Sadism,the Intuitive System,and Antisocial Punishment in the Public Goods Game

Abstract

In public goods situations, a specific destructive behavior emerges when individuals face the possibility of punishing others: antisocial punishment, that is, costly punishing cooperative individuals. So far, little is known about the (intuitive or reflective) processes underlying antisocial punishment. Building on the Social Heuristics Hypothesis and arguing that antisocial punishment reflects the basic characteristics of sadism, namely, aggressive behavior to dominate and to harm other individuals it is assumed that everyday sadists intuitively engage in antisocial punishment. Two studies document that activating (Study 1) and inhibiting (Study 2) the intuitive system when a punishment option can be realized in one-shot iterated public goods games increased (Study 1) and reduced (Study 2) antisocial punishment, in particular among individuals who reported a proneness to sadism. In sum, the present research suggests that sadistic tendencies executed intuitively play a crucial role regarding antisocial punishment in public goods situations.

Keywords

antisocial punishment intuition punishment sadism social dilemma

Introduction

In social dilemma situations, cooperative behavior benefits the collective but is costly for every single individual involved in the dilemma (e.g., van Lange, Balliet, Parks, & van Vugt, 2014). Accordingly, uncooperative behavior is frequently observed in real-life situations, for instance when farmers overuse public water sources during a drought (cf. Ostrom, 1990), and in laboratory settings (e.g., in a public goods game; Fehr & Gächter, 2002). One prominent solution to increase cooperation in social dilemmas is to establish a system of costly punishment, that is, the option to invest private resources to punish interaction partners (Fehr & Gächter, 2002). In fact, a remarkable amount of empirical evidence has convincingly shown substantial prosocial effects of costly punishment on the individual and collective level of cooperation (cf. Balliet, Mulder, & van Lange, 2011).

Interestingly, when a punishment option is available, not only uncooperative individuals are punished but also cooperative individuals. This latter tendency is termed antisocial punishment. Remarkably, antisocial punishment can be observed across societies (Herrmann, Thöni, & Gächter, 2008). Yet, the emergence of antisocial punishment is extremely puzzling because it stands in contrast to economic self-interest and the notion of punishment as an approach to increase the welfare of the collective (Fehr & Gächter, 2002; Sylwester et al., 2013). Of note, the boundary conditions (such as personality traits or the predominant processing mode) regarding antisocial punishment have been almost completely neglected in research on social dilemmas so far (cf. Dreber & Rand, 2012; Sylwester et al., 2013; van Dijk, Molenmaker, & de Kwaadsteniet, 2015). This gap in knowledge provides the motivation for the present contribution.

Specifically, we aim to illuminate boundary conditions of antisocial punishment from the perspective of motivated social cognition. We first examine whether antisocial punishment is based on the intuitive system¹ or the deliberative system. In this way, we can contribute to an ongoing debate in the field of research on social dilemmas examining whether behavior in social dilemmas is primarily intuitively or deliberatively executed (e.g., Achtziger et al., 2015; Evans, Dillon, & Rand, 2015; Krajbich, Bartling, Hare, & Fehr, 2015; Rand, Greene, & Nowak, 2012; Verkoeijen & Bouwmeester, 2014). In this regard, we integrate the important but largely neglected case of antisocial punishment into the debate. Second, we argue that antisocial punishment reflects the basic characteristics of sadism, namely, aggressive behavior to dominate and to harm other individuals. Accordingly, we examine whether a sadistic orientation is associated with antisocial punishment.

Overall, our approach to examine the associations between the intuitive system, sadistic orientations, and antisocial punishment reflects a step in a new direction and constitutes a contribution to research on social dilemmas that addresses a substantial gap in this field of study. The theoretical notions underlying the present contribution are discussed in the next sections.

The Intuitive System and Behavior in Social Dilemmas

In a series of experiments, Rand and colleagues (Rand & Kraft-Todd, 2014; Rand et al., 2012; Rand et al., 2014) document that conditions fostering the intuitive system (e.g., priming of an intuitive thinking style) increase cooperation whereas conditions that inhibit the intuitive system (e.g., a time delay prior to decisions) decrease cooperation. While some other studies have found contradictory results (e.g., Achtziger et al., 2015; Verkoeijen & Bouwmeester, 2014), Rand’s (2016) meta-analysis of 51 such studies and over 15,000 participants confirmed the positive link between intuition and cooperation. Rand and colleagues (e.g., Rand, 2016; Rand et al., 2012) conclude that cooperation is typically intuitively executed.

