Resolving the Chatbot Disclosure Dilemma: Leveraging Selective Self-Presentation to Mitigate the Negative Effect of Chatbot Disclosure

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0285.pdf (502.83 KB)
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2021-01-05
Authors
Mozafari, Nika
Weiger, Welf H.
Hammerschmidt, Maik
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2916
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Abstract
Chatbots are increasingly able to pose as humans. However, this does not hold true if their identity is explicitly disclosed to users—a practice that will become a legal obligation for many service providers in the imminent future. Previous studies hint at a chatbot disclosure dilemma in that disclosing the non-human identity of chatbots comes at the cost of negative user responses. As these responses are commonly attributed to reduced trust in algorithms, this research examines how the detrimental impact of chatbot disclosure on trust can be buffered. Based on computer-mediated communication theory, the authors demonstrate that the chatbot disclosure dilemma can be resolved if disclosure is paired with selective presentation of the chatbot’s capabilities. Study results show that while merely disclosing (vs. not disclosing) chatbot identity does reduce trust, pairing chatbot disclosure with selectively presented information on the chatbot’s expertise or weaknesses is able to mitigate this negative effect.
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Mediated Conversation, chatbot disclosure, computer-mediated communication, selective self-presentation, trust
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http://hdl.handle.net/10125/70969
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8 pages
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Proceedings of the 54th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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Mediated Conversation
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