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British Journal of Psychology (2014) © 2014 The British Psychological Society www.wileyonlinelibrary.com
Beliefs in moral luck: When and why blame hinges on luck Heather C. Lench*, Darren Domsky, Rachel Smallman and Kathleen E. Darbor Department of Psychology, Texas A&M University, College Station, Texas, USA Belief in moral luck is represented in judgements that offenders should be held accountable for intent to cause harm as well as whether or not harm occurred. Scores on a measure of moral luck beliefs predicted judgements of offenders who varied in intent and the outcomes of their actions, although judgements overall were not consistent with abstract beliefs in moral luck. Prompting participants to consider alternative outcomes, particularly worse outcomes, reduced moral luck beliefs. Findings suggest that some people believe that offenders should be punished based on the outcome of their actions. Furthermore, prompting counterfactuals decreased judgements consistent with moral luck beliefs. The results have implications for theories of moral judgement as well as legal decision making.
Two men stand at the middle of a highway overpass. Each man plans to toss a brick down onto traffic below and realizes that the brick could kill someone. On this particular overpass, cars below are not visible because a wall blocks the view. Thus, the men have to throw their bricks without being able to see the traffic. Red sprays his brick red, and Green sprays his brick green. They throw their bricks over the wall. One brick hits the pavement, breaking into harmless pieces. The other smashes through a car roof, and kills someone instantly. The two men are arrested. Obviously these two men are worthy of blame – their actions put others at risk of harm. But are they equally blameworthy? Put another way, to recommend punishment for each man, do you need to know the colour of the brick that killed someone? If you need to know the colour, your judgement reflects a belief in moral luck. If you do not need to know the colour, your judgement does not reflect a belief in moral luck. The focus of this investigation was on two unresolved questions regarding moral luck beliefs: (1) do abstract beliefs in moral luck predict judgements in scenarios that vary in intent and outcome of a perpetrator? and (2) can judgements consistent with belief in moral luck, that weight outcome more than intent, be altered by people’s focus during judgement?
The concept of moral luck beliefs Moral luck beliefs are demonstrated when judgements of blameworthiness hinge not just on whether or not harm was intended, but on the outcome of whether or not harm
*Correspondence should be addressed to Heather C. Lench, Department of Psychology, Texas A&M University, College Station, TX 77843-4235, USA (email: [email protected]). DOI:10.1111/bjop.12072
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occurred (Nagel, 1993; Smith, 1759).1 Accordingly, blame is incurred with actions that risk taking innocent life, and additional blame is incurred if actions result in loss of innocent life. Thus, although Red and Green both incurred blame when they threw their bricks, one of these men is more blameworthy because his brick killed someone. The belief in moral luck is incorporated in many legal systems, with punishments more severe if harm occurs than if it does not. Non-belief in moral luck is demonstrated when judgements of blameworthiness hinge on commission of negligent actions regardless of actual outcome. All that matters is whether a negative outcome could have occurred given the actions taken. Thus, Red and Green are equally morally blameworthy and deserve equal punishment because their actions introduced foreseeable risk of negative outcomes. According to this perspective, the colour of the killer brick is purely a matter of (morally irrelevant) luck. Note that these arguments can also be applied to people who unintentionally cause negative outcomes, such as a driver who runs over someone through no fault of his own (Williams, 1993). Beliefs in moral luck dictate that this person be held accountable for the outcome, whereas a non-belief in moral luck dictates that this person is not blameworthy because the negative outcome could not have been foreseen.2 Most people do not strictly adhere to either of these opposing viewpoints. On the contrary, belief in moral luck appears to vacillate depending on specific circumstances. When asked if blameworthiness should ever hinge on the luck of how things turn out, people indicate that they do not believe in moral luck (90% disagree; Nichols, 2009). In other words, as a matter of abstract principle, most people uphold that blaming people according to how lucky they are is morally inappropriate. However, when faced with actual positive or negative outcomes of actions taken by another, people’s judgements reflect belief in moral luck and they judge others to be more blameworthy if actions resulted in negative outcomes than if, by luck, their actions caused no harm (Cushman, 2008; Cushman, Dreber, Wang, & Costa, 2009; Young, Nichols, & Saxe, 2010). These findings suggest that people decry belief in moral luck in principle, but often exhibit it in judgements about specific circumstances. This apparent paradoxical behaviour has not been empirically addressed and, as a result, it is unclear whether people can report on moral luck beliefs.
STUDY 1 Study 1 focused on establishing whether self-reported belief in moral luck corresponded to judgements about protagonists whose actions did or did not result in harm. To reduce additional factors that might influence judgement, we selected vignettes that included acts that most people were unlikely to have committed, acts that were clearly malicious or not, and acts with clear harm.
1 Philosophers have identified four kinds of moral luck, including resultant (which outcome follows), constitutive (an individual’s characteristics), causal (circumstances that affect actions), and circumstantial luck (the types of situations that one faces; Nagel, 1993). In the present investigation, we refer to resultant as moral luck for simplicity. 2 Luck is commonly defined as something experienced to the extent that a person cannot control or foresee which particular outcome out of a set of possible outcomes will follow an action (Domsky, 2004). Although luck is sometimes defined more broadly, we focus on the specific definition and situations in which potential danger can be foreseen. Also, philosophers disagree about whether agents must act negligently to be seen as having good or bad moral luck. Some believe that good or bad moral luck can only befall negligent agents (Domsky, 2004), and others disagree (Statman, 2005). Because restricting moral luck is controversial, we assume, here, that forseeability and negligence may not be required.
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Method Undergraduates (n = 70; Mage = 18.97; 56% women) participated for partial course credit. Participants read scenarios developed from philosophical discussions of moral luck beliefs. Participants received three scenarios, in random counterbalanced order (there were no order effects, ps > .30) that varied in intent of the protagonist and the outcome. These scenarios were presented interspersed with nine other similar descriptions, to reduce the salience of target scenarios. The Intent-Negative scenario read: “A man decides to risk people’s lives by walking to the middle of a freeway overpass and throwing a brick down onto the freeway below. He realizes that a falling brick might go through the roof of a passing car and kill someone, but goes ahead anyway. A tall cement wall blocks his view, and so he has no idea where the cars are. He only knows that the cars are down below, and so throws the brick over the cement wall and down onto the freeway below. As it turned out, the brick went through a car roof and killed someone instantly.” The Intent-Neutral scenario was identical except that the brick fell harmlessly. The Nointent-Negative scenario was identical except that a man on a walk rested against the wall, accidentally causing a brick to fall and kill someone. A Nointent-Neutral condition was not included because it was expected that this person would be considered not at all blameworthy. Supplemental materials contain these vignettes. Participants then judged how blameworthy the man was on scales ranging from not at all (1) to extremely (7). They also recommended punishment for the protagonist on scales with nine response points (no punishment, small fine, large fine, probation, less than 2 years in prison, between 2 and 5 years in prison, over 5 years in prison, life sentence, death sentence). Finally, participants responded to ten items created to measure moral luck beliefs, based on a philosophical definition of moral luck belief (see Appendix). Participants rated the extent to which they agreed with statements on scales ranging from strongly disagree (1) to strongly agree (7) (a = .88).
