The Challenges of Building Fair Crowdsourcing: Analyzing Work and Income in the Case of Amara on Demand

Abstract

Building on the success of online collaborative communities, crowdsourcing platforms have emerged as an answer to private capital’s interest in having work without hired workers, and workers’ interest in flexible online work. Scholars have highlighted the risks associated with profit-seeking crowdsourcing, from its exploitative and alienating nature, to its impact on labor relations and inequalities, to its subpar working conditions. However, not all crowdsourcing platforms are the same. The subtitling platform Amara On Demand (AOD)  is one example where profit is not the motive and the business is built on cooperative values. AOD provides a global and inclusive platform for subtitling services based on a multilingual community of professionals. This paper presents a statistical examination of working conditions at AOD, with a focus on the characteristics of work and the distribution of both work and remuneration among workers. It also offers insights into the characteristic multilingual nature of AOD and its federated organization into language groups—which sets it apart from other crowdsourcing platforms. Among other findings, we can observe a significant concentration in the distribution of both work and earnings inside each language group, and among workers in general, in line with patterns of participation inequality found across online communities.

Keywords: Crowdsourcing, Digital Labor, Participation Inequality, Platform Cooperativism, Income Distribution, Multilingual Subtitling, Amara on Demand