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Prestige Questions, Online Agents, and Gender-Driven Differences in Disclosure

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Intelligent Virtual Agents (IVA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10498))

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Abstract

This work considers the possibility of using virtual agents to encourage disclosure for sensitive information. In particular, this research used “prestige questions”, which asked participants to disclose information relevant to their socioeconomic status, such as credit limit, as well as university attendance, and mortgage or rent payments they could afford. We explored the potential for agents to enhance disclosure compared to conventional web-forms, due to their ability to serve as relational agents by creating rapport. To consider this possibility, agents were framed as artificially intelligent versus avatars controlled by a real human, and we compared these conditions to a version of the financial questionnaire with no agent. In this way, both the perceived agency of the agent and its ability to generate rapport were tested. Additionally, we examined the differences in disclosure between men and women in these conditions. Analyses reveled that agents (either AI- or human-framed) evoked greater disclosure compared to the no agent condition. However, there was some evidence that human-framed agents evoked greater lying. Thus, users in general responded more socially to the presence of a human- or AI-framed agent, and the benefits and costs of this approach were made apparent. The results are discussed in terms of rapport and anonymity.

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Correspondence to Johnathan Mell .

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Mell, J., Lucas, G., Gratch, J. (2017). Prestige Questions, Online Agents, and Gender-Driven Differences in Disclosure. In: Beskow, J., Peters, C., Castellano, G., O'Sullivan, C., Leite, I., Kopp, S. (eds) Intelligent Virtual Agents. IVA 2017. Lecture Notes in Computer Science(), vol 10498. Springer, Cham. https://doi.org/10.1007/978-3-319-67401-8_36

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  • DOI: https://doi.org/10.1007/978-3-319-67401-8_36

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  • Publisher Name: Springer, Cham

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