Collective-risk Social Dilemma Research Articles

Assessing the effects of pandemic risk on cooperation and social norms using a before-after Covid-19 comparison in two long-term experiments

How does threat from disease shape our cooperative actions and the social norms that guide such behaviour? To study these questions, we draw on a collective-risk social dilemma experiment that we ran before the emergence of the Covid-19 pandemic (Wave 1, 2018) and compare this to its exact replication, sampling from the same population, that we conducted during the first wave of the pandemic (Wave 2, 2020). Tightness-looseness theory predicts and evidence generally supports that both cooperation and accompanying social norms should increase, yet, we mostly did not find this. Contributions, the probability of reaching the threshold (cooperation), and the contents of the social norm (how much people should contribute) remained similar across the waves, although the strength of these social norms were slightly greater in Wave 2. We also study whether the results from Wave 1 that should not be affected by the pandemic—the relationship between social norms and cooperation and specific behavioural types—replicate in Wave 2 and find that these results generally hold. Overall, our work demonstrates that social norms are important drivers of cooperation, yet, communicable diseases, at least in the short term, have little or no effects on either.

Evolution of cooperation driven by sampling reward

A social dilemma implies that individuals will choose the defection strategy to maximize their individual gains. Reward is a powerful motivator to promote the evolution of cooperation, thus addressing the social dilemma. Nevertheless, it is costly since we need to monitor all participants in the game. Inspired by these observations, we here propose an inexpensive protocol, a so-called sampling reward mechanism, and apply it to social dilemmas, including public goods game and collective-risk social dilemma. More precisely, the actual usage of reward depends on the portion of cooperators in the sample. We show that the average cooperation level can be effectively improved under high reward threshold and high reward intensity, albeit at the expense of reward cost. It is intriguing to discover that for the latter aspect, there is a critical threshold at which further increases in reward intensity have no significant effect on improving the cooperation level. Moreover, we find that the small sample size favors the evolution of cooperation while an intermediate sample size always results in a lower reward cost. We also demonstrate that our findings are robust and remain valid for both types of social dilemmas.

Evolution of conditional cooperation in collective-risk social dilemma with repeated group interactions.

The evolution and long-term sustenance of cooperation has consistently piqued scholarly interest across the disciplines of evolutionary biology and social sciences. Previous theoretical and experimental studies on collective risk social dilemma games have revealed that the risk of collective failure will affect the evolution of cooperation. In the real world, individuals usually adjust their decisions based on environmental factors such as risk intensity and cooperation level. However, it is still not well understood how such conditional behaviours affect the evolution of cooperation in repeated group interactions scenario from a theoretical perspective. Here, we construct an evolutionary game model with repeated interactions, in which defectors decide whether to cooperate in subsequent rounds of the game based on whether the risk exceeds their tolerance threshold and whether the number of cooperators exceeds the collective goal in the early rounds of the game. We find that the introduction of conditional cooperation strategy can effectively promote the emergence of cooperation, especially when the risk is low. In addition, the risk threshold significantly affects the evolutionary outcomes, with a high risk promoting the emergence of cooperation. Importantly, when the risk of failure to reach collective goals exceeds a certain threshold, the timely transition from a defective strategy to a cooperative strategy by conditional cooperators is beneficial for maintaining high-level cooperation.

Coevolutionary dynamics via adaptive feedback in collective-risk social dilemma game.

Human society and natural environment form a complex giant ecosystem, where human activities not only lead to the change in environmental states, but also react to them. By using collective-risk social dilemma game, some studies have already revealed that individual contributions and the risk of future losses are inextricably linked. These works, however, often use an idealistic assumption that the risk is constant and not affected by individual behaviors. Here, we develop a coevolutionary game approach that captures the coupled dynamics of cooperation and risk. In particular, the level of contributions in a population affects the state of risk, while the risk in turn influences individuals' behavioral decision-making. Importantly, we explore two representative feedback forms describing the possible effect of strategy on risk, namely, linear and exponential feedbacks. We find that cooperation can be maintained in the population by keeping at a certain fraction or forming an evolutionary oscillation with risk, independently of the feedback type. However, such evolutionary outcome depends on the initial state. Taken together, a two-way coupling between collective actions and risk is essential to avoid the tragedy of the commons. More importantly, a critical starting portion of cooperators and risk level is what we really need for guiding the evolution toward a desired direction.

Evolution of cooperation driven by sampling punishment

Punishment is a key incentive to maintain cooperation. But it is costly, hence its effectiveness is under permanent debate. To overcome this difficulty, we here introduce a sampling punishment method and explore its consequences on public goods game and collective-risk social dilemma. In our model, just a small portion of participants are sampled and defectors are punished only if their portion exceeds a certain threshold. We show that the cooperation level can be effectively improved under low punishment threshold and small sample size when the punishment intensity is considerable. To identify the optimal conditions of sampling punishment, we monitor the punishment probability and related cost. We find that the adoption of a low punishment threshold and a small sample size under a considerable punishment intensity is the best, which always leads to a high cooperation level with a low related cost. Our observations are both valid in these two games.

