How human library users categorize a robot in a service encounter
Comment les utilisateurs d'une librairie catégorisent un robot
Résumé
Our paper will investigate the opening of human-robot interactions (HRI) in a service encounter. In our data, students freely interact with a robot (Pepper) that is supposed to inform and orient them in a university library in Lyon. We developed an interaction script with regard to the robot’s tasks and conversational findings concerning human-human interactions in service encounters (e.g. Mondada 2021, Harjunpää et al. 2018). The script has then been adapted to the robot’s built-in software and capabilities. While the robot’s initial programming is based on basic word recognition, the analyses are part of an interdisciplinary project which aims at creating new algorithms that take into account the multi-modality and progressivity (Fischer et al. 2019) of social interactions. We video-recorded (multiple cameras and a first person view) 17 hours of data from which we extracted approximately 500 HRI from 6 seconds to 3 minutes (a total amount of 4 hours and 42 minutes). However, data show that the library users do not align with the categories and interactional formats of the expected (human-human) service encounter.
In our paper, we are interested in the responses to the first and second scripted turns produced by the robot. As a first turn, a generic offer of assistance is packed with a greeting (“Hello (.) can I help you”). At his point, if the humans accept this first offer or if they solely respond to the greeting, a second offer (“How can I help you”) that projects a set of relevant requests or information questions is iterated. We analyse how the turn design of users responses (rejects, acceptances and requests) frame different actions and preferences than a regular service encounter (e.g. doing designing a request as an instructed action). Focusing on the organization of turn-taking and participation framework during multiparty HRI, we then show how these user responses display a contingent treatment of the robot as a co-participant or as just another technological device like a voice agent (Avgustis et al. 2021), how students understand its purpose, its relevant institutional identity and the rights and obligations attached to these.
Our conclusions problematize the setting that we aimed to reproduce when we designed a robot as a service provider as institutions and companies do. In particular, the robot’s script expects human participants to act with benefactive statuses and stances (Clayman and Heritage 2014) that do not seem to virtually operate with robots.