Results and discussion An ANOVA with blame judgements for each scenario (Intent-Negative, Intent-Neutral, Nointent-Negative) as the within-subject factor revealed an effect of scenario, F (2,134) = 154.78, p < .001, g2 = .70. Consistent with moral luck theory, participants held the protagonist who intended and caused harm to be more blameworthy (M = 6.54, SD = 0.91) than the protagonist who intended harm but nothing happened (M = 5.68, SD = 1.57), t(68) = 5.63, p < .001, d = 1.37, and the protagonist who did not intend harm but caused a negative outcome (M = 2.50, SD = 1.60), t(67) = 16.35, p < .001, d = 3.99. Participants also held the protagonist who intended harm but nothing happened to be more blameworthy than the protagonist who did not intend harm but caused a negative outcome, t(67) = 10.59, p < .001, d = 2.59. A similar analysis for punishment recommendations3 revealed an effect of scenario, F(2,134) = 188.20, p < .001, g2 = .74. As depicted with the means reported in 3 The punishment scale used is technically ordinal rather than interval because, although punishments were listed in order of increasingly severe consequences, the intervals between response points are not equal for the scale. Note, however, that almost all scales used in psychological research use arbitrary metrics in which the exact difference between points on a scale are unknown but assumed to reflect interval scales during analysis, with few problems for internal reliability or interpretation (Blanton & Jaccard, 2006). Analyses were conducted treating this scale as an ordinal or an interval scale and both sets of analyses yielded consistent results across studies. For simplicity and to keep analyses consistent for blame and punishment judgements, analyses that treat the scale as interval are reported in the text.
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Punishment RecommendaƟon
8 7 6 5 4 3 2 1 Intent,Harm
Intent,NoHarm
No Intent,Harm
Figure 1. Means (SE) for punishment recommendations in study 1.
Figure 1, contrasts revealed that, consistent with blame judgements, participants recommended the most intense punishment for the protagonist who acted intentionally and caused a negative outcome, compared with the protagonist who acted intentionally but nothing happened, t(68) = 16.66, p < .001, d = 4.04, and the protagonist who did not intend harm but caused a negative outcome, t(67) = 16.97, p < .001, d = 4.15. Participants also recommended less punishment for the protagonist who did not intend harm but caused a negative outcome compared with the protagonist who intended harm but nothing happened, t(67) = 5.82, p < .001, d = 1.42. Participants made judgements consistent with a belief in moral luck, with protagonists judged to be more blameworthy and deserving of more punishment if malevolent actions resulted in a negative outcome. These findings also support the additive nature of blame assigned for intent and outcome, such that either malevolent intent or a negative outcome resulted in some blame, but the combination of intent and a negative outcome was regarded as particularly blameworthy. Composite scores on the measure of belief in moral luck ranged from 1 to 6.3, with an overall mean of 2.94 and a standard deviation of .95, suggesting that there was variation in the degree to which participants endorsed moral luck beliefs. Comparison of the mean score to the neutral mid-point of the agreement scale indicated that, on average, participants rated that they did not agree with moral luck beliefs that people should be punished based on outcome rather than on intent, t(69) = 9.32, p < .001. Indeed, 88.6% of participants had an average rating below the mid-point of the scale, indicating that they did not believe in moral luck, while 11.4% had an average rating at or above the mid-point of the scale, indicating that they did believe in moral luck and that people should be punished based on outcomes rather than intent. To examine the relationship between explicit beliefs in moral luck and a tendency to judge others based on intent or outcome, difference scores were created for scenario judgements. Two difference scores represented the difference in blame and punishment judgements based on intent only (Intent-Negative minus Nointent-Negative) and two difference scores represented the difference in blame and punishment judgements based on outcome only (Intent-Negative minus Intent-Neutral). Explicit beliefs in moral luck did not relate to blame or punishment judgements for scenarios that differed in intent only, r(68) = .18, p = .14, and r(68) = .09, p = .46, respectively. Explicit beliefs in moral luck did relate to judgements for scenarios that differed in outcome only. Greater beliefs in moral luck predicted relatively more blame for the protagonist who intentionally caused a negative outcome compared with the protagonist with negative intent but
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who did not cause a negative outcome, r(69) = .41, p < .001. This relationship was similar for punishment recommendations of these two protagonists, r(69) = .35, p = .004. Thus, self-reported beliefs in moral luck correlated as would be expected with judgements of blame and punishment. Participants’ self-reported belief in moral luck predicted their tendency to blame and punish a malevolent protagonist who caused a negative outcome more than an equally malevolent protagonist who did not cause a negative outcome. This study is the first to demonstrate that participants vary in their endorsement of moral luck beliefs and that their endorsement predicts actual judgements. It suggests that, for at least some people, judgements consistent with moral luck beliefs may arise from consciously accessible attitudes.
STUDY 2 Study 1 revealed that (1) participants self-reported on average that they do not believe in moral luck, but their judgements reflected these beliefs; however, (2) despite this disconnect between beliefs and judgements, variability in self-reported beliefs in moral luck predicted judgements. Studies 2 and 3 focused on the possibility that additional consideration of outcomes might reduce the discrepancy between attitudes against moral luck beliefs and judgements consistent with moral luck beliefs. Imagining alternative outcomes that are either better (i.e., upward counterfactual thoughts) or worse (i.e., downward counterfactual thoughts) may influence participants’ judgements. Upward counterfactuals are frequently activated by a negative outcome (Roese & Hur, 1997; Roese & Olson, 1997). Compared with the imagined alternative, the actual negative outcome may seem even worse and increase judgements of blame, responsibility, and victim compensation accordingly (Macrae, 1992; Macrae & Milne, 1992; Wells & Gavanski, 1989). Although less common, downward counterfactuals can also be triggered after some negative events, as in ‘near miss’ situations (Markman & McMullen, 2003). A salient negative alternative outcome could increase perceptions of blame, especially in situations in which the perpetrator had intent but narrowly missed the negative outcome. In Study 2, we hypothesized that people would be more likely to base judgements on the intent of the protagonist to the extent that they focused on negative outcomes that might have been. Because we were also interested in tendencies to consider different types of outcomes based on the scenario (i.e., would a near miss situation prompt more downward counterfactuals?), participants were not directed to consider particular outcomes.
Method Undergraduates (n = 170; 64.1% women) completed the study for course credit. The method was similar to that employed in Study 1, in that participants made judgements of blame and recommended punishments for the protagonist in the brick vignette and then completed the measure of moral luck beliefs. However, Study 2 utilized a between-subject design with participants randomly assigned to a 3(scenario) 9 2(writing focus) design, in part because the order in which scenarios are presented may affect judgements. Each participant saw only one of the scenarios (Intent-Negative, Intent-Neutral, Nointent-Negative). Participants were also assigned, before making their judgements, to write a brief response to each vignette that focused on ‘how things might have ended differently in this story’ (Counterfactual condition) or the ‘motivations of the person in this story’ (Motivation condition). The motivation condition was selected as a control
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because it involved participants writing about and thinking about the scenario, as in the counterfactual condition, but the focus was not on the outcome of the scenario. This condition was considered a conservative control, because, if anything, it should have increased thoughts about the intent of the protagonist and thus decreased a reliance on outcome information relative to intent. Thus, showing that considering counterfactuals had an impact above and beyond this control condition would support the impact of counterfactuals on judgement relative to other cognitions that should increase the salience of intent information. Written responses were coded for counterfactual content by two independent judges. They were instructed to code a response as a counterfactual only when there was clear evidence that an alternative to reality had been considered (j = .76; 95% CI: .70–.81; 88% agreement). Additionally, each counterfactual response was also coded as to whether it contained an upward counterfactual (better alternative) or downward counterfactual (worse alternative) (j = .88; 95% CI: .82–.96; 95% agreement). Discrepancies between judges were resolved by a third judge.
Results and discussion Preliminary analyses Those in the counterfactual conditions wrote more counterfactuals (M = 2.41, SD = 1.63) than those in the motivation condition (M = .15, SD = .66), t(168) = 10.49, p < .001, d = 1.62. Thus, the manipulation of writing focus was effective. Results from all analyses remain identical if the six participants in the motivation condition who wrote a counterfactual thought were excluded; therefore, all participants were retained in analyses. There was a significant interaction between scenario and type of counterfactual, F(1,167) = 26.64, p < .001, g2 = .24. Participants generated more upward counterfactuals than downward counterfactuals for a protagonist who intended and caused harm, Mup = 1.02, Mdown = .18, t(54) = 4.57, p < .001, and a protagonist who did not intend but caused harm, Mup = 0.98, Mdown = .14, t(57) = 4.92, p < .001. For a protagonist who intended but did not cause harm, participants generated more downward counterfactuals (M = 0.98, SD = 1.51) than upward counterfactuals (M = .16, SD = .46), t(56) = 4.05, p < .001.
