Preventing Robot Abuse through Emotional Robot Responses

Connolly, Joe

doi:10.1145/3371382.3377433

Cited by 8 publications

(6 citation statements)

References 12 publications

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“…De Angeli and Carpenter, 2005;De Angeli et al, 2001;Brahnam and De Angeli, 2012;Hill et al, 2015). Broader research on agent abuse suggests that humanlikeness may be related to users proclivity to abuse (Connolly, 2020;Keijsers and Bartneck, 2018;Lortie and Guitton, 2011). However, arguments can be found in the literature both in favour (Connolly, 2020;Keijsers and Bartneck, 2018;Lortie and Guitton, 2011;Lee et al, 2010) and against (Tan et al, 2018;Brahnam and De Angeli, 2012) a negative relationship between humanlikeness and abuse.…”

Section: Discussionmentioning

confidence: 99%

“…Broader research on agent abuse suggests that humanlikeness may be related to users proclivity to abuse (Connolly, 2020;Keijsers and Bartneck, 2018;Lortie and Guitton, 2011). However, arguments can be found in the literature both in favour (Connolly, 2020;Keijsers and Bartneck, 2018;Lortie and Guitton, 2011;Lee et al, 2010) and against (Tan et al, 2018;Brahnam and De Angeli, 2012) a negative relationship between humanlikeness and abuse. To our knowledge so far no research has directly studied the relationship between chatbot humanlikeness and abuse.…”

Section: Discussionmentioning

confidence: 99%

“…At the same time, activation of genderspecific social scripts in human-chatbot interaction was related to more abuse (at least towards the female chatbot Brahnam and De Angeli, 2012;. Connolly (2020) found that a robot's emotional response to bullying was related to a higher tendency from bystanders to intervene (but see Tan et al, 2018, who did not find such an effect). Keijsers and Bartneck (2018) used the dehumanisation theory framework, which predicts that a lower perception of human characteristics in an interaction partner reduces people's felt obligation to treat the interaction partner in a moral way, thus facilitating abuse (Haslam et al, 2008;Haslam, 2006).…”

Section: Need For a Theoretical Framework Of Chatbot Abusementioning

confidence: 99%

“…To date, chatbot abuse has been described by various scholars (see for example De Angeli, 2009;Strait et al, 2018) but few empirical studies have been published on what motivates users to engage in abusive behaviour (but see Brahnam and De Angeli, 2012;De Angeli et al, 2001). Literature from both human-chatbot interaction specifically (Brahnam and De Angeli, 2012;Lortie and Guitton, 2011) and human-agent interaction in general (Connolly, 2020;Keijsers and Bartneck, 2018) suggests a relationship between humanlikeness of the agent and likelihood of abuse, but results are contradictory (see for example Tan et al, 2018;Lee et al, 2010;.…”

Section: Introductionmentioning

confidence: 99%

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What’s to bullying a bot?

Keijsers

Bartneck

Eyssel

2021

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In human-chatbot interaction, users casually and regularly offend and abuse the chatbot they are interacting with. The current paper explores the relationship between chatbot humanlikeness on the one hand and sexual advances and verbal aggression by the user on the other hand. 283 conversations between the Cleverbot chatbot and its users were harvested and analysed. Our results showed higher counts of user verbal aggression and sexual comments towards Cleverbot when Cleverbot appeared more humanlike in its behaviour. Caution is warranted with the interpretation of the results however as no experimental manipulation was conducted and causality can thus not be inferred. Nonetheless, the findings are relevant for both the research on the abuse of conversational agents, and the development of efficient approaches to discourage or prevent verbal aggression by chatbot users.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Need For a Theoretical Framework Of Chatbot Abusementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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What’s to bullying a bot?

Keijsers

Bartneck

Eyssel

2021

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“…R.9 It is to be expected that passersby will test the ability of an autonomous robot to stop if an object is in the way. If the testing behavior, gets violent (i.e., bullying), counter mechanisms should be in place (e.g., video surveillance, physical modifications to the robot [60], interaction strategies such as emotional responses [90] or inducing bystander interventions [61]).…”

Section: Participants' Ideas For the Prevention Of Robot Bullyingmentioning

confidence: 99%

Findings From A Qualitative Field Study with An Autonomous Robot in Public: Exploration of User Reactions and Conflicts

Babel¹,

Kraus²,

Baumann³

2022

Int J of Soc Robotics

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Soon service robots will be employed in public spaces with frequent human-robot interaction (HRI). To achieve a safe, trustworthy and acceptable HRI, service robots need to be equipped with interaction strategies suitable for the robot, user, and context. To gain realistic insights into the initial user reactions and challenges that arise when a mechanoid, autonomous service robot in public is applied, a field study with three data sources was conducted. In a first step, lay users’ intuitive reactions to a cleaning robot at a train station were observed ($$N = 344$$ N = 344 ). Second, passersby’s preferences for HRI interaction strategies were explored in interviews ($$n = 54$$ n = 54 ). As a third step, trust and acceptance of the robot were assessed with questionnaires ($$n = 32$$ n = 32 ). Identified challenges were social robot navigation in crowded places also applicable to vulnerable passersby, inclusive communication modalities, information of staff and public about the service robot application and the need for conflict resolution strategies to avoid an inefficient robot (e.g., testing behavior, path is blocked). This study provides insights into naive HRI in public and illustrates challenges, provides recommendations supported by literature and highlights aspects for future research to inspire a research agenda in the field of public HRI.

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“Our Hearts Go Out to the Victim’s Family”: Death by Robot and Autonomous Vehicle

Oravec

2022

Social and Cultural Studies of Robots and AI

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Preventing Robot Abuse through Emotional Robot Responses

Cited by 8 publications

References 12 publications

What’s to bullying a bot?

What’s to bullying a bot?

Findings From A Qualitative Field Study with An Autonomous Robot in Public: Exploration of User Reactions and Conflicts

“Our Hearts Go Out to the Victim’s Family”: Death by Robot and Autonomous Vehicle

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