Understanding Collaboration with Virtual Assistants – The Role of Social Identity and the Extended Self

Abstract

Organizations introduce virtual assistants (VAs) to support employees with work-related tasks. VAs can increase the success of teamwork and thus become an integral part of the daily work life. However, the effect of VAs on virtual teams remains unclear. While social identity theory describes the identification of employees with team members and the continued existence of a group identity, the concept of the extended self refers to the incorporation of possessions into one’s sense of self. This raises the question of which approach applies to VAs as teammates. The article extends the IS literature by examining the impact of VAs on individuals and teams and updates the knowledge on social identity and the extended self by deploying VAs in a collaborative setting. Using a laboratory experiment with N = 50, two groups were compared in solving a task, where one group was assisted by a VA, while the other was supported by a person. Results highlight that employees who identify VAs as part of their extended self are more likely to identify with team members and vice versa. The two aspects are thus combined into the proposed construct of virtually extended identification explaining the relationships of collaboration with VAs. This study contributes to the understanding on the influence of the extended self and social identity on collaboration with VAs. Practitioners are able to assess how VAs improve collaboration and teamwork in mixed teams in organizations.

Hybrid intelligence in hospitals: towards a research agenda for collaboration

“…Currently deployed CAs are particularly useful for highly standardized processes or repetitive procedures, thus are rather domain-specific focusing on a narrow task (Batin et al 2017;Knote et al 2019). Results provided by CAs are generated according to an explicit pattern (Brachten et al 2020;Mirbabaie et al 2020). More complex contexts are still jointly solved with humans (Maedche et al 2019).…”

The rise of artificial intelligence – understanding the AI identity threat at the workplace

“…The findings indicate that, first, the collaborative execution of tasks is more efficient and, second, VAs decrease the load, illustrating that collaboration also reduces the perceived workload of employees in the workplace. Furthermore, Mirbabaie et al (2020) examined social identity, i.e., the identification of employees with team members, and extended self, i.e., the incorporation of possessions into one's sense of self, when humans work with VAs in teams. The authors derived a new concept, virtually extended identification, elaborating that individuals who identify themselves with (virtual) team members are also more likely to identify with the technology as a part of their extended selves and vice versa.…”

“…One major factor driving this discussion is the ongoing development of artificial intelligence (AI), which that can be described as "the ability of a machine to perform cognitive functions that we associate with human minds, such as perceiving, reasoning, learning, interacting with the environment, problem solving, decision-making, and even demonstrating creativity" (Rai et al, 2019, p. iii). In digital work, AI is applied for various functions, such as (managerial) decision making (Haesevoets et al, 2021), data analysis and prediction work (Grønsund & Aanestad, 2020;Marabelli et al, 2021), or (human-AI) collaboration (Brachten et al, 2020;Mirbabaie et al, 2020Mirbabaie et al, , 2021. Therefore, AI will change workplaces and professions persistently, potentially threatening the livelihoods of individuals whose jobs are taken over (Aleksander, 2017;Haenlein & Kaplan, 2019).…”

Artificial intelligence in hospitals: providing a status quo of ethical considerations in academia to guide future research

“…Applications of AI are rather narrowed down to a specific task (Batin et al 2017 ; Frick et al 2019b ; Mirbabaie et al 2020 ) but commonly generate superior results compared to humans. When integrated into the existing technical infrastructure of hospitals, AI accelerates data collection from multiple sources (Nasirian et al 2017 ), provides medical experts with more accurate and timely information (Atherton et al 2013 ; Preece et al 2017 ; Diederich et al 2019 ), tailors to the needs of patients and their treatment processes (Dilsizian and Siegel 2014 ) and enhances integration with other hospital IS (Serrano et al 2020 ).…”