The theoretical notion that cooperation should emerge intuitively is grounded in the Social Heuristics Hypothesis (SHH; Rand, 2016; Rand, Brescoll, Everett, Capraro, & Barcelo, 2016; Rand et al., 2014). The SHH postulates that individuals who learned and experienced that cooperation reflects a beneficial strategy in daily life should apply this strategy per default (i.e., intuitively) in new and atypical situations, for instance in the new situation of playing a public goods game in the laboratory. In contrast, individuals who did not learn and experience that cooperation reflects a beneficial strategy in daily life should possess an uncooperative default mode and therefore should not cooperate intuitively in new and atypical situations. In line with the SHH, cooperation is only intuitive for those individuals who learned and experienced that cooperation reflects a beneficial strategy (Capraro & Cococcioni, 2015; Kieslich & Hilbig, 2014; Mischkowski & Glöckner, 2016; Rand et al., 2012; Rand & Kraft-Todd, 2014).

In the present contribution, we assume that individuals who learned and experienced that antisocial tendencies reflect a beneficial strategy should apply this strategy per default (i.e., intuitively) in new and atypical situations. Specifically, we apply the SHH to antisocial punishment and individuals with sadistic tendencies.

Sadism, the Intuitive System, and Antisocial Punishment

The very essence of sadism is that sadists are motivated to dominate and to control other individuals by harming them because they experience pleasure through their cruelty (Cooke, 2001; Dietz, Hazelwood, & Warren, 1990; O’Meara, Davies, & Hammond, 2011). Sadism emerges not only in the clinical but also in the subclinical context (Chabrol et al., 2015), for instance when killing bugs or harming an innocent person (Buckels, Jones, & Paulhus, 2013), when engaging in trolling, a practice that reflects destructive behavior toward innocent others on the internet (Buckels, Trapnell, & Paulhus, 2014), or playing violent video games (Greitemeyer, 2015).

Taking up the notion of antisocial punishment, we argue that the punishment of cooperative others corresponds to the main characteristics of sadism. Specifically, individuals can harm others by engaging in punishment, while punishing cooperative individuals is particularly destructive (Pfattheicher & Schindler, 2015). Additionally, through antisocial punishment one can also control and dominate other individuals in terms of personal states and resources (Sylwester et al., 2013). In line with these considerations, Pfattheicher, Landhäußer, and Keller (2014) showed that antisocial punishment could be predicted by aggressive dominance concerns and the dominance-related hormone testosterone given a relatively low level of cortisol (i.e., the dual hormone hypothesis; Carré & Mehta, 2011; Mehta & Josephs, 2010). Thus, antisocial punishment reflects aggressive behavior to dominate and to harm other individuals which fits the destructive mold of sadism (Pfattheicher & Schindler, 2015). Given that individuals with sadistic tendencies have experienced and learned that aggressive behavior to dominate and to harm other individuals can be beneficial, that is, pleasurable (Baumeister & Campbell, 1999; Baumeister & Vohs, 2004; Fromm, 1973), individuals with sadistic tendencies should, according to the SHH, execute their antisocial tendencies as automatic intuitions. On this basis, it is assumed that individuals with sadistic tendencies intuitively engage in antisocial punishment. This assumption is tested in two studies as reported below. We additionally test whether sadistic motivations in particular and not other antisocial tendencies, for instance the dark triad of psychopathy, narcissism, and Machiavellianism, are related to antisocial punishment (e.g., Jones & Paulhus, 2012).

Study 1

Method

We first assessed individuals’ dispositions to everyday sadism (Buckels et al., 2013; Paulhus & Jones, 2014) as well as individuals’ proneness to psychopathy, narcissism, and Machiavellianism (Jones & Paulhus, 2014). After these assessments, participants read the explanation of a public goods game (Fehr & Gächter, 2002).² Next, participants were randomly assigned to one of three conditions and instructed which thinking style to apply when engaging in punishment (i.e., intuitive vs. reflective vs. no instructions; see below for exact wording). After these instructions, participants played a typical public goods game with the option to costly punish other group members (cf. Fehr & Gächter, 2002).

