Emotion and Intuition: Does Schadenfreude Make Interns Poor Learners?

EMOTION AND INTUITION: DOES SCHADENFREUDE MAKE INTERNS POOR LEARNERS?

OLIVER H. TURNBULL, RICHARD B. WORSEY, AND CAROLINE H. BOWMAN ______

While emotion has often been regarded as a negative force for human decision making, there are times when emotion is essential in order for human beings to make sensible choices.The basis for the phenomenon appears to be the ‘hunches’ that we often generate about complex problems, typically described as intuition —- a source of knowledge that has a vital role to play in creativity and imagination. In this study we describe an attempt to investigate the indirect, or empathic, experience of these intuitive phenomena, in a context akin to an ‘intern’ relationship. Using a well-established tool (the Iowa Gambling Task), we attempted to establish how intuition was empathically experienced by an observer. Critically, we also measured the extent to which this process was helpful in the observer’s later performance, measuring the phenomena using behavioral, subjective experience and video-monitoring methods.The most remarkable ﬁnding is that, even where the observers have ample opportunity for observation, they later perform very poorly when required to demonstrate the extent of their learning -– at levels worse than those of a naïve player. Based on an analysis of video-captured material, a plausible account of these data is that the experience of schadenfreude (a feeling of pleasure at someone else’s misfortune) might account for this surprisingly poor performance. A series of control experiments allow us to examine this hypothesis in more detail, primarily by making it possible to rule out a range of plausible confounds.The additional experiments also allow us to establish some of the boundary conditions for this phenomenon, and make it clear that when human beings can work together towards a common goal, in which they both have some degree of investment in the process, the disruptive (schadenfreude-based) effects are no longer observed.

After decades of neglect, emotion has recently become a central theme in psychological science (e.g., Damasio, 1994; 1999; 2004; LeDoux, 2000; Panksepp, 1998; Rolls, 1999). Indeed, it has now become clear that emotion is not only an interesting and potentially worthwhile topic of study in its own right, but also that it may play a role in intellectually demanding tasks, such as complex problem solving and decision making. This stands in sharp contrast to the view, held by philosophers from Plato (360BC/1956) through Kant (1781/2004), that emotion typically is a rather negative force in human intellectual life (see Damasio, 2004, for a readable survey of philosophical antecedents). Most philosophers have suggested that, in order to make successful and appropriate decisions, human beings need to exclude emotions from the decision-making process and instead focus on an entirely rational (or in modern

The authors are affiliated with the Centre for Cognitive Neuroscience School of Psychology, University of Wales in Bangor, Wales Contact: Dr. Oliver Turnbull, Centre for Cognitive Neuroscience, School of Psychology, University of Wales, Bangor, Wales, LL57 2AS, UK Telephone: +44 (0) 1248 383670 E-mail: [email protected] Key words: intuition, emotion-based learning, Iowa Gambling Task, internship, schadenfreude 5 Philoctetes Center Journal VOLUME 1 · NUMBER 1 parlance ‘cognitive’) approach to tackling complex problems (Damasio, 2004). It has become clear in the last decade or so that there are times when emotion is absolutely essential in order for human beings to make sensible choices, and indeed some work in modern neuroscience has demonstrated this with great clarity (Bechara, Traniel, & Damasio, 2000; Damasio, 1994; Eslinger & Damasio, 1985; Manes, Sahakian, Clark, Rogers, Antonin, Aitken, & Robbins, 2002; Rolls, 2000). The best class of evidence comes from human neuropsychology, and in particular from patients who have damage to the ventromedial frontal lobes (Bechara, Damasio, Damasio, & Anderson, 1994) –-patients who appear to be intellectually intact, but who show severe deficits in decision making. The classic example is that of Phineas Gage (Harlow, 1848; 1868; 1869), a railway work- er in the Northeastern United States who suffered a terrible injury with a tamping rod, which passed up through the medial parts of his frontal lobes (Damasio, Grabowski, Frank, Galaburda, & Damasio, 1994). While he made a remarkable physical recovery and attempted to return to his original job, it rapidly became clear to his employers that he had become, in many respects, a different ‘person’ (Harlow, 1848; 1868; 1869). Many such cases have been reported since the original Gage report (e.g., Dimitrov, Phipps, Zahn, & Grafman, 1999; Eslinger & Damasio, 1985). Such patients appear to have preserved intellectual capabilities but, in spite of this, make a number of dreadful real-world decisions. Such decision-making difficulties are especially apparent in their interpersonal life, their work, and the management of their finances (Dimitrov et al., 1999; Eslinger & Damasio, 1985; Goel, Grafman, Tajik, Gana, & Danto, 1998). Finally, such patients appear to undergo a form of personality change, with, for example, once loyal husbands becoming promiscuous (Dimitrov et al., 1999; Ogden, 2005) and once stable earners becoming drifters (Eslinger & Damasio, 1985; Macmillan, 2000).

EMOTION AND INTELLECTUAL LIFE The likely anatomical basis of this class of psychological disorder is also becoming clear. In particular, it now seems apparent that phylogenetically ancient subcortical emotion systems might input to prefrontal cortex (e.g., Damasio, 1994; Panksepp, 1998), thus enabling emotion systems to directly inﬂuence the most sophisticated aspects of human thought (for review, see Bechara et al., 2000a). The primary mechanism by which this seems to occur is rooted in previous learning about the emotional consequences of actions (Bechara et al, 1994; Damasio, 1994). It seems that these emotion systems are capable of providing some sort of average or aggregate from a whole range of previous experiences with regard to any particular object (Bowman & Turnbull, 2004). Thus, damage to ventromedial prefrontal cortex appears to prevent an individual using information based on prior emotional experience to guide future choices (Bechara et al., 2000b; Damasio, 1994). Put more simply, we all have experiences with people in the world, some of which are positive and some negative, but we seem somehow to be able to gauge an average level of

6 Intuition and Schadenfreude

experience in relation to those individuals; for example, judging whether someone is trust- worthy or not, helpful or not, friendly or not. This class of information is potentially very useful in solving problems that are yet to occur in the future, which occur by a process of trial action (Freud, 1915). Thus, we inhibit action in the world, but instead run intellectual scenarios of possible actions, and experience the emotional consequences associated with each outcome (c.f., Damasio, 1994; 1996). For example, one could test out whether a col- league or friend would be a suitable person to babysit your child for an afternoon. This, of course, requires the blending together of ill-specified variables, such as the character of your child, the competence and trustworthiness of the friend, and the likely childcare setting. Nevertheless, it seems clear that a process of trial action plays a potentially central role in the decision-making process, especially with regard to novel scenarios which can be test- ed before being implemented in the real world. The neuroscientific literature supports this claim of anticipatory emotional experience (Bechara, Tranel, & Damasio, 2000; Bechara, Tranel, Damasio, & Damasio, 1996) with its requirement for the rapid evaluation of poorly defined variables. Indeed, the personality change described in frontal patients may be so catastrophic because some of the most complex decision-making circumstances that human beings are likely to encounter are rooted in the interpersonal domain (Dimitrov et al., 1999; Eslinger & Damasio, 1985). The interpersonal world is, of course, characterised by constant change, requiring that you evaluate a number of complex variables, such as the way in which your feelings and your potential actions might interfere with the feelings and potential actions of others. In addition, these judgements must be made ‘online,’ because social settings require virtually immediate responses and leave no time for lengthy cogitation.

EMOTION AND INTUITION In sum, emotion based systems appear to serve as the intermediary between low-level emotional experience, and high-level cognition. Indeed, the interface between emotion and cognition appears to form the basis for the phenomenon that has long been formally described as intuition, that ‘gut feeling’ or ‘hunch’ that we have about the potential outcome of a problem, often in the absence of our being able to consciously identify how we arrived at that solution (Damasio, 1994, pp.187-189; Myers, 2002). Intuition also seems to have an important role to play in a range of imaginative and creative activities, all of which involve potentially operating in a complicated ‘workspace’ which has been incompletely explored: a world in which you know that there might be interesting options available, but in which the landscape has yet to be clearly laid out. While the literature on these intuition related phenomena suggests that emotion can potentially play a substantial role in intellectual life, no one suggests that the role of ration- ality in human decision making should be completely denied (Kahneman & Tversky, 1982). Indeed, there are many settings in which rational choice is an entirely appropriate

7 Philoctetes Center Journal VOLUME 1 · NUMBER 1

way of making decisions (Kahneman & Tversky, 1982). However, there seem to be two general circumstances under which intuition ‘appears’ to have an advantage over pure rea- soning. The ﬁrst of these are settings of high levels of complexity: for example, domains in which you have to track multiple objects and the potential interaction between all such objects (Damasio, 1994). The second of these are settings of high levels of uncertainty or ambiguity: for example, the fact that the world does not consist only of ‘good’ and ‘bad’ objects, in which the ‘good’ objects have exclusively positive properties, and vice versa. Instead, humans are typically faced with decision-making scenarios in which objects have ambiguous or incompletely known pleasantness or unpleasantness. For example, your friendly work colleagues are probably not charming all of the time.

INTUITION AND CREATIVITY IN SCIENCE To take an example of intuition in action, we might perhaps observe its role in the creative process. While imaginative thought is often associated with the arts, there is also clearly a creative and imaginative aspect to scientiﬁc work. Indeed, we might argue that creativity needs to be even more exacting in science than elsewhere, because it is not limitless in its extent (as one might see in the arts) but remains bounded by the inﬂexible character of physical law. How then is such creativity achieved? Here is an example from the work of the physi- cist Richard P. Feynman: In general we look for a new law by the following process. First we guess it. Then we compare the consequences of the guess to see what would be implied if this law that we guessed is right. Then we compare the result of the computation to nature, with experiment or experience. . . . If it disagrees with experiment it is wrong. In that simple state- ment is the key to science. It does not make any difference how beautiful your guess is. It does not make any difference how smart you are, who made the guess, or what his name is — if it disagrees with experiment it is wrong (Feynman, 1965, p.156). This is, of course, a charming account of the importance of empiricism in science. But it also contains some sleight of hand in a crucial aspect of the process. How does Feynman generate his tentative law? Apparently, he recommends that we should ‘guess,’ a surprisingly ‘magical’ suggestion for such an empirically minded thinker! By what process might this ‘guess’ occur? There have been many attempts at describing this potential role for intuition in imaginative thought, from the work of Poincaré as a mathematician (see Damasio, 1994, pp.187-189 for a readable account) to Kekulé von Stradonitz’s famous discovery of the structure of the benzene ring in a dream (Kekulé, 1865). It is clear that the creative process is frequently described as one in which the scientist has some form of ‘hunch’ or ‘intuitive’ feeling about the more likely or plausible solutions to a problem. Based on the personal accounts of this creative process, it appears that these ideas are generated largely (but not entirely) outside of conscious awareness, although they can clearly test-out or ‘interrogate’ this landscape of ideas. This then seems to act as a

8 Intuition and Schadenfreude

springboard for a second phase of investigation, using the more conscious tools of rational enquiry (Damasio, 1994).

