The Fundamental Attribution Error in Human-Robot Interaction: An Experimental Investigation on Attributing Responsibility to a Social Robot for Its Pre-Programmed Behavior

Since social robots are rapidly advancing and thus increasingly entering people’s everyday environments, interactions with robots also progress. For these interactions to be designed and executed successfully, this study considers insights of attribution theory to explore the circumstances under which people attribute responsibility for the robot’s actions to the robot. In an experimental online study with a 2 × 2 × 2 between-subjects design (N = 394), people read a vignette describing the social robot Pepper either as an assistant or a competitor and its feedback, which was either positive or negative during a subsequently executed quiz, to be generated autonomously by the robot or to be pre-programmed by programmers. Results showed that feedback believed to be autonomous leads to more attributed agency, responsibility, and competence to the robot than feedback believed to be pre-programmed. Moreover, the more agency is ascribed to the robot, the better the evaluation of its sociability and the interaction with it. However, only the valence of the feedback affects the evaluation of the robot’s sociability and the interaction with it directly, which points to the occurrence of a fundamental attribution error.

Does the Correspondence Bias Apply to Social Robots?: Dispositional and Situational Attributions of Human Versus Robot Behavior

Increasingly, people interact with embodied machine communicators and are challenged to understand their natures and behaviors. The Fundamental Attribution Error (FAE, sometimes referred to as the correspondence bias) is the tendency for individuals to over-emphasize personality-based or dispositional explanations for other people’s behavior while under-emphasizing situational explanations. This effect has been thoroughly examined with humans, but do people make the same causal inferences when interpreting the actions of a robot? As compared to people, social robots are less autonomous and agentic because their behavior is wholly determined by humans in the loop, programming, and design choices. Nonetheless, people do assign robots agency, intentionality, personality, and blame. Results of an experiment showed that participants made correspondent inferences when evaluating both human and robot speakers, attributing their behavior to underlying attitudes even when it was clearly coerced. However, they committed a stronger correspondence bias in the case of the robot–an effect driven by the greater dispositional culpability assigned to robots committing unpopular behavior–and they were more confident in their attitudinal judgments of robots than humans. Results demonstrated some differences in the global impressions of humans and robots based on behavior valence and choice. Judges formed more generous impressions of the robot agent when its unpopular behavior was coerced versus chosen; a tendency not displayed when forming impressions of the human agent. Implications of attributing robot behavior to disposition, or conflating robot actors with their actions, are addressed.

Netflix and Crime: Identification with the Characters of ‘La Casa de Papel’ Spanish Series

This study examines the Netflix Spanish series La Casa de Papel as a pragmatic example of a series that addresses questions of criminal justification. In this qualitative study, in-depth interviews were conducted with 17 Saudi participants. The findings suggest that the Saudi viewers justified the characters’ crimes influenced by fundamental attribution error. Viewers’ identification with the characters could be seen in their empathy with the robbery team and their desire for threatening characters to die. Viewers also stated that they did not want the criminals to be caught. In fact, viewers felt sad and emotional when the characters were shot or caught. Participants ranked the Professor, Tokyo, Berlin, and Nairobi as the most liked characters. Conversely, the least liked characters were Arturo Román and Sierra because they threatened the success of the robbery. Finally, participants accepted the banker joining the team, while they opposed detective Lisbon joining it.

Influence of the Fundamental Attribution Error on Perceptions of Blame and Negligence

Automobile accidents are a frequent occurrence in the United States and commonly result in legal ramifications. Through a fundamental attribution error (FAE) framework ( Ross, 1977 ), the current research examined how individuals perceive blame and negligence in these cases. In Study 1 ( N = 360), we manipulated the driver (you vs. stranger) of a hypothetical accident scenario and the situational circumstances surrounding the accident (favorable vs. unfavorable). Supporting the FAE, individuals' situational blame attributions only varied as a function of situational circumstances when they themselves were hypothetically driving. However, neither the driver nor the situation significantly predicted dispositional blame attributions. Yet, Study 1 provided initial support for the importance of an individual's trait tendency to neglect situational constraints when making dispositional blame attributions. In Study 2 ( N = 212), we again manipulated situational circumstances surrounding the hypothetical accident, but within the context of a mock civil trial. Results provided additional support for the importance of this trait tendency and expanded our findings of dispositional blame attributions to perceptions of negligence. Implications include the importance of considering trait individual differences in the likelihood to ignore situational demands when individuals are making legally relevant judgments about automobile accidents.

Does What We Know About Actors’ Real Lives Influence Our Reactions to the Characters They Play?

The current study examines the effect of the valence of information provided about an actor on viewers’ identification with the character played by that actor and enjoyment of watching the film. The results from an experiment we conducted demonstrate that the valence of information about an actor influences identification with the character through the mediation of perceptions about the character’s traits and through transportation into the narrative. Information about the actor also indirectly affects the enjoyment of watching the film. We discuss these effects using the concepts of mental models, priming, and the fundamental attribution error as well as transportation theory.