Sample

Using G*Power (Faul, Erdfelder, Buchner, & Lang, 2009), a power analysis was conducted for a two-tailed t test for a single regression coefficient including six predictors in the model (four main effects, two interactions; see below). Power was set to .80 (Cohen, 1992) and sample size for a medium effect (f² = .09) was calculated. This power analysis revealed a required sample size of n = 45 per condition. We obtained data from 150 individuals (M_age = 22.66; 38.67% women), that is, 50 per condition. Study 1 was conducted at Ulm University, Germany. The subject pool can be classified to “protestant Europe” (Gächter, Herrmann, & Thöni, 2010).

Sadism and dark triad

Dispositional sadism was measured using six items of the Varieties of Sadistic Tendencies Scale (Buckels et al., 2013; Paulhus & Jones, 2014).³ Sample items read “I enjoy hurting people” and “I dominate others using fear” (α = .75, M = 2.49, SD = 0.92). The 27-item Short Dark Triad questionnaire (Jones & Paulhus, 2014) was used to assess narcissism (“I have been compared to famous people”; α = .66, M = 3.76, SD = 0.81), Machiavellianism (e.g., “It’s not wise to tell your secrets”; α = .82, M = 4.00, SD = 1.02), and subclinical psychopathy (e.g., “Payback needs to be quick and nasty”; α = .69, M = 2.79, SD = 0.84). The scale endpoints of all response scales in the present studies were labeled (1) not at all true and (7) completely true.

Public goods game

We investigated antisocial punishment using a standard public goods game with the costly option to punish (cf. Fehr & Gächter, 2002; Pfattheicher & Keller, 2014). As in a typical public goods game, four players constituted one group (cf. Fehr & Gächter, 2002). Each player was endowed with 20 money units (MUs; 1 MU was equal to 3€ cent ~ 3.27 US$ cent) and was free to choose how many of these to keep and how many to contribute to a common group project (i.e., the public good). Each MU contributed was multiplied by 1.6. Next, each player received one fourth of the public good, independent of their contribution. Accordingly, it was always in the material self-interest of every individual within the contribution stage to keep all of his/her MUs irrespective of how much the other three participants contribute to the group project: if every group member invested 20 MUs, each participant would earn (80 × 1.6) / 4 MUs, that is, 32 MUs. If one group member engaged in free riding (e.g., she/he contributes 0 MUs) and the other three group members still invest their 20 MUs, the free rider earns 44 MUs (20 MUs already owned plus one fourth of the public good, that is, 24 MUs) and each of the other three group members earns 24 MUs.

Following this stage, each player was given information on the contributions made by the other three players and was then given the option to punish them by investing his/her own MUs (between 0 and 10 for each player) which reduced the selected other player’s payoff by a factor of three (e.g., the investment of two MUs decreases the payoff of another by six MUs).⁴

Six periods of the public goods game were played under anonymous conditions. All interactions were computer-mediated using z-Tree (Fischbacher, 2007). Participants were explicitly told that the group composition was shuffled from period to period. This excludes direct revenge. Participants were anonymously paid their earnings (M = €3.72 ~ $4.05, SD = 0.61) at the end of the session.

Punishment

To compute antisocial punishment, we counted how often across the six periods participants punished someone who contributed as much as or more than the player himself/herself (cf. Herrmann et al., 2008). We also counted how often participants engaged in the punishment of uncooperative individuals (i.e., how often another player was punished who contributed less than the player himself/herself reflecting costly punishment of non-cooperators).

Conditions

Participants were randomly assigned to the intuition condition (n = 50), reflection condition (n = 50), or control condition (n = 50). In the two experimental conditions (intuition and reflection), after reading the explanation of a public goods game, participants were told that people can make decisions in different ways and the intuitive and reflective thinking mode was briefly explained. In the intuition [reflection] condition, participants read that they should apply the intuitive [reflective] thinking mode when they had the possibility to reduce the other group members’ income. Participants in the intuition condition read right before they could engage in costly punishment “On the next screen we ask you to make your decisions from the gut. That is, rely on your intuition and just follow your predominant feelings.” In the reflection condition, participants read “On the next screen we ask you to think deliberatively about your decision. That is, consider pros and cons and reflect before you make your decision.” In the control condition, participants were given no thinking style instructions. This kind of experimental manipulation was found to be the most effective for affecting cooperation behavior in recent research (see Rand, 2016).

