Digital Discrimination in Sharing Economy A Requirements Engineering Perspective

Abstract

Recent evidence has revealed that Sharing Economy platforms such as Uber, Airbnb, and TaskRabbit, have become active hubs for digital discrimination. This new form of discrimination refers to a phenomenon where a business transaction is influenced by race, gender, age, or any other non-business related characteristic of providers or consumers. Existing research often tackles this problem from a socio-economic and regulatory points of view. However, the research on the design aspects of Sharing Economy software, which enable such complex sociotechnical problems to emerge online, is still underdeveloped. To bridge this gap, in this paper, we propose a new perspective on digital discrimination, tackling the problem from a Requirements Engineering point of view. Specifically, we analyze a large dataset of online user feedback as well as synthesize existing literature to identify and classify pervasive discrimination concerns in the Sharing Economy market. Based on this analysis, we devise a crowd-driven domain model to represent these concerns along with their relations to the functional features and user goals of Sharing Economy platforms. This model is intended to provide requirements engineers, working on Sharing Economy software, with systematic insights into the complex types of socio-technical problems that can emerge in the operational environments of their systems.

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