Paper Number
ECIS2026-2149
Paper Type
SP
Abstract
Digital labour platforms (DLPs) use algorithms to manage platform users: workers and customers. These users engage in a complex process known as algorithm sensemaking to interpret algorithmic outputs, which is often induced by the opaque nature of algorithms. Existing research has predominantly examined algorithm sensemaking from the workers’ perspective, with limited attention to customers. However, workers and customers possess distinct characteristics that shape their sensemaking differently. To understand how customers of DLPs engage in algorithm sensemaking, we conducted an empirical case study of Uber, drawing on a customer discussion forum on Reddit. Our analysis reveals specific insights on how customers engage in algorithm sensemaking through enactment triggers, selection logics, and retention forms. In addition, we also identify similarities and differences between customers’ and workers’ algorithm sensemaking. Overall, our findings extend the understanding of DLPs by explaining how a key user group, customers, makes sense of the algorithms that manage them. Keywords: Algorithm Sensemaking, Algorithmic Management, Algorithms, Digital Labour Platforms, Uber
Recommended Citation
Ishara Senaratne, Sanduni; Fielt, Erwin; Kowalkiewicz, Marek; and Bittner, Kendra, "Algorithm Sensemaking In Digital Labour Platforms: A Customer Perspective" (2026). ECIS 2026 Proceedings. 6.
https://aisel.aisnet.org/ecis2026/algo_fow/algo_fow/6
Algorithm Sensemaking In Digital Labour Platforms: A Customer Perspective
Digital labour platforms (DLPs) use algorithms to manage platform users: workers and customers. These users engage in a complex process known as algorithm sensemaking to interpret algorithmic outputs, which is often induced by the opaque nature of algorithms. Existing research has predominantly examined algorithm sensemaking from the workers’ perspective, with limited attention to customers. However, workers and customers possess distinct characteristics that shape their sensemaking differently. To understand how customers of DLPs engage in algorithm sensemaking, we conducted an empirical case study of Uber, drawing on a customer discussion forum on Reddit. Our analysis reveals specific insights on how customers engage in algorithm sensemaking through enactment triggers, selection logics, and retention forms. In addition, we also identify similarities and differences between customers’ and workers’ algorithm sensemaking. Overall, our findings extend the understanding of DLPs by explaining how a key user group, customers, makes sense of the algorithms that manage them. Keywords: Algorithm Sensemaking, Algorithmic Management, Algorithms, Digital Labour Platforms, Uber
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