Please note that the manipulation took place before participants could engage in costly punishment, but after the decision how much to contribute to the public good. Thus, there should be no effects on the contribution to the public good.

Results

Preliminary results

To give the reader an impression of the contributions to the public good and antisocial punishment, the descriptive statistics are reported first. The mean number of MUs contributed to the public good across the six periods (maximum 6 × 20 MUs = 120 MUs) was 57.11 MUs (SD = 31.38). Participants engaged, on average, 2.55 times (SD = 3.73) in antisocial punishment. Seventy-eight participants (52.00%) engaged in antisocial punishment at least once. Contribution to the public good and investment in antisocial punishment were negatively correlated (r = −.22, p < .01; see also Pfattheicher & Schindler, 2015). Participants engaged, on average, 3.07 times (SD = 2.89) in punishment of uncooperative individuals. One hundred and fourteen participants (76.00%) engaged in punishment of uncooperative individuals at least once. As in the study of Fehr and Gächter (2002), contribution to the public good and investment in punishment of uncooperative individuals were positively correlated (r = .41, p < .001), reflecting the notion that the more someone contributed, the more uncooperative targets were available that were then punished. Antisocial punishment and the punishment of uncooperative individuals were also slightly positively correlated (r = .13, p = .10), as in previous research (Pfattheicher et al., 2014). In line with Rand and Nowak (2011), we found more antisocial punishment in the very first period than in later periods, speaking to the validity of the present study (see Supplementary Material for detailed results). Sex effects are also provided in the Supplementary Material (women engaged significantly more in punishment, both in punishment of uncooperative individuals and in antisocial punishment). There were no significant main effects of the manipulation on the contribution to the public good, on punishment of uncooperative individuals, or on antisocial punishment (see Supplementary Material for detailed results).

Main results

We report standard ordinary least squares (OLS) regression and also Tobit regression to account for participants scoring zero on antisocial punishment (cf. McDonald & Moffitt, 1980; Pfattheicher & Keller, 2013). The results are displayed in Table 1 and the OLS slopes are plotted in Figure 1.

Table 1.

Regression Coefficients of the Main Analyses in Study 1 (N = 150).

Criterion: Antisocial punishment	OLS regression					Tobit regression
Criterion: Antisocial punishment	B	SE	p value	Lower 95% CI	Upper 95% CI	B	SE	p value
Constant	2.41	0.52	<.001	1.39	3.44	1.76	0.09	<.001
Contribution	−0.03	0.01	<.01	−0.05	−0.01	−0.06	0.02	<.01
Sadism	−0.57	0.51	.26	−1.58	0.43	−1.02	0.94	.28
Dummy 1	0.81	0.74	.27	−0.65	2.26	0.75	1.31	.57
Dummy 2	−0.05	0.73	.94	−1.49	1.39	−0.36	1.30	.78
Sadism × Dummy 1	1.92	0.75	.01	0.39	3.13	3.07	1.37	.03
Sadism × Dummy 2	1.36	0.83	.10	−0.25	2.75	1.96	1.49	.19
Simple slopes: Intuition vs. control
−1 SD sadism	−1.02	1.06	.34	−3.14	1.09	−2.00	1.86	.28
+1 SD sadism	2.73	1.08	.01	0.59	4.88	3.64	1.85	<.05
Simple slopes: Reflection vs. control
−1 SD sadism	−1.18	0.96	.22	−3.11	0.74	−2.05	1.72	.23
+1 SD sadism	1.30	1.00	.20	−0.69	3.29	1.45	1.64	.38

Note. Contribution and sadism are mean centered; reference category dummies: Dummy 1 (codes: 1 = Intuition, 0 = otherwise), Dummy 2 (codes: 1 = Reflection, 0 = otherwise). OLS = ordinary least squares; CI = confidence interval.

Figure 1.

Plotted slopes of Study 1: Antisocial punishment as a function of sadism and the conditions.