Judgements of blame and punishment An ANOVA was conducted with scenario (Intent-Negative, Intent-Neutral, NointentNegative) and writing focus (Counterfactual, Motivation) as the between-subjects factors and blame judgements as the dependent variable. There was a main effect of writing focus, F(1,163) = 4.63, p = .03, g2 = .03, and a main effect of scenario, F(2,163) = 153.45, p < .001, g2 = .65, but this main effect was subsumed by an interaction between writing focus and scenario, F(2,163) = 6.02, p = .003, g2 = .07. Contrasts revealed that writing focus did not impact blame judgements for the protagonist who intended and caused harm (Mcounter = 6.36, SD = 0.83; Mmotive = 5.85, SD = 1.29), t(53) = 1.73, p = .09, d = .48. Writing focus also did not impact judgements for the protagonist who did not intend harm but caused a negative outcome (Mcounter = 2.52, SD = 1.16; Mmotive = 2.93, SD = 1.20), t(55) = 1.33, p = .19, d = .36. Counterfactual writing did influence judgements of the protagonist who intended but did not cause harm. In this scenario, participants judged the protagonist to be more blameworthy when they wrote about how
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9 Counterfactual
Punishment ReccomendaƟons
8
MoƟvaƟon 7 6 5 4 3 2 1 Intent,Harm
Intent,NoHarm
No Intent,Harm
Figure 2. Means (SE) for punishment recommendations in study 2.
the scenario might have ended differently (M = 6.19, SD = 0.83) than about his motivations (M = 5.17, SD = 1.26), t(55) = 3.55, p = .001, d = .96. Furthermore, if participants wrote about how the scenario might have ended differently, they judged the protagonist who intended harm but did not cause a negative outcome to be as blameworthy as the protagonist who intended harm and caused a negative outcome, t (53) = .77, p = .45, d = .21. In other words, participants’ judgements were influenced by intent rather than whether or not the negligent act happened to result in a negative outcome when they wrote counterfactual statements. A similar analysis was conducted with punishment recommendations as the dependent variable. There was no main effect of writing focus, F(1,164) = 1.97, p = .16, g2 = .01. There was a main effect of scenario, F(2,164) = 95.84, p < .001, g2 = .54, but this main effect was again subsumed by an interaction between writing focus and scenario, F(2,164) = 5.86, p = .003, g2 = .07. As depicted with the means in Figure 2, contrasts revealed that punishment recommendations were marginally harsher for the protagonist who intended and caused harm if participants wrote about how the scenario might have ended differently than if they wrote about the motivations of the protagonist, t(53) = 1.95, p = .06, d = .54, although judgements were less harsh than in other studies. For the protagonist who did not intend but caused a negative outcome, punishment recommendations were marginally less if participants wrote about how the scenario might have ended differently than if they wrote about the motivations of the protagonist, t(56) = 1.80, p = .08, d = .48. Consistent with the findings for blame judgements, punishment recommendations were harsher for the protagonist who intended but did not cause harm if participants wrote about how the scenario might have ended differently compared with the motivations of the protagonist, t(55) = 2.60, p = .01, d = .70. Thus, writing counterfactuals reduced the presence of moral luck in judgements, consistent with rational accounts of moral decision making, and judgements were more influenced by intent than whether or not a negative outcome happened to occur.
Consideration of counterfactuals We did not direct participants to consider particular types of counterfactuals in Study 2, but hypothesized that participants would hold the protagonist who intended but did not cause harm to be more blameworthy when they considered how the situation could have
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ended in a negative outcome. Preliminary analyses confirmed that the number of upward counterfactuals did not predict blame judgements or punishment recommendations and these counterfactuals are not considered further. To explore the possibility that downward counterfactuals might explain differences in blame among scenarios, we conducted analyses with the coded number of downward counterfactuals. An ANOVA, including the counterfactual conditions only, with scenario as the between-subjects factor and downward counterfactuals as the dependent variable, confirmed that the number of counterfactuals varied by scenario, F(2,80) = 20.30, p < .001, g2 = .34. Post-hoc contrasts revealed that more downward counterfactuals were produced in the scenario with a protagonist who intended but did not cause harm (M = 1.78, SD = 1.55) than a protagonist who intended and caused harm (M = 0.36, SD = 0.56), t(32.41) = 4.48, p < .001, d = 1.56 (unequal variances resulted in a change in dfs), and a protagonist who did not intend but caused harm (M = 0.25, SD = 0.52), t(31.54) = 4.86, p < .001, d = 1.72. The number of downward counterfactuals produced did not differ between scenarios with a protagonist who intended and caused harm compared with a protagonist who did not intend but caused harm, t(54) = 0.74, p = .46, d = .20. Self-reported beliefs in moral luck did not predict the number of counterfactuals generated overall or for any particular scenario, all ps > .29. Could downward counterfactuals account for harsher judgements in the counterfactual versus motivation conditions as predicted? To find out, we conducted a mediation analysis (Hayes, 2013; 5,000 samples), with writing condition as the IV, blame judgements as the DV, and downward counterfactuals as the mediator, R2 = .11, F(1,167) = 20.68, p < .001. The direct effect of writing condition on blame judgements (b = .66, t = 4.55, p < .001) was reduced when counterfactuals were included (b = .17, t = .58, p = .56). There was also a significant indirect effect of .55 (SE = .10), which was significant because the confidence interval did not include zero (95% CI: .10–.50), revealing that writing condition influenced blame through the number of counterfactuals generated. An analysis with punishment recommendations yielded similar findings. Thus, the number of downward counterfactuals considered accounted for harsher judgements.
Self-reported beliefs in moral luck Composite scores on the measure of belief in moral luck ranged from 1 to 6.4, with an overall mean of 2.88 and a standard deviation of .81, strikingly similar to the descriptives reported in Study 1. Comparison of the mean score to the neutral mid-point of the agreement scale (4) indicated that, on average, participants reported that they did not agree with moral luck beliefs, t(169) = 18.04, p < .001. Indeed, 91.2% of participants had an average rating below the mid-point of the scale, indicating that they did not believe in moral luck, while 8.8% had an average rating above the mid-point of the scale, indicating that they did believe in moral luck (that people should be punished based on outcomes rather than intent). Greater belief in moral luck (that people should be punished based on outcome) again predicted less blame of the protagonist who intended but did not cause harm, b = .28, t = 2.20, p = .03. Self-reported beliefs again did not predict blame of the protagonist who intended and caused harm, b = .24, t = 1.78, p = .08, or the protagonist who did not intend but caused harm, b = .05, t = 0.40, p = .69. Self-reported beliefs did not predict punishment recommendations. This finding suggests that participants self-reported beliefs partially predicted their blame judgements in a scenario where moral luck beliefs
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are especially relevant. Consistent with our prediction that consideration of counterfactuals should make judgements more congruent with abstract beliefs in moral luck, there was a greater correlation between self-reported belief in moral luck and blame judgements of the protagonist with intent but who did not cause harm in the counterfactual condition (r = .38) than the motivation condition (r = .20).
