TY - GEN
T1 - To Trust or Not To Trust
T2 - 31st ACM World Wide Web Conference, WWW 2022
AU - Gupta, Akshit
AU - Basu, Debadeep
AU - Ghantasala, Ramya
AU - Qiu, Sihang
AU - Gadiraju, Ujwal
PY - 2022
Y1 - 2022
N2 - Trust is an important component of human-AI relationships and plays a major role in shaping the reliance of users on online algorithmic decision support systems. With recent advances in natural language processing, text and voice-based conversational interfaces have provided users with new ways of interacting with such systems. Despite the growing applications of conversational user interfaces (CUIs), little is currently understood about the suitability of such interfaces for decision support and how CUIs inspire trust among humans engaging with decision support systems. In this work, we aim to address this gap and answer the following question: to what extent can a conversational interface build user trust in decision support systems in comparison to a conventional graphical user interface? To this end, we built a text-based conversational interface, and a conventional web-based graphical user interface. These served as the means for users to interact with an online decision support system to help them find housing, given a fixed set of constraints. To understand how the accuracy of the decision support system moderates user behavior and trust across the two interfaces, we considered an accurate and inaccurate system. We carried out a 2 × 2 between-subjects study (N = 240) on the Prolific crowdsourcing platform. Our findings show that the conversational interface was significantly more effective in building user trust and satisfaction in the online housing recommendation system when compared to the conventional web interface. Our results highlight the potential impact of conversational interfaces for trust development in decision support systems.
AB - Trust is an important component of human-AI relationships and plays a major role in shaping the reliance of users on online algorithmic decision support systems. With recent advances in natural language processing, text and voice-based conversational interfaces have provided users with new ways of interacting with such systems. Despite the growing applications of conversational user interfaces (CUIs), little is currently understood about the suitability of such interfaces for decision support and how CUIs inspire trust among humans engaging with decision support systems. In this work, we aim to address this gap and answer the following question: to what extent can a conversational interface build user trust in decision support systems in comparison to a conventional graphical user interface? To this end, we built a text-based conversational interface, and a conventional web-based graphical user interface. These served as the means for users to interact with an online decision support system to help them find housing, given a fixed set of constraints. To understand how the accuracy of the decision support system moderates user behavior and trust across the two interfaces, we considered an accurate and inaccurate system. We carried out a 2 × 2 between-subjects study (N = 240) on the Prolific crowdsourcing platform. Our findings show that the conversational interface was significantly more effective in building user trust and satisfaction in the online housing recommendation system when compared to the conventional web interface. Our results highlight the potential impact of conversational interfaces for trust development in decision support systems.
KW - AI
KW - Conversational user interface
KW - Decision support system
KW - Trust
UR - http://www.scopus.com/inward/record.url?scp=85129844451&partnerID=8YFLogxK
U2 - 10.1145/3485447.3512248
DO - 10.1145/3485447.3512248
M3 - Conference contribution
AN - SCOPUS:85129844451
T3 - WWW 2022 - Proceedings of the ACM Web Conference 2022
SP - 3531
EP - 3540
BT - WWW 2022 - Proceedings of the ACM Web Conference 2022
PB - ACM
Y2 - 25 April 2022 through 29 April 2022
ER -