MEASURING INTUITION: THE IOWA GAMBLING TASK It is one thing to describe this intuitive process, but another issue entirely to measure it. Currently, the optimal way to measure emotion-based decision making involves the Iowa Gambling Task (Bechara et al., 1994). Here participants freely choose 100 consecutive cards from any of four different decks. They can select a card from any deck, in any sequence, encountering financial reward or punishment on each occasion. Two decks are regarded as ‘good’ (with modest gains but smaller losses). Two are considered ‘bad’ (with high gains but even higher losses). The complex and ambiguous nature of the task ensures that it rapidly becomes very difficult for people to hold in working memory the exact consequences of the last few choices which they have made (Bechara, Damasio, Tranel, & Anderson, 1998). Instead, each of the four decks gradually takes on a particular emotional ‘flavor,’ presumably determined by the aggregate weighting of which deck has led to more ‘good’ than ‘bad’ consequences (Bechara, Damasio, Tranel, & Damasio, 1997; Bowman, Evans, & Turnbull, 2005; Evans, Bowman, & Turnbull, 2005; Maia & McClelland, 2004). Typical performance involves participants initially choosing more bad than good cards. Their choices then gradually drift from levels close to chance, towards more frequent selections from the good rather than the bad decks, though participants cannot formally describe the rational basis for their choices (Bechara et al., 1997).

INTUITION AND EMPATHY We have focused, thus far, on the role for emotion in complex decision-making scenarios, but always in a setting where the emotional experience has been direct. That is, the person who makes the decision is also the person who experiences the consequences of these choices. However, there are many real-world settings in which emotion is indirectly experienced -– which forms the basis of the phenomenon which we describe as empathy. The central role for empathic experience in our society is, of course, well known. It forms the basis for a range of phenomena that underpin civilization (Freud, 1930; Pigman, 1995), such as altruism (Singer, Seymour, O’Doherty, Stephan, Dolan, & Frith, 2006) and the maintenance of law and order (De Quervain et al., 2004). Empathy is of especial importance in the interpersonal domain, made evident by the social failures which typify certain psychiatric conditions, such as autism and Asperger’s syndrome (e.g., Baron-Cohen & Wheelwright, 2004), and sociopathy (e.g., Intrator, Hare, Stritzke, et al., 1997). The literature on empathy has focused almost exclusively on the simplest forms of interpersonal empathic experiences, in order to understand the basic aspects of the problem. In particular, research has focused on empathic experience for pain ( Jackson, Brunet, Meltzoff, & Decety, 2005; Morrison, Poliakoff, Gordon, & Downing, in press; Morrison,

9 Philoctetes Center Journal VOLUME 1 · NUMBER 1

Lloyd, Di Pellegrino, & Roberts, 2004; Singer & Frith, 2005) and simple actions (e.g., Gallese, 2001; Rizzolatti, Fogassi, & Gallese, 2001). It has become clear that certain emotion-related brain areas are active when individuals experience pain themselves, but also when they view an image of somebody else experiencing pain (Morrison et al., in press; Singer & Frith, 2005). While a range of other brain regions (e.g., insula, amygdala, peri- aqueductal grey) may be central for emotional experience (e.g., Damasio, 1994; 1999; Panksepp, 1998), a key brain area for empathic experience (at least in the case of pain) appears to be the anterior cingulate gyrus: a region which lies between the phylogenetically very old subcortical emotion systems and the more sophisticated dorsolateral prefrontal cortex (Morrison et al., 2004).

INTUITION AND INTERNSHIP However, there appears to be a lack of research on empathy in relation to more complex emotional experiences. In particular, empathy may facilitate learning in the domain of expert knowledge and in the process of internship or apprenticeship. For example, our society almost invariably requires individuals not merely to train formally in a university setting but also to have practical experience after formal training. This period of apprenticeship or internship allows the junior trainee an opportunity not only to observe but indirectly experience the outcomes of decisions made by the more senior partner. Thus, internships in medicine, law, engineering, and indeed in practical domains like plumbing and carpentry all require that the more experienced individuals allow the beginners to observe them in action, often in very complex and uncertain situations where they make difﬁcult decisions.

THE PRESENT STUDY In the study described below, we investigate the extent to which it is possible for an ‘intern’ to acquire knowledge on the basis of indirect emotion-based experience. To focus on the sorts of skills that underpin intuition, with high levels of complexity and uncertainty, we used the Iowa Gambling Task. We sought to devise an experimental situation where it was possible to monitor how much empathy was experienced by the ‘observer,’ but also to measure the extent to which this process was helpful in the observer’s later performance.

METHOD Participants A total of 164 undergraduate psychology students from the University of Wales, Bangor, were recruited in dyads and allocated to one of ﬁve experimental groups. Four groups (Experimental conditions 2, 3, 4, and 5; see Table 1) were composed of same-sex pairs of friends. An additional group of unpaired undergraduate psychology students formed a ﬁfth age and education matched experimental condition (see Experimental condition 1; Table 1). None of the participants had any neurological or psychiatric history.

10 Intuition and Schadenfreude

TABLE 1.Demographic Data for Participants in Each of the 5 Experimental Conditions

Experimental Number of Mean age Relationship condition Title participants in years (SD)

1 Unobserved Player 16 20.8 Solo (2m, 14f ) (2.2) 2 No Interaction Viewing-Observer 48 20.6(3.1) Same-sex friends (14m, 34f ) 3 Blind-Observer 42 21.6 Same-sex friends (6m, 36f ) (1.8) 4 Interaction Viewing-Observer 34 19.9 Same-sex friends (6m, 28f ) (1.2) 5 Dual Reward Viewing-Observer 24 21.9 Same-sex friends (6m, 18f ) (4.6)

MEASURES AND APPARATUS Iowa Gambling Task An entirely computerized version of the Iowa Gambling Task (IGT) was programmed in the same manner as in Bechara, Damasio, Damasio, & Lee (1999). It was administered in the real money condition, with an enforced 6-second time delay between card selections (see Bowman & Turnbull, 2003; Bowman, Evans, & Turnbull, 2005). The IGT is composed of four decks of cards, two of which are disadvantageous to gamble on, and two of which are advantageous to gamble on. For the disadvantageous decks (A & B), participants won 10p for every card turn, therefore for every 10 cards turned on each of these decks, the overall reward was £1.00, but due to unpredicted punishment the overall loss was £1.25, thus incurring a net loss of 25p. On the advantageous decks (C & D), participants won 5p for every card turned, therefore for every 10 cards selected on each of these decks, the overall reward was 50p. However, the overall punishment totalled 25p, thus resulting in an overall net gain of 25p. Participants made 100 card selections, and each deck of cards consisted of 60 cards (following Bechara, Dolan, Denburg, Hindes, Anderson, & Nathan, 2001; Table 2 reviews the reward and punishment schedule for each deck).

TABLE 2. Schedules of Reward and Punishment in the Real Money Iowa Gambling Task

Cards per Reward per Punishments per Net standing per Deck deck card turn (pence) 10 card turns 10 card turns (pence)

A 60 10 5 25 loss B 60 10 1 25 loss C 60 5 5 25 gain D 60 5 1 25 gain

11 Philoctetes Center Journal VOLUME 1 · NUMBER 1

Subjective Experience Ratings After each block of 20 card selections, the game was interrupted brieﬂy as participants completed subjective experience ratings, where each deck was rated on a scale from 0 (very bad) to 10 (very good), dependent on how good or bad the participant(s) felt it was (see Bowman, Evans, & Turnbull, 2005).

PROCEDURE In each of the ﬁve conditions, the IGT was played twice – that is, there were 2 phases within each condition. The participants were uninformed at the beginning of the task as to the nature of the second phase of the game. Thus, Phase 1 involved playing the original Iowa Gambling Task which consisted of 100 card selections; a 10-minute break commenced at the end of Phase 1, followed by Phase 2 which consisted of a second session of the IGT, identical to the game in Phase 1. The rationale, speciﬁc procedure, and results for each experimental condition will now be addressed in turn.

EXPERIMENT 1: THE UNOBSERVED PLAYER – BASELINE LEARNING Rationale This baseline condition was created to assess whether repeat exposure to the IGT (playing the game more than once) would increase performance in the same individual. It would, of course, be expected that the Player (‘A,’ see Figure 1) would learn to avoid the disadvantageous decks as normal during the ﬁrst 100 trials of testing (Phase 1; e.g., Bechara et al., 1994; Bowman, Evans, & Turnbull, 2005). During a second 100 trials of testing (Phase 2), due to prior experience with the game, it seems likely that performance would surpass that of Phase 1. Previous studies suggest that gains on repeating the IGT are signiﬁcant, but relatively modest (see Turnbull & Evans, 2006; Turnbull, Evans, Kemish, Park, & Bowman, 2006). In particular, participants begin the new task at a level lower than that which they had achieved at the end of Phase 1, but higher than that which they had achieved at the beginning of Phase 1. They then progress to show more rapid learning than in Phase 1. Procedure Phase 1 Phase 2

FIGURE 1. Representation of the Unobserved Player Testing Paradigm

12 Intuition and Schadenfreude

Phase 1: The Player performs the computerized Iowa Gambling Task (following Bechara et al., 1999) in the real money, time constrained format (following Bowman, Evans, & Turnbull, 2005) alone. Subjective experience ratings were taken from the Player after each block of 20 card selections. Phase 2: The Player performs the same task for a second time, having re-read the exact same set of instructions given at the start of Phase 1. Again, subjective experience ratings were taken from the Player after each block of 20 card selections. Experiment 1: The Unobserved Player – Results Phase 1 and 2: Behavioral Performance. Behavioral performance on each phase of the IGT was scored as the total number of advantageous cards selected (C + D) minus total number of disadvantageous cards selected (A + B) for each block of 20 cards (5 blocks in total). A mean score above 0 represented advantageous selection.

12 Phase 1 Phase 2 10 8 6 4 2 0 M

e -2 a n B

B B B B B B B -4 B B l ( o c l l l l l l l l l o o o o o o o o o c + k c c c c c c c c c

d -6 k k k k k k k k k 1 ) - 0 9 8 7 6 5 4 3 2 1 ( Order of selections in blocks of 20 cards FIGURE a 2. Mean number of advantageous minus disadvantageous card selections across each IGT block and by phase +

In Phase 1, Playersb learn to avoid the disadvantageous decks over time. In Phase 2, participants make a comparatively greater number of

advantageous) card selections across time. (Variance is represented by one standard error.)

