2022
Upward Influence Tactics: Playful Virtual Reality Approach for Analysing Human Multi-robot Interaction
GERDENITSCH, Cornelia; Matthias WEINHOFER; Jaison PUTHENKALAM a Simone KRIGLSTEINZákladní údaje
Originální název
Upward Influence Tactics: Playful Virtual Reality Approach for Analysing Human Multi-robot Interaction
Autoři
GERDENITSCH, Cornelia; Matthias WEINHOFER; Jaison PUTHENKALAM a Simone KRIGLSTEIN
Vydání
Bremen, Germany, Entertainment Computing – ICEC 2022: 21st IFIP TC 14 International Conference, od s. 76-88, 13 s. 2022
Nakladatel
Springer
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Švýcarsko
Utajení
není předmětem státního či obchodního tajemství
Forma vydání
tištěná verze "print"
Odkazy
Impakt faktor
Impact factor: 0.402 v roce 2005
Označené pro přenos do RIV
Ano
Kód RIV
RIV/00216224:14330/22:00127295
Organizační jednotka
Fakulta informatiky
ISBN
978-3-031-20211-7
ISSN
UT WoS
EID Scopus
Klíčová slova anglicky
Virtual reality; Robot; Leadership; Influence tactics; Human robot interaction
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 13. 8. 2025 17:45, Mgr. Petra Trembecká, Ph.D.
Anotace
V originále
The interest, the potential, and also the technical development in artificial intelligence assistants shows us that these will play an essential role in the future of work. Exploring the interaction and communication between human and artificial intelligence (AI) assistants forms the basis for the development of trustworthy and meaningful AI-based systems. In this paper we focused on the question how humans react to AI - more precisely, AI gents as robots - that act to influence human behavior and emotions by using two upward influencing tactics: Ingratiating and Blocking. For this purpose, we developed a playful virtual reality approach that creates a leader-subordinate relationship between humans and the AI agents in a factory environment. We explore how humans react to those agents. Among other things, we found that behaviors that are seen as likable in humans are perceived as distracting in robots (e.g., compliments used by the ingratiating tactic). Further, robots were perceived as a group and not as individuals. Our findings showed us directions and open questions which need to be investigated in future work investigating human-multi-robot interaction at the workplace.