Comparing How a Chatbot References User Utterances from Previous Chatting Sessions: An Investigation of Users' Privacy Concerns and Perceptions

TL;DR

This study examines how different ways of referencing past conversations in chatbots affect user perceptions and privacy concerns, revealing a trade-off between engagement and privacy risk.

Contribution

It provides empirical insights into user perceptions of chatbot referencing formats and their impact on privacy concerns, guiding better dialogue design.

Findings

Verbatim and Paraphrase references increase perceived intelligence and engagement.

Verbatim referencing raises higher privacy concerns.

Design choices in referencing format influence user trust and privacy perceptions.

Abstract

Chatbots are capable of remembering and referencing previous conversations, but does this enhance user engagement or infringe on privacy? To explore this trade-off, we investigated the format of how a chatbot references previous conversations with a user and its effects on a user's perceptions and privacy concerns. In a three-week longitudinal between-subjects study, 169 participants talked about their dental flossing habits to a chatbot that either, (1-None): did not explicitly reference previous user utterances, (2-Verbatim): referenced previous utterances verbatim, or (3-Paraphrase): used paraphrases to reference previous utterances. Participants perceived Verbatim and Paraphrase chatbots as more intelligent and engaging. However, the Verbatim chatbot also raised privacy concerns with participants. To gain insights as to why people prefer certain conditions or had privacy concerns, we conducted semi-structured interviews with 15 participants. We discuss implications from our findings that can help designers choose an appropriate format to reference previous user utterances and inform in the design of longitudinal dialogue scripting.