Societies can become a conspiratorial society where there is a majority of humans that believe, and therefore spread, conspiracy theories. Artificial intelligence gave rise to social media bots that can spread conspiracies in an automated fashion. Currently, organizations combat the spread of conspiracies through manual fact-checking processes and the dissemination of counter-narratives. However, the effects of harnessing the same automation to create useful bots are not well explored. To address this, we create BotSim, an Agent-Based Model of a society in which useful bots are introduced into a small world network. These useful bots are: Info-Correction Bots, which correct bad information into good, and Good Bots, which put out good messaging. The simulated agents interact through generating, consuming and propagating information. Our results show that, left unchecked, Bad Bots can create a conspiratorial society, and this can be mitigated by either Info-Correction Bots or Good Bots; however, Good Bots are more efficient and sustainable than Info-Correction Bots . Proactive good messaging is more resource-effective than reactive information correction. With our observations, we expand the concept of bots as a malicious social media agent towards automated social media agent that can be used for both good and bad purposes. These results have implications for designing communication strategies to maintain a healthy social cyber ecosystem.
Despite extensive work on the evolution of cooperation, the roles of teaching and leadership in transmitting opaque cultural norms—foundations of cooperative behaviors—are underexplored. Similarly, while teaching is well-studied in the evolution of instrumental culture, little attention is given to its role in transmitting opaque culture, such as social values and norms. Transmitting opaque culture often requires teaching, and group leaders are well-positioned to facilitate this process. Using comparative ethnographic data, we explore teaching, leadership, and instrumental versus opaque culture by examining whether opaque culture is primarily transmitted via teaching, which age groups tend to learn these norms, and whether leaders are disproportionately involved in teaching. Drawing on ethnographic data from 23 egalitarian foraging societies, we find teaching is more strongly associated with transmitting cultural values and kinship knowledge than subsistence skills and is closely linked to opaque culture and leadership. Leader-directed teaching may drive cooperation, suggesting new research avenues. Teaching and leadership are under-studied in connection with the opaque norms that underpin cooperation. The authors show that among egalitarian foragers, influential individuals often pass on these norms, hinting at a possible relationship between leadership and cooperative teaching.
People are keen to exploit cooperative artificial agents for selfish gain. While this phenomenon has been observed in numerous Western societies, we show here that it is absent in Japan. We examined people’s willingness to cooperate with artificial agents and humans in two classic economic games requiring a choice between self interest and mutual benefit. Our participants in the United States cooperated with artificial agents significantly less than they did with humans, whereas participants in Japan exhibited equivalent levels of cooperation with both types of co-player. We found a notable difference in how people felt about exploiting their cooperative partner: people in Japan emotionally treated artificial agents and humans alike, whereas people in the United States felt bad about exploiting humans, but not machines. Our findings underscore the necessity for nuanced cultural considerations in the design and implementation of such technology across diverse societies
Cooperation, the process through which individuals work together to achieve common goals, is fundamental to human and animal societies and increasingly critical in artificial intelligence. Here, we investigated cooperation in mice and artificial intelligence systems, examining how they learn to actively coordinate their actions to obtain shared rewards. We identified key social behavioral strategies and decision-making processes in mice that facilitate successful cooperation. These processes are represented in the anterior cingulate cortex (ACC) and ACC activity causally contributes to cooperative behavior. We extended our findings to artificial intelligence systems by training artificial agents in a similar cooperation task. The agents developed behavioral strategies and neural representations reminiscent of those observed in the biological brain, revealing parallels between cooperative behavior in biological and artificial systems.
Kavindu Warnakulasuriya, P. Dissanayake, Navindu De Silva
et al.