During Phase 1 (see Figure 2), as expected, Players initially made more bad card selections than good card selections (Block 1: M = -3.9, SD = 1.35), but between Blocks 2 to 5, Players consistently selected more advantageous than disadvantageous cards (e.g., Block 5: M = 2.75, SD = 2.1). A within-subjects ANOVA found a main effect of Block (F(4, 60) = 3.46, p = .01) highlighting the shift in favor of good cards across time. During every block in Phase 2 (see Figure 2), Players made more good selections than at the same time during Phase 1 (e.g., Block 1: M = -1.0, SD = 1.75; Block 5: M = 6.4, SD = 2.9). A within-subjects ANOVA revealed a main effect of Block during Phase 2 (F(4, 60) = 2.6, p = .04). Comparison of Phase 1 and Phase 2. Despite the improvement in performance between

13 Philoctetes Center Journal VOLUME 1 · NUMBER 1

Phase 1 and Phase 2, a mixed-factor ANOVA found no main effect of Phase (F(1, 30) = 1.3, p = .27), no Block by Phase interaction (F(4, 120) = .06, p = .99), but a significant main effect of Block (4, 120) = 5.88, p < .001) was revealed. A mixed-factor ANOVA run on the last 3 blocks of the game found no significant between groups differences]: Phase (F(1, 30) = .66, p = .42), Block (F(2, 60) = .18, p = .84), Block x Phase (F (2, 60) = .22, p = .80). Behavioral Performance: Comment As expected, Players during Phase 1 of the IGT learned to avoid the disadvantageous decks, at levels typical of IGT performance previously reported (e.g., Bechara et al., 1994; 1996; 1997; Evans, Kemish, & Turnbull, 2004). During Phase 2, Players began at performance levels better than in the initial stages of Phase 1 and showed better performance at each block thereafter. This pattern of performance confirms the prediction that prior exposure to the IGT improves subsequent performance (c.f., Turnbull & Evans, 2006; Turnbull et al., 2006). Phase 1 and Phase 2: Subjective Experience Ratings Subjective experience ratings were calculated as mean good deck (C + D) ratings minus mean bad deck (A + B) ratings for each block of 20 cards selected, and for each phase of play. A mean score above 0 indicates that advantageous decks are rated as better than disadvantageous decks, and vice versa.

8 Phase 1 Phase 2 7

6 5

M 1 e a

n 0 ( c

+ -1 d B ) - B B B B B B B B B l ( -2 o a l l l l l l l l l o o o o o o o o o c + k c c c c c c c c c b Block at which ratings given k k k k k k k k k 1 FIGURE) 3. In Phase 1 the Player showed substantial awareness of which decks were bad and which were good.This pattern continued 0 9 8 7 6 5 4 during Phase3 2,2 with deck1 ratings remaining consistent with those given at the end of Phase 1.

During Phase 1 (see Figure 3), Players initially rated the disadvantageous decks as better than the advantageous decks (M = -.55, SD = .93), but from Block 2 onwards, good decks were consistently and increasingly rated as being better than the bad decks (e.g.,

14 Intuition and Schadenfreude

Block 5: M = 4.88, SD = 2.08). A within-subjects ANOVA confirmed a main effect of Block (F(4, 32) = 3.18, p =.03). In Phase 2 (see Figure 3), Players demonstrated a substantial awareness of the relative goodness and badness of decks from as early as the end of Block 1 (M = 3.0, SD = .85). These ratings remained consistent throughout Phase 2, reaching their highest level by Block 5 (M = 5.77, SD = 1.16). Due to the consistency in ratings, a within-subjects ANOVA did not find a significant effect of Block (F(4, 32) = 1.06, p = .39) Comparison of Phase 1 and Phase 2. A mixed-factor ANOVA performed on the subjective experience data across Phase 1 and Phase 2 revealed a main effect of Block (F(4, 64) = 3.43, p = .01), but neither a main effect of Phase (F(1, 16) = 1.3, p = .28) nor an interaction between Block and Phase (F(4, 64 ) = .97, p = .43). Subjective Experience Ratings: Comment During Phase 1, Players showed a considerable, and increasing, awareness of which decks were good and which were bad; such findings are consistent with those previously reported (e.g. Bowman, Evans, & Turnbull, 2005; Evans, Bowman, & Turnbull, 2005). In Phase 2, Players again rated the good decks as better than the bad decks, but, unlike in Phase 1, this preference was well above chance levels from the very earliest trials of the game. This finding appears to show that prior experience with the game influences the ratings of decks which at first appear to be good but which are, in actual fact, bad.

EXPERIMENT 2: THE NO INTERACTION VIEWING-OBSERVER Rationale In order to investigate the effect of vicarious learning on the Iowa Gambling Task, a paradigm was created which enabled one person, the Player (see ‘A’ in Figure 4) to play the game as in Experiment 1. A same-sex friend, the Observer, (see ‘B’ in Figure 4) was seated next to the Player (A) and was able to observe directly the choices and the consequences of the choices made during the game. Critically, and in order to mirror the effect of vicarious learning in real-world situations, the Observer neither gained nor lost any monies directly. Further, as we were concerned to tap the extent to which the Player’s emotional experience was captured by the Observer, we wished to avoid confounding the measurement of emotion with explicit verbal instruction from the Player. For this reason neither participant was allowed to verbally communicate with the other. The effect of watching the Player during the IGT was assessed by a second phase of testing, where the Observer played the IGT unobserved. One might logically anticipate that there would be one of two possible outcomes. First, if there was something akin to‘100%’vicarious learning,then the Observer would show as much improvement in performance during Phase 2 as was seen during Phase 2 of the Unobserved

15 Philoctetes Center Journal VOLUME 1 · NUMBER 1

Player experiment, where the same person played the game twice. Second, if there was something akin to ‘0%’ vicarious learning, it might be anticipated that the Observer would achieve a level of performance during Phase 2 only as good as the Player during Phase1.

Procedure

FIGURE 4. Representation of the No Interaction Viewing-Observer Testing Paradigm

Phase 1: The Player (A) was given £2.00 start money to gamble with. The Player and Observer (B) were told that any rewards and punishments accrued during the game applied to the Player only.The Player performed the task. The Observer observed both the Player and the screen. Participants were forbidden to verbally interact with one another at any stage during the task. Subjective experience ratings were taken after each block of 20 card selections: These were of three kinds. First, the Player rated his/her own subjective awareness, on the computer, out of view of the Observer. Additionally, the Observer provided two sorts of subjective experience ratings, on paper, again out of view of the Player. These ratings were, ﬁrst, the Observer’s own subjective impression of the decks, and second, an impression of how he/she thought the Player would rate each deck. The Player then left the testing room. Phase 2: The Observer performed the task unobserved. Again, subjective experience ratings were taken from the Observer after each block of 20 card selections. Experiment 2: The No Interaction Viewing-Observer – Results Phase 1 and 2: Behavioral performance. As expected in Phase 1 of the IGT, (see Figure 5), participants in the Player condition (n = 24) began by selecting disadvantageously (M = - 4.75, SD = 5.07), but by Block 2 were selecting more good cards than they were bad (M = 1.92, SD = 6.91). This pattern increased in favor of advantageous selection throughout the 100 card selections, revealing the characteristic learning proﬁle associated with the IGT (e.g., Block 5; M = 6.67, SD = 7.23). A within-subjects ANOVA revealed a main effect of Block (F(4, 92) = 11.95, p < .001) highlighting the increasing preference for advantageous selections as the game progressed. During Phase 2, however, participants in the Observer condition (n = 24) began by selecting almost as many bad cards as good cards during Block 1 (M = -.67, SD = 8.06); a pattern which continued throughout the duration of the game (e.g., Block 5; M =

16 Intuition and Schadenfreude

1.75, SD = 7.58). A within-subjects factor ANOVA revealed that there was no main effect of Block (F(3.04, 70.03) = .53, p = .67), illustrating that there was no shift in favor of either good or bad decks during the game.

Phase 1: Player Phase 2: Observer 10

-2 M e B B B B B B B B B B

a -4 l l l l l l l l l l n o o o o o o o o o o c c c c c c c c c c ( k k k k k k k k k k

c -6 + 5 4 3 2 1 5 4 3 2 1 d

) -8 - ( a Order of selections acrossblock + b

FIGURE 5. In) Phase 1, the Player shows substantial learning across time. In Phase 2, the Observer shows no signiﬁcant learning across time. (Variance is represented as one standard error.)

Comparison of Phase 1 and Phase 2. A mixed-factor ANOVA performed between Phase and across each of the 5 blocks of the game found a main effect of Block (F(4, 184) = 8.4, p < .001), a significant interaction between Block and Phase (F(4, 184) = 3, 4, p = .004), but no main effect of Phase (F(1, 46) = .92, p = .34). However, a mixed-factor ANOVA run on the final 3 blocks of the game revealed that there was no main effect of Block (F(2, 92) = 2.1, p = .13), no interaction between Block and Phase (F(2, 92) = .48, p = .63), but a significant main effect of Phase (F(1, 46) = 4.1, p = .05). Behavioral Performance: Comment The results from the behavioral analysis revealed that during Phase 1, Players learned to avoid the disadvantageous decks as the game progressed. Somewhat unexpectedly, there was no significant avoidance of the bad decks across time when the Observers played the game during Phase 2 of the experiment. In fact, performance by the Observers in Phase 2 did not deviate much from chance; that is, almost as many bad card selections as good card selections were made. Comparatively, across the final three blocks of the game (i.e., card selections 40 to 100) mean Observer performance was significantly worse than mean Player performance. This finding is of course sharply at odds with the ‘100%’ vicarious learning prediction suggested above. Remarkably, it also suggests a significantly lower level of performance than even the ‘0%’ vicarious learning prediction. Indeed, it suggests that the Observer’s performance was worse than that of a novice.

17 Philoctetes Center Journal VOLUME 1 · NUMBER 1 Phase 1 & 2: Subjective Experience Ratings During Phase 1 (see Figure 6), Players rated the advantageous decks as better than the disadvantageous decks from the outset of the game (e.g., Block 1: M = 1.27, SD = .91; Block 4: M = 5.55, SD = .91). This ﬁnding is consistent with the subjective experience ratings given by Players during Experiment 1, and is also consistent with the behavioral performance by Players in Experiment 2. Except for during Block 1 (M = -1.41, SD = 1.16) Observers also rated the good decks as better than the bad decks during Phase 1 of the IGT (e.g., Block 4: M = 2.0, SD = 1.28), although to a lesser degree than the Players during Blocks 3 and 4 (see Figure 6). Lastly during Phase 1, Observers rated how they predicted Players would rate the decks after each block of 20 card selections. As can been seen from Figure 3, Observers tended to mirror their own ratings with the predicted ratings for Players (e.g., Block 1: M = -2.15, SD = 1.3) although during Blocks 4 and 5, Observers predicted ratings were higher than their actual ratings (e.g., Block 4: M = 2.95, SD = 1.39).