STUDY 3 Study 2 suggested that participants who focused on how the situation might have ended badly made harsher judgements of the protagonist who intended to cause harm but, through luck, his actions did not result in harm. These judgements were more congruent with participants’ self-reported denial of moral luck (such denial should result in punishing offenders for negligent acts rather than harmful outcomes) and rational standards for judgements in which luck should not influence blame. However, participants in Study 2 were prompted to consider how the situation could have ended differently and were not specifically prompted to consider how the outcome could have been better or worse than it actually was. This resulted in relatively low levels of downward counterfactuals across scenarios. In Study 3, therefore, we explicitly instructed participants to make upward counterfactuals, downward counterfactuals, or neutral semifactuals (statements of how the outcome would remain the same; McCloy & Byrne, 2002), to examine the impact of such thoughts on judgements.
Method Participants (n = 314; 56% women) completed the study for course credit. The method was similar to that employed in previous studies, in that participants made judgements of blame and recommended punishments for the protagonist in the brick vignette, then reported their beliefs in moral luck. Study 3 utilized a between-subject design with participants randomly assigned to receive one of four scenarios (Intent-Negative, Intent-Neutral, Nointent-Negative; Nointent-Neutral). This latter condition, where the protagonist did not intend harm (i.e., leaned on a wall and the brick accidentally fell) and did not cause harm (i.e., the brick fell harmlessly to the ground), was included primarily to allow a fully crossed design that would estimate the impact of intent and negative outcome between the scenarios. Participants were also assigned to write one of three brief responses to each vignette for 3 min before making their judgements. This writing focused on upward counterfactuals, downward counterfactuals, or neutral semifactuals. In the upward counterfactuals conditions participants were instructed, “people often have thoughts like ‘if only. . .’ after events, in that they can see how things might have turned out better. For example, a woman who recently sustained minor injuries in an accident told reporters, ‘If only I had checked the machine a second time, I would’ve been fine. Also, I wish I hadn’t been so distracted, because then I would have been fine.’ Often, we wish we could change things to avoid outcomes. Focusing on the situation you just read about the man on the freeway overpass, use the next page to list some changes that would have, in retrospect, improved the outcome of this particular situation. Each thought you list should complete one of these phrases: ‘if he had ___ the outcome would have been better’ or ‘if he had NOT ___ the outcome would have been better.” The instructions for downward counterfactual conditions were similar (see online supplemental materials for full wording) except that
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participants were instructed that people often have thoughts about how things might have turned out worse, and they were asked to complete one of these phrases: ‘if he had ___ the outcome would have been even worse’ or ‘if he had NOT ___ the outcome would have been even worse.’ The instructions for the neutral semifactuals were also similar except that participants were instructed that people often have thoughts about how things would have ended similarly, and they were asked to complete the phrase: ‘Even if he had ___ the outcome would still have been the same.’ After writing the counterfactual statements, participants made blame and punishment judgements as described in previous studies. They also rated the extent to which the man caused the outcome, the extent to which the man intended the outcome, and their anger at the man. These judgements were highly correlated and were combined into an ‘intent’ composite for analysis (a = .86). Although these judgements might represent distinct theoretical constructs, the high correlations among these items suggested that participants treated them as equivalent judgements, and results were similar with any of the judgements.
Coding As a manipulation check, written responses were coded for counterfactual content. Two independent judges coded each response. They were instructed to code a response as a counterfactual only when there was clear evidence that an alternative to reality had been considered (j = .87; 95% CI: .80–.94; 94% agreement). Additionally, each counterfactual response was also coded as to whether it contained an upward counterfactual (better alternative to reality) or downward counterfactual (worse alternative to reality; j = .94; 95% CI: .89–.99; 97% agreement). Discrepancies between judges were resolved by a third independent judge.
Results and discussion Manipulation check An ANOVA on number of counterfactual statements with counterfactual condition (upward, downward, neutral) as the between-subjects factor revealed a main effect of counterfactual condition, F(2,295) = 224.90, p < .001, g2 = .60. Those in the upward and downward counterfactual conditions wrote more counterfactuals overall (Mupward = 2.67, SD = 1.11; Mdownward = 2.55, SD = 1.17) than those in the neutral condition (M = 0.06, SD = .35), t(191) = 21.77, p < .001, d = 3.15, and t(197) = 19.85, p < .001, d = 2.83, respectively, with no other significant contrasts. A similar analysis on number of upward counterfactual statements again revealed a main effect of counterfactual condition, F(2,295) = 388.32, p < .001, g2 = .73. Those in the upward counterfactual conditions wrote more upward counterfactuals (M = 2.66, SD = 1.08) than those in the downward condition (M = 0.20, SD = 0.66), t(202) = 19.76, p < .001, d = 2.78, or those in the neutral condition (M = 0.03, SD = 0.18), t(191) = 23.26, p < .001, d = 3.37, with no other contrasts significant. A similar analysis on number of downward counterfactual statements also revealed a main effect of counterfactual condition, F(2,295) = 317.33, p < .001, g2 = .68. Those in the downward counterfactual conditions wrote more downward counterfactuals (M = 2.35, SD = 1.25) than those in the neutral condition (M = 0.03, SD = 0.31), t(197) = 17.55, p < .001, d = 2.50, or those in the upward condition (M = 0.01, SD = 0.10), t(202) = 18.62,
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p < .001, d = 2.62, with no other contrasts significant. All effects remain similar if the few participants who wrote a counterfactual not specified in their condition were excluded (4 in the neutral condition; 13 in the downward condition; 1 in the upward condition). Thus, the manipulation of counterfactual writing effectively elicited the specified counterfactual content.
Judgements of blame and punishment An ANOVA was conducted on judgements of the extent to which the protagonist was to blame with counterfactual condition (downward, upward, neutral), intent (intent, no intent), and harm (harm, no harm) as between-subjects factors. Values from the full analysis are reported in Table 1. The main effect associated with intent of the protagonist was large compared with small effects for other factors, with participants judging a protagonist who intended harm to be more blameworthy (M = 6.13, SD = 1.19) than a protagonist who did not intend harm (M = 2.20, SD = 1.37). This suggests that intent has a large effect on judgements of blame and that this effect is larger than that associated with whether or not a negative outcome occurred. However, there was a significant interaction between intent and harm, such that protagonists were judged as more blameworthy if they intended and caused harm (M = 6.56, SD = .86) than if they intended harm but by luck did not cause harm (M = 5.66, SD = 1.31), t(164) = 5.23, p < .001, d = .82. Protagonists were also judged as somewhat more blameworthy if they did not intend but caused harm (M = 2.37, SD = 1.49) than if they did not intend and did not cause harm (M = 2.04, SD = 1.24), although this difference was not significant, t (146) = 1.47, p = .63, d = .24. Thus, although participants took the intent of the protagonist into account when assigning blame, they were also influenced by whether or not a negative outcome occurred. There was also an interaction between harm and writing condition, as blame was greater for protagonists who caused harm (M = 4.95) than did not cause harm (M = 4.09) if participants wrote downward counterfactuals, t(108) = 1.92, p = .058, d = .37, or upward counterfactuals (Mharm = 4.65; Mnoharm = 3.60), t(103) = 2.38, p = .02, d = .47, but not if they wrote neutral semi-factuals (Mharm = 4.27; Mnoharm = 4.02), t(97) = .52, p = .60, d = .11. A similar ANOVA was conducted on punishment recommendations. Values from the full analysis are reported in Table 2. As with blame judgements, the main effect associated with intent of the protagonist was large compared with effects for other factors, with participants recommending greater punishment for a protagonist who intended harm (M = 5.76, SD = 2.19) than a protagonist who did not intend harm (M = 1.86, SD = 1.41). This finding again suggests that intent of the protagonist has a large impact Table 1. Results from ANOVA for blame judgements
Counterfactual Intent Harm Counterfactual 9 Intent Counterfactual 9 Harm Intent 9 Harm Counterfactual 9 Intent 9 Harm
df
F
p-value
g2
2,302 1,302 1,302 2,302 2,302 1,302 2,302
2.63 795.37 19.31 .40 2.96 4.33 1.19
.07
British Journal of Psychology (2014) © 2014 The British Psychological Society www.wileyonlinelibrary.com
Beliefs in moral luck: When and why blame hinges on luck Heather C. Lench*, Darren Domsky, Rachel Smallman and Kathleen E. Darbor Department of Psychology, Texas A&M University, College Station, Texas, USA Belief in moral luck is represented in judgements that offenders should be held accountable for intent to cause harm as well as whether or not harm occurred. Scores on a measure of moral luck beliefs predicted judgements of offenders who varied in intent and the outcomes of their actions, although judgements overall were not consistent with abstract beliefs in moral luck. Prompting participants to consider alternative outcomes, particularly worse outcomes, reduced moral luck beliefs. Findings suggest that some people believe that offenders should be punished based on the outcome of their actions. Furthermore, prompting counterfactuals decreased judgements consistent with moral luck beliefs. The results have implications for theories of moral judgement as well as legal decision making.