Staring at the Abyss: a neurocognitive grounded agent-based model of collective-risk social dilemma under the threat of environmental disaster

Increasingly visible climate change consequences challenge carbon-based economies worldwide. While expert knowledge on climate change percolates through political initiatives and public awareness, its translation into large-scale policy actions appears limited. Climate change consequences unequally target regions, countries and social classes, a vital issue for social cooperation. When facing an imminent ecological collapse, in which conditions can self-interested agents gain environmental awareness and settle on a sustainable path of actions when their knowledge of the imminent collapse is bounded? This cooperation emerges from the interaction between individuals and the interaction of various cognitive processes within individuals. This article develops an agent-based model for this emergence of cooperation enriched with the Agent Zero neurocognitive grounded cognitive architecture. We investigate when agents endowed with deliberative, affective and social modules can settle on actions that safeguard their environment through numerical simulations. Our results show that cooperation on sustainable actions is the strongest when the system is at the edge of collapse. Policy measures that increase the environment’s resilience become internalized by the agents and undermine awareness of the ecological catastrophe. Depending on the cognitive channels activated, agent behaviors and reactions to specific interventions significantly vary. Our analysis suggests that taking different cognitive channels, deliberative, affective, social, and others into account, significantly impact results. The complexity of agent cognition deserves more attention to assess parameter sensitivity in social simulation models.

Dishonesty as a Collective-Risk Social Dilemma

Dishonesty as a Collective-Risk Social Dilemma

Dishonesty as a Collective-Risk Social Dilemma

Dishonesty as a Collective-Risk Social Dilemma

Evidence from a long-term experiment that collective risks change social norms and promote cooperation

Social norms can help solve pressing societal challenges, from mitigating climate change to reducing the spread of infectious diseases. Despite their relevance, how norms shape cooperation among strangers remains insufficiently understood. Influential theories also suggest that the level of threat faced by different societies plays a key role in the strength of the norms that cultures evolve. Still little causal evidence has been collected. Here we deal with this dual challenge using a 30-day collective-risk social dilemma experiment to measure norm change in a controlled setting. We ask whether a looming risk of collective loss increases the strength of cooperative social norms that may avert it. We find that social norms predict cooperation, causally affect behavior, and that higher risk leads to stronger social norms that are more resistant to erosion when the risk changes. Taken together, our results demonstrate the causal effect of social norms in promoting cooperation and their role in making behavior resilient in the face of exogenous change.

Financial incentives to poor countries promote net emissions reductions in multilateral climate agreements

Financial incentives to poor countries promote net emissions reductions in multilateral climate agreements

Reducing the bystander effect via decreasing group size to solve the collective-risk social dilemma

Collective cooperation is essential to human society, and it exists in many social dilemmas. In the scenario of a collective-risk social dilemma, a group of players have to collectively contribute to a public fund to prevent the tragedy of the commons, such as dangerous climate change, because everybody will lose all their remaining money when the damage happens with a certain probability if the group fails to reach a fixed fundraising target. Yet, it remains largely unclear how the group size affects the probability of reaching the collective target and the mechanism that drives different outcomes of the collective cooperation. Here, we contribute to the literature by exploring the role of group size in the collective-risk social dilemma and the potential underlying mechanism using both model simulations and human experiments. Through simulations we found that the rate of failure for collective cooperation increases for larger groups, along with the arising of bystander effect and a decrease in average contributions, which are confirmed by our experimental observations. We further analyze the patterns of investment behaviors in the experiment setting by categorizing players into cooperators, altruists, and free riders using both a clustering method and a golden standard. We found that altruists who tend to contribute more, rather than cooperators who prefer contributing a fair-share investment, play a crucial role in groups with success outcome in early and/or middle stages of the game. Our results indicate that bystanders are dynamic and their amount depends on the contribution of others. When others contribute less, bystanders also contribute less. If the collective goal is unlikely to achieve, more players choose to be bystanders who strategically contribute less, intriguing the failure of the collective goal. Our findings suggest a potentially effective way to solve the collective-risk social dilemma by reducing the bystander effect through the mechanism design of forming small groups.