Phase 1 Phase 2 8

-2 B B B B B B B B B B l l l l l l l l l l

o o o o o o o o -4o o M c c c c c c c c c c e k k k k k k k k k k a

5 4 3 2 1 5 4 3 -62 1 n

g Time at which ratings given o o

d Phase 1: Player Phase 1: Observer rating Player - b

a Phase1: Observer Phase 2: Observer d d

FIGUREe 6. In Phase 1 there was substantial awareness of which decks were good and bad in all three conditions: the Player (N), the c

Observerk (L), and the Observer’s prediction of the Player’s ratings (I).These effects grow rapidly early in the task, and remain positive for

the remainderr of Phase 1. In Phase 2, the Observer () again showed substantial awareness regarding the relative goodness and badness of a t

each ofi the decks.This pattern persisted throughout Phase 2. n g s To analyze the deck ratings during Phase 1 further, t-tests were run on these data. An independent samples t-test found that, interestingly, there were no significant differences between Players actual deck ratings and the predicted deck ratings attributed to Players by Observers. However, there was a significant difference in ratings between Players actual deck ratings and Observers actual deck ratings during Block 4 of Phase 1 (t(42) = 2.4, p = .023). Paired samples t-tests identified a significant difference between Observers deck ratings and Observers predicted ratings during Block 5 (t(20) = 2.3, p = .04), but at no other point during Phase 1. During Phase 2 (see Figure 6), it can be seen that Observers deck ratings were consis-

18 Intuition and Schadenfreude

tently and increasingly above 0 as the game progressed, illustrating that good decks were always perceived as better than bad decks (e.g., Block 1: M = 1.95, SD = .76; Block 2: M = 4.14, SD = 1.06). Contrary to Players performances during Phase 1, the subjective experience ratings by Observers during Phase 2 were substantially different from the Observer’s behavioral performance during Phase 2. Comparison of Phase 1 and Phase 2. A mixed-factor ANOVA performed on the subjective experience data across both phases of the IGT and between each type of rating revealed that there was a significant main effect of Block (F(4, 332) = 17, p < .001), a significant Type of Rating by Block interaction (F(12, 332) = 2.23, p = .01), but no main effect of Type of Rating (F(3, 83) = 1.12, p = .35). Along with the t-test results reported previously, paired t-tests between Observers’ actual deck ratings during blocks 1, 2 and 4 (t(21) = 2.1, p = .045; t(21) = 2.3, p = .03; t(21) = 2.0, p = .05) of Phase 1 and 2, account for the significant Type of Rating by Block interaction. Subjective Experience Ratings: Comment The subjective experience ratings during Phase 1 are interesting for several reasons. First, the Players appear to have some degree of explicit awareness of the relative goodness and badness of the decks from the earliest trials of the game. Centrally, the Observers not only appear to be aware of the nature of the decks from their own perspective, but are also able to rate how the Players might feel about the decks. Thus, it would be fair to surmise that both Players and Observers have a good awareness of which decks are advantageous and which are disadvantageous during Phase 1. In Phase 2, the Observer again demonstrates an explicit awareness of which decks are good and which are bad. Surprisingly, however, there is a striking dissociation between Observers’ subjective awareness of the decks during Phase 1 and 2, and their behavioral performance. That is, although seemingly aware of the valence of the decks, behavioral card choice does not seem to be influenced by this knowledge. This contrasts starkly with the behavioral performance and subjective awareness ratings of the Players, which remain compatible throughout the duration of Phase 1. Experiment 2 - Phase 1 and 2: Facial Expression Analysis In order to better understand the nature of the interaction between participants, we also studied video footage of 6 couples during both Phase 1 and Phase 2. We coded whether each reward or punishment trial produced either a positive (e.g., laughing, smiling) or a negative (frowning, angry) response. The data in Figure 7 demonstrates that the Players, during Phase 1, show an essentially congruent pattern of emotional responses. That is, they show many more instances of positive emotions in relation to reward trials (3.83 vs. 0), and many more negative than positive emotions to punishment trials (8.67 vs. 3.67 respectively).

19 Philoctetes Center Journal VOLUME 1 · NUMBER 1

10 8.67 9 8 7 6 5 3.83 3.67 4 3

N 2 u

m 1

b 0

e 0 r

o Rewarding consequence Punishing consequence f

o Outcome after card selection c c a s

i Positive expression Negative expression o n s FIGURE 7. Number of Positive and Negative Facial Expressions Associated With Rewarding and Punishing Outcomes for the Player During Phase 1

However, the Observer, during Phase 1 (see Figure 8) shows a starkly contrasting effect. While Observers also show positive emotions during the Players’ reward trials, they show a striking preference for positive emotion in response to the Players’ punishment trials (with 6 instances of positive emotion compared with only 1.67 occurrences of positive emotion). This ﬁnding might well represent a phenomenon akin to schadenfreude, the feeling of pleasure at another’s misfortune. Indeed, it may be that the Players’ occasionally paradoxical response of positive emotion to a punishing trial may simply be a social response to the Observers’ pleasure at their own misfortune.

10 s

n 9 o i

s 8 a

c 7 c 6 o

f 6 o

. 5 o 3.67 n 4 n

a 3 e 1.67

M 2 1 0 0 Rewarding consequence Punishing consequence Outcome after card selection

Positive expression Negative expression

FIGURE 8. Number of Positive and Negative Facial Expressions Associated With Rewarding and Punishing Outcomes for the Observer During Phase 1

20 Intuition and Schadenfreude

Finally, there were fewer emotional responses subsequent to reward trials during Phase 2 (see Figure 9). This is perhaps consistent with the well-known ‘signalling’ or commu- nicative aspects of emotion (Ekman, 1993), such that there is less need for a participant to be emotionally expressive when alone. Interestingly, during Phase 2 the Observer seemed to display as much positive as negative emotion in response to a directly punishing outcome (4.83 vs. 4.33). This contrasts substantially with the expression proﬁle seen in the Player during Phase 1, where more than dou- ble the number of expressions accompanying a punishment trial were negative (8.67 vs. 3.67). It is possible that this proﬁle of emotional expression arose due to the attributing of punishment decks with a positive feeling during Phase 1.

s 9 n o i 8 s a

c 7 c

o 6 f 4.83 o 5 4.33 r e 4 b

m 3 u

N 2 1 1 0 0 Rewarding consequence Punishing consequence Outcome after card selection

Positive expression Negative expression

FIGURE 9. Number of Positive and Negative Facial Expressions Associated With Rewarding and Punishing Outcomes for the Observer During Phase 2

EXPERIMENT 3: THE BLIND-OBSERVER Rationale The poor behavioral performance by the Observer during the No Interaction Viewing- Observer experiment (Experiment 2, Phase 2) was unexpected. As a result of this ﬁnding, a control condition was devised to investigate whether the Observers’ performances were confounded by simply having been present in the same room as their friends during the ﬁrst phase of testing. In this new Blind-Observer experiment, the Player (see ‘A’ in Figure 10) played the game as in Experiment 1, with the Observer (see ‘B’ in Figure 10) seated in the same room as the Player. However, while the Observers were able to observe directly the facial expressions and bodily movements of the Players, their location made them unable to view the choices and consequences on the computer screen. In order to match Experiment 2 in every other aspect, the Observer neither gained nor lost any money, and

21 Philoctetes Center Journal VOLUME 1 · NUMBER 1

neither the Player nor the Observer was allowed to communicate verbally. A second phase of testing, exactly as in Experiment 2, assessed IGT performance in the Observer. It was expected that the Observer would learn on the IGT at a level akin to that of the ‘0%’ vicarious learning prediction. That is, being unable to view the IGT during Phase 1, the Observer during Phase 2 should perform in the same manner as a novice, i.e., like the Players in Phase 1 of Experiments 1 and 2. Procedure

FIGURE 10. Representation of the Blind-Observer Testing Paradigm

Phase 1: The Player (A) played the IGT. The Observer (B) viewed the Player performing the task, but could not view the computer screen. Subjective experience ratings were taken from the Player only, via the computer (out of view of the Observer), at the end of each block of 20 card selections. Participants were not allowed to verbally interact with one another. The Player then left the testing room. Phase 2: The Observer performed the task unobserved. Subjective experience ratings were taken from the Observer at the end of each block of selections. Experiment 3: The Blind-Observer Results Phase 1 & 2: Behavioral Performance. During Phase 1 (see Figure 11), as expected, the Player showed an initial preference for the bad decks during Block 1 (M = -4.7, SD = .84), but learned to avoid the disadvantageous decks as the game progressed (e.g., Block 5: M = 4.6, SD = 1.9). A within-subjects ANOVA highlighted this learning over time by revealing a significant main effect of Block (F(4, 80) = 9.02, p < .001). During Phase 2 (see Figure 11) the Observer, consistent with the Player, demonstrated a preference for the bad decks during Block 1 (M = -1.8, SD = 1.6), but increasingly avoid- ed these disadvantageous decks during the remainder of the game (e.g., Block 5: M = 7.2, SD = 2.0). A within-subjects ANOVA confirmed that learning during this phase was significant, revealing a significant main effect of Block (F(4, 80) = 10.57, p < .001). Comparison of Phase 1 and Phase 2. A mixed-factor ANOVA revealed a significant main effect of Block (F(4, 160) = 19.16, p < .001), but neither a Block by Phase interaction (F(4, 160) = .20, p = .88), nor a main effect of Phase (F(1, 40) = 1.99, p =.16). A mixed-factor ANOVA run on the final three blocks of the game revealed no main effect of Block (F(2, 80) = 1.18, p = .31), no Block by Phase interaction (F(2, 80) = .29, p = .75), and no main effect of Phase (F(1, 40) = 1.3, p =.26). 22 Intuition and Schadenfreude

Phase 1: Player Phase 2: Observer 10

-2 M e B B B B B B B B B B a -4 l l l l l l l l l l n o o o o o o o o o o c c c c c c c c c c ( k k k k k k k k k k c -6 + 5 4 3 2 1 5 4 3 2 1 d

) -8 - ( a

+ Order of selections across block b ) FIGURE 12. In Phase 1, the Player showed a marked awareness regarding which decks were good and which decks were bad. In Phase 2, the Observer rated the decks in the same way as the Player did during Phase 1. (Variance is represented as one standard error.)

Behavioral Performance: Comment The behavioral analysis revealed that during Phase 1, Players learned to make more good than bad card selections during the course of the game. As expected, and in accordance with the ‘0%’ vicarious learning prediction, the Observers performed at a level typical of that achieved by a novice. These findings suggest that it was not being in the same room as the Player during Phase 1 that resulted in the poor behavioral performance of Observers during Experiment 2 (Phase 2 of the No Interaction Viewing-Observer experiment). Phase 1 and 2: Subjective experience ratings. In Phase 1 (see Figure 12) as expected, Players demonstrated considerable awareness regarding the relative goodness and badness of the decks. From Block 2 onwards advantageous decks were rated as better than disadvantageous decks (e.g., Block 5: M = 3.5, SD = 1.1). A within-subjects ANOVA confirmed that there was a main effect of Block in accordance with increasing preference for advantageous decks across time (F(4, 56) = 2.78, p = .04). In Phase 2, the Observers’ deck ratings were consistent with those given by the Players, demonstrating a substantial and increasing ratings preference for the advantageous decks (e.g., Block 5: M = .43, SD = 1.5). A within-subjects ANOVA established a significant main effect of Block (F(4, 52) = 3.65, p =. 01). Comparison of Phase 1 and Phase 2. A mixed-factor ANOVA revealed a significant main effect of Block (F(4, 108) = 6.32, p < .001), but neither a main effect of Phase (F(1,27) = .63, p = .44), nor an interaction between Phase and Block (F(4, 108) = .13, p = .97). These findings confirm that there were no significant differences in subjective experience between groups.