Two men stand at the middle of a highway overpass. Each man plans to toss a brick down onto traffic below and realizes that the brick could kill someone. On this particular overpass, cars below are not visible because a wall blocks the view. Thus, the men have to throw their bricks without being able to see the traffic. Red sprays his brick red, and Green sprays his brick green. They throw their bricks over the wall. One brick hits the pavement, breaking into harmless pieces. The other smashes through a car roof, and kills someone instantly. The two men are arrested. Obviously these two men are worthy of blame – their actions put others at risk of harm. But are they equally blameworthy? Put another way, to recommend punishment for each man, do you need to know the colour of the brick that killed someone? If you need to know the colour, your judgement reflects a belief in moral luck. If you do not need to know the colour, your judgement does not reflect a belief in moral luck. The focus of this investigation was on two unresolved questions regarding moral luck beliefs: (1) do abstract beliefs in moral luck predict judgements in scenarios that vary in intent and outcome of a perpetrator? and (2) can judgements consistent with belief in moral luck, that weight outcome more than intent, be altered by people’s focus during judgement?
The concept of moral luck beliefs Moral luck beliefs are demonstrated when judgements of blameworthiness hinge not just on whether or not harm was intended, but on the outcome of whether or not harm
*Correspondence should be addressed to Heather C. Lench, Department of Psychology, Texas A&M University, College Station, TX 77843-4235, USA (email: [email protected]). DOI:10.1111/bjop.12072
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occurred (Nagel, 1993; Smith, 1759).1 Accordingly, blame is incurred with actions that risk taking innocent life, and additional blame is incurred if actions result in loss of innocent life. Thus, although Red and Green both incurred blame when they threw their bricks, one of these men is more blameworthy because his brick killed someone. The belief in moral luck is incorporated in many legal systems, with punishments more severe if harm occurs than if it does not. Non-belief in moral luck is demonstrated when judgements of blameworthiness hinge on commission of negligent actions regardless of actual outcome. All that matters is whether a negative outcome could have occurred given the actions taken. Thus, Red and Green are equally morally blameworthy and deserve equal punishment because their actions introduced foreseeable risk of negative outcomes. According to this perspective, the colour of the killer brick is purely a matter of (morally irrelevant) luck. Note that these arguments can also be applied to people who unintentionally cause negative outcomes, such as a driver who runs over someone through no fault of his own (Williams, 1993). Beliefs in moral luck dictate that this person be held accountable for the outcome, whereas a non-belief in moral luck dictates that this person is not blameworthy because the negative outcome could not have been foreseen.2 Most people do not strictly adhere to either of these opposing viewpoints. On the contrary, belief in moral luck appears to vacillate depending on specific circumstances. When asked if blameworthiness should ever hinge on the luck of how things turn out, people indicate that they do not believe in moral luck (90% disagree; Nichols, 2009). In other words, as a matter of abstract principle, most people uphold that blaming people according to how lucky they are is morally inappropriate. However, when faced with actual positive or negative outcomes of actions taken by another, people’s judgements reflect belief in moral luck and they judge others to be more blameworthy if actions resulted in negative outcomes than if, by luck, their actions caused no harm (Cushman, 2008; Cushman, Dreber, Wang, & Costa, 2009; Young, Nichols, & Saxe, 2010). These findings suggest that people decry belief in moral luck in principle, but often exhibit it in judgements about specific circumstances. This apparent paradoxical behaviour has not been empirically addressed and, as a result, it is unclear whether people can report on moral luck beliefs.
STUDY 1 Study 1 focused on establishing whether self-reported belief in moral luck corresponded to judgements about protagonists whose actions did or did not result in harm. To reduce additional factors that might influence judgement, we selected vignettes that included acts that most people were unlikely to have committed, acts that were clearly malicious or not, and acts with clear harm.
1 Philosophers have identified four kinds of moral luck, including resultant (which outcome follows), constitutive (an individual’s characteristics), causal (circumstances that affect actions), and circumstantial luck (the types of situations that one faces; Nagel, 1993). In the present investigation, we refer to resultant as moral luck for simplicity. 2 Luck is commonly defined as something experienced to the extent that a person cannot control or foresee which particular outcome out of a set of possible outcomes will follow an action (Domsky, 2004). Although luck is sometimes defined more broadly, we focus on the specific definition and situations in which potential danger can be foreseen. Also, philosophers disagree about whether agents must act negligently to be seen as having good or bad moral luck. Some believe that good or bad moral luck can only befall negligent agents (Domsky, 2004), and others disagree (Statman, 2005). Because restricting moral luck is controversial, we assume, here, that forseeability and negligence may not be required.
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Method Undergraduates (n = 70; Mage = 18.97; 56% women) participated for partial course credit. Participants read scenarios developed from philosophical discussions of moral luck beliefs. Participants received three scenarios, in random counterbalanced order (there were no order effects, ps > .30) that varied in intent of the protagonist and the outcome. These scenarios were presented interspersed with nine other similar descriptions, to reduce the salience of target scenarios. The Intent-Negative scenario read: “A man decides to risk people’s lives by walking to the middle of a freeway overpass and throwing a brick down onto the freeway below. He realizes that a falling brick might go through the roof of a passing car and kill someone, but goes ahead anyway. A tall cement wall blocks his view, and so he has no idea where the cars are. He only knows that the cars are down below, and so throws the brick over the cement wall and down onto the freeway below. As it turned out, the brick went through a car roof and killed someone instantly.” The Intent-Neutral scenario was identical except that the brick fell harmlessly. The Nointent-Negative scenario was identical except that a man on a walk rested against the wall, accidentally causing a brick to fall and kill someone. A Nointent-Neutral condition was not included because it was expected that this person would be considered not at all blameworthy. Supplemental materials contain these vignettes. Participants then judged how blameworthy the man was on scales ranging from not at all (1) to extremely (7). They also recommended punishment for the protagonist on scales with nine response points (no punishment, small fine, large fine, probation, less than 2 years in prison, between 2 and 5 years in prison, over 5 years in prison, life sentence, death sentence). Finally, participants responded to ten items created to measure moral luck beliefs, based on a philosophical definition of moral luck belief (see Appendix). Participants rated the extent to which they agreed with statements on scales ranging from strongly disagree (1) to strongly agree (7) (a = .88).