Understanding Decisions in Collective Risk Social Dilemma Games Using Reinforcement Learning

Prior research has used reinforcement-learning models to investigate human decisions in choice games. However, research has not investigated how reinforcement-learning models expectancy valence learning (EVL) and prospect valence learning (PVL) would explain human decisions in applied judgment games where people face a collective risk social dilemma (CRSD) against societal problems such as climate change. In CRSD game, a group of players invested some part of their private incomes to a public fund over several rounds with the goal of collectively reaching a climate target, failing which climate change would occur with a certain probability making players lose their remaining incomes. In this article, we propose EVL and PVL models in the CRSD game and calibrate model parameters to aggregate and individual human decisions across four between-subjects information conditions, where half of the players in each condition possessed lesser wealth (poor) compared to the other half (rich). Results showed that model calibration to individual decisions provided a more accurate account compared to the calibration to aggregate decisions and the EVL model was better fit compared to the PVL model across most conditions. Both models outperformed the symmetric Nash model across all conditions. Overall, moderate recency, loss aversion, and exploration drove people’s decisions. We present the implications of our model results for situations involving a CRSD.

The economic interaction between climate change mitigation, climate migration and poverty

Mitigation of anthropogenic climate change takes place against the backdrop of poor countries being most affected by climate change impacts; climate-induced migration is expected to increase in the future. However, the interaction between mitigation, climate migration and poverty has not been investigated explicitly. Here, we represent simultaneous poverty- and climate-induced migration in a laboratory setting, within the collective-risk social dilemma that arises from attempts to avert dangerous climate change. The relatively rich participants try to prevent migration by the relatively poor but in the long run these attempts are unsuccessful because of free-riding among the rich. The rich are willing to increase their effort at averting dangerous climate change when the poor are hit by a climate extreme event exacerbating their poverty. Conversely, the poor are willing to compensate some weaker effort by the rich, as long as the effort by the rich lies above a threshold emerging within the experiment. Poverty increases vulnerability to climate-related shocks and both drive migration decisions. In a laboratory-based economic game, Marotzke et al. find that the rich are unable to prevent migration by the poor, and increase their effort to avert climate change when the poor are hit by a climate event.

Rewarding endowments lead to a win-win in the evolution of public cooperation and the accumulation of common resources

Abstract We consider different resource allocations of rewarding endowments in the collective-risk social dilemma, and we study their impact on the evolution of public cooperation and the accumulation of common resources in structured populations. We assume that if the accumulated resources in the common pool meet the basic demands of everybody in the group, then each group member obtains an equal basic endowment. However, if the resources in the group exceed this sum, then each group member can get an additional rewarding endowment from the common-pool resource. By means of Monte Carlo simulations, we find that the consideration of rewarding endowment is favorable for the evolution of cooperation. But the common resources may be exhausted if the rewarding is too frequent or too generous. Interestingly, we do find a parameter region in the basic endowment and the reward intensity in which cooperation is promoted whilst the common resources are maintained. We introduce a quantitative index to precisely identify this parameter region, and find that such win-win situations for the evolution of cooperation and the maintenance of common resources occur when the basic endowment is low and the reward intensity is intermediate.

Staring at the Abyss: A Neurocognitive Founded Agent Based Model of Collective-Risk Social Dilemma under the Threat of Environmental Disaster

We propose an agent-based model that explores the dynamics of a collective-social risk dilemma, within the framework of a simplified shallow lake model (Scheffer 1998). The agents are endowed with realistic cognitive abilities, building on the Agent Zero framework (Epstein, 2014). Deliberative, affective and social components are behind the agent decisions, accounting for both bounded rationality and the plurality of channels by which dispositions to act and opinions are transmitted. Individual decisions, aggregated over the entire population, may push a shallow lake over a regime shift threshold where a polluted (turbid) state settles in. This multifaceted model allows us to obtain a more precise understanding of the emergent process of cooperation induced by environmental awareness, and in so doing, it helps us understand how to possibly prevent the transition to the polluted state. To that purpose, we consider various cases on the combination of cognitive modules, and different multilayered network topologies in the population of agents. Simulation results, analyzed with novel computational methods, emphasize that environmental awareness is maximized when the socio-environmental system converges to self-organized criticality. Improved natural conditions, such as higher natural pollution decay, does not result in higher awareness as the agents internalize these constraints and are encouraged to pollute more. These results provide an insightful explanation behind the experimental result that more resistant environments (lower probability of collapse) may shelter a less environmentally concerned population, and that cooperation in the context of collective-social risk dilemma is the strongest when the system is at the edge of collapse.

Collective risk social dilemma and the consequences of the US withdrawal from international climate negotiations

International climate negotiations represent an interesting theoretical problem, which can be analyzed as a collective risk social dilemma as well as an n-person bargaining model. The problem is made more complicated by politics due to the differences between: (1) total and per capita emissions; and (2) present-day and cumulative emissions. Here, we use a game theoretic approach in conjunction with the literature on effort-sharing approaches to study a model of climate negotiations based on empirical emissions data. We introduce a ‘fair equilibrium’ bargaining solution and examine the consequences of the United States’ withdrawal from the Paris Agreement. Our results suggest that the collective goal can still be reached but that this requires additional greenhouse gas emissions cuts from other countries, notably, China and India. Given the history of climate negotiations, it is unclear if these countries will have sufficient political will to accept the additional costs created by the US defection.