23 Philoctetes Center Journal VOLUME 1 · NUMBER 1 Subjective Experience Ratings: Comment The findings of the subjective experience analysis revealed that there was no significant difference in deck ratings between Phase 1 and Phase 2; Players and Observers both exhib- ited substantial awareness regarding valence of the decks. These ratings were consistent with subjective experience ratings given by Players during Phase 1 of both Experiment 1 and Experiment 2, and with those previously reported during the first 100 trials of play (see Bowman et al., 2005; Evans et al., 2005). These findings confirm that the ‘blind’ Observer played the game as well as a novice (i.e., in accordance with the ‘0%’ vicarious learning supposition).

EXPERIMENT 4: THE INTERACTION VIEWING-OBSERVER Rationale The Blind-Observer experiment (Experiment 3) could not account for the poor behavioral performance of Observers during the No Interaction Viewing-Observer task (Experiment 2). Therefore, a new task was developed to investigate whether preventing participants from verbally communicating during Phase 1 might have produced the unexpected ﬁnding of less than ‘0%’ vicarious learning in the Observer during Experiment 2. The rationale for forbidding verbal interaction between the Player and Observer during Experiment 2 was in order to assess the extent to which emotional experience was captured by the Observer. However, we note that the real-world experience of vicarious learning (e.g., in the many forms of ‘internship’ that our society uses) is not one of poorer-than-novice performance. It might follow that if verbal communication was allowed between participants, akin to that seen in real-world situations, (i.e., the Player provides commentary regarding the properties of the decks) then the Observer should show increased performance during Phase 2. Ideally, this might even reach the ‘100%’ vicarious learning prediction, matching the behavioral performance levels of the Unobserved Player during Phase 2 of Experiment 1. Procedure

FIGURE 13. Representation of the Interactive Viewing-Observer Testing Paradigm

Phase 1: The Player and the Observer were told that any rewards and punishments accrued during the game applied to the Player only. The Player played the IGT while the Observer viewed both the Player and the computer screen. In exactly the same manner as

24 Intuition and Schadenfreude

in Experiment 2 (i.e., out of view from one another), subjective experience ratings were taken from the Player and the Observer. The Observers additionally provided subjective experience ratings based on how they thought the Players would rate each deck. The Players were explicitly instructed to provide a commentary to the Observers explaining why they were choosing any given card and what they were learning as the game progressed. The Observers were allowed to ask questions and freely comment on the game. The Player then left the testing room. Phase 2: The Observer performed the task unobserved. Subjective experience ratings were taken from B. Experiment 4: The Interaction Viewing-Observer – Results Phase 1 and 2: Behavioral Results. During Phase 1 (see Figure 14), Players initially began by selecting more disadvantageous cards than advantageous cards (M = -4.1, SD = 1.36), as typical. Over the remainder of the game, more good cards than bad cards were selected during every block (e.g., Block 3: M = 4.94, SD = 1.55; Block 5: M = 4.82, SD = 1.71). A within-subjects ANOVA conﬁrmed that this preference for good cards was signiﬁcant over time (F(4, 64) = 9.3, p < .001).

Phase 1 (Player) Phase 2 (Observer)

14 12 10 8 6 4 2 0 -2 -4 B B B B B B B B B B l l l l l l l l l l o o o o o o o o o o M -6 c c c c c c c c c c k k k k k k k k k k e -8 5 4 3 2 1 5 4 3 2 1 a n Order of card selections ( c + d ) -

FIGURE( 14. In Phase 1, Players learn to avoid the disadvantageous decks over time. In Phase 2, Observers commence the game at a a

level well+ above chance, and continue to show a preference for the advantageous decks for the duration of the game. (Variance is repre- sentedb as one standard error.) ) s e l e c

Duringt Phase 2 (see Figure 14), the Observers demonstrated a proﬁle of performance i o

unliken that of the Players’. Indeed, Observers began by selecting at a level well above s chance (Block 1: M = 5.33, SD = 2.0), and consistently selected cards above this level during the remainder of the game (e.g., Block 3: 9.3, SD = 2.5; Block 5: M = 6.0, SD = 2.8). A within-subjects ANOVA did not reveal a main effect of Block (F(4, 56) = .66, p = .62)

25 Philoctetes Center Journal VOLUME 1 · NUMBER 1

confirming that card selections during this phase remained stable over time. Comparison of Phase 1 and Phase 2. Comparatively, the Observers selected substantially more good than bad cards during Block 1 (M = -4.1, SD = 1.36) than did Players (M = 5.3, SD = 2.0). An independent samples t-test confirmed that this difference was statistically significant (t(32) = 3.24, p = .003). A mixed-factor ANOVA revealed a main effect of Block (F(4, 120 )= 4.95, p < .001), a significant Block by Phase interaction (F(4, 120) = 2.84, p = .03). The difference in performance between groups in each Phase was margin- ally significant (F(1, 30) = 4.1, p = .052). A mixed-factor ANOVA run on the final three blocks of the game found no significant main effect of Block (F(2, 60) = .64, p = .5), and neither a significant Block by Phase interaction (F(2, 60) = 1.4, p = .26), nor a significant main effect of Phase (F(1, 30) = .48, p = .49). Behavioral Performance: Comment The behavioral analysis revealed that during Phase 1, Players performed at a level typical of that seen in Phase 1 of Experiments 1, 2, and 3. Interestingly, during Phase 2, Observers selected well above chance from the outset of the game. This finding suggests that previous interactive experience of the IGT improves future performance during the game. Indeed, the Observers’ good performance during Block 1 of Phase 2 may even be better than that of Players (who were playing the game for a second time) during Phase 2 of Experiment 1. Thus, the behavioral performance of the Observer during this experiment was consistent with the ‘100%’ vicarious learning prediction. Phase 1 and 2: Subjective Experience Ratings. During Phase 1 (see Figure 15), Players rated the good decks as better than the bad decks from the earliest trials of the game (Block 1: M = 1.3, SD = .48). This finding is consistent with the subjective experience ratings given by Players during Phase 1 of Experiment 1 and 2. Consistent with the Players, Observers also rated the advantageous decks as better than the disadvantageous decks (Block 1: M = .82, SD = .79) at the beginning of the game, with this preference increasing as the game progressed (e.g., Block 5: M = 4.88, SD = 1.6). Finally, during Phase 1, the Observers’ ratings which predicted the subjective awareness of the Players’, paralleled the actual ratings provided by the Observers (e.g., Block 1: M = -65, SD = 1.2; Block 5: M = 4.1, SD = 1.24). Independent and between-samples t-tests conducted on this data confirmed that there were no significant differences in deck ratings between conditions at any Block during Phase 1.

26 Intuition and Schadenfreude

Phase 1 Phase 2

10 8 6 4 2 0 -2 M B B B B B B B B -4B B e l l l l l l l l l l o o o o o o o o o o a c c c c c c c c c c

n Time at which ratings given k k k k k k k k k k 5 4 3 2 1 5 4 3 2 1 g o

o Phase 1: Player Phase 1: Observer d

- Phase 1: Observer rating Player Phase 2: Observer b a d

FIGUREd 15. In Phase 1, there was substantial awareness of which decks were good and bad in all three conditions: the Player (N), the Observere ( ), and the Observer’s prediction of the Player’s ratings ( ). Deck ratings were strikingly similar in all three conditions. In Phase c I L

2, the Obserk ver () again showed considerable awareness regarding the deck properties. r a t i n

Duringg Phase 2 (see Figure 15) it can be seen that Observers’ deck ratings were consistently and substantially above 0 throughout the game (e.g., Block 1: M = 4.1, SD = 1.5; Block 3: M = 7.5, SD = 1.6; Block 5: M = 7.0, SD = 1.63). In addition, at every Block in Phase 2, the Observers’ ratings were higher than those given at that same block in any condition during Phase 1. Comparison of Phase 1 and Phase 2. A mixed-factor ANOVA performed on the subjective experience data across both phases of the IGT and between each type of rating, revealed that there was a significant main effect of Block (F(4, 248) = 13.2, p < .001), but no main effect of Type of Rating (F(3, 62) = 2.26, p = .09), and no Block by Type of Rating interaction (F(12, 248) = .75, p = .70). Subjective Experience Ratings: Comment The subjective experience ratings provided during Phase 1, in all three conditions, were in line with those given during the No Interaction Viewing-Observer experiment (Experiment 2). These were at levels typical of those seen during the first 100 trials of the Gambling Task (e.g., Bowman et al., 2005; Evans et al., 2005). Interestingly, during Phase 2, Observers rated the good decks as better than they had during Phase 1. In fact, the ratings provided by Observers during Phase 2 were higher than those given in any condition during Phase 1. This finding might suggest that as well as an enhanced behavioral performance by Observers during Phase 2, verbal interaction between the Player and Observer during Phase 1 may also enhance subjective experience of deck valence. This finding is especially interesting as it is greater than that seen during the

27 Philoctetes Center Journal VOLUME 1 · NUMBER 1

Unobserved Player experiment (Experiment 1), where the same participant played the game for a second time. Thus, verbal interaction during Phase 1 of the IGT appears to positively inﬂuence subsequent performance. Experiment 4 - Phase 1 and 2: Facial Expression Analysis As in Experiment 2, the No Interaction Viewing-Observer condition, we also studied video footage of 6 couples during both Phase 1 and Phase 2 of the Interactive Viewing- Observer condition. We coded whether each reward or punishment trial produced either a positive (e.g., laughing, smiling) or a negative (frowning, angry) response. The data in Figure 16 demonstrates that, as might be logically expected, the Player during Phase 1 shows many more instances of positive than negative emotion in relation to reward trials (9.83 vs. 3.67 respectively), and only negative emotions in response to punishment trials (17.5 vs. 0 respectively).

s 20

n 17.5

o 18 i

s 16 a c

c 14 o

f 12 9.83 o

. 10 o

n 8 n

a 6

e 3.67 4 M 2 0 0 Rewarding consequence Punishing consequence Outcome after card selection

Positive expression Negative expression

FIGURE 16. Number of Positive and Negative Facial Expressions Associated With Rewarding and Punishing Outcomes for the Player During Phase 1

In contrast, the Observer during Phase 1 seems to show slightly more negative than positive emotion in response to the Player being rewarded (8.0 vs. 5.83 respectively; see Figure 17). Despite this, the Observer in this condition displays a substantial amount of negative emotion in response to the Player being punished during Phase 1. Indeed, congruent with the Player, the Observer does not express any positive emotion after the Player has been punished. This contrasts greatly with the ﬁndings in the No Interaction Viewing- Observer condition where the Observers seemed to derive some pleasure (schadenfreude) in watching their friends being penalized during Phase 1.

