual update produces a powerful form of opinion alignment. The researchers identified a recipient-evaluation rule called recipient image scoring, or RIS, that was particularly effective. Under RIS, an observer evaluates a recipient positively if that person receives help and negatively if that person does not. The rule does not require observers to exchange messages, compare notes, or consult a central authority. Instead, people gradually revise their private opinions by watching how others are treated. If several observers see a person receive assistance, their assessments are more likely to converge. If the person is repeatedly denied assistance, observers may also move toward a shared negative evaluation.

The model suggests that this apparently simple rule can prevent disagreements from multiplying through a population. Without recipient evaluation, observers may disagree about whether a person deserves help, and those disagreements can influence how they judge later donors. With dual reputation updates, the treatment of recipients supplies an additional pathway through which information travels. A single interaction communicates not only that a donor chose to help or refuse, but also that the recipient was treated in a particular way. In technical terms, the model links the state of the donor’s reputation to the observer’s estimate of the recipient’s reputation, reducing divergence among private assessments and improving the conditions for stable cooperation.

To test how broadly the effect applied, the researchers used Fugaku, the supercomputer located in Kobe that was the world’s fastest supercomputer when it began regular operation in 2021. They examined more than one million combinations of social norms—rules specifying how people should act toward individuals with different reputations and how observers should evaluate those actions. The search identified 61 norms that produced both high levels of cooperation and evolutionary stability. Every one of these successful norms included some form of dual reputation updating, indicating that recipient evaluation was not merely a special feature of RIS. It appeared repeatedly among the most successful solutions in the model.

The results do not mean that gossip, public records, or institutions are unnecessary. Those mechanisms may still help societies coordinate judgments, especially when interactions are hidden or information is unreliable. The researchers instead propose that multiple systems may work together, each reducing disagreement in a different way. Their findings also point to a darker implication. People may judge someone not only by what that person does, but by how others treat them. That tendency can support cooperation when assistance signals social worth, but it can also reinforce exclusion, stigma, or bullying when observers imitate hostile treatment without independent evidence. Whether people consistently form reputations in this way remains an empirical question, but the model suggests that observing social treatment may be a fundamental and double-edged component of human judgment.

Subject of Research: People

Article Title: Indirect reciprocity with dual private assessment

News Publication Date: 24-Aug-2026

Web References: https://doi.org/10.1073/pnas.2624656123

References: Proceedings of the National Academy of Sciences; DOI: 10.1073/pnas.2624656123

Image Credits: Kobe University

Keywords: cooperation, reputation, indirect reciprocity, social norms, recipient image scoring, evolutionary stability, private assessment, social psychology, bystander effect, group behavior, prosocial behavior, computational modeling

However, the story does not end with the emergence of cooperation. Equally critical is how the collective benefits—the public goods—are distributed among the population. This distribution affects not only the behavior of individuals within the social network but also the long-term prosperity and equity of the society. Recently, a groundbreaking study by Sheng, Su, McAvoy, et al., published in Nature (2026), has delved into the complex interplay between cooperation and equity in the allocation of public goods. Their research contrasts two fundamentally different policies for distributing the returns generated by cooperative interactions: equitable allocation and uniform allocation.

Equitable allocation assigns benefits proportionally to individuals’ potential contributions, theoretically rewarding effort and encouraging sustained cooperation among the highly connected or more productive nodes in a network. In contrast, uniform allocation distributes returns equally, regardless of individuals’ contributions or positions within the social network. This seemingly fair approach ensures that all participants receive an equal slice of the pie, aiming to foster a sense of collective ownership and possibly mitigate inequalities.

Through a detailed analysis across a broad spectrum of social network structures, the study reveals a striking and counterintuitive result: uniform allocation tends to facilitate the spread of cooperation more effectively than equitable allocation in most settings. The egalitarian distribution method creates an environment where cooperative strategies can flourish, catalyzing a broader acceptance of prosocial behavior across the network. This finding challenges previously held assumptions that rewarding proportional contributions is the optimal path for cooperation to thrive.

