Privacy-Preserving Behaviour of Chatbot Users: Steering Through Trust Dynamics
Julia Ive, Vishal Yadav, Mariia Ignashina, Matthew Rand, and Paulina Bondaronek

TL;DR
This study investigates user awareness and behaviors regarding privacy risks in chatbot interactions, revealing significant gaps in understanding and inconsistent privacy-preserving actions, especially among more knowledgeable users.
Contribution
It introduces a novel privacy-safe experimental setup and provides insights into user privacy behaviors and misconceptions in chatbot use.
Findings
Majority of users lack understanding of data handling (73%)
Older users fear data selling by providers
Knowledgeable users often do not practice privacy-preserving behaviors
Abstract
Introduction: The use of chatbots is becoming increasingly important across various aspects of daily life. However, the privacy concerns associated with these communications have not yet been thoroughly addressed. The aim of this study was to investigate user awareness of privacy risks in chatbot interactions, the privacy-preserving behaviours users practice, and how these behaviours relate to their awareness of privacy threats, even when no immediate threat is perceived. Methods: We developed a novel "privacy-safe" setup to analyse user behaviour under the guarantees of anonymization and non-sharing. We employed a mixed-methods approach, starting with the quantification of broader trends by coding responses, followed by conducting a qualitative content analysis to gain deeper insights. Results: Overall, there was a substantial lack of understanding among users about how chatbot…
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Taxonomy
TopicsPrivacy, Security, and Data Protection · Ethics and Social Impacts of AI · Cognitive Functions and Memory
