Would You Trust a (Faulty) Robot?

Salem, Maha; Lakatos, Gabriella; Amirabdollahian, Farshid; Dautenhahn, Kerstin

doi:10.1145/2696454.2696497

Cited by 361 publications

(132 citation statements)

References 19 publications

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“…In the latter case, warmth attributions and trust were significantly decreased. Moreover, we detected similar effects of the manipulations on behavioral and self-reported measures, which is not always achieved in related studies (Hancock et al, 2011;Salem et al, 2015).…”

Section: Discussionsupporting

confidence: 81%

A Social Cognition Perspective on Human–Computer Trust: The Effect of Perceived Warmth and Competence on Trust in Decision-Making With Computers

Kulms

Kopp

2018

Front. Digit. Humanit.

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Trust is a crucial guide in interpersonal interactions, helping people to navigate through social decision-making problems and cooperate with others. In human-computer interaction (HCI), trustworthy computer agents foster appropriate trust by supporting a match between their perceived and actual characteristics. As computers are increasingly endowed with capabilities for cooperation and intelligent problem-solving, it is critical to ask under which conditions people discern and distinguish trustworthy from untrustworthy technology. We present an interactive cooperation game framework allowing us to capture human social attributions that indicate trust in continued and interdependent human-agent cooperation. Within this framework, we experimentally examine the impact of two key dimensions of social cognition, warmth and competence, as antecedents of behavioral trust and self-reported trustworthiness attributions of intelligent computers. Our findings suggest that, first, people infer warmth attributions from unselfish vs. selfish behavior and competence attributions from competent vs. incompetent problem-solving. Second, warmth statistically mediates the relation between unselfishness and behavioral trust as well as between unselfishness and perceived trustworthiness. We discuss the possible role of human social cognition for human-computer trust.

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Section: Discussionsupporting

confidence: 81%

A Social Cognition Perspective on Human–Computer Trust: The Effect of Perceived Warmth and Competence on Trust in Decision-Making With Computers

Kulms

Kopp

2018

Front. Digit. Humanit.

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“…People are more likely to interact with automation, artificial intelligence (AI), and robots that they can trust (Lee & See, 2004). However, a psychology that evolved to navigate interactions with fellow humans regulates this trust, and people worry that we may overly-trust robots (Robinette, Li, Allen, Howard, & Wagner, 2016;Salem, Lakatos, Amirabdollahian, & Dautenhahn, 2015).…”

Section: Introductionmentioning

confidence: 99%

Trust in humans and robots: Economically similar but emotionally different

Schniter

Shields

Sznycer

2020

Journal of Economic Psychology

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Trust-based interactions with robots are increasingly common in the marketplace, workplace, on the road, and in the home. However, a looming concern is that people may not trust robots as they do humans. While trust in fellow humans has been studied extensively, little is known about how people extend trust to robots. Here we compare trust-based investments and emotions from across three nearly identical economic games: human-human trust games, human-robot trust games, and human-robot trust games where the robot decision impacts another human. Robots in our experiment mimic humans: they are programmed to make reciprocity decisions based on previously observed behaviors by humans in analogous situations. We find that people invest similarly in humans and robots. By contrast, the social emotions elicited by the interactions (but not non-social emotions) differed across human and robot trust games, and did so lawfully. Emotional reactions depended on how one's trust game decision interacted with the partnered agent's decision, and whether another person was affected economically and emotionally.

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“…We designed a 4 condition, between-subject, wizard-ofoz (WoZ) laboratory study to investigate the above research [17] Trust of and intent to work with a robot Similarity to participant --Lohani et al [18] Compliance with robot suggestions on item-ranking task Use of social interaction (dialogue) Kahn et al [19] Compliance with request to keep a secret Sociability / social intelligence Salem et al [20] Compliance with unconventional tasks Robot errors o -Ham et al [21] Agreement with a persuasive story Gaze, gestures o -Ham et al [6] Minimising energy consumption on a virtual washing task Social feedback (emotion expression) --Chidambaram et al [22] Compliance with robot suggestions on item-ranking task Gaze, gesturing, proxemics o Nakagawa et al [23] Time spent/ actions on a monotonous task Touch o Gockley and Mataric [4] Time spent/ actions on an exercise task Engagement in user activity o o questions using the social robot Pepper 1 . An exercise session interaction scenario was designed in order to give the study real world context and applicability, whilst representing a low elaboration scenario for participants.…”

Section: Methodsologymentioning

confidence: 99%

Effective Persuasion Strategies for Socially Assistive Robots

Winkle

Lemaignan

Caleb-Solly

et al. 2019

2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

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In this paper we present the results of an experimental study investigating the application of human persuasive strategies to a social robot. We demonstrate that robot displays of goodwill and similarity to the participant significantly increased robot persuasiveness, as measured objectively by participant behaviour. However, such strategies had no impact on subjective measures concerning perception of the robot, and perception of the robot did not correlate with participant behaviour. We hypothesise that this is due to difficulty in accurately measuring perception of a robot using subjective measures. We suggest our results are particularly relevant for the design and development of socially assistive robots.

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Would You Trust a (Faulty) Robot?

Cited by 361 publications

References 19 publications

A Social Cognition Perspective on Human–Computer Trust: The Effect of Perceived Warmth and Competence on Trust in Decision-Making With Computers

A Social Cognition Perspective on Human–Computer Trust: The Effect of Perceived Warmth and Competence on Trust in Decision-Making With Computers

Trust in humans and robots: Economically similar but emotionally different

Effective Persuasion Strategies for Socially Assistive Robots

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