AI Service and Emotion

Abstract

AI in service can be for routine mechanical tasks, analytical thinking tasks, or empathetic feeling tasks. We provide a conceptual framework for the customer, firm, and interactional use of AI for empathetic tasks at the micro-, meso-, and macro-levels. Emotions resulting from AI service interactions can include basic emotions (e.g., joy, sadness, and fear), self-conscious emotions (e.g., pride, guilt, embarrassment), and moral emotions (e.g., contempt, righteous anger, social disgust). These emotions are mostly likely to occur during frontline interactions in which both firms and customers use AI, a phenomenon called “AI as customer.” The analysis level of AI service and emotion can be at the macro-level in which AI is transforming the service economy into a feeling economy, at the meso-level in which firms can use “thoughtful AI” to make the employees’ and customers’ lives a little bit better by brightening their days, and at the micro-level in which customers can experience basic, self-conscious, and moral emotions from interactions with service AI.

Pepper, just show me the way! How robotic shopping assistants should look and act

“…Consequently, the hedonic and utilitarian attributes of robotic technology have been largely overlooked particularly in relation to the appearance of RSAs (Blut et al, 2016;van der Heijden, 2004). As more emotional AI is developed (Bagozzi et al, 2022;Huang & Rust, 2021;Labbé, 2022), our research adds the theoretical implications of hedonic versus utilitarian attributes of robots in relation to anthropomorphism (Batra & Ahtola, 1991;Botti & McGill, 2011;Wang et al, 2015). We do so by showing how internal factors of robots (hedonic attributes) trigger negative customer responses in relation to external factors of robots (the physical appearance).…”

Enablers or Inhibitors? Unpacking the Emotional Power Behind In-Vehicle AI Anthropomorphic Interaction: A Dual-Factor Approach by Text Mining

“…Orea-Giner et al [52] used text-mining techniques to explore the relationship between emotions and sentiments generated by customers during hotelrobot interactions and the potential impact on hotel ratings. From the micro-, meso-, and macrolevels, Bagozzi et al [53] classified emotions resulting from AI service interaction into basic emotions (e.g., joy, sadness, and fear), self-conscious emotions (e.g., pride, guilt, embarrassment), and moral emotions (e.g., contempt, righteous anger, social disgust). Taking the use of AI Chatbots by employees in the digital workplace as a specific type of AI system, Gkinko and Elbanna revealed the emotional experience of this system: hope, tolerance, and empathy [54].…”

A Systematic and Visual Overview of 25 Years of the Journal of Service Research: The Journey Continues

“…The special issues on AI Service and Emotion (Bagozzi et al 2022) and Disrupting the Organizational Frontlines (Arnold and Marinova 2023) also explore the impacts of service technology and artificial intelligence (AI) and the boundaries of the service frontline, such that they extend a strong and stable core service topic. Recent calls for special issues on Human–Robot Interactions in Service and Smart Service Failure–Recovery seek to build on existing core concepts and stable research themes from the service domain and extend them to innovative and emerging service technologies.…”