Abstract
Groups can do better than individuals through two mechanisms: aggregation and synergy. Aggregation means bringing knowledge together, and synergy means increasing the effectiveness that comes about through joint action or cooperation. However, we usually measure a group’s effectiveness by productivity outcome but disregard the other critical aspects, specifically the experiences and sustainability of the team: does the group member feel fair? Without the sense of fairness, group members do not have a clear metric on how their contributions lead to rewards, and may gradually lose the motivation to engage and contribute. Groups can suffer both in terms of aggregation and synergy. Our goal in this work-in-progress paper is to formulate a user-interpretable and -transparent reward model to operationalize fairness in groups. We apply the model to design a workload tracking dashboard for group members to view and negotiate individual workloads transparently, and to improve fairness both in group procedure and outcome.
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Liang, JW., Wang, HC. (2023). Reshaping Group Life: A Transparent and Interpretable Reward Model to Enhance Fairness in Groups. In: Takada, H., Marutschke, D.M., Alvarez, C., Inoue, T., Hayashi, Y., Hernandez-Leo, D. (eds) Collaboration Technologies and Social Computing. CollabTech 2023. Lecture Notes in Computer Science, vol 14199. Springer, Cham. https://doi.org/10.1007/978-3-031-42141-9_18
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