Ludification as a Lens for Algorithmic Management: A Case Study of Gig-Workers’ Experiences of Ambiguity in Instacart Work

This is the authors' abstract. We don't add key points for this paper.

On-demand work platforms are attractive alternatives to traditional employment arrangements. However, several questions around employment classification, compensation, data privacy, and equitable outcomes remain open. The abilities of algorithmic management to structure different forms of platform-worker relationships compounds fraught regulatory debates. Understanding the conditions of algorithmic management that result in these variations could point us towards better worker futures. In this work, we studied the platform-worker relationships in Instacart work through the accounts of its workers. From a qualitative analysis of 400 Reddit posts by Instacart’s workers, we identified sources and types of ambiguity that gave rise to open-ended experiences for workers. Ambiguities supplemented gamification mechanisms to regulate worker behaviors. Yet, they also generated affective experiences for workers that enabled their playful participation in the Reddit community. We propose the frame of ludification to explain these seemingly contradicting findings and conclude with implications for accountability in on-demand work platforms.