28 Intuition and Schadenfreude

12 s

n 11 o i

s 10 8.83 a

c 9 8 c 8 o

f 7

o 5.83

. 6 o

n 5

n 4 a

e 3

M 2 1 0 0 Rewarding consequence Punishing consequence Outcome after card selection

Positive expression Negative expression

FIGURE 17. Number of Positive and Negative Facial Expressions Associated With Rewarding and Punishing Outcomes for the Observer During Phase 1.

Finally, as in Experiment 2, there were fewer emotional responses subsequent to reward trials during Phase 2 (see Figure 18). In sharp contrast to the findings in the No Interaction Viewing-Observer condition, the Observers in this condition displayed a great deal more negative emotion in response to a punishing card selection (10.83 vs. 1.66 respectively). Thus, in response to punishment during Phase 2, the Observers demonstrated a profile of expression befitting of one having been punished, and similar to that shown by their friends during Phase 1 of the task.

12 s 10.83 n 11 o i

s 10 a

c 9 c 8 o

f 7 o

. 6 o

n 5

n 4 a

e 3 1.66 M 2 1 0 0.16 0 Rewarding consequence Punishing consequence Outcome after card selection

Positive expression Negative expression

FIGURE 18. Number of Positive and Negative Facial Expressions Associated With Rewarding and Punishing Outcomes for the Observer During Phase 2

29 Philoctetes Center Journal VOLUME 1 · NUMBER 1

EXPERIMENT 5: THE DUAL REWARD VIEWING-OBSERVER Rationale The ﬁndings of Experiment 3 (the Blind-Observer) were consistent with a ‘0%’ vicarious learning prediction, and those of Experiment 4 (Interaction Viewing-Observer) were consistent with a ‘100%’ vicarious learning prediction. However, neither of these studies was able to account for the unexpected less than ‘0%’ vicarious learning performance of the Observer during Experiment 2 (the No Interaction Viewing-Observer). Thus, a third control experiment was devised, identical in nature to Experiment 2, but in which the losses and gains sustained by the Player during Phase 1 of testing, were also sustained by the Observer. As with Experiment 2, the Observer and Player were forbidden to interact verbally, and the Observer was unable to inﬂuence card choice in any way. By making the consequences of card choice directly relevant to the Observer, it was predicted that the Observer would have a more explicit experience of the rewards and punishments of card selections on certain decks. Thus, it was anticipated that during Phase 2, the Observer would perform at a level consistent with the ‘100%’ vicarious learning prediction. Procedure

FIGURE 19. The Dual Reward Viewing-Observer Testing Paradigm

Phase 1: The Player and the Observer were given £2.00 start money. The Player and the Observer were told that any rewards and punishments accrued by the Player during the game, applied to both the Player and the Observer. The Player performed the task while the Observer viewed both the Player and the computer screen. Subjective experience measures were taken from the Player and the Observer (in exactly the same way as in Experiment 2 and 4). Additionally the Observers provided subjective experience ratings based on how they thought the Players would rate each deck. Participants were not allowed to verbally interact with one another. The Player then left the testing room. Phase 2: The Observer performed the task unobserved. Subjective experience ratings were taken from the Observer. Experiment 5: The Dual Reward Viewing-Observer Results Phase 1 & 2: Behavioral Results. During Phase 1 (see Figure 20), the Player showed an initial preference for the disadvantageous decks (M = -2, SD = 1.81) and selected more good

30 Intuition and Schadenfreude

than bad cards during the remainder of the game (e.g., Block 3: M = 5.8, SD = 1.1; Block 5: M = 4.0, SD = 1.6), as typical of performance during Phase 1. A within-subjects ANOVA conﬁrmed that the shift in favor of the good decks was signiﬁcant across time (F(4, 44 ) = 5.5, p = .001).

Phase 1: Player Phase 2: Observer

6 4

M -2 e a n B B B B B B B B -4B B l l l l l l l l l l ( o o o o o o o o o o c c c c c c c c c c c + k k k k k k k k -6k k d 5 4 3 2 1 5 4 3 2 1 )

- Order of selections in blocks of 20 cards ( a + b

FIGURE) 20. In Phase 1, Players learn to avoid the disadvantageous decks over time. In Phase 2, Observers perform the game in a similar manner to those playing the game for the ﬁrst time, although there is an uncharacteristic decline in selection of advantageous cards during Block 5.

During Phase 2 (see Figure 20), the Observers displayed an initial preference for the disadvantageous decks during Block 1 (M = -1.7, SD = 1.7) with a shift in favor of the advantageous decks during the first four blocks of the game (e.g., Block 3: M = 6.7, SD = 2.6). During Block 5, however, a marked decline in selection of advantageous cards was found (M = 1.2, SD = 2.9). In spite of this, a within-subjects ANOVA confirmed a main effect of Block (F(4, 44) = 3.65, p = .01). Comparison of Phase 1 and Phase 2. Comparatively, the performance of Observers during Phase 2 of the IGT was similar to that of the Player during Phase 1 of the game. In fact, the profile of performance was the same for both Player and Observer in each Phase, except for during Block 5, where the Observer selected more disadvantageous cards than did the Player (M = 1.2, SD = 2.9; M = 4.0, SD = 1.6, respectively). However, an independent t- test did not uncover a statistically significant difference in Block 5 performance between the Player and the Observer (t(22) = .84, p = .41). A mixed-factor ANOVA revealed a main- effect of Block (F(2.3, 49.5) = 8.2, p < .001), but neither a significant Block by Phase interaction (F(2.3, 49.5) = .65, p = .63) nor a significant main effect of Phase (F(1, 22) = .004, p = .95). A mixed-factor ANOVA run on the last three blocks of the game revealed a main effect of Block (F(2, 44) = 5.1, p = .01), but neither a significant Block by Phase interaction (F(2, 44) = 1.2, p = .32), nor a main effect of Phase (F(1, 22) = .12, p =.74).

31 Philoctetes Center Journal VOLUME 1 · NUMBER 1 Behavioral Performance: Comment In both Phase 1 and Phase 2, there was a substantial increase in performance across blocks. Importantly, the magnitude of this increase was not significantly different between the two phases. Thus, in Experiments 2, 4, and 5 there were virtually identical experimental circumstances for the task, with only minor differences with regard to participant interaction or in the receipt of reward. When there was no interaction (Experiment 2), there was virtually no learning in Phase 2. However, when there was verbal interaction between participants during Phase 1 (Experiment 4), and when there was explicit reward for the Observer during Phase 1 (but no verbal interaction; Experiment 5), then substantial learning occurred during Phase 2 of the game. This suggests that any form of ‘investment’ in the game by the Observer during Phase 1, positively influences later performance, and appears to negate any effects of schadenfreude. Phase 1 and 2: Subjective Experience Ratings. During Phase 1 (see Figure 21), Players rated the good decks as better than the bad decks from the earliest selections of the game (Block 1: M = .2, SD .87), a pattern maintained across the duration of the game. After a slight initial preference for the disadvantageous decks (M = -.5, SD 1.0), the Observer continued to rate the good decks as better than the bad decks throughout the remainder of the game. As in Experiment 4, the ratings provided by the Observer predicting the Players subjective awareness, paralleled the actual ratings provided by the Observer during Phase 1. Independent and between-samples t-tests conducted on this data confirmed that there were no significant differences in deck ratings between conditions at any Block during Phase 1.

12 s

n 11 o i

s 10 8.83 a

c 9 8 c 8 o

f 7

o 5.83

. 6 o

n 5

n 4 a

e 3

M 2 1 0 0 Rewarding consequence Punishing consequence Outcome after card selection

Positive expression Negative expression

FIGURE 21. In Phase 1, there was substantial awareness of which decks were good and bad in all three conditions the Player (N), the Observer (I), and the Observer’s prediction of the Player’s ratings (L). Deck ratings were strikingly similar in all three conditions. In Phase 2, the Observer () again showed considerable awareness regarding the deck properties.

32 Intuition and Schadenfreude

During Phase 2, (see Figure 21) the Observers’ deck ratings began with a slight preference for the disadvantageous decks (M = -.54, SD = 1.4). Across the duration of the game, however, a marked preference for the advantageous decks was demonstrated at every Block (e.g., Block 3: M = 4.18, SD = 1.6, Block 5: M = 3.6, SD = 1.5). Comparison of Phase 1 and Phase 2. A mixed-factor ANOVA performed on the subjective experience data across both phases of the IGT and between each type of rating, revealed that there was a significant main effect of Block (F(4, 172) = 15.3, p < .001), but neither a significant interaction between Block and Type of Rating (F(12, 172) = 1.1, p = .38), nor a significant main effect of Type of Rating (F(3, 43) = .19, p =. 90). Subjective Experience Ratings: Comment The subjective experience ratings provided by participants during Phase 1, in all three conditions, were consistent with those during the No Interaction Viewing-Observer experiment (Experiment 2) and the Interaction Viewing-Observer experiment (Experiment 4). These were at levels typical of those seen during the first 100 trials of the Gambling Task (e.g., Bowman et al., 2005; Evans et al., 2005). During Phase 2, the Observers continued to rate the good decks as better than the bad decks from Block 2 onwards. This pattern of subjective experience is consistent with deck ratings typically provided by the Player during Phase 1 of the game (see Experiment 1, 2, 3, and 4). Experiment 5 - Phase 1 and 2: Facial Expression Analysis As in Experiment 2 and 4 (the No Interaction and Interaction Viewing-Observer conditions), we studied video footage of 6 couples during both Phase 1 and Phase 2. We coded whether each reward or punishment trial produced either a positive (e.g., laughing, smiling) or a negative (frowning, angry) response. The data in Figure 22 demonstrates that the Player, during Phase 1 displays as many positive as negative expressions (6 vs. 6) in response to reward trials, and only negative emotions to punishment trials (7.33 vs. 0 respectively). In fact, it was only in the No Interaction Viewing-Observer condition that the Player ever displayed positive emotion in response to punishment (3.67 occa- sions), adding weight to the suggestion that during this condition, the positive expression was a social gesture to prevent loss of esteem. The Observer, during Phase 1 (see Figure 23) shows a pattern similar to that seen in the Interaction Viewing Observer condition (Experiment 4). That is, a roughly equal amount of positive and negative expression is observed when the Player is rewarded (4.66 vs. 4.33 respectively). Further, only negative emotion is displayed when the Player is punished (4 vs. 0 respectively); this again contrasts greatly with the suspected effect of schadenfreude observed during Experiment 2 (No Interaction Viewing Observer condition) where positive emotion at the Player’s loss far outweighed a negative response at such times (1.67 vs. 6 respectively). 33 Philoctetes Center Journal VOLUME 1 · NUMBER 1 s n

o 10 i t

c 9 e l

e 8 7.33 s

d 7

r 6 6

a 6 c

f 5 o

. 4 o

n 3 n

a 2 e

M 1 0 0 Rewarding consequence Punishing consequence Outcome after card selection

Positive expression Negative expression

FIGURE 22. Number of Positive and Negative Facial Expressions Associated With Rewarding and Punishing Outcomes for the Player During Phase 1

s 10 n

o 9 i t

c 8 e l

e 7 s

f 6

o 4.66 . 5 4.33 4 o

n 4

n 3 a e 2 M 1 0 0 Rewarding consequence Punishing consequence Outcome after card selection

Positive expression Negative expression

FIGURE 23. Number of Positive and Negative Facial Expressions Associated With Rewarding and Punishing Outcomes for the Observer During Phase 1

Finally, as in Experiment 2, there were fewer emotional responses subsequent to reward trials during Phase 2 (see Figure 24). Consistent with the Observers during Phase 2 of Experiment 4 (Interaction Viewing Reward condition) the Observers during Phase 2 of this condition displayed a great deal more negative than positive emotion in response to punishment (5.67 vs. 0.83 respectively), as would be expected. This again contrasts to the roughly equal expression of both positive (4.83) and negative (4.33) emotion displayed by the Observers during Phase 2 of the No Interaction Viewing Observer condition.