Yet, this apparent success of uniform allocation comes at a significant cost, exposing a fundamental trade-off between promoting cooperation and maintaining social equality. The researchers discovered that uniform allocation disproportionately concentrates resources into the hands of a small subset of highly connected individuals—essentially network hubs—while marginalizing peripheral or less connected individuals. Ironically, some members of the network may find themselves worse off under uniform allocation than if everyone had acted selfishly, leading to a paradoxical reduction in equality despite the policy’s egalitarian intentions.

This concentration of power and wealth among the network’s central players is reminiscent of social stratification dynamics observed in real-world societies, where access to resources and influence tends to cluster among elite groups. The study harnesses theoretical frameworks to elucidate this tension, highlighting how the spatial heterogeneity of social networks inherently channel benefits unevenly when public goods are shared uniformly. Consequently, the pursuit of cooperation inadvertently sows the seeds of inequality, raising profound questions about the desirability and sustainability of such outcomes.

Importantly, the authors ground their conclusions in empirical data gleaned from diverse real-world social networks, demonstrating that these patterns are not merely theoretical curiosities but observable realities. Across various types of social structures—ranging from offline human communities to online interaction networks—the conflict between equality and cooperation emerges consistently. This ubiquity suggests that policy designers and social architects must confront this dilemma directly if they seek to nurture cooperative societies that are also equitable.

Fundamentally, this study complicates the narrative of cooperation as an unalloyed good. While fostering cooperation is necessary for the production and maintenance of public goods, it cannot be pursued without consideration of how resource allocation policies shape the distribution of benefits. The resulting social stratification and inequality may undermine the collective welfare and generate new tensions, revealing the multifaceted nature of cooperation as both a social glue and a source of conflict.

The implications extend beyond theoretical biology or economics into practical realms where public goods are managed—such as environmental conservation, public health, and collective infrastructure. Policymakers implementing cooperative frameworks must balance the dual objectives of promoting widespread cooperation and mitigating the concentration of resources that can engender resentment or marginalization. Failure to address this balance could perpetuate cycles of inequality, undermining the long-term stability of social systems.

Moreover, this research underscores the necessity of refining classical evolutionary models of cooperation to incorporate the nuances of benefit distribution and social heterogeneity. Future models must account for the complex feedback loops between cooperation, network structure, and resource allocation to better predict and manage social dynamics. The study calls for an integrated approach combining evolutionary game theory, network science, and social policy analysis.

From a broader perspective, the findings open a new frontier in the study of social dilemmas that merges ethical considerations with evolutionary dynamics. The recognition that cooperation and equality may conflict challenges simplistic views of social welfare and encourages deeper investigation into how societies can design fairer cooperative systems that do not exacerbate inequalities. As such, this line of inquiry aligns with growing concerns over social justice, resource distribution, and inclusive governance in the 21st century.

In essence, Sheng and colleagues invite researchers, policymakers, and communities alike to rethink the foundational assumptions about cooperation. Their research not only reveals that the method of allocating public goods shapes cooperation patterns but also exposes the unintended consequences of such mechanisms for social equality. This dual dynamic compels us to consider cooperation not merely as a means to an end but as a complex process intertwined with power, fairness, and social cohesion.

Ultimately, the question “how should we promote cooperation?” must now be reframed to include considerations of equity and justice. Cooperation fostering policies that overlook the resultant social stratification risk cultivating divisions that could erode trust and collective action in the long run. Therefore, the path forward involves deliberate choices that weigh the benefits of cooperation against the costs of inequality, striving for models of social organization that can reconcile these competing pressures.

This research marks a paradigm shift, highlighting that the quest for cooperation in spatially heterogeneous populations is intrinsically connected with the challenge of managing inequality. As societies become increasingly interconnected and complex, understanding and addressing this interplay will be critical in shaping cooperative frameworks that are not only effective but also fair and inclusive.

Article Title:
Cooperation conflicts with equality when allocating public goods

Article References:
Sheng, A., Su, Q., McAvoy, A. et al. Cooperation conflicts with equality when allocating public goods. Nature (2026). https://doi.org/10.1038/s41586-026-10550-3

Image Credits: AI Generated

DOI:
https://doi.org/10.1038/s41586-026-10550-3