Understanding users’ responses to disclosed vs. undisclosed customer service chatbots

A mixed methods study

Bibliographic Data

ID20396506
AuthorsMargot J van der Goot (0000-0001-6904-6515, University of Amsterdam, corresponding author), Nathalie Koubayová (0000-0002-6741-0747, Charles University), Eva A Van Reijmersdal (0000-0002-3950-3524, University of Amsterdam)
Year2024
Volume39
Issue6
Pages2947-2960
Publication date2024-12-01
Open AccessYes
TypeARTICLE
VenueAI & Society (JOURNAL)
Journal identifiersISSN: 0951-5666 • E-ISSN: 1435-5655
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s00146-023-01818-7
OpenAlexW4390619488
LanguageEN
Citations received4
References cited33

Due to huge advancements in natural language processing (NLP) and machine learning, chatbots are gaining significance in the field of customer service. For users, it may be hard to distinguish whether they are communicating with a human or a chatbot. This brings ethical issues, as users have the right to know who or what they are interacting with (European Commission in Regulatory framework proposal on artificial intelligence. https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai , 2022). One of the solutions is to include a disclosure at the start of the interaction (e.g., “this is a chatbot”). However, companies are reluctant to use disclosures, as consumers may perceive artificial agents as less knowledgeable and empathetic than their human counterparts (Luo et al. in Market Sci 38(6):937–947, 2019). The current mixed methods study, combining qualitative interviews ( n = 8) and a quantitative experiment ( n = 194), delves into users’ responses to a disclosed vs. undisclosed customer service chatbot, focusing on source orientation, anthropomorphism, and social presence. The qualitative interviews reveal that it is the willingness to help the customer and the friendly tone of voice that matters to the users, regardless of the artificial status of the customer care representative. The experiment did not show significant effects of the disclosure (vs. non-disclosure). Implications for research, legislators and businesses are discussed

Business · Chatbot · Customer care · Customer service · Internet privacy · Knowledge management · Political science · Public relations · Qualitative research · Sociology · World Wide Web · AI in Service Interactions · Computer Science · Ethics and Social Impacts of AI · Psychology · Social Robot Interaction and HRI · Marketing

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