The evolution of cooperation has been extensively studied using abstract mathematical models and simulations. Recent advances in Large Language Models (LLMs) and the rise of LLM agents have demonstrated their ability to perform social reasoning, thus providing an opportunity to test the emergence of norms in more realistic agent-based simulations with human-like reasoning using natural language. In this research, we investigate whether the cooperation dynamics presented in Boyd and Richerson's model persist in a more realistic simulation of the Diner's Dilemma using LLM agents compared to the abstract mathematical nature in the work of Boyd and Richerson. Our findings indicate that agents follow the strategies defined in the Boyd and Richerson model, and explicit punishment mechanisms drive norm emergence, reinforcing cooperative behaviour even when the agent strategy configuration varies. Our results suggest that LLM-based Multi-Agent System simulations, in fact, can replicate the evolution of cooperation predicted by the traditional mathematical models. Moreover, our simulations extend beyond the mathematical models by integrating natural language-driven reasoning and a pairwise imitation method for strategy adoption, making them a more realistic testbed for cooperative behaviour in MASs.
Immigration has shaped many nations, posing the challenge of integrating immigrants into society. While economists often focus on immigrants' economic outcomes compared to natives (such as education, labor market success, and health) social interactions between immigrants and natives are equally crucial. These interactions, from everyday exchanges to teamwork, often lack enforceable contracts and require cooperation to avoid conflicts and achieve efficient outcomes. However, socioeconomic, ethnic, and cultural differences can hinder cooperation. Thus, evaluating integration should also consider its impact on fostering cooperation across diverse groups. This paper studies how priming different identity dimensions affects cooperation between immigrant and native youth. Immigrant identity includes both ethnic ties to their country of origin and connections to the host country. We test whether cooperation improves by making salient a specific identity: Common identity (shared society), Multicultural identity (ethnic group within society), or Neutral identity. In a lab in the field experiment with over 390 adolescents, participants were randomly assigned to one of these priming conditions and played a Public Good Game. Results show that immigrants are 13 percent more cooperative than natives at baseline. Natives increase cooperation by about 3 percentage points when their multicultural identity is primed, closing the initial gap with immigrant peers.
Riccardo Vasellini, Gilda Ferrandino, Luisa Sernicola
et al.
This study intends to test the hypothesis that, contrary to traditional interpretation, the social structure of the polity of Aksum - especially in its early stages - was not characterized by a vertical hierarchy with highly centralized administrative power, and that the leaders mentioned in the few available inscriptions were predominantly ritual leaders with religious rather than coercive political authority. This hypothesis, suggested by the available archaeological evidence, is grounded in Charles Stanish's model, which posits that pre-state societies could achieve cooperative behavior without the presence of coercive authority. Using agent-based modeling applied to data inspired by the Aksum civilization, we examine the dynamics of cooperation in the presence and absence of a Public Goods Game. Results show that while cooperative behavior can emerge in the short term without coercive power, it may not be sustainable over the long term, suggesting a need for centralized authority to foster stable, complex societies. These findings provide insights into the evolutionary pathways that lead to state formation and complex social structures.
Hasrat Efendi Samosir, Md Noor Bin Hussin, Sudianto
et al.
This study explores the Constitution of Medina as an early model of prophetic political communication grounded in consensus, offering a relevant framework for managing diversity and fostering social cohesion in pluralistic societies. Utilizing a qualitative library research method, the study draws upon the primary source—the text of the Constitution of Medina—and integrates secondary literature from the field of political communication. The data were analyzed through content analysis to identify underlying communicative principles and political strategies within the Charter. The findings reveal that the Constitution operationalizes participatory dialogue and peaceful conflict resolution mechanisms, aligning closely with contemporary consensus-based political communication theories. These principles served not only to manage inter-group tensions but also to build a cooperative and just social order. The study concludes that the Constitution of Medina is not merely a historical document but a normative model that offers practical insights into inclusive governance, interfaith cooperation, and the ethical foundations of political discourse. Its relevance is especially significant today, where polarized societies seek coexistence and constructive engagement frameworks. Thus, the Medina Charter is relevant as a prophetic guide for inclusive political communication in multicultural and multireligious contexts. This study contributes to Islamic political thought and communication by providing a normative and historically grounded model for inclusive governance. It bridges classical Islamic sources with contemporary political communication theory, offering a framework applicable to modern pluralistic societies seeking ethical and participatory governance models.
