Location
Hilton Waikoloa Village, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2025 12:00 AM
End Date
10-1-2025 12:00 AM
Description
This study explores the dynamics of social loafing within human-AI teams, shedding light on how AI influences human motivation and group behavior. With advancements in AI technology, these entities are no longer mere tools but active team participants, potentially changing traditional teamwork dynamics. We conducted a series of experiments to investigate whether the presence of AI induces social loafing among human team members and how attitudes toward AI might affect individual efforts. Our findings reveal that while AI integration impacts team dynamics, its effect on social loafing varies depending on the perceived presence of AI and individual knowledge self-efficacy. This study contributes to understanding the interactions in human-AI teams and offers insights for designing more effective collaborative environments.
Recommended Citation
Elshan, Edona; De Vreede, Triparna; De Vreede, Gj; Ebel, Philipp Alexander; and Siemon, Dominik, "Idle Minds: The Role of Social Loafing in Human-AI Teams" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 4.
https://aisel.aisnet.org/hicss-58/cl/ai_and_future_work/4
Idle Minds: The Role of Social Loafing in Human-AI Teams
Hilton Waikoloa Village, Hawaii
This study explores the dynamics of social loafing within human-AI teams, shedding light on how AI influences human motivation and group behavior. With advancements in AI technology, these entities are no longer mere tools but active team participants, potentially changing traditional teamwork dynamics. We conducted a series of experiments to investigate whether the presence of AI induces social loafing among human team members and how attitudes toward AI might affect individual efforts. Our findings reveal that while AI integration impacts team dynamics, its effect on social loafing varies depending on the perceived presence of AI and individual knowledge self-efficacy. This study contributes to understanding the interactions in human-AI teams and offers insights for designing more effective collaborative environments.
https://aisel.aisnet.org/hicss-58/cl/ai_and_future_work/4