The findings revealed one significant interaction, that is, a significant Sadism × Dummy 1 (i.e., intuition vs. control) interaction. Decomposing this interaction (Aiken & West, 1991; Hayes, 2013) revealed a significant effect of the experimental condition, but only when an individual’s disposition for sadism was relatively strong (see Table 1). That is, those with relatively strong sadistic tendencies engaged in antisocial punishment more frequently when the intuitive system was activated (as compared with the control condition).

We want to note that this central finding remains robust in terms of significance level and strength when controlling for psychopathy, narcissism, and Machiavellianism as well as the amount of received punishment and the punishment of uncooperative group members. There was no significant interaction with any of the facets of the dark triad and the conditions. The pattern regarding the predicted interaction (Sadism × Manipulation of Intuition) emerged in both sexes, and was present in the first game period, speaking to the notion that everyday sadists need no provocation to intuitively engage in antisocial punishment (we provide all these analyses in the Supplementary Material).

Furthermore, no significant interaction between sadism and condition emerged when punishment of uncooperative individuals was set as the dependent variable or individuals’ contribution to the public good (ps > .05; for more focused analyses and statistical parameters see Supplementary Material).

In sum, the finding of the first study revealed that the activation (vs. no activation) of the intuitive system stimulated individuals with relatively strong sadistic tendencies to engage more frequently in antisocial punishment.

Study 2

In Study 1, we activated the intuitive system and found an increased frequency of antisocial punishment in individuals with relatively strong sadistic tendencies. In the second study, we flipped this logic. If it is true that antisocial punishment is based on the intuitive system and especially likely executed by individuals with a proneness to sadistic tendencies, then the inhibition of the intuitive system should reduce antisocial punishment in individuals with a proneness to sadistic tendencies. To test this logic appropriately, we ran a male only sample in Study 2 as we expected in male-to-male interactions aggressive dominance motives would likely be activated (Hilton, Harris, & Rice, 2000). In this way, we wanted to increase aggressive dominance motives in the control group which might then be less likely executed by the inhibition of the intuitive system, especially in those individuals most likely to execute aggressive dominance motives, that is, individuals with a proneness to sadistic tendencies.

Method

Participants first read the explanation of the public goods game (Fehr & Gächter, 2002). After these instructions, participants played the game. In the public goods game, participants were randomly assigned to one of two conditions (inhibited intuitive system vs. control; for details see below).⁵

Sample

Using G*Power (Faul et al., 2009), the same power analysis as in Study 1 was conducted (minimum sample size per condition: 45). We obtained data from 129 men (M_age = 21.96). Study 2 was conducted at Ulm University, Germany.

Sadism and dark triad

Dispositional sadism was again measured using six items of the Varieties of Sadistic Tendencies Scale (Buckels et al., 2013; Paulhus & Jones, 2014; α = .68, M = 2.53, SD = 0.97). The 27-item Short Dark Triad questionnaire (Jones & Paulhus, 2014) was again used to assess narcissism (α = .60, M = 3.97, SD = 0.81), Machiavellianism (α = .73, M = 4.15, SD = 0.93), and subclinical psychopathy (α = .59, M = 2.93, SD = 0.83). In this study, sadism and the dark triad was measured after the public goods game.

Public goods game

We used the same paradigm and procedure as in Study 1

Punishment

The same calculations as in Study 1 were applied.

Conditions

Participants were randomly assigned to an experimental condition (inhibited intuitive system; n = 65) or a control condition (n = 64). Participants in both conditions were first given information on the contributions made by the other three players. In the experimental condition, the execution of intuitive behavior was inhibited via a 2-min time delay directly prior to the punishment decision (cf. Rand et al., 2012, and Wang et al., 2011, for this approach). Thus, the execution of intuitive (punishment) behavior was inhibited through the time delay prior to the punishment decision. Wang et al. (2011) showed that a 2.5-min delay was enough to inhibit the intuitive execution of behavior (a 30-s delay was insufficient to show effects). Our approach of 2 min converges to the 2.5 min of Wang et al. (2011). During the 2 min, participants worked on a simple paper–pencil distraction task (linking numbered dots; see Supplementary Material) before they could engage in punishment. The distraction task was necessary to inhibit interfering rumination thoughts (Wang et al., 2011). In contrast, in the control condition, intuitive execution of behavior was possible in that participants could directly punish after they were given information on the contributions made by the other three players.

