Users’ Information Disclosure Behaviors during Interactions with Chatbots: The Effect of Information Disclosure Nudges

Abstract

Drawing from the tension between a company’s desire for customer information to tailor experiences and a consumer’s need for privacy, this study aims to test the effect of two information disclosure nudges on users’ information disclosure behaviors. Whereas previous literature on user-chatbot interaction focused on encouraging and increasing users’ disclosures, this study introduces measures that make users conscious of their disclosure behaviors to low and high-sensitivity questions asked by chatbots. A within-subjects laboratory experiment entailed 19 participants interacting with chatbots, responding to pre-tested questions of varying sensitivity while being presented with different information disclosure nudges. The results suggest that question sensitivity negatively impacts users’ information disclosures to chatbots. Moreover, this study suggests that adding a sensitivity signal—presenting the level of sensitivity of the question asked by the chatbot—influences users’ information disclosure behaviors. Finally, the theoretical contributions and managerial implications of the results are discussed.

How do friendship artificial intelligence chatbots (FAIC) benefit the continuance using intention and customer engagement?

“…However, users' privacy concerns and perceived risks often arise with personalized recommendations, and perceived risks negatively impact users' experience and reduce the level of users' satisfaction with chatbots (Cheng & Jiang, 2020). How realize the “personalization‐privacy trade‐off” (Carmichael et al, 2022) is vital to the development of social chatbots. The anthropomorphic cues and humanlike qualities increasing social presence are the main strategies at present (Ng et al, 2020; Zeng et al, 2018).…”

“…Information collection is beneficial for chatbots to provide personalized recommendations and services to users (Carmichael et al, 2022). However, users' privacy concerns and perceived risks often arise with personalized recommendations, and perceived risks negatively impact users' experience and reduce the level of users' satisfaction with chatbots (Cheng & Jiang, 2020).…”

Special Issue on Human and Artificial Intelligence

“…The experimental results of this study on public online datasets allow us to develop increasingly effective AI-based assistants capable, for example, of helping visually impaired people to understand the content of digital images. • Carmichael et al [11] explore another compelling aspect of human-computer interaction systems. They analyze the impact of information disclosure nudges on the behavior of chatbot users.…”