As artificial intelligence (AI) systems are increasingly embedded in our lives, their presence leads to interactions that shape our behaviour, decision-making and social interactions. Existing theoretical research on the emergence and stability of cooperation, particularly in the context of social dilemmas, has primarily focused on human-to-human interactions, overlooking the unique dynamics triggered by the presence of AI. Resorting to methods from evolutionary game theory, we study how different forms of AI can influence cooperation in a population of human-like agents playing the one-shot Prisoner’s dilemma game. We found that Samaritan AI agents who help everyone unconditionally, including defectors, can promote higher levels of cooperation in humans than Discriminatory AI that only helps those considered worthy/cooperative, especially in slow-moving societies where change based on payoff difference is moderate (small intensities of selection). Only in fast-moving societies (high intensities of selection), Discriminatory AIs promote higher levels of cooperation than Samaritan AIs. Furthermore, when it is possible to identify whether a co-player is a human or an AI, we found that cooperation is enhanced when human-like agents disregard AI performance. Our findings provide novel insights into the design and implementation of context-dependent AI systems for addressing social dilemmas.
Play is generally considered an immature affair. However, adult play is present in several mammal species living in complex social systems. Here, I hypothesize that adult social play is favored by natural selection in those species characterized by high level of social tolerance and/or by the need of others' cooperation to reach a goal (i.e., leverage). The integration and comparison of bio-behavioral data on non-human primates and wild social carnivores allows drawing a comprehensive picture on the importance of adult play in facing unpredictable, novel social situations and in overcoming stressful experiences. The ability to cope with potentially competitive interactions through play can favor the emergence of egalitarian societies. A further interesting and beneficial aspect of adult play is its role in synchronizing group activities and favoring collective decision making by renovating the motivation to cooperate in groupmates. As a last step, some considerations about the presence of adult play in the most egalitarian and cooperative human groups (e.g., hunter-gatherer societies) allows discussing the apparent dichotomy between cultural and biological evolution of certain behavioral traits, including social play in adulthood.
The worsening socioeconomic situation of the country has threatened the socioeconomic development of rural communities, necessitating a socioeconomic alternative that will be responsive to rural needs and stimulate sustainable socioeconomic growth. Cooperative societies are alternative strategies that can foster socioeconomic growth at rural levels, thus building on the spirit of cooperation that is domiciled in the rural areas. Cooperative society is a voluntary association of individuals who come together to meet their common economic, social and cultural needs and aspirations. These societies are based on the principles of self-help, democracy, self-responsibility, equality, equity and solidarity. If effectively utilized, cooperatives are vehicles that can bring about sustainable socio-economic development in rural communities especially in times of worsening economic situations. This paper explores cooperative societies as a vehicle that can bring about the needed socioeconomic development in rural areas through, creation of jobs, raising capital for business and alleviation of poverty. The paper adopts the sustainable development theory as its theoretical underpinning. The study found that cooperatives are instrumental in the sustainability of livelihood in rural communities through the provision of credit facilities, assisting small businesses to stay profitable, creation of employment etc. The paper recommends rural dwellers should be adequately sensitized on the importance of cooperatives and should be encouraged to associate with cooperatives so as to derive benefits of cooperatives which can in turn bring about sustainable development.
Abstract Addressing collective issues in social development requires a high level of social cohesion, characterized by cooperation and close social connections. However, social cohesion is challenged by selfish, greedy individuals. With the advancement of artificial intelligence (AI), the dynamics of human–machine hybrid interactions introduce new complexities in fostering social cohesion. This study explores the impact of simple bots on social cohesion from the perspective of human–machine hybrid populations within network. By investigating collective self-organizing movement during migration, results indicate that cooperative bots can promote cooperation, facilitate individual aggregation, and thereby enhance social cohesion. The random exploration movement of bots can break the frozen state of greedy population, help to separate defectors in cooperative clusters, and promote the establishment of cooperative clusters. However, the presence of defective bots can weaken social cohesion, underscoring the importance of carefully designing bot behavior. Our research reveals the potential of bots in guiding social self-organization and provides insights for enhancing social cohesion in the era of human–machine interaction within social networks.