Results and discussion An ANOVA with blame judgements for each scenario (Intent-Negative, Intent-Neutral, Nointent-Negative) as the within-subject factor revealed an effect of scenario, F (2,134) = 154.78, p < .001, g2 = .70. Consistent with moral luck theory, participants held the protagonist who intended and caused harm to be more blameworthy (M = 6.54, SD = 0.91) than the protagonist who intended harm but nothing happened (M = 5.68, SD = 1.57), t(68) = 5.63, p < .001, d = 1.37, and the protagonist who did not intend harm but caused a negative outcome (M = 2.50, SD = 1.60), t(67) = 16.35, p < .001, d = 3.99. Participants also held the protagonist who intended harm but nothing happened to be more blameworthy than the protagonist who did not intend harm but caused a negative outcome, t(67) = 10.59, p < .001, d = 2.59. A similar analysis for punishment recommendations3 revealed an effect of scenario, F(2,134) = 188.20, p < .001, g2 = .74. As depicted with the means reported in 3 The punishment scale used is technically ordinal rather than interval because, although punishments were listed in order of increasingly severe consequences, the intervals between response points are not equal for the scale. Note, however, that almost all scales used in psychological research use arbitrary metrics in which the exact difference between points on a scale are unknown but assumed to reflect interval scales during analysis, with few problems for internal reliability or interpretation (Blanton & Jaccard, 2006). Analyses were conducted treating this scale as an ordinal or an interval scale and both sets of analyses yielded consistent results across studies. For simplicity and to keep analyses consistent for blame and punishment judgements, analyses that treat the scale as interval are reported in the text.
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Punishment RecommendaƟon
8 7 6 5 4 3 2 1 Intent,Harm
Intent,NoHarm
No Intent,Harm
Figure 1. Means (SE) for punishment recommendations in study 1.
Figure 1, contrasts revealed that, consistent with blame judgements, participants recommended the most intense punishment for the protagonist who acted intentionally and caused a negative outcome, compared with the protagonist who acted intentionally but nothing happened, t(68) = 16.66, p < .001, d = 4.04, and the protagonist who did not intend harm but caused a negative outcome, t(67) = 16.97, p < .001, d = 4.15. Participants also recommended less punishment for the protagonist who did not intend harm but caused a negative outcome compared with the protagonist who intended harm but nothing happened, t(67) = 5.82, p < .001, d = 1.42. Participants made judgements consistent with a belief in moral luck, with protagonists judged to be more blameworthy and deserving of more punishment if malevolent actions resulted in a negative outcome. These findings also support the additive nature of blame assigned for intent and outcome, such that either malevolent intent or a negative outcome resulted in some blame, but the combination of intent and a negative outcome was regarded as particularly blameworthy. Composite scores on the measure of belief in moral luck ranged from 1 to 6.3, with an overall mean of 2.94 and a standard deviation of .95, suggesting that there was variation in the degree to which participants endorsed moral luck beliefs. Comparison of the mean score to the neutral mid-point of the agreement scale indicated that, on average, participants rated that they did not agree with moral luck beliefs that people should be punished based on outcome rather than on intent, t(69) = 9.32, p < .001. Indeed, 88.6% of participants had an average rating below the mid-point of the scale, indicating that they did not believe in moral luck, while 11.4% had an average rating at or above the mid-point of the scale, indicating that they did believe in moral luck and that people should be punished based on outcomes rather than intent. To examine the relationship between explicit beliefs in moral luck and a tendency to judge others based on intent or outcome, difference scores were created for scenario judgements. Two difference scores represented the difference in blame and punishment judgements based on intent only (Intent-Negative minus Nointent-Negative) and two difference scores represented the difference in blame and punishment judgements based on outcome only (Intent-Negative minus Intent-Neutral). Explicit beliefs in moral luck did not relate to blame or punishment judgements for scenarios that differed in intent only, r(68) = .18, p = .14, and r(68) = .09, p = .46, respectively. Explicit beliefs in moral luck did relate to judgements for scenarios that differed in outcome only. Greater beliefs in moral luck predicted relatively more blame for the protagonist who intentionally caused a negative outcome compared with the protagonist with negative intent but
Moral luck beliefs
5
who did not cause a negative outcome, r(69) = .41, p < .001. This relationship was similar for punishment recommendations of these two protagonists, r(69) = .35, p = .004. Thus, self-reported beliefs in moral luck correlated as would be expected with judgements of blame and punishment. Participants’ self-reported belief in moral luck predicted their tendency to blame and punish a malevolent protagonist who caused a negative outcome more than an equally malevolent protagonist who did not cause a negative outcome. This study is the first to demonstrate that participants vary in their endorsement of moral luck beliefs and that their endorsement predicts actual judgements. It suggests that, for at least some people, judgements consistent with moral luck beliefs may arise from consciously accessible attitudes.
STUDY 2 Study 1 revealed that (1) participants self-reported on average that they do not believe in moral luck, but their judgements reflected these beliefs; however, (2) despite this disconnect between beliefs and judgements, variability in self-reported beliefs in moral luck predicted judgements. Studies 2 and 3 focused on the possibility that additional consideration of outcomes might reduce the discrepancy between attitudes against moral luck beliefs and judgements consistent with moral luck beliefs. Imagining alternative outcomes that are either better (i.e., upward counterfactual thoughts) or worse (i.e., downward counterfactual thoughts) may influence participants’ judgements. Upward counterfactuals are frequently activated by a negative outcome (Roese & Hur, 1997; Roese & Olson, 1997). Compared with the imagined alternative, the actual negative outcome may seem even worse and increase judgements of blame, responsibility, and victim compensation accordingly (Macrae, 1992; Macrae & Milne, 1992; Wells & Gavanski, 1989). Although less common, downward counterfactuals can also be triggered after some negative events, as in ‘near miss’ situations (Markman & McMullen, 2003). A salient negative alternative outcome could increase perceptions of blame, especially in situations in which the perpetrator had intent but narrowly missed the negative outcome. In Study 2, we hypothesized that people would be more likely to base judgements on the intent of the protagonist to the extent that they focused on negative outcomes that might have been. Because we were also interested in tendencies to consider different types of outcomes based on the scenario (i.e., would a near miss situation prompt more downward counterfactuals?), participants were not directed to consider particular outcomes.
Method Undergraduates (n = 170; 64.1% women) completed the study for course credit. The method was similar to that employed in Study 1, in that participants made judgements of blame and recommended punishments for the protagonist in the brick vignette and then completed the measure of moral luck beliefs. However, Study 2 utilized a between-subject design with participants randomly assigned to a 3(scenario) 9 2(writing focus) design, in part because the order in which scenarios are presented may affect judgements. Each participant saw only one of the scenarios (Intent-Negative, Intent-Neutral, Nointent-Negative). Participants were also assigned, before making their judgements, to write a brief response to each vignette that focused on ‘how things might have ended differently in this story’ (Counterfactual condition) or the ‘motivations of the person in this story’ (Motivation condition). The motivation condition was selected as a control
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because it involved participants writing about and thinking about the scenario, as in the counterfactual condition, but the focus was not on the outcome of the scenario. This condition was considered a conservative control, because, if anything, it should have increased thoughts about the intent of the protagonist and thus decreased a reliance on outcome information relative to intent. Thus, showing that considering counterfactuals had an impact above and beyond this control condition would support the impact of counterfactuals on judgement relative to other cognitions that should increase the salience of intent information. Written responses were coded for counterfactual content by two independent judges. They were instructed to code a response as a counterfactual only when there was clear evidence that an alternative to reality had been considered (j = .76; 95% CI: .70–.81; 88% agreement). Additionally, each counterfactual response was also coded as to whether it contained an upward counterfactual (better alternative) or downward counterfactual (worse alternative) (j = .88; 95% CI: .82–.96; 95% agreement). Discrepancies between judges were resolved by a third judge.
Results and discussion Preliminary analyses Those in the counterfactual conditions wrote more counterfactuals (M = 2.41, SD = 1.63) than those in the motivation condition (M = .15, SD = .66), t(168) = 10.49, p < .001, d = 1.62. Thus, the manipulation of writing focus was effective. Results from all analyses remain identical if the six participants in the motivation condition who wrote a counterfactual thought were excluded; therefore, all participants were retained in analyses. There was a significant interaction between scenario and type of counterfactual, F(1,167) = 26.64, p < .001, g2 = .24. Participants generated more upward counterfactuals than downward counterfactuals for a protagonist who intended and caused harm, Mup = 1.02, Mdown = .18, t(54) = 4.57, p < .001, and a protagonist who did not intend but caused harm, Mup = 0.98, Mdown = .14, t(57) = 4.92, p < .001. For a protagonist who intended but did not cause harm, participants generated more downward counterfactuals (M = 0.98, SD = 1.51) than upward counterfactuals (M = .16, SD = .46), t(56) = 4.05, p < .001.