34 Intuition and Schadenfreude

s 10 n

o 9 i t

c 8 e l

e 7

s 5.67

f 6 o

. 5 o

n 4

n 3 a e 2 1.16 M 0.83 1 0 0 Rewarding consequence Punishing consequence Outcome after card selection

Positive expression Negative expression

FIGURE 24. Number of Positive and Negative Facial Expressions Associated With Rewarding and Punishing Outcomes for the Observer During Phase 2.

Experiments 2, 4, and 5: Comparison of Behavioral Performance During Phase 1 and 2 Across Viewing-Observer Conditions In order to further investigate the effect of watching a friend playing the IGT on subsequent learning by the Observer, behavioral scores for both Phase 1 and Phase 2 were collapsed across Block to produce an overall IGT score for each condition. The mean overall scores are presented in Figure 25. Typically, normal IGT performance is defined by an overall score of greater than +9 (see Bechara & Damasio, 2002; 1999; & Bowman et al., 2004, for a review of impaired vs. unimpaired IGT performance), and as can be seen in Figure 25, mean overall Phase 1 performance in each of the three Viewing-Observer conditions is characterized by a score greater than +9 (No Interaction M = 10.92, SD = 4.5; Dual-Reward M = 14.83, SD = 4.1, Interaction = 16.0, SD = 3.95). In Phase 2, however, it can be seen in the Dual-Reward condition that mean overall performance is both greater than +9, and at least as good as the Player’s performance during Phase 1 (M = 14.67, SD = 9.6). This suggests that the Observers in this condition do not necessarily benefit from having witnessed the game previously, but that their performance is not disrupted by having watched the game during Phase 1, most likely due to the shared investment in the game by receiving rewards and punishments. In the Interaction condition, however, there appears to be a striking positive effect on learning during Phase 2 by those Observers who, despite not receiving any rewards or punishments, were allowed to discuss the game with their friends during Phase 1 (M = 28.7, SD = 6.6). The findings in both Phase 2 of the Dual-Reward and Interaction conditions contrast sharply with Phase 2 performance in the No Interaction Viewing-Observer condition (M

35 Philoctetes Center Journal VOLUME 1 · NUMBER 1

= 3.5, SD = 6.3), where overall performance was not only within the impaired range (<+9) but seemingly disrupted because of prior experience with the game. Again this result high- lights the necessity for the Observer (or the intern) to have an investment in the initial learning process, with conversation impacting most effectively on subsequent performance. A two-way between-subjects ANOVA with factors of ‘Condition’ (No Interaction, Dual-Reward, and Interaction) and ‘Phase’ (Phase 1 and Phase 2) was run on the overall scores. Despite there being neither a main effect of Phase (F(1, 98) = .11, p = .74), nor an interaction between Phase and Condition (F(2, 98) = 1.55, p = .22), there was a significant main effect of Condition (F(2, 98) = 3.54, p = .03). Post hoc t-tests confirmed that this main effect of condition was attributable to a significant difference in Phase 2 performance by Observers in the Interaction vs. the No Interaction Viewing-Observer conditions (t(38) = 2.78, p = .01).

36 *

30 ) b + a

( 24 - ) d + c ( 18 n a e m l

l 12 a r

e * v

O 6

0 No Interaction Dual-Reward Interaction

FIGURE 25. Overall Mean ‘Good-Bad’ Card Selections Collapsed Across Block for Each Viewing-Observer Condition for Both Phase 1 (Player Making Choices) and Phase 2 (Observer Making Choices) (* signiﬁcant at the .01 level.)

DISCUSSION The series of experiments presented in this paper represent a novel attempt to investigate empathic experience within a complex emotion-related learning paradigm (c.f., Morrison et al., in press; Morrison et al., 2004; Singer and Frith, 2005). In particular, this study has tried to address the notion that a naive ‘observer’ will acquire emotion-based knowledge having vicariously experienced the successes and failures of another. Our experimental par-

36 Intuition and Schadenfreude

adigm allows us to examine the extent to which intuitive processes assist people in the tackling of complex problems in a social learning setting –- scenarios which seem likely to underpin a range of internship and apprenticeship experiences. An important aspect of this study was that performance of both the Player and the Observer was typically compatible with the established learning profile found on the Iowa Gambling Task (e.g., Bechara, Damasio, Damasio, & Anderson, 1994; Bowman, Evans, & Turnbull, 2005; Evans, Kemish, & Turnbull, 2004). However, there was one remarkable exception, that of the No Interaction Viewing-Observer condition (Experiment 2). Sub-zero Empathy? In the central finding of the study, Experiment 2 demonstrated that after observation during Phase 1 of the IGT, the Observers performed very poorly (at virtually chance levels) when later required to demonstrate the extent of their learning. Indeed the performance level was poorer than that seen when a naive player encounters the game for the first time (e.g., Phase 1, Experiment 1). Thus, there would appear to be a less-than-0% effect of vicarious learning on performance. This finding suggests that the apprenticeship, or intern, interaction between participants, seems to have failed spectacularly. This result runs contrary to the widely-held assumption that the intern relationship facilitates learning, backed by a wealth of evidence for some specific classes of ‘internship’ experience (e.g., Lieberman & Hilliard, 2006; Rogoff, Paradise, Mejia Arauz, Correa-Chavez, & Angelillo, 2003; Want & Harris, 2001; Varga, 1970). Investigating Confounds This was an unexpected and entirely counter-intuitive finding. It is, of course, possible that the striking effect was due to one or other class of experimental artifact. However, on the basis of a series of further control studies, it seems possible to rule out a range of plausible confounds. For example, the effect seems unlikely to be due to simple fatigue in Phase 2. This is clear because, for example, when the same players endured a second phase of testing during the baseline condition (Experiment 1), their performance improved substantially. Further, such findings cannot be accounted for by the mere presence of a friend within the testing environment, because in the further control setting of the Blind-Observer condition (Experiment 3) learning of an entirely normal level occurred both during Phase 1 and Phase 2. On a related point, it should be noted that performance of the Player during Phase 1 of the No Interaction Viewing-Observer (Experiment 2) condition was not different from performance by the Player in any of the other experimental conditions. Thus, the disruption of the Observer’s performance in Experiment 2 cannot be accounted for by an atypical performance of the Player in this task. Finally, it is of some note that the Observer in the No Interaction Viewing-Observer condition (Experiment 2) showed a substantial subjective awareness of the nature of the

37 Philoctetes Center Journal VOLUME 1 · NUMBER 1

deck properties during both Phase 1 and Phase 2. However, such awareness was not translated into good behavioral performance, which suggests that it was not an indifference to the deck contingencies which led to poor learning. This stands in clear contrast to other studies of the subjective awareness of participants who perform poorly in normal IGT test settings. Here, poor behavioral performance also tends to produce low subjective experience scores (e.g., Evans, Bowman, & Turnbull, 2005). A Potential Explanation: Schadenfreude? One feature of performance during the No Interaction Viewing-Observer condition which was especially apparent when analyzing video footage of the couples during Phase 1 of the game, was the extent to which the Observer appeared to experience pleasure in relation to the bad choices made by the Player. Thus, it is at least plausible that schadenfreude (a feeling of pleasure at someone else’s misfortune) could account for the poor subsequent performance of the Observer during Phase 2. On this argument, the Observer would resent the Player’s non-shared good fortune (c.f., Henrich et al., 2006), and experience some pleasure from their failure (c.f., Singer et al., 2005). The unfortunate consequence would be the association of a rewarding response (pleasure) to a negative card choice (a deck where the friend is likely to lose money). Thus, when the Observer comes to play the game during Phase 2, the mapping between objects (good and bad decks) and emotional valence (reward and punishment) is inappropriate. It is, however, notable that the Players’ performances do not appear to suffer from this mutual experience of pleasure at their own misfortune, despite the Players displaying some level of shared amusement during punishing card selections. This perhaps suggests that the Players’ shared pleasure at the ﬁnancial penalty is little more than a socially appropriate external gesture, perhaps generated to ‘save face,’ rather than a true expression of their internal state (c. f., McCullagh, Moore, Gawel, & Feinstein, 1999). Testing Schadenfreude If the schadenfreude hypothesis is sound, then it would logically be expected that the Observers should show better learning during Phase 2 (akin to performance during Experiment 1), when they have more explicit roles in both card selection and the receipt of rewards and punishments during Phase 1 of the game. Video footage of the Interaction Viewing-Observer condition (Experiment 4) conﬁrmed that when given the opportunity to discuss possible card selections with the Player, the Observer assumed a more reciprocally supportive role, consistent with the shared experience at hand. Despite not receiving any direct rewards and punishments during Phase 1 of the IGT, the behavioral performance of the Observer in this interactive condition was far more impressive during Phase 2 than that of the Observer in the No Interaction Viewing-Observer condition (Experiment 2).

38 Intuition and Schadenfreude

Similarly, in the Dual-Reward Viewing-Observer condition (Experiment 5), participants were not given the opportunity to discuss the possible card selections, but did receive an explicit reward. Again, this additional ‘investment’ in the game produced a much more positive learning outcome than that seen in the No Interaction Viewing-Observer condition (Experiment 2).