Summary In cooperative societies, group members typically exchange different commodities among each other, which involves an incessant negotiation process. How is the conflict of fitness interests resolved in this continual bargaining process between unequal partners, so that maintaining the cooperative interaction is the best option for all parties involved? Theory predicts that relatedness between group members may alleviate the conflict of fitness interests, thereby promoting the evolution of cooperation. To evaluate the relative importance of relatedness and direct fitness effects in the negotiation process, we experimentally manipulated both the relatedness and mutual behavioral responses of dominant breeders and subordinate helpers in the cooperatively breeding cichlid fish Neolamprologus pulcher. Results show that coercion by breeders is crucial for the performance of alloparental egg care by helpers, but that kinship significantly decreases the need for coercion as predicted by theory. This illustrates the relative importance of kinship and enforcement in the bargaining process.
The confluence of the advancement of Autonomous Vehicles (AVs) and the maturity of Vehicle-to-Everything (V2X) communication has enabled the capability of cooperative connected and automated vehicles (CAVs). Building on top of cooperative perception, this paper explores the feasibility and effectiveness of cooperative motion prediction. Our method, CMP, takes LiDAR signals as model input to enhance tracking and prediction capabilities. Unlike previous work that focuses separately on either cooperative perception or motion prediction, our framework, to the best of our knowledge, is the first to address the unified problem where CAVs share information in both perception and prediction modules. Incorporated into our design is the unique capability to tolerate realistic V2X transmission delays, while dealing with bulky perception representations. We also propose a prediction aggregation module, which unifies the predictions obtained by different CAVs and generates the final prediction. Through extensive experiments and ablation studies on the OPV2V and V2V4Real datasets, we demonstrate the effectiveness of our method in cooperative perception, tracking, and motion prediction. In particular, CMP reduces the average prediction error by 12.3% compared with the strongest baseline. Our work marks a significant step forward in the cooperative capabilities of CAVs, showcasing enhanced performance in complex scenarios. More details can be found on the project website: https://cmp-cooperative-prediction.github.io.
Giorgio Piatti, Zhijing Jin, Max Kleiman-Weiner
et al.
As AI systems pervade human life, ensuring that large language models (LLMs) make safe decisions remains a significant challenge. We introduce the Governance of the Commons Simulation (GovSim), a generative simulation platform designed to study strategic interactions and cooperative decision-making in LLMs. In GovSim, a society of AI agents must collectively balance exploiting a common resource with sustaining it for future use. This environment enables the study of how ethical considerations, strategic planning, and negotiation skills impact cooperative outcomes. We develop an LLM-based agent architecture and test it with the leading open and closed LLMs. We find that all but the most powerful LLM agents fail to achieve a sustainable equilibrium in GovSim, with the highest survival rate below 54%. Ablations reveal that successful multi-agent communication between agents is critical for achieving cooperation in these cases. Furthermore, our analyses show that the failure to achieve sustainable cooperation in most LLMs stems from their inability to formulate and analyze hypotheses about the long-term effects of their actions on the equilibrium of the group. Finally, we show that agents that leverage "Universalization"-based reasoning, a theory of moral thinking, are able to achieve significantly better sustainability. Taken together, GovSim enables us to study the mechanisms that underlie sustainable self-government with specificity and scale. We open source the full suite of our research results, including the simulation environment, agent prompts, and a comprehensive web interface.
Till Weber, Jonathan F. Schulz, Benjamin Beranek
et al.
