The effect of conversational agent skill on user behavior during deception

Schuetzler, Ryan M.; Grimes, G. Mark; Giboney, Justin Scott

doi:10.1016/j.chb.2019.03.033

Cited by 44 publications

(21 citation statements)

References 56 publications

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“…Using psychophysiological data, they conclude that the simpler the chatbot (simpler texts and animations), the less strange and negative the conversation. Similar conclusions have been reached by Schuetzler et al [57], who observe that the better the chatbot's conversational skills, the more counter‐indications produced when trying to discover deceptions on the part of the interlocutor. Conversation between a student and a chatbot may lead to frustration [35] if it is not fluid enough or if the chatbot does not give the answers the student is asking for.…”

Section: Resultssupporting

confidence: 85%

Rediscovering the use of chatbots in education: A systematic literature review

Pérez

Daradoumis

Puig

2020

Comp Applic In Engineering

164

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Chatbots have been around for years and have been used in many areas such as medicine or commerce. Our focus is on the development and current uses of chatbots in the field of education, where they can function as service assistants or as educational agents. In this research paper, we attempt to make a systematic review of the literature on educational chatbots that address various issues. From 485 sources, 80 studies on chatbots and their application in education were selected through a step-by-step procedure based on the guidelines of the PRISMA framework, using a set of predefined criteria. The results obtained demonstrate the existence of different types of educational chatbots currently in use that affect student learning or improve services in various areas. This paper also examines the type of technology used to unravel the learning outcome that can be obtained from each type of chatbots. Finally, our results identify instances where a chatbot can assist in learning under conditions similar to those of a human tutor, while exploring other possibilities and techniques for assessing the quality of chatbots. Our analysis details these findings and can provide a solid framework for research and development of chatbots for the educational field.

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Section: Resultssupporting

confidence: 85%

Rediscovering the use of chatbots in education: A systematic literature review

Pérez

Daradoumis

Puig

2020

Comp Applic In Engineering

164

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“…Schuetzler et al [83] present a very interesting study that addresses how the conversational skills of an agent elicit deception and compare the behaviour of deceiving users compared to truthful interactions. Gratch et al [54] performed a study with three settings: human-human, Wizard-of-Oz (where the users believed they were interacting with an automatic agent when they were in fact interacting with a human), and a conversational agent (the users knowingly interacted with an agent).…”

Section: Deception and Impression Managementmentioning

confidence: 99%

Conversational Agents for Mental Health and Wellbeing

Callejas

Griol

2021

Logic, Argumentation &Amp; Reasoning

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Recent advances in spoken language technology, artificial intelligence, and conversational interface design, coupled with the emergence of smart devices, have increased the possibilities of using conversational interfaces for a growing range of application domains. These interfaces are currently applied in the healthcare domain in a range of innovative tasks that allow to provide a more natural an user-friendly human-machine communication, promote patient participation in their own care, and help and support medical professionals. This chapter provides a detailed description of the great potential for the use of conversational interfaces for the specific area of mental health by means of the description of their most valuable applications in this domain and the open challenges for future research.

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“…A CA is a computer system designed to communicate with people in natural languages [26][27][28]. Most CAs are designed based on similar technology, whereas the application of these CAs varies significantly according to their purposes [27].…”

Section: Conversational Agentmentioning

confidence: 99%

“…The scores of nine items were measured on a scale ranging from 0 (not at all) to 3 (nearly every day), and these scores were added to derive the final score. A degree of depression of counselees was determined based on the scores and classified into five stages, including none (0-4), mild (5-9), moderate (10)(11)(12)(13)(14)(15)(16)(17)(18)(19), severe (20)(21)(22)(23)(24)(25)(26)(27), high risk of suicide (answer to the risk of suicidality). Those who received scores corresponding to severe and high risk of suicide stages were excluded from the experiment and guided to professional counseling institutes.…”

Section: Assessmentmentioning

confidence: 99%

The Impact of an Agent’s Voice in Psychological Counseling: Session Evaluation and Counselor Rating

Kim

Chul

2021

Applied Sciences

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As an agent delivers content during the communication between an artificial intelligence (AI) machine and a person, the voice of the agent is a crucial factor to be considered. Particularly in the fields of eHealth, the perception of users toward an agent is crucial as it significantly affects the communication between the agent and its patients, as well as the treatment results. Thus, this study examined the effects of the voice of an agent on the perception of users toward the agent and its counseling effects. This study developed a psychological counseling agent with four voices according to gender and age, communicated with the subjects through such agent, and measured the perception of users toward the agent and its counseling effects through a questionnaire. Results demonstrated that the female-voiced agent had a higher level of attractiveness than the male-voiced agent, regardless of the age of such voice, and the agent using an older voice had a higher level of expertness and depth than the agent using a younger voice, regardless of the gender of such voice. The findings of this study are expected to be effectively used to design a voice-based AI agent that considers the optimal voice according to the purpose of use.

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The effect of conversational agent skill on user behavior during deception

Cited by 44 publications

References 56 publications

Rediscovering the use of chatbots in education: A systematic literature review

Rediscovering the use of chatbots in education: A systematic literature review

Conversational Agents for Mental Health and Wellbeing

The Impact of an Agent’s Voice in Psychological Counseling: Session Evaluation and Counselor Rating

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