Judgements of blame and punishment An ANOVA was conducted with scenario (Intent-Negative, Intent-Neutral, NointentNegative) and writing focus (Counterfactual, Motivation) as the between-subjects factors and blame judgements as the dependent variable. There was a main effect of writing focus, F(1,163) = 4.63, p = .03, g2 = .03, and a main effect of scenario, F(2,163) = 153.45, p < .001, g2 = .65, but this main effect was subsumed by an interaction between writing focus and scenario, F(2,163) = 6.02, p = .003, g2 = .07. Contrasts revealed that writing focus did not impact blame judgements for the protagonist who intended and caused harm (Mcounter = 6.36, SD = 0.83; Mmotive = 5.85, SD = 1.29), t(53) = 1.73, p = .09, d = .48. Writing focus also did not impact judgements for the protagonist who did not intend harm but caused a negative outcome (Mcounter = 2.52, SD = 1.16; Mmotive = 2.93, SD = 1.20), t(55) = 1.33, p = .19, d = .36. Counterfactual writing did influence judgements of the protagonist who intended but did not cause harm. In this scenario, participants judged the protagonist to be more blameworthy when they wrote about how
Moral luck beliefs
7
9 Counterfactual
Punishment ReccomendaƟons
8
MoƟvaƟon 7 6 5 4 3 2 1 Intent,Harm
Intent,NoHarm
No Intent,Harm
Figure 2. Means (SE) for punishment recommendations in study 2.
the scenario might have ended differently (M = 6.19, SD = 0.83) than about his motivations (M = 5.17, SD = 1.26), t(55) = 3.55, p = .001, d = .96. Furthermore, if participants wrote about how the scenario might have ended differently, they judged the protagonist who intended harm but did not cause a negative outcome to be as blameworthy as the protagonist who intended harm and caused a negative outcome, t (53) = .77, p = .45, d = .21. In other words, participants’ judgements were influenced by intent rather than whether or not the negligent act happened to result in a negative outcome when they wrote counterfactual statements. A similar analysis was conducted with punishment recommendations as the dependent variable. There was no main effect of writing focus, F(1,164) = 1.97, p = .16, g2 = .01. There was a main effect of scenario, F(2,164) = 95.84, p < .001, g2 = .54, but this main effect was again subsumed by an interaction between writing focus and scenario, F(2,164) = 5.86, p = .003, g2 = .07. As depicted with the means in Figure 2, contrasts revealed that punishment recommendations were marginally harsher for the protagonist who intended and caused harm if participants wrote about how the scenario might have ended differently than if they wrote about the motivations of the protagonist, t(53) = 1.95, p = .06, d = .54, although judgements were less harsh than in other studies. For the protagonist who did not intend but caused a negative outcome, punishment recommendations were marginally less if participants wrote about how the scenario might have ended differently than if they wrote about the motivations of the protagonist, t(56) = 1.80, p = .08, d = .48. Consistent with the findings for blame judgements, punishment recommendations were harsher for the protagonist who intended but did not cause harm if participants wrote about how the scenario might have ended differently compared with the motivations of the protagonist, t(55) = 2.60, p = .01, d = .70. Thus, writing counterfactuals reduced the presence of moral luck in judgements, consistent with rational accounts of moral decision making, and judgements were more influenced by intent than whether or not a negative outcome happened to occur.
Consideration of counterfactuals We did not direct participants to consider particular types of counterfactuals in Study 2, but hypothesized that participants would hold the protagonist who intended but did not cause harm to be more blameworthy when they considered how the situation could have
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ended in a negative outcome. Preliminary analyses confirmed that the number of upward counterfactuals did not predict blame judgements or punishment recommendations and these counterfactuals are not considered further. To explore the possibility that downward counterfactuals might explain differences in blame among scenarios, we conducted analyses with the coded number of downward counterfactuals. An ANOVA, including the counterfactual conditions only, with scenario as the between-subjects factor and downward counterfactuals as the dependent variable, confirmed that the number of counterfactuals varied by scenario, F(2,80) = 20.30, p < .001, g2 = .34. Post-hoc contrasts revealed that more downward counterfactuals were produced in the scenario with a protagonist who intended but did not cause harm (M = 1.78, SD = 1.55) than a protagonist who intended and caused harm (M = 0.36, SD = 0.56), t(32.41) = 4.48, p < .001, d = 1.56 (unequal variances resulted in a change in dfs), and a protagonist who did not intend but caused harm (M = 0.25, SD = 0.52), t(31.54) = 4.86, p < .001, d = 1.72. The number of downward counterfactuals produced did not differ between scenarios with a protagonist who intended and caused harm compared with a protagonist who did not intend but caused harm, t(54) = 0.74, p = .46, d = .20. Self-reported beliefs in moral luck did not predict the number of counterfactuals generated overall or for any particular scenario, all ps > .29. Could downward counterfactuals account for harsher judgements in the counterfactual versus motivation conditions as predicted? To find out, we conducted a mediation analysis (Hayes, 2013; 5,000 samples), with writing condition as the IV, blame judgements as the DV, and downward counterfactuals as the mediator, R2 = .11, F(1,167) = 20.68, p < .001. The direct effect of writing condition on blame judgements (b = .66, t = 4.55, p < .001) was reduced when counterfactuals were included (b = .17, t = .58, p = .56). There was also a significant indirect effect of .55 (SE = .10), which was significant because the confidence interval did not include zero (95% CI: .10–.50), revealing that writing condition influenced blame through the number of counterfactuals generated. An analysis with punishment recommendations yielded similar findings. Thus, the number of downward counterfactuals considered accounted for harsher judgements.
Self-reported beliefs in moral luck Composite scores on the measure of belief in moral luck ranged from 1 to 6.4, with an overall mean of 2.88 and a standard deviation of .81, strikingly similar to the descriptives reported in Study 1. Comparison of the mean score to the neutral mid-point of the agreement scale (4) indicated that, on average, participants reported that they did not agree with moral luck beliefs, t(169) = 18.04, p < .001. Indeed, 91.2% of participants had an average rating below the mid-point of the scale, indicating that they did not believe in moral luck, while 8.8% had an average rating above the mid-point of the scale, indicating that they did believe in moral luck (that people should be punished based on outcomes rather than intent). Greater belief in moral luck (that people should be punished based on outcome) again predicted less blame of the protagonist who intended but did not cause harm, b = .28, t = 2.20, p = .03. Self-reported beliefs again did not predict blame of the protagonist who intended and caused harm, b = .24, t = 1.78, p = .08, or the protagonist who did not intend but caused harm, b = .05, t = 0.40, p = .69. Self-reported beliefs did not predict punishment recommendations. This finding suggests that participants self-reported beliefs partially predicted their blame judgements in a scenario where moral luck beliefs
Moral luck beliefs
9
are especially relevant. Consistent with our prediction that consideration of counterfactuals should make judgements more congruent with abstract beliefs in moral luck, there was a greater correlation between self-reported belief in moral luck and blame judgements of the protagonist with intent but who did not cause harm in the counterfactual condition (r = .38) than the motivation condition (r = .20).
