The Pratfall Effect and Interpersonal Impressions of a Robot that Forgets and Apologizes

Packard, Christine; Boelk, Tayler; Andres, James; Edwards, Chad; Edwards, Autumn; Spence, Patric R.

doi:10.1109/hri.2019.8673101

Cited by 16 publications

(4 citation statements)

References 13 publications

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“…[12]). Functional deviations are those in which the robot commits errors or behaves in ways that are technically or contextually inappropriate, such as forgetting information [13] or when a function-focused robot suddenly appears emotional [14]. Magnitude of robot errors are associated with the magnitude of lost trust [15].…”

Section: Introductionmentioning

confidence: 99%

Good Robots, Bad Robots: Morally Valenced Behavior Effects on Perceived Mind, Morality, and Trust

Banks

2020

Int J of Soc Robotics

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Both robots and humans can behave in ways that engender positive and negative evaluations of their behaviors and associated responsibility. However, extant scholarship on the link between agent evaluations and valenced behavior has generally treated moral behavior as a monolithic phenomenon and largely focused on moral deviations. In contrast, contemporary moral psychology increasingly considers moral judgments to unfold in relation to a number of moral foundations (care, fairness, authority, loyalty, purity, liberty) subject to both upholding and deviation. The present investigation seeks to discover whether social judgments of humans and robots emerge differently as a function of moral foundation-specific behaviors. This work is conducted in two studies: (1) an online survey in which agents deliver observed/mediated responses to moral dilemmas and (2) a smaller laboratory-based replication with agents delivering interactive/live responses. In each study, participants evaluate the goodness of and blame for six foundation-specific behaviors, and evaluate the agent for perceived mind, morality, and trust. Across these studies, results suggest that (a) moral judgments of behavior may be agent-agnostic, (b) all moral foundations may contribute to social evaluations of agents, and (c) physical presence and agent class contribute to the assignment of responsibility for behaviors. Findings are interpreted to suggest that bad behaviors denote bad actors, broadly, but machines bear a greater burden to behave morally, regardless of their credit- or blame-worthiness in a situation.

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Section: Introductionmentioning

confidence: 99%

Good Robots, Bad Robots: Morally Valenced Behavior Effects on Perceived Mind, Morality, and Trust

Banks

2020

Int J of Soc Robotics

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“…It describes an increased likeability towards a superior person due to a demonstration of at least some degree of imperfection. Nevertheless, these findings have to be interpreted carefully, most notably because a more recent experiment gained empirical insights, which justify skepticism towards the Pratfall mechanism [16]. In contrast to the first investigation, the authors relied on social norm violations exclusively to manipulate their robot's faulty behavior.…”

Section: Robots As Social Interactive Entitiesmentioning

confidence: 99%

“…Therefore, negative expectancy violations are likely to be accompanied by negative consequences for the eliciting person, such as social exclusion [3]. But not only other persons can be targets of these negative effects because also people's evaluations of robots are supposed to deteriorate in an equally unfavorable way [4,16]. This could have the potential to sustainably worsen a person's attitudes towards a robot as well as the interaction's quality.…”

Section: Introductionmentioning

confidence: 99%

Does the Robot Get the Credit?

Finkel

Szczuka

Krämer

2020

Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents

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During interactions with others, people have expectancies concerning their communication partners' behaviors. Negative violations of these expectancies are known to exert an adverse impact on people's perceptions and attitudes. Likewise, with regard to human-robot interactions, previous research on one-time interactions indicates that people's evaluations of robots can deteriorate equally. To simultaneously investigate possible compensation for this effect, the concept of idiosyncrasy credit was tested for transferability to human-robot interactions. It postulates that compensation can be achieved by an individual's consistent, beneficial behavior over time that results in a social deviation credit. During an experimental medium-term study with a 2x2 between-subjects design, 80 participants interacted with a humanoid, social robot in three time-separated sessions distributed over an average time span of ten days. The robot's acquisition of idiosyncrasy credit was manipulated as well as the occurrence of a negative expectancy violation by systematically varying the robot's polite communication style. Results of repeated measures ANOVAs support the assumption that negative expectancy violations decrease people's evaluations of a robot. However, this effect seems non-persistent over time. Furthermore, no support for the robot's acquisition of idiosyncrasy credit was gained.

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“…比如, Salem等人 [52] 比较了人们对不同能力表现(即是否在任务中犯错)机器人的评价, 结果发现犯错会显著影响人们对机器人可靠性和可信度的评价, 这一研究结论在儿童被试中也同样得到了验证 [53] . 类似地, 有研究也发现, 与表现的健忘(即记忆能力不佳)的机器人相比, 人们对不健忘的机器人评价更好 [54] . 当然, 机器人的真实能力与人们对其能力的感知之间也可能存在差异.…”

Section: 拟人化是在机器人外观研究中最为热点的一个问题unclassified

Factors that influence robot acceptance

Xu¹,

Ye²

2019

Chin. Sci. Bull.

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The Pratfall Effect and Interpersonal Impressions of a Robot that Forgets and Apologizes

Cited by 16 publications

References 13 publications

Good Robots, Bad Robots: Morally Valenced Behavior Effects on Perceived Mind, Morality, and Trust

Good Robots, Bad Robots: Morally Valenced Behavior Effects on Perceived Mind, Morality, and Trust

Does the Robot Get the Credit?

Factors that influence robot acceptance

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