Ziang Xiao 1, Michelle X. Zhou2, Wenxi Chen2, Huahai Yang2, Changyan Chi2

1University of Illinois at Urbana-Champaign, 2Juji, Inc.

Abstract

Interview chatbots engage users in a text-based conversation to draw out their views and opinions. It is, however, challenging to build effective interview chatbots that can handle user free-text responses to open-ended questions and deliver engaging user experience. As the first step, we are investigating the feasibility and effectiveness of using publicly available, practical AI technologies to build effective interview chatbots. To demonstrate feasibility, we built a prototype scoped to enable interview chatbots with a subset of active listening skills—the abilities to comprehend a user’s input and respond properly. To evaluate the effectiveness of our prototype, we compared the performance of interview chatbots with or without active listening skills on four common interview topics in a live evaluation with 206 users. Our work presents practical design implications for building efective interview chatbots, hybrid chatbot platforms, and empathetic chatbots beyond interview tasks.

Bibtex

        @inproceedings{10.1145/3313831.3376131,
            author = {Xiao, Ziang and Zhou, Michelle X. and Chen, Wenxi and Yang, Huahai and Chi, Changyan},
            title = {If I Hear You Correctly: Building and Evaluating Interview Chatbots with Active Listening Skills},
            year = {2020},
            isbn = {9781450367080},
            publisher = {Association for Computing Machinery},
            address = {New York, NY, USA},
            url = {https://doi.org/10.1145/3313831.3376131},
            doi = {10.1145/3313831.3376131},
            booktitle = {Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems},
            pages = {1–14},
            numpages = {14},
            keywords = {interview chatbot, chatbot platform, conversational agents, ai chatbot, active listening, deep learning},
            location = {Honolulu, HI, USA},
            series = {CHI ’20}
            }