Collective Risk Social Dilemma: Role of information availability in achieving cooperation against climate change

Behaviour change via monetary investments is a way to fighting climate change. Prior research has investigated the role of climate-change investments using a Collective-Risk-Social-Dilemma (CRSD) game, where players have to collectively reach a target by contributing to a climate fund; failing which they lose their investments with a probability. However, little is known on how variability in the availability of information about players’ investments influences investment decisions in CRSD. In an experiment involving CRSD, 480 participants were randomly assigned to different conditions that differed in the availability of investment information among players. Half of the players possessed a higher starting endowment (rich) compared to other players (poor). Results revealed that investments against climate change were higher when investment information was available to all players compared to when this information was available only to a few players or to no one. Similarly, investments were higher among rich players compared to poor players when information was available among all players compared to when it was available only to a few players or to no one. Again, the average investment was significantly greater compared to the Nash investment when investment information was available to all players compared to when this information was available only to a few players or to no one. We highlight some implications of our laboratory experiment for human decision-making against climate change.

Central governance based on monitoring and reporting solves the collective-risk social dilemma

Monitoring and reporting incorrect acts are pervasive for maintaining human cooperation, but in theory it is unclear how they influence each other. To explore their possible interactions we consider spatially structured population where individuals face the collective-risk social dilemma. In our minimal model cooperator players report defection according to the loss of their interests. In parallel we assume a monitoring institution that monitors all group member and identifies wrong behavior with a certain probability. In response to these feedbacks a sanctioning institution develops punishment schemes by imposing fines on related defector players stochastically. By means of Monte Carlo simulations, we find that the introduction of monitoring and reporting mechanisms can greatly promote the evolution of cooperation and there exists a sudden change of the cooperation level by varying model parameters, which can lead to an outbreak of cooperation for solving the collective-risk social dilemma.

The level of climate-change mitigation depends on how humans assess the risk arising from missing the 2\xb0C target

The established international 2°C target stipulates that global warming should be limited to below 2°C compared with pre-industrial periods; this has emerged as the most prominent interpretation of how to avoid dangerous climate change. The 2°C target was confirmed and made legally binding in the Paris agreement at the “climate summit” (Conference of Parties 21, COP21) in December 2015. But despite agreement on the target, greenhouse-gas emissions are unlikely to fall soon and fast enough to meet the target, raising the question of whether this target needs to be revised or reinterpreted, and also of why there is insufficient cooperation toward emissions reduction despite the risk of dangerous climate change. Previous theoretical and experimental research has suggested that cooperation towards emissions reduction is undermined by uncertainty about the threshold marking the transition to dangerous climate change. However, even if the threshold and hence the location of the target are known precisely, uncertainty ensues because of an unknown risk that arises from missing the collective target. How humans deal with this risk has not been investigated experimentally. Here we investigate how individuals behave under different risk scenarios if a collective target is missed. We perform economics experiments framed as a collective-risk social dilemma and directly examine the extent to which human subjects trade pay-out reduction for risk. We show that a reduced assessed risk arising from missing the collective target leads to reduced contributions towards the target; but that risk reduction causes the subjects almost to maximize their individual pay-out by balancing the effort to reach the target against the risk posed by missing it. We provide quantitative support for the argument that group contributions toward the collective target can be interpreted as proportional to mitigated warming. We conclude that reinterpretation of the 2°C target as less strict causes additional warming. However, our subjects deal effectively with a risk of dangerous climate change that they assess to depend gradually on global warming. Our results suggest that, if the additional warming is judged to be acceptable, a less strict interpretation of the 2°C target might support finding a trade-off between the effort put into climate mitigation and the risk of dangerous climate change.

Humans choose representatives who enforce cooperation in social dilemmas through extortion.

Social dilemmas force players to balance between personal and collective gain. In many dilemmas, such as elected governments negotiating climate-change mitigation measures, the decisions are made not by individual players but by their representatives. However, the behaviour of representatives in social dilemmas has not been investigated experimentally. Here inspired by the negotiations for greenhouse-gas emissions reductions, we experimentally study a collective-risk social dilemma that involves representatives deciding on behalf of their fellow group members. Representatives can be re-elected or voted out after each consecutive collective-risk game. Selfish players are preferentially elected and are hence found most frequently in the ‘representatives' treatment. Across all treatments, we identify the selfish players as extortioners. As predicted by our mathematical model, their steadfast strategies enforce cooperation from fair players who finally compensate almost completely the deficit caused by the extortionate co-players. Everybody gains, but the extortionate representatives and their groups gain the most.