Please note again that the manipulation only applied to the punishment stage and not to the contribution stage because the time delay was set before participants could engage in costly punishment but not before participants contributed to the public good. Thus, there should be no effects on the contribution to the public good.

Results

Preliminary results

The mean number of MUs contributed to the public good across the six periods (maximum 6 × 20 MUs = 120 MUs) was 64.34 MUs (SD = 31.70). Participants engaged, on average, 1.38 times (SD = 2.74) in antisocial punishment. We again found more antisocial punishment in the very first period than in later periods (see also Rand & Nowak, 2011; detailed results are provided in the Supplementary Material).

Forty-nine participants (38.00%) engaged in antisocial punishment at least once. Contribution to the public good and investment in antisocial punishment were again negatively correlated (r = −.38, p < .001). Participants engaged, on average, 2.95 times (SD = 2.69) in punishment of uncooperative individuals. Ninety-two participants (71.32%) engaged in punishment of uncooperative individuals at least once. Again, contribution to the public good and investment in punishment of uncooperative individuals were positively correlated (r = .25, p < .01). The correlation between antisocial punishment and the punishment of uncooperative individuals was quasi-absent (r = .002, p = .98). There were also no significant main effects of the manipulation on the contribution to the public good, t(127) = 1.62, p = .11, on punishment of uncooperative individuals, t(127) = 0.72, p = .47. There was a significant main effect of antisocial punishment, t(127) = 1.99, p = .05, in that participants engaged less in antisocial punishment in the experimental condition (M = 0.91, SD = 1.73) compared with the control condition (M = 1.86, SD = 3.43). This main effect was qualified by the interaction reported below.

Main results

The results are displayed in Table 2 and the OLS slopes are plotted in Figure 2. The findings revealed a significant Sadism × Condition interaction (inhibited intuition vs. control). Decomposing this interaction (Aiken & West, 1991; Hayes, 2013) revealed a significant effect of the experimental condition, but only when individuals’ disposition for sadism was relatively strong (see Table 2). That is, those with relatively strong sadistic tendencies engaged in antisocial punishment less frequently when the intuitive system was inhibited (as compared with the control condition).

Table 2.

Regression Coefficients of the Main Analyses in Study (N = 129).

Criterion: Antisocial punishment	OLS regression					Tobit regression
Criterion: Antisocial punishment	B	SE	p value	Lower 95% CI	Upper 95% CI	B	SE	p value
Constant	1.46		<.001	1.05	1.86	1.46	0.11	<.001
Contribution	−0.03	−0.39	<.001	−0.05	−0.02	−0.09	0.02	<.001
Sadism	0.54	0.19	.01	0.67	1.81	0.53	0.50	.29
Condition	−0.38	−0.14	.07	−0.79	0.03	−0.44	0.47	.35
Sadism × Condition	−0.70	−0.25	<.01	−2.17	−0.55	−1.24	0.50	.01
Simple slopes: Experimental vs. control
−1 SD sadism	0.30	0.29	.30	−0.28	0.88	0.76	0.70	.27
+1 SD sadism	−1.06	0.29	<.001	−1.64	−0.49	−1.64	0.66	.01

Note. Contribution and sadism are mean centered. OLS = ordinary least squares; CI = confidence interval.

Figure 2.

Plotted slopes of Study 2: Antisocial punishment as a function of sadism and the conditions.

Again, this central finding remains robust in terms of significance level and strength when controlling for psychopathy, narcissism, and Machiavellianism as well as the punishment of uncooperative group members. There was no significant interaction with any of the facets of the dark triad and the conditions (see Supplementary Material). Also, no significant interaction involving sadism and condition emerged when punishment of uncooperative individuals was set as the dependent variable or individuals’ contribution to the public good (for more focused analyses and statistical parameters, see Supplementary Material).

In sum, the finding of the second study revealed that the inhibition (vs. control) of the intuitive system reduces antisocial punishment in individuals with relatively strong sadistic tendencies. This effect was present for antisocial punishment, but not for the punishment of uncooperative individuals. Also, only sadistic tendencies but no other antisocial tendencies (i.e., the dark triad) were significantly related to antisocial punishment.