CONCLUSION This series of investigations has studied the extent to which it is possible for humans to use empathy-related skills to acquire knowledge about the intuitions of others–an ability that is undoubtedly important for a range of educational and training needs, as well as in the creative and imaginative process. We have been able to gain a good deal of knowledge about the boundary conditions of this interaction. Our ﬁndings suggest that the process can be disrupted relatively easily (Experiment 2), and that this disruption may be the result of some extraordinarily human feelings such as the complex emotions which may underpin schadenfreude. Moreover, we have shown (Experiments 4 and 5) that when human beings can work together towards a common goal, in which they both have some degree of investment in the process, the disruptive (schadenfreude-based) effects are no longer observed.

ACKNOWLEDGMENTS We would like to thank the Philoctetes Center for funding this research. Also, we greatly appreciate the experimental design and data analysis suggestions generated during a meet- ing at the Philoctetes Center in January 2006. We are grateful to India Morrison for advice in the early phase of the study and Stephanie Wood and Ling Shi for their assistance in analyzing the video footage presented in Experiments 2, 4, and 5.

REFERENCES Baron-Cohen, S., & Wheelwright, S. (2004). The empathy quotient: An investigation of adults with Asperger syndrome or high functioning autism, and normal sex differences. Journal of Autism and Developmental Disorders, 34(2), 163-175. Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, 7-15. Bechara, A., & Damasio, H. (2002). Decision-making and addiction (part I): impaired activation of somatic states in substance dependent individuals when pondering decisions’ negative future consequences. Neuropsychologia, 40, 1675-1689. Bechara, A., et al. (2000a). Emotion, decision-making, and the orbitofrontal cortex. Cerebral Cortex, 10, 295-307. Bechara, A., Damasio, H., Damasio, A. R., & Lee, G. P. (1999). Different contributions of the human amygdala and ventromedial prefrontal cortex to decision-making. The Journal of Neuroscience, 19, 5473-5481.

39 Philoctetes Center Journal VOLUME 1 · NUMBER 1

Bechara, A., Damasio, H., Tranel, D., & Anderson, S.W. (1998). Dissociation of working memory from decision-making within the human prefrontal cortex. The Journal of Neuroscience, 18, 428-437. Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (1997). Deciding advantageously before know- ing the advantageous strategy. Science, 275, 1293-1295. Bechara, A., Dolan, S., Denburg, N., Hindes, A., Anderson, S. W., & Nathan, P. E. (2001). Decision- making deficits linked to a dysfunctional ventromedial prefrontal cortex, revealed in alcohol and stimulant abusers. Neuropsychologia, 39, 376-389. Bechara, A., et al. (2000b). Characterisation of the decision-making deficit of patients with ventromedial prefrontal cortex lesions. Brain, 123, 2189-2202. Bechara, A., Tranel, D., Damasio, H., & Damasio, A. R. (1996). Failure to respond autonomically to anticipated future outcomes following damage to prefrontal cortex. Cerebral Cortex, 6, 215-225. Bowman, C. H., Evans, C. E. Y., & Turnbull, O. H. (2005). Artificial time-constraints on the Iowa Gambling Task: The effects on behavioural performance and subjective experience. Brain & Cognition, 57, 21-25. Bowman, C. H., & Turnbull, O. H. (2003). Real versus facsimile reinforcers on the Iowa Gambling Task. Brain and Cognition, 53, 207-210. Bowman, C. H., & Turnbull, O. H. (2004). Emotion-based learning on a simplified card game: The Iowa and Bangor Gambling Tasks. Brain and Cognition, 55, 277-282. Damasio, A. R. (1994). Descartes’ error: Emotion, reason and the human brain. New York: Grosset / Putnam. Damasio, A.R. (1996). The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philosophical Transactions of the Royal Society of London B, 351, 1413-1420. Damasio, A. R. (1999). The feeling of what happens. London: William Heinemann. Damasio, A. R. (2004). Looking for Spinoza. London: Vintage. Damasio, H., Grabowski, T. Frank, R., Galaburda, A. M., & Damasio, A. R. (1994). The return of Phineas Gage: Clues about the brain from the skull of the famous patient. Science, 264, 1102-1105. De Quervain, D. J. F., Fischbacher, U., Treyer, V., Schellhammer, M., Schnyder, U., Buck, A., & Fehr, E. (2004). The neural basis of altruistic punishment. Science, 305, 1254-1258. Dimitrov, M., Phipps, M., Zahn, T. P., & Grafman, J. (1999). A thoroughly modern Gage. Neurocase, 5(4), 345-354. Ekman, P. (1993). Facial expression and emotion. American Psychologist, 48, 384-392. Eslinger, P. J., & Damasio, A. R. (1985). Severe disturbance of higher cognition after bilateral frontal lobe ablation: Patient EVR. Neurology 35(12), 1731-1741. Evans, C.E.Y., Bowman, C.H., & Turnbull, O.H. (2005). Subjective awareness on the Iowa Gambling Task: The key role of emotional experience in schizophrenia. Journal of Clinical and Experimental Neuropsychology, 27(6), 656-664. Evans, C.E.Y., Kemish, K., & Turnbull, O. H. (2004). Paradoxical effects of education on the Iowa Gambling Task. Brain and Cognition, 54, 240-244. Feynman, R. P. (1965). The character of physical law. Cambridge, MA: MIT Press. Freud, S. (1930). Civilisation and its discontents. Standard Edition, 21, 59. Freud, S. (1915). Instincts and their vicissitudes. Standard Edition, 14, 117-140.

40 Intuition and Schadenfreude

Gallese, V. (2001). The “Shared Manifold” Hypothesis: From mirror neurons to empathy. Journal of Consciousness Studies, 8(5-7), 33-50. Goel, V., Grafman, J., Tajik, J., Gana, S., & Danto, D. (1998). A study of the performance of patients with frontal lobe lesions in a ﬁnancial planning task. Brain, 120, 1805-1822. Harlow, J. M. (1869). Recovery from the passage of an iron bar through the head. Boston: Clapp. Harlow, J. M. (1868). Recovery from passage of an iron bar through the head. Pub. Mass. Med. Soc., 2, 327-347. Harlow, J. M. (1848). Passage of an iron rod through the head. Boston Medical and Surgical Journal, 39, 389-393. Henrich, J., McElreath, R., Barr, A., Ensminger, J., Barrett, C., Bolyanatz, A., et al. (2006). Costly punishment across human societies. Science, 312, 1767-1770. Intrator J., Hare R., Stritzke P., et al. (1997). A brain imaging (single photon emission computerized tomography) study of semantic and affective processing in psychopaths. Biological Psychiatry, 42(2), 96-103. Jackson, P. L., Brunet, E., Meltzoff, A. N., & Decety, J. (2005). Empathy examined through the neural mechanisms involved in imagining how I feel versus how you feel pain. Neuropsychologia, 44(5), 752- 761. Kahneman, D., & Tversky, A (1982). The psychology of preferences. Scientiﬁc American, 246, 160-173. Kant, I. (2004). Critique of pure reason (translated). England: Dover Publications. Kekulé, F.A. (1865). Vizsgálatok az aromás vegyületek körében Részletek. Annalen der Chemie, 137, 129–196. In H. M. Leicester & H. S. Klickstein. (1969). A Source Book in Chemistry 1400 -1900. Cambridge, MA: Harvard University Press. LeDoux, J. E. (2000). Emotion circuits in the brain. Annual Review of Neuroscience, 23, 155-184. Lieberman, L., & Hilliard, R.I. (2006). How well do paediatric residency programmes prepare residents for clinical practice and their future careers? Medical Education, 40(6), 539-546. Macmillan, M. B. (2000). An odd kind of fame: Stories of Phineas Gage. Cambridge, MA: MIT Press. Maia, T.V., & McClelland, J. L. (2004). A re-examination of the evidence for the somatic marker hypothesis: What participants really know in the Iowa Gambling Task. Proceedings of the National Academy of Sciences, 45, 16075-16080. Manes, F., Sahakian, B., Clark, L., Rogers, R., Antonin, N., Aitken, M., & Robbins, T. (2002). Decision-making processes following damage to the prefrontal cortex. Brain, 125, 624-639. McCullagh, S., Moore, M., Gawel, M., & Feinstein, A. (1999). Pathological laughing and crying in amyotrophic lateral sclerosis: An association with prefrontal cognitive dysfunction. Journal of the Neurological Sciences, 169(1-2), 43-48. Morrison, I., Lloyd, D., Di Pelligrino, G., Roberts, N. (2004). Vicarious responses to pain in anterior cingulate cortex: Is empathy a multisensory issue? Cognitive, Affective, and Behavioral Neuroscience, 4(2), 270-278. Morrison, I., Poliakoff, E., Gordon, L., & Downing, P. (in press). Effects of pain observation on motor behaviour. Psychological Science. Myers, D.G. (2002). Intuition: Its powers and perils. New Haven, CT and London: Yale University Press. Ogden, J. A. (2005). A case-study approach to Clinical Neuropsychology. New York: Oxford University Press. Panksepp, J. (1998). Affective Neuroscience: The foundations of human and animal emotions. Series in affec-

41 Philoctetes Center Journal VOLUME 1 · NUMBER 1

tive science. London: Oxford University Press. Pigman, G.W. (1995). Freud and the history of empathy. International Journal of Psycho-Analysis, 76, 237-252. Plato (1956). Plato’s Phaedrus (translated). Indianopolis: Bobbs-Merrill. Rizzolatti, G., Fogassi, L., & Gallese, V. (2001). Neurophysiological mechanisms underlying action understanding and imitation. Nature Reviews Neuroscience, 2, 661-670. Rogoff, B., Paradise, R., Mejia Arauz, R., Correa-Chavez, M., & Angelillo, C. (2003). First hand learning through intent participation. Annual Review of Psychology, 54, 175-203. Rolls, E. T. (2000). The orbitofrontal cortex and reward. Cerebral Cortex, 20, 284-294. Rolls, E. T. (1999). The Brain and Emotion. Oxford: Oxford University Press. Singer, T., & Frith, C. (2005). The painful side of empathy. Nature Neuroscience, 8(7),845-846. Singer, T., Seymour, B., O’Doherty, J. P., Stephan, K. E., Dolan, R. J., & Frith, C. D. (2006). Empathic neural responses are modulated by the perceived fairness of others. Nature, 439, 466-469. Turnbull, O. H. & Evans. C. E. Y. (2006). Preserved complex emotion-based learning in amnesia. Neuropsychologia, 44, 300-306. Turnbull, O. H., Evans, C. E. Y., Kemish, K., Park, S., & Bowman, C. H. (2006). A novel ‘set-shifting’ modiﬁcation of the Iowa Gambling Task: Flexible emotion-based learning in schizophrenia. Neuropsychology, 20(3), 290-298. Varga, L. (1970). The value of internship in psychiatry. American Journal of Psychiatry, 127(1), 104-105. Want, S. C., & Harris, P. L. (2001). Learning from other people’s mistakes: Causal understanding in learning to use a tool. Child Development, 72(2), 431-443.