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AI on My Shoulder: Supporting Emotional Labor in Front-Office Roles with an LLM-based Empathetic Coworker

Authors :
Swain, Vedant Das
Zhong, Qiuyue "Joy"
Parekh, Jash Rajesh
Jeon, Yechan
Zimmerman, Roy
Czerwinski, Mary
Suh, Jina
Mishra, Varun
Saha, Koustuv
Hernandez, Javier
Publication Year :
2024

Abstract

Client-Service Representatives (CSRs) are vital to organizations. Frequent interactions with disgruntled clients, however, disrupt their mental well-being. To help CSRs regulate their emotions while interacting with uncivil clients, we designed Pro-Pilot, an LLM-powered assistant, and evaluated its efficacy, perception, and use. Our comparative analyses between 665 human and Pro-Pilot-generated support messages demonstrate Pro-Pilot's ability to adapt to and demonstrate empathy in various incivility incidents. Additionally, 143 CSRs assessed Pro-Pilot's empathy as more sincere and actionable than human messages. Finally, we interviewed 20 CSRs who interacted with Pro-Pilot in a simulation exercise. They reported that Pro-Pilot helped them avoid negative thinking, recenter thoughts, and humanize clients; showing potential for bridging gaps in coworker support. Yet, they also noted deployment challenges and emphasized the irreplaceability of shared experiences. We discuss future designs and societal implications of AI-mediated emotional labor, underscoring empathy as a critical function for AI assistants in front-office roles.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2411.02408
Document Type :
Working Paper