General Discussion

Whenever humans face the antagonism of benefiting oneself to the disadvantage of the collective, free riding is a potential tragedy (Hardin, 1968). One prominent solution to avoid free riding is to establish a system of costly punishment (Balliet et al., 2011). However, a specific destructive behavior emerges when individuals face the possibility of punishing others: antisocial punishment—the punishment of cooperative individuals. In two studies we could document that activating (Study 1) and inhibiting (Study 2) the intuitive system when punishing in a public goods game increased (Study 1) and reduced (Study 2) the occurrence of antisocial punishment, specifically among individuals who report a proneness to sadism. It is notable that sadism but not the Dark Triad (i.e., narcissism, Machiavellianism, and psychopathy) emerged as crucial moderating factor.

So far, little is known about the boundary conditions and underlying mechanisms of antisocial punishment. In this sense, the current work contributes to a better understanding of antisocial punishment which is quite important given that the analysis of antisocial punishment has been largely neglected so far (cf. Dreber & Rand, 2012; Sylwester et al., 2013; van Dijk et al., 2015).

The reported research findings are remarkable and significant in several respects. First, we can contribute to the current debate discussing whether cooperative and uncooperative behavior in social dilemmas is primarily intuitively or deliberatively executed (e.g., Achtziger et al., 2015; Krajbich et al., 2015; Rand et al., 2012; Verkoeijen & Bouwmeester, 2014). Our results suggest that antisocial punishment is based on the intuitive system, executed by individuals who are motivated to dominate and to harm other individuals.

In this regard, one might ask the interesting question how the present studies’ findings are reconcilable with the findings by Rand and colleagues (Cone & Rand, 2014; Rand & Kraft-Todd, 2014; Rand et al., 2012; Rand et al., 2014). These authors show that conditions which promote the intuitive system increase prosocial behavior (i.e., cooperation) whereas conditions that inhibit the intuitive system decrease prosocial behavior. In contrast, we show that a condition that promotes the intuitive system increase antisocial behavior (i.e., antisocial punishment) whereas conditions that inhibit the intuitive system decrease antisocial behavior. To reconcile these seemingly contrary findings, reference to the SHH can be very fruitful (Rand et al., 2014). The SHH postulates that individuals intuitively apply their deeply grounded knowledge and experiences in new and atypical situations. As individuals in Western countries typically experience a cooperative environment and possess cooperative knowledge structures (Capraro & Cococcioni, 2015; Rand & Kraft-Todd, 2014), they should, according to the SHH, intuitively engage in prosocial behavior, as shown by Rand and colleagues (Cone & Rand, 2014; Rand et al., 2012; Rand et al., 2014). However, individuals who deeply hold antisocial tendencies (such as individuals with a proneness to sadism) should intuitively apply their basic tendencies in new and atypical situations as well—as shown in the present contribution.

These considerations support the theoretical SHH account. Specifically, as the SHH predicts, the findings suggest that activating the intuitive system does not foster prosocial behavior per se. Instead, activating the intuitive system fosters the application of individuals’ default mode (i.e., deeply rooted knowledge, heuristics, dispositions, and experiences). When these are prosocial, activating the intuitive system fosters prosocial behavior (Rand et al., 2012; Rand & Kraft-Todd, 2014; Rand et al., 2014). When these are antisocial, activating the intuitive system fosters antisocial behavior—as shown in the present contribution. As such, the present work also contributes to a better understanding with respect to the question under which conditions the activation of the intuitive system fosters pro- or antisocial behavior. The present research further complements theoretical models on how antisocial punishment evolves (Hauser, Nowak, & Rand, 2014; Rand, Armao, Nakamaru, & Ohtsuki, 2010). From the present findings one can deduce that intuition as well as sadistic dispositions play a crucial role in this regard.

