scholarly journals Constraining free riding in public goods games: designated solitary punishers can sustain human cooperation

2008 ◽  
Vol 276 (1655) ◽  
pp. 323-329 ◽  
Author(s):  
Rick O'Gorman ◽  
Joseph Henrich ◽  
Mark Van Vugt
Keyword(s):  
Public Goods ◽  
Large Scale ◽  
Free Riding ◽  
Single Individual ◽  
Evolutionary Models ◽  
Public Goods Games ◽  
Specific Individual ◽  
Large Groups ◽  
Group Member ◽  
Theoretical Proposal

Much of human cooperation remains an evolutionary riddle. Unlike other animals, people frequently cooperate with non-relatives in large groups. Evolutionary models of large-scale cooperation require not just incentives for cooperation, but also a credible disincentive for free riding. Various theoretical solutions have been proposed and experimentally explored, including reputation monitoring and diffuse punishment. Here, we empirically examine an alternative theoretical proposal: responsibility for punishment can be borne by one specific individual. This experiment shows that allowing a single individual to punish increases cooperation to the same level as allowing each group member to punish and results in greater group profits. These results suggest a potential key function of leadership in human groups and provides further evidence supporting that humans will readily and knowingly behave altruistically.

scholarly journals Cheater-altruist synergy in immunopathogenic ecological public goods games

2017 ◽  
Author(s):  
Bryce Morsky ◽  
Dervis Can Vural
Keyword(s):  
Immune System ◽  
Public Goods ◽  
Free Riding ◽  
Average Growth ◽  
Public Goods Games ◽  
Cheating Behavior ◽  
Long Run ◽  
Population Dynamics Models ◽  
The Cost ◽  
Dynamics Models

AbstractMuch research has focused on the deleterious effects of free-riding in public goods games, and a variety of mechanisms that suppresses cheating behavior. Here we argue that under certain conditions cheating behavior can be beneficial to the population. In a public goods game, cheaters do not pay for the cost of the public goods, yet they receive the benefit. Although this free-riding harms the entire population in the long run, the success of cheaters may aid the population when there is a common enemy that antagonizes both cooperators and cheaters. Here we study models in which an immune system antagonizes a cooperating pathogen. We investigate three population dynamics models, and determine under what conditions the presence of cheaters help defeat the immune system. The mechanism of action is that a polymorphism of cheaters and altruists optimizes the average growth rate. Our results give support for a possible synergy between cooperators and cheaters in ecological public goods games.

scholarly journals Predicting Group Contribution Behaviour in a Public Goods Game from Face-to-Face Communication

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2786 ◽  
Author(s):  
Ehsan Othman ◽  
Frerk Saxen ◽  
Dmitri Bershadskyy ◽  
Philipp Werner ◽  
Ayoub Al-Hamadi ◽  
...  
Keyword(s):  
Facial Expression ◽  
Public Goods ◽  
Facial Expressions ◽  
Free Riding ◽  
Random Forest Classification ◽  
Face To Face ◽  
Public Goods Games ◽  
Facial Expression Analysis ◽  
Forest Classification ◽  
Theoretical Predictions

Experimental economic laboratories run many studies to test theoretical predictions with actual human behaviour, including public goods games. With this experiment, participants in a group have the option to invest money in a public account or to keep it. All the invested money is multiplied and then evenly distributed. This structure incentivizes free riding, resulting in contributions to the public goods declining over time. Face-to-face Communication (FFC) diminishes free riding and thus positively affects contribution behaviour, but the question of how has remained mostly unknown. In this paper, we investigate two communication channels, aiming to explain what promotes cooperation and discourages free riding. Firstly, the facial expressions of the group in the 3-minute FFC videos are automatically analysed to predict the group behaviour towards the end of the game. The proposed automatic facial expressions analysis approach uses a new group activity descriptor and utilises random forest classification. Secondly, the contents of FFC are investigated by categorising strategy-relevant topics and using meta-data. The results show that it is possible to predict whether the group will fully contribute to the end of the games based on facial expression data from three minutes of FFC, but deeper understanding requires a larger dataset. Facial expression analysis and content analysis found that FFC and talking until the very end had a significant, positive effect on the contributions.

scholarly journals The strategy method conflates confusion with conditional cooperation in public goods games: evidence from large scale replications

