Start Date
10-12-2017 12:00 AM
Description
As individuals increasingly interact with algorithms in a work context, it is important to understand these new types of ‘human-algorithm’ relationships. We investigate the human-algorithm interaction between Uber drivers and the Uber driver app in managing customers, routes and fares. This research-in-progress paper reports on initial findings from an ongoing study, from interviews with ten Uber drivers in the United States. Our findings illustrate that Uber drivers experience role ambiguity and role conflict as they attribute different roles to the algorithms embedded in their app. The literature shows that ambiguity and conflict create workplace uncertainty. We expand on it by identifying several new sources of role ambiguity and role conflict that emerge between the driver and the algorithm. Our initial results are positioned within the literature that studies the emerging role of algorithms at work.
Recommended Citation
Page, Xinru; Marabelli, Marco; and Tarafdar, Monideepa, "Perceived Role Relationships in Human-Algorithm Interactions: The Context of Uber Drivers" (2017). ICIS 2017 Proceedings. 25.
https://aisel.aisnet.org/icis2017/HumanBehavior/Presentations/25
Perceived Role Relationships in Human-Algorithm Interactions: The Context of Uber Drivers
As individuals increasingly interact with algorithms in a work context, it is important to understand these new types of ‘human-algorithm’ relationships. We investigate the human-algorithm interaction between Uber drivers and the Uber driver app in managing customers, routes and fares. This research-in-progress paper reports on initial findings from an ongoing study, from interviews with ten Uber drivers in the United States. Our findings illustrate that Uber drivers experience role ambiguity and role conflict as they attribute different roles to the algorithms embedded in their app. The literature shows that ambiguity and conflict create workplace uncertainty. We expand on it by identifying several new sources of role ambiguity and role conflict that emerge between the driver and the algorithm. Our initial results are positioned within the literature that studies the emerging role of algorithms at work.