STUDY 3 Study 2 suggested that participants who focused on how the situation might have ended badly made harsher judgements of the protagonist who intended to cause harm but, through luck, his actions did not result in harm. These judgements were more congruent with participants’ self-reported denial of moral luck (such denial should result in punishing offenders for negligent acts rather than harmful outcomes) and rational standards for judgements in which luck should not influence blame. However, participants in Study 2 were prompted to consider how the situation could have ended differently and were not specifically prompted to consider how the outcome could have been better or worse than it actually was. This resulted in relatively low levels of downward counterfactuals across scenarios. In Study 3, therefore, we explicitly instructed participants to make upward counterfactuals, downward counterfactuals, or neutral semifactuals (statements of how the outcome would remain the same; McCloy & Byrne, 2002), to examine the impact of such thoughts on judgements.
Method Participants (n = 314; 56% women) completed the study for course credit. The method was similar to that employed in previous studies, in that participants made judgements of blame and recommended punishments for the protagonist in the brick vignette, then reported their beliefs in moral luck. Study 3 utilized a between-subject design with participants randomly assigned to receive one of four scenarios (Intent-Negative, Intent-Neutral, Nointent-Negative; Nointent-Neutral). This latter condition, where the protagonist did not intend harm (i.e., leaned on a wall and the brick accidentally fell) and did not cause harm (i.e., the brick fell harmlessly to the ground), was included primarily to allow a fully crossed design that would estimate the impact of intent and negative outcome between the scenarios. Participants were also assigned to write one of three brief responses to each vignette for 3 min before making their judgements. This writing focused on upward counterfactuals, downward counterfactuals, or neutral semifactuals. In the upward counterfactuals conditions participants were instructed, “people often have thoughts like ‘if only. . .’ after events, in that they can see how things might have turned out better. For example, a woman who recently sustained minor injuries in an accident told reporters, ‘If only I had checked the machine a second time, I would’ve been fine. Also, I wish I hadn’t been so distracted, because then I would have been fine.’ Often, we wish we could change things to avoid outcomes. Focusing on the situation you just read about the man on the freeway overpass, use the next page to list some changes that would have, in retrospect, improved the outcome of this particular situation. Each thought you list should complete one of these phrases: ‘if he had ___ the outcome would have been better’ or ‘if he had NOT ___ the outcome would have been better.” The instructions for downward counterfactual conditions were similar (see online supplemental materials for full wording) except that
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participants were instructed that people often have thoughts about how things might have turned out worse, and they were asked to complete one of these phrases: ‘if he had ___ the outcome would have been even worse’ or ‘if he had NOT ___ the outcome would have been even worse.’ The instructions for the neutral semifactuals were also similar except that participants were instructed that people often have thoughts about how things would have ended similarly, and they were asked to complete the phrase: ‘Even if he had ___ the outcome would still have been the same.’ After writing the counterfactual statements, participants made blame and punishment judgements as described in previous studies. They also rated the extent to which the man caused the outcome, the extent to which the man intended the outcome, and their anger at the man. These judgements were highly correlated and were combined into an ‘intent’ composite for analysis (a = .86). Although these judgements might represent distinct theoretical constructs, the high correlations among these items suggested that participants treated them as equivalent judgements, and results were similar with any of the judgements.
Coding As a manipulation check, written responses were coded for counterfactual content. Two independent judges coded each response. They were instructed to code a response as a counterfactual only when there was clear evidence that an alternative to reality had been considered (j = .87; 95% CI: .80–.94; 94% agreement). Additionally, each counterfactual response was also coded as to whether it contained an upward counterfactual (better alternative to reality) or downward counterfactual (worse alternative to reality; j = .94; 95% CI: .89–.99; 97% agreement). Discrepancies between judges were resolved by a third independent judge.
Results and discussion Manipulation check An ANOVA on number of counterfactual statements with counterfactual condition (upward, downward, neutral) as the between-subjects factor revealed a main effect of counterfactual condition, F(2,295) = 224.90, p < .001, g2 = .60. Those in the upward and downward counterfactual conditions wrote more counterfactuals overall (Mupward = 2.67, SD = 1.11; Mdownward = 2.55, SD = 1.17) than those in the neutral condition (M = 0.06, SD = .35), t(191) = 21.77, p < .001, d = 3.15, and t(197) = 19.85, p < .001, d = 2.83, respectively, with no other significant contrasts. A similar analysis on number of upward counterfactual statements again revealed a main effect of counterfactual condition, F(2,295) = 388.32, p < .001, g2 = .73. Those in the upward counterfactual conditions wrote more upward counterfactuals (M = 2.66, SD = 1.08) than those in the downward condition (M = 0.20, SD = 0.66), t(202) = 19.76, p < .001, d = 2.78, or those in the neutral condition (M = 0.03, SD = 0.18), t(191) = 23.26, p < .001, d = 3.37, with no other contrasts significant. A similar analysis on number of downward counterfactual statements also revealed a main effect of counterfactual condition, F(2,295) = 317.33, p < .001, g2 = .68. Those in the downward counterfactual conditions wrote more downward counterfactuals (M = 2.35, SD = 1.25) than those in the neutral condition (M = 0.03, SD = 0.31), t(197) = 17.55, p < .001, d = 2.50, or those in the upward condition (M = 0.01, SD = 0.10), t(202) = 18.62,
Moral luck beliefs
11
p < .001, d = 2.62, with no other contrasts significant. All effects remain similar if the few participants who wrote a counterfactual not specified in their condition were excluded (4 in the neutral condition; 13 in the downward condition; 1 in the upward condition). Thus, the manipulation of counterfactual writing effectively elicited the specified counterfactual content.
Judgements of blame and punishment An ANOVA was conducted on judgements of the extent to which the protagonist was to blame with counterfactual condition (downward, upward, neutral), intent (intent, no intent), and harm (harm, no harm) as between-subjects factors. Values from the full analysis are reported in Table 1. The main effect associated with intent of the protagonist was large compared with small effects for other factors, with participants judging a protagonist who intended harm to be more blameworthy (M = 6.13, SD = 1.19) than a protagonist who did not intend harm (M = 2.20, SD = 1.37). This suggests that intent has a large effect on judgements of blame and that this effect is larger than that associated with whether or not a negative outcome occurred. However, there was a significant interaction between intent and harm, such that protagonists were judged as more blameworthy if they intended and caused harm (M = 6.56, SD = .86) than if they intended harm but by luck did not cause harm (M = 5.66, SD = 1.31), t(164) = 5.23, p < .001, d = .82. Protagonists were also judged as somewhat more blameworthy if they did not intend but caused harm (M = 2.37, SD = 1.49) than if they did not intend and did not cause harm (M = 2.04, SD = 1.24), although this difference was not significant, t (146) = 1.47, p = .63, d = .24. Thus, although participants took the intent of the protagonist into account when assigning blame, they were also influenced by whether or not a negative outcome occurred. There was also an interaction between harm and writing condition, as blame was greater for protagonists who caused harm (M = 4.95) than did not cause harm (M = 4.09) if participants wrote downward counterfactuals, t(108) = 1.92, p = .058, d = .37, or upward counterfactuals (Mharm = 4.65; Mnoharm = 3.60), t(103) = 2.38, p = .02, d = .47, but not if they wrote neutral semi-factuals (Mharm = 4.27; Mnoharm = 4.02), t(97) = .52, p = .60, d = .11. A similar ANOVA was conducted on punishment recommendations. Values from the full analysis are reported in Table 2. As with blame judgements, the main effect associated with intent of the protagonist was large compared with effects for other factors, with participants recommending greater punishment for a protagonist who intended harm (M = 5.76, SD = 2.19) than a protagonist who did not intend harm (M = 1.86, SD = 1.41). This finding again suggests that intent of the protagonist has a large impact Table 1. Results from ANOVA for blame judgements
Counterfactual Intent Harm Counterfactual 9 Intent Counterfactual 9 Harm Intent 9 Harm Counterfactual 9 Intent 9 Harm
df
F
p-value
g2
2,302 1,302 1,302 2,302 2,302 1,302 2,302
2.63 795.37 19.31 .40 2.96 4.33 1.19
.07