IZA DP No. 16415 AUGUST 2023 The Behavioral Mechanisms of Voluntary Cooperation across Culturally Diverse Societies: Evidence from the US, the UK, Morocco, and Turkey We examine the role of cooperative preferences, beliefs, and punishments to uncover potential cross-societal differences in voluntary cooperation. Using one-shot public goods experiments in four comparable subject pools from the US and the UK (two similar Western societies) and Morocco and Turkey (two comparable non-Western societies), we find that cooperation is lower in Morocco and Turkey than in the UK and the US. Using the ABC approach – in which cooperative attitudes and beliefs explain cooperation – we show that cooperation is mostly driven by differences in beliefs rather than cooperative preferences or peer punishment, both of which are similar across the four subject pools. Our methodology is generalizable across subject pools and highlights the central role of beliefs in explaining differences in voluntary cooperation within and across culturally, economically, and institutionally diverse societies. Because our behavioral mechanisms correctly predict actual contributions, we argue that our approach provides a suitable methodology for analyzing the determinants of voluntary cooperation of any group of interest. JEL Classification: C9, H4, C7, D2
We investigated the capability of the GPT-3.5 large language model (LLM) to operationalize natural language descriptions of cooperative, competitive, altruistic, and self-interested behavior in two social dilemmas: the repeated Prisoners Dilemma and the one-shot Dictator Game. Using a within-subject experimental design, we used a prompt to describe the task environment using a similar protocol to that used in experimental psychology studies with human subjects. We tested our research question by manipulating the part of our prompt which was used to create a simulated persona with different cooperative and competitive stances. We then assessed the resulting simulacras' level of cooperation in each social dilemma, taking into account the effect of different partner conditions for the repeated game. Our results provide evidence that LLMs can, to some extent, translate natural language descriptions of different cooperative stances into corresponding descriptions of appropriate task behaviour, particularly in the one-shot game. There is some evidence of behaviour resembling conditional reciprocity for the cooperative simulacra in the repeated game, and for the later version of the model there is evidence of altruistic behaviour. Our study has potential implications for using LLM chatbots in task environments that involve cooperation, e.g. using chatbots as mediators and facilitators in public-goods negotiations.
Social capital is one of the influential components in the performance and success of cooperatives, including rural cooperatives, which is considered by experts. The purpose of this study is to investigate the role of social capital in the success of the rural cooperative in Dana women. The method of this research is descriptive-analytic and a questionnaire technique is used to collect information. The statistical population is 600 members of the rural women's rural cooperative in Dena County, according to Bartlett's table, 100 were identified. The questionnaire was the most important tool for collecting data. The results of the questionnaire were analyzed using Spss software. To test the hypothesis, t-test, Pearson correlation coefficient was used. In order to investigate the role of social capital in the success of rural women's cooperatives in Dena, indicators such as social capital, social trust, and social participation were measured. Based on the results obtained from the indicators of social capital research, social trust index the impact on the success of the DENA Women's Co-operative.
Context and purpose. The aim of this study was to find factors affecting the training courses' effectiveness on handmade-carpet cooperatives in Zanjan Province of Iran, the research's type was an applied study in terms of aim and surveying study in terms of data collection.
Methodology/approach. Data collection tool was a researcher made questionnaire. The study population included all members of Handmade-Carpet cooperative of Zanjan province. The number of all Handmade-Carpet cooperatives was 38 including 366 members. Of those members 181 people were selected as the samples through Morgans' sampling table. A proportionate selection method was used to select the fit samples from each cooperative. The validity of the questions was done by experts' views and recommendations. The reliability of the questions was tested through Alpha's test (alpha =0.874 to 0.909).
Findings and conclusions. After gathering data, SPSS software was used to analyze and describe the data. In descriptive part, both frequency tables and central statistics such as mean, median and mode as well as discrepancy statistics such as standard deviation and coefficient of variation were used. In analytical part, correlation and regression analysis methods and Mann-Whitenny and Kruskal- Wallis tests were used. The correlation's results showed that there was a significant relationship between variables attendance into training courses, income's amount from the cooperatives, the level of content relevancy, the level of objectives relevancy, the level of educators' knowledge, the level of training methods relevancy and the the effectiveness of the training courses. In addition, the results of regression analysis by a stepwise method revealed that the variables the level of objectives relevancy, income's amount from the cooperatives, and the level of educators' knowledge were determined 81.6 percent of dependent variable (the training courses' effectiveness).
Originality. Iranian hand-woven carpets have a special place in the economy, now considering the essential role of cooperatives in strengthening Iranian hand-woven carpets, this research examines the important factors affecting the educational effectiveness of these cooperatives.