2021 ◽  
Author(s):  
Maxwell Burton-Chellew ◽  
Victoire D'Amico ◽  
Claire Guérin
Keyword(s):  
Public Goods ◽  
Large Scale ◽  
Social Behaviors ◽  
Conditional Cooperation ◽  
Strategy Method ◽  
Public Goods Games ◽  
Willingness To Cooperate

The strategy method is often used in public goods games to measure individuals’ willingness to cooperate depending on the level of cooperation by others (conditional cooperation). However, while the strategy method is informative, it risks being suggestive and inducing elevated levels of conditional cooperation that are not motivated by concerns for fairness, especially in uncertain or confused participants. Here we make 845 participants complete the strategy method two times, once with human and once with computerized groupmates. Cooperation with computers cannot rationally be motivated by concerns for fairness. Worryingly, 69% of participants conditionally cooperated with computers, whereas only 7% conditionally cooperated with humans while not cooperating with computers. Overall, 83% of participants cooperated with computers, contributing 89% as much as towards humans. Results from games with computers present a serious problem for measuring social behaviors.

scholarly journals Pareto meets Olson – A Note on Pareto-optimality and Group Size in Linear Public Goods Games

ORDO ◽  
2012 ◽  
Vol 63 (1) ◽  
Author(s):  
Michael Pickhardt
Keyword(s):  
Public Goods ◽  
Group Size ◽  
Small Groups ◽  
Pareto Optimality ◽  
Pareto Optimal ◽  
Public Goods Games ◽  
Optimal Allocations ◽  
Large Groups ◽  
The Relationship ◽  
Pareto Optimal Allocations

SummaryIn this paper I examine the relationship between Pareto-optimality and group size in linear public goods games or experiments. In particular, I use the standard setting of homogeneous linear public goods experiments and apply a recently developed tool to identify all Pareto-optimal allocations in such settings. It turns out that under any conceivable circumstances, ceteris paribus, small groups have a higher Pareto-ratio (Pareto-optimal allocations over total allocations) than large groups. Hence, if Pareto-optimality of an allocation is a property that makes such allocations acceptable and maintainable, small groups will find is easier to provide Pareto-optimal amounts of a public good than large groups. This is a novel reasoning for Mancur Olson′s claim, in particular, with respect to what he has termed inclusive goods and inclusive groups.

scholarly journals Noncompliance With Safety Guidelines as a Free-Riding Strategy: An Evolutionary Game-Theoretic Approach to Cooperation During the COVID-19 Pandemic

2021 ◽  
Vol 12 ◽  
Author(s):  
Jose C. Yong ◽  
Bryan K. C. Choy
Keyword(s):  
Public Goods ◽  
Social Dynamics ◽  
Evolutionary Game ◽  
Free Riding ◽  
Theoretic Approach ◽  
Psychological Mechanisms ◽  
Public Goods Games ◽  
The Social ◽  
Evolved Psychological Mechanisms ◽  
Game Theoretic

Evolutionary game theory and public goods games offer an important framework to understand cooperation during pandemics. From this perspective, the COVID-19 situation can be conceptualized as a dilemma where people who neglect safety precautions act as free riders, because they get to enjoy the benefits of decreased health risk from others’ compliance with policies despite not contributing to or even undermining public safety themselves. At the same time, humans appear to carry a suite of evolved psychological mechanisms aimed at curbing free riding in order to ensure the continued provision of public goods, which can be leveraged to develop more effective measures to promote compliance with regulations. We also highlight factors beyond free riding that reduce compliance rates, such as the emergence of conspiratorial thinking, which seriously undermine the effectiveness of measures to suppress free riding. Together, the current paper outlines the social dynamics that occur in public goods dilemmas involving the spread of infectious disease, highlights the utility and limits of evolutionary game-theoretic approaches for COVID-19 management, and suggests novel directions based on emerging challenges to cooperation.

Epistemic Free Riding

2018 ◽  
Author(s):  
Jeffrey Dunn
Keyword(s):  
Problem Solving ◽  
Empirical Evidence ◽  
Free Riding ◽  
Group Problem ◽  
Group Problem Solving ◽  
Division Of Cognitive Labor ◽  
Group Member

Free riding occurs in the practical domain when some action is rational for each group member to perform but such that when everyone performs that action, it is worse overall for everyone. Dunn argues that some surprising empirical evidence about group problem-solving reveals that groups will often face cases where it is epistemically best for each individual to believe one thing, even though this is ultimately epistemically worse for the group that each member believes in this way. Dunn’s work is thus an extension of work on the division of cognitive labor and ways that group inquiry might differ from individual inquiry.

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