One can further connect the present investigation to research on (prosocial) third-party punishment (Liu, He, & Dou, 2015; Wang et al., 2011; Yudkin, Rothmund, Twardawski, Thalla, & Van Bavel, 2015). This research shows that intuition increases punishment (see Bear & Rand, 2016, for formal modeling of this idea). In line with the present research showing that the antisocial tendency of sadism moderates the relation of intuition and antisocial punishment, one can expect that dispositional prosocial tendencies (e.g., moral concerns; Haidt, 2003) moderate the relation between intuition and punishment in a third-party punishment paradigm. Future research can empirically test this notion.

Second, given that research on antisocial punishment seems still in its infancy, psychosocial boundary conditions that may inhibit the execution of antisocial punishment have hardly been addressed. Herrmann et al. (2008) showed that antisocial punishment is less likely to emerge in societies with relatively strong norms of civic cooperation and an established and functioning judiciary. Bernhard, Fischbacher, and Fehr (2006) showed that antisocial punishment is less likely to emerge when an ingroup member (as compared with an outgroup member) can be punished (see also Goette, Huffman, Meier, & Sutter, 2012). The present contribution documents a boundary condition from a motivated social cognition perspective. Specifically, it is shown that the inhibition of the possibility to intuitively execute behavior reduced antisocial punishment. Thus, the present research also contributes to an understanding of the psychosocial boundary conditions of antisocial punishment and how it might be inhibited.

Third, the present work can also contribute to the theory of (everyday) sadism. Research on sadism in the subclinical context has only recently been established and stimulated specifically by the article of Buckels and colleagues (2013; see also Chabrol et al., 2015). We contribute to this research in that we show a specific behavior that fits the destructive mold of sadism, this is, antisocial punishment. Remarkably, antisocial punishment seems to be sadism-specific given that the facets of the dark triad were not significantly associated with antisocial punishment. Moreover, little is known about the cognitive processes of behavior executed by everyday sadists. We address this gap in that we show that the intuitive system plays a role when everyday sadists engage in evil behavior. In this way, the findings correspond to the notion of intuitive antimoralism, reflecting the intuitive and proactive action of individuals with antisocial dispositions to harm others (Knežević, 2003).

In critically reflecting the current work, we want to discuss the idea that everyday sadists might not only punish cooperative individuals but punish others indiscriminately because they just like to punish. As shown, sadism significantly predicted antisocial punishment but did not significantly predict the punishment of uncooperative individuals. Although one could argue that especially the punishment of cooperative individuals is destructive and particularly fits the destructive mold of sadism, the mentioned findings do not empirically speak against the notion that everyday sadists punish indiscriminately. Non-sadistic individuals also punish uncooperative individuals, for instance for reasons of fairness and equity concerns (Fehr & Gächter, 2002; Pfattheicher et al., 2014). Thus, the statistical variance of punishment of uncooperative others may be “diluted” by non-sadistic individuals and therefore not specifically attributable to sadism. Yet, a look at the correlations involving antisocial punishment and punishment of uncooperative individuals separately among sadists (i.e., participants scoring above the median on the sadism instrument) and non-sadists speaks to the fact that sadists are not indiscriminant in their punishment. If that was the case, one should observe a very strong positive correlation in the sadist subsample but not in the subsample of non-sadists. However, we observed pretty weak correlations in both subsamples, and one correlation in the sadist subsample even turned out negative (in Study 2; see Supplementary Material).

A relevant question for future research is whether the present findings are dependent on individuals’ sex. We found that the interaction regarding the central predicted interaction (Sadism × Manipulation of intuition) emerged in both sexes (see Supplementary Material for the analyses). One must note, however, that the interaction does not reach conventional levels of significance when the analysis is done separately for each sex. However, this can be attributed to a substantially reduced statistical power of these analyses. Future research may consider sex differences in punishment more systematically, also by examining the sex of the punisher, the sex of the punished individual as well as whether punishment occurs more often in within-sex interactions (vs. between-sex interactions). In fact, sex effects are generally a fairly neglected topic in research on social dilemmas.

To conclude, the presented work addressed a substantial gap in the understanding of antisocial punishment in public goods games. Specifically, our analyses suggest that individuals’ intuitive system and sadistic orientations are relevant for antisocial punishment. As such, the present work contributes to a better understanding of this important social phenomenon and opens up a new avenue of research for the study of antisocial punishment in particular and behavior in social dilemma situations in general.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Supplemental Material

The supplemental material is available with the online version of the article.

Notes

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