Chapter 2 Related Research
2.2 Emotion
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offers in the initial ultimatum game. Surprisingly, proposers who were initially induced to feel happy made more selfish proposals in the second ultimatum game.
2.2 Emotion
Emotions play an essential role in everyday life. Emotions shape how we perceive the world, bias our beliefs, and influence our decisions. And emotions also play in large measure guide how we adapt our behavior to the physical and social environment. Some people believe that emotions play a functional role in the behavior of humans and animals, particularly behavior as part of complex social systems (Toda, 1982).
Recent trends in cognitive modeling research have emphasized the development of integrated cognitive systems that combine a broad spectrum of human cognitive abilities into a single integrated architecture. In contrast with detailed models of specific phenomena, such systems have potential, not only as a means to formalizing our basic understanding of human cognition, but also as practical proxies for human behavior in a wide range of applications (Gratch & Marsella, 2005).
The acknowledged weakness of such technology, however, is it is particularly ill-suited for capturing the influence that factors such as stress and emotion can have.
Damasio (2008) finds that people with relatively minor emotional impairments have trouble making decisions and, when they do, they often make disastrous ones. A four-fold
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classification of emotions with respect to their functions in decision making is proposed (Pfister & Böhm, 2008). It is argued that emotions are not homogenous concerning their role in decision making, but that four distinct functions can be distinguished concerning emotional phenomena. One function is to provide information about pleasure and pain for preference construction, a second function is to enable rapid choices under time pressure, a third function is to focus attention on relevant aspects of a decision problem, and a fourth function is to generate commitment concerning morally and socially significant decisions.
Table 1 Four classification of emotions (Pfister & Böhm, 2008)
2.2.1 Emotions in ultimatum game
Scientists applied emotion to study ultimatum game very early age. Kirchsteiger (1994) shown that emotion (such as envy) is a potential explanation for the most important experimental ‘anomalies’. Empirical data show that individuals differ largely from the predictions of rational choice theory, often rejecting unfair offers. Such decisions have been interpreted as altruistic punishment (Fehr & Gachter, 2002); that is, proposers making unfair offers are penalized despite the personal costs accompanying this behavior.
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Therefore, it has been proposed that a limitation of rational choice theory is that it fails to acknowledge the role in decision making (Harlé & Sanfey, 2007). For example, Hewig et al. (2011) found that unfair offers in the ultimatum and dictator games elicited negative affect, which in turn predicted participants’ decisions to either accept or reject these offers.
Pillutla and Murnighan (1996) measured the feelings of responders when confronted with unfair offers and they found that rejection of unfair offers was mediated by feelings of anger, which were particularly pronounced when individuals inferred that proposers intended to cause them harm. Likewise, rejection of unfair offers was also accompanied by higher skin conductance activity, which may reflect involvement of the affect arousal system(van 't Wout et al., 2006). Furthermore, using a more direct test, emotions induced by video clips were found to bias decision making (Harlé & Sanfey, 2007), with reduced acceptance rates after sad clips, compared to clips that were neutral or amusing. Similarly, Harle and Sanfey (2010) reported reduced acceptance rates after initial induction of withdrawal-related affect (disgust, serenity), compared to approach-related affect (amusement, anger).
Recent physiological (van 't Wout et al., 2006) and neuroimaging (Sanfey et al., 2003) studies of the ultimatum game have indeed found that responders’ emotion and arousal levels increase when presented with unfair offers and that this increase is reliably associated with the rejection of unfair offers. The responder role in the ultimatum game thus provides an ideal venue to study whether incidental emotions can additionally bias decision making and potentially interact with important task based emotions (e.g., indignation or anger) or whether these emotional states are too subtle to have tangible consequences on economic decisions
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Whereas anger and disgust have respectively been classified in the literature as approach-based and withdrawal-based (because they respectively prompt engagement with, and withdrawal from, an offending stimulus), positive withdrawal-based emotion has been harder to identify (Harle & Sanfey, 2010).
The present findings highlight the potential contribution of studying the influence of specific emotions to reveal the nature of the motives underlying behavior. We are aware of only a single other study that also used affective measures to identify the role of strategic and non-selfish motives in proposers' offers (Haselhuhn & Mellers, 2005). In this study, proposers indicated their anticipated pleasure over a range of possible payoffs (i.e., accepted offers) as well as their preference for each of these offers. It was found that some proposers derived pleasure from fairness, indicating highest preferences and most pleasure for equal offers whereas their preference and pleasure decreased as offers deviated from the 50–50 split. Self-interested proposers showed similar preferences, yet their pleasure linearly increased with the offer size. This latter discrepancy suggests that preferences are based on strategic considerations (or “strategic pleasure”, cf. Haselhuhn and Mellers (2005)).
The main reason for looking into the role of emotions in ultimatum bargaining was our conviction that we cannot exclusively infer motives from ultimatum offers alone, nor from changes in average offers due to various structural manipulations of the ultimatum game. Proposers who make generous ultimatum offers because they fear rejection do recognize that responders may evaluate their offer in terms of fairness criteria. Strategic considerations imply that the proposer is aware of and understands these criteria. Fear and fairness considerations are inextricably linked in that respect(Nelissen et al., 2011).
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2.2.2 Emotion in AI
Since Beaudoin et al. (1996) and Rosalind W Picard (2000; 2003) placed emotion into computational theory, emotions become an important research in several AI-related fields (Andrade & Ariely, 2009; Camurri & Coglio, 1998; M. El-Nasr et al., 2000; M. S.
El-Nasr & Yen, 1998; Steunebrink et al., 2010), however most prominently in human-robot/computer interaction, which focus on how to express or sense emotions. The influence of emotions on decision-making is largely ignored (Jiang & Vidal, 2006).
Philosophers and computer scientists have continued to be interested in integrating computing theory with emotions (de Sousa, 2014) in early days. Sloman and Croucher (1981) have elaborated the sort of ideas that were embryonic in Schank et al. (1973) into a more sophisticated computational theory of the mind in which emotions are virtual machines, playing a crucial role in a complex hierarchic architecture in which they control, monitor, schedule and sometimes disrupt other control modules (Beaudoin et al., 1996).
Rosalind W Picard (2000) adverts to the role of emotions in evaluation and the pruning of search spaces. But she is as much or more concerned to provide an emotional theory of computation than to elaborate a computational theory of emotions. Also, a book by Minsky (2007) takes the promising title of “The emotion machine”. Gratch and Marsella (2005) work on “computational models of human emotion”, which typically are studied in simulations in artificial environments.
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