Digital Commerce and the Digitally Connected Enterprise
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Paper Type
Short
Paper Number
1325
Description
Chatbots are predicted to play a key role in customer service based on recent advances in the area of Artificial Intelligence (AI). However, a lack of user trust impedes the wide-spread adaption of AI-based chatbots. Still, there is a lack of systematically derived design knowledge concerning user trust in those agents. In this short paper, we report on the first steps of our design science research project on which design principles are relevant for building trust in chatbots. Based on trust literature and user interviews, we propose preliminary requirements and design principles for trust-enhancing design features for chatbots in customer service. Furthermore, we present a first instantiation of those principles. These insights will support researchers and practitioners to better understand how user trust in chatbots can be systematically built to increase adoption and usage.
Recommended Citation
Zierau, Naim; Hausch, Michael; Bruhin, Olivia; and Soellner, Matthias, "Towards Developing Trust-Supporting Design Features for AI-Based Chatbots in Customer Service" (2020). ICIS 2020 Proceedings. 2.
https://aisel.aisnet.org/icis2020/digital_commerce/digital_commerce/2
Towards Developing Trust-Supporting Design Features for AI-Based Chatbots in Customer Service
Chatbots are predicted to play a key role in customer service based on recent advances in the area of Artificial Intelligence (AI). However, a lack of user trust impedes the wide-spread adaption of AI-based chatbots. Still, there is a lack of systematically derived design knowledge concerning user trust in those agents. In this short paper, we report on the first steps of our design science research project on which design principles are relevant for building trust in chatbots. Based on trust literature and user interviews, we propose preliminary requirements and design principles for trust-enhancing design features for chatbots in customer service. Furthermore, we present a first instantiation of those principles. These insights will support researchers and practitioners to better understand how user trust in chatbots can be systematically built to increase adoption and usage.
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