How Do People Ascribe Humanness to Chatbots? An Analysis of Real-World Human-Agent Interactions and a Theoretical Model of Humanness

AbstractA central problem in text-based chatbot research revolves around humanness: not only chatbots may reproduce fundamental aspects of being human, but also users may attribute humanlike features to chatbots. Humanness is paramount in human-chatbot conversations because it may profoundly impact the quality of the interaction: for example, when users expect that interactions with chatbots are similar to human conversations and these expectations are not met by the agent, they may easily become frustrated. This is particularly relevant in customer care, where efficient support is essential: here, unmet expectations about the chatbot’s humanlike capabilities can undermine customer satisfaction. In this article, we qualitatively analyzed 12,477 real-world exchanges with a task-based chatbot in the customer care domain, involving a total of 1,060 conversations. We conducted a single case study to define a preliminary theoretical model of humanness for chatbot technology. The study findings point to a novel conceptualization of humanness in customer-chatbot interaction, highlighting that it is multiple, contextual, modular, and dynamic. Moreover, the theoretical model that we propose explains that the kind of humanness attributed to a chatbot depends on the context in which people expect to interact, the objectives and needs that they aim to fulfill, and the cues that the chatbot exhibits: all these factors may change as the interaction evolves over time, and such changes may further affect the users’ ascriptions of humanness. Finally, we propose design implications of the model, like the need to create “context” and account for the plurality of humanness.Keywords: Conversational agentschatbotshumannesshuman-AI interactionhuman-agent interactionartificial intelligencecustomer care Disclosure statementThe research was partially funded by TIM S.p.A. within the project “Studi e ricerche su sistemi conversazionali intelligenti” agreement n. S19AARLL. The funding source owned the chatbot investigated in this article and the dataset, and had the unique role of collecting the raw conversational data. It had no other roles in the analysis and interpretation of data, in the writing of the article (apart from the writing of the paragraph that describes the technical details of the chatbot, i.e., “3.2 Chatbot characteristics”, provided by Alessandro Perrucci), or in the decision to submit it for publication in this journal, and in no way influenced the findings reported in this article.Notes1 The translation of the conversation on the left is: C: “Hello, I am Angie! The TIM virtual assistant” C: “I can help you manage your offers, give you business assistance, administrative assistance, and solve technical problems.” C: “Reduce your spending up to 2500€with government vouchers for fiber and FWA. Hurry they are limited…! To learn more type in VOUCHER anytime.” C: “How can I help you?” U: “Hi” C: “Hello, I am Angie! How can I help you?”. The translation of the conversation on the right is: U: “Hello, how are you?” C: “I’m fine, thanks. How can I help you?” U: “I wanted to ask you about tim vision” C: “Sorry, I would like to understand your request better to be able to help you” C: “Are you referring to the landline or the mobile line?” C: “Landline” C: “Mobile line”.2 Italian language has four different pronouns to refer to an interlocutor, that is “lei”, “tu”, “voi”, and “esso”.Additional informationNotes on contributorsAmon RappAmon Rapp is an associate professor in the Computer Science Department at the University of Torino. His research interests revolve around self-tracking and wearable devices, video games, intelligent agents, and behavior change technologies.Arianna BoldiArianna Boldi is a PhD student in the Psychology Department at the University of Torino. Her research interests revolve around video games, self-tracking and intelligent agents, as well as the use of technology in the context of work.Lorenzo CurtiLorenzo Curti is a psychologist with an interest in human-computer interaction, artificial intelligence and gender identity.Alessandro PerrucciAlessandro Perrucci is a computer engineer with an interest in machine learning, artificial intelligence, process & service innovation and project management; he is currently employed in the Data Office department of TIM S.p.A.Rossana SimeoniRossana Simeoni is a computer scientist with an interest in intelligent interactive systems, human-computer interaction, knowledge-based systems, AI technologies, UX & interaction design, system integration; she is an innovation project manager in the Data Office department of TIM S.p.A. and an adjunct professor at the University of Torino.