Paper Number

ICIS2025-2826

Paper Type

Short

Abstract

The flourishing application of AI chatbots in chronic disease management and prevention leads to the requirement of a theoretical basis for chatbot design. Anthropomorphized features of such AI healthcare assistants are paid a lot of attention. However, there have been inconsistent results found on the effects of anthropomorphism, and the underlying mechanism of such features haven’t been fully explored, considering anthropomorphism works as a result of the intertwining of two similarities that sometimes overlap: similarity between chatbot and human, and similarity between chatbot and user. Therefore, we plan to conduct laboratory experiments to explore how different kinds of similarities affect intention to adopt suggestions and willingness to self-disclose through psychological distance and privacy concern. We expect to improve the understanding of anthropomorphism, providing insights into how to design AI healthcare assistants efficiently.

Comments

21-Healthcare

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Dec 14th, 12:00 AM

Anthropomorphism or Individualization? The effects of Two Similarities of AI Healthcare Assistant to Users

The flourishing application of AI chatbots in chronic disease management and prevention leads to the requirement of a theoretical basis for chatbot design. Anthropomorphized features of such AI healthcare assistants are paid a lot of attention. However, there have been inconsistent results found on the effects of anthropomorphism, and the underlying mechanism of such features haven’t been fully explored, considering anthropomorphism works as a result of the intertwining of two similarities that sometimes overlap: similarity between chatbot and human, and similarity between chatbot and user. Therefore, we plan to conduct laboratory experiments to explore how different kinds of similarities affect intention to adopt suggestions and willingness to self-disclose through psychological distance and privacy concern. We expect to improve the understanding of anthropomorphism, providing insights into how to design AI healthcare assistants efficiently.

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