152 Sinneswahrnehmung, Bewegung, Emotionen, Triebe
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Facing Enemies. Modulation of Revenge Interactions based on Opponent State Indicators of Suffering
(2023)
Research on revenge often treats vengeful acts as singular one-way experiences, an approach which fails to account for the social nature and functions of revenge. This dissertation aims to integrate emotional punishment reactions into dynamic revenge sequences to investigate the affective and cognitive consequences of revenge within a social interaction.
Exacting revenge can evoke intense affective consequences, from feelings of guilt to the genuine enjoyment of the suffering of others. In Chapter 2, affective responses towards suffering opponents and the regulation of aggression based on the appraisal of distinct suffering indicators were investigated. Results indicate that the observation of opponent pain evokes positive affect (measured via facial muscle contractions during the observation), which is followed by a downregulation of subsequent punishment. Both, positive affective reactions and the downregulation of punishment, were only observed following pain and not sadness expressions. Empathic distress, indexed by negative affective reactions, was only present following the observation of pain in non-provoking opponents. Showcasing the modulation of empathy related processes due to provocation and competition.
In Chapter 3, a significant escalation of punishment, when being confronted with Schadenfreude, was observed. Results are interpreted as supporting the assumption that opponent monitoring processes inform subsequent action selection. The observation of opponent smiles led to imitation behavior (facial mimicry), which was partially attenuated due to previous provocation. The different functions of smile mimicry in the context of the aggressive competitive setting are discussed as containing simulation aspects (to aid in opponent understanding) and as a potential mirroring of dominance gestures, to avoid submission.
In an additional series of studies, which are presented in Chapter 4, changes in memory of opponent faces following vengeful encounters were measured. Based on provocation, and punishment outcomes (pain & anger), face memory was distorted, resulting in more positive representations of opponents that expressed pain. These results are discussed as evidence of the impact of outcome appraisals in the formation of opponent representations and are theorized to aid empathy avoidance in future interactions.
The comparison of desired and observed opponent states, is theorized to result in appraisals of the punishment outcomes, which evoke affective states, inform the action selection of subsequent punishments, and are integrated into the representation of the opponent in memory.
Overall, the results indicate that suffering cues that are congruent with the chosen punishment action are appraised as positive, evoking an increase in positive affect. The emergence of positive affect during the observation of successful aggressive actions supports recent theories about the chronification of aggressive behavior based on reinforcement learning. To allow positive affect to emerge, affective empathic responses, such as distress, are theorized to be suppressed to facilitate the goal attainment process. The suffering of the opponent constitutes the proximate goal during revenge taking, which highlights the importance of a theoretical differentiation of proximate and ultimate goals in revenge to allow for a deeper understanding of the underlying motives of complex revenge behavior.
Manifestations of aggressive driving, such as tailgating, speeding, or swearing, are not trivial offenses but are serious problems with hazardous consequences—for the offender as well as the target of aggression. Aggression on the road erases the joy of driving, affects heart health, causes traffic jams, and increases the risk of traffic accidents. This work is aimed at developing a technology-driven solution to mitigate aggressive driving according to the principles of Persuasive Technology. Persuasive Technology is a scientific field dealing with computerized software or information systems that are designed to reinforce, change, or shape attitudes, behaviors, or both without using coercion or deception.
Against this background, the Driving Feedback Avatar (DFA) was developed through this work. The system is a visual in-car interface that provides the driver with feedback on aggressive driving. The main element is an abstract avatar displayed in the vehicle. The feedback is transmitted through the emotional state of this avatar, i.e., if the driver behaves aggressively, the avatar becomes increasingly angry (negative feedback). If no aggressive action occurs, the avatar is more relaxed (positive feedback). In addition, directly after an aggressive action is recognized by the system, the display is flashing briefly to give the driver an instant feedback on his action.
Five empirical studies were carried out as part of the human-centered design process of the DFA. They were aimed at understanding the user and the use context of the future system, ideating system ideas, and evaluating a system prototype. The initial research question was about the triggers of aggressive driving. In a driver study on a public road, 34 participants reported their emotions and their triggers while they were driving (study 1). The second research question asked for interventions to cope with aggression in everyday life. For this purpose, 15 experts dealing with the treatment of aggressive individuals were interviewed (study 2). In total, 75 triggers of aggressive driving and 34 anti-aggression interventions were identified. Inspired by these findings, 108 participants generated more than 100 ideas of how to mitigate aggressive driving using technology in a series of ideation workshops (study 3). Based on these ideas, the concept of the DFA was elaborated on. In an online survey, the concept was evaluated by 1,047 German respondents to get a first assessment of its perception (study 4). Later on, the DFA was implemented into a prototype and evaluated in an experimental driving study with 32 participants, focusing on the system’s effectiveness (study 5). The DFA had only weak and, in part, unexpected effects on aggressive driving that require a deeper discussion.
With the DFA, this work has shown that there is room to change aggressive driving through Persuasive Technology. However, this is a very sensitive issue with special requirements regarding the design of avatar-based feedback systems in the context of aggressive driving. Moreover, this work makes a significant contribution through the number of empirical insights gained on the problem of aggressive driving and wants to encourage future research and design activities in this regard.