Digital Labour

Be Mindful of the Short-Circuiting of Platform Work Narratives

The fight for fair and decent digital work involves multiple fronts. These include advocacy for accountable applications of technology, an inclusive policy-making agenda, and the construction of alternative narratives to those favored by companies or neoliberal governments or both, to list a few. The fight for fair and decent digital work is also deeply affected by local and national contextual factors such as the existing labor market and local income level. All seem to be uphill battles calling for joint efforts from concerned scholars, activists, and workers.

The latest globally uneven proliferations of platform-dependent jobs (e.g., gig driving and micro-work) raise serious challenges in terms of how to localize the multi-front battle for fair and decent digital work. For developing countries in particular, which often concern themselves with integrating into the global (digital) economy and development agenda, the discursive front of the fight for fair and decent digital work—that is, mainstreaming the worker-centered narratives about platform work—turns out to be tougher than other fronts.

Scholars like to use the trope of the “black box” (Pasquale, 2015) to describe the secretive and opaque way in which private IT companies utilize proprietary algorithms to manipulate consumers, users, and workers. Though scholars may perform reverse engineering to gather information on the inner workings of certain algorithms, systematic knowledge is hard to acquire. For example, the secrets of Uber’s surge pricing algorithm were revealed in 2015. However, the surge pricing algorithm does not function in isolation in shaping drivers’ working experience with the ride-hailing apps, while Uber may change how the algorithm works at its will. Thanks to the work of many scholars (see, for example, Rosenblat & Stark, 2016), the informational asymmetry between companies on the one hand and consumers, users, and workers on the other has been recognized as a structural feature of the power dynamics among workers, the platform company, and the regulatory authority.

Besides opaque algorithms operating in the dark, I have become aware of the back-channel circulation of narratives about digital platforms and jobs (workers) directly from private companies to governmental official reports without engaging with third-party institutions or scholars’ voices, not to mention the inclusion of workers’ perspectives. I call this phenomenon the “short-circuiting of platform (work) narratives.”

Platform companies have the tendency to brand themselves as pioneers in offering technological solutions to social problems, and the leading Chinese ride-hailing company Didi Chuxing is no exception. It builds its platform work narratives around creating jobs and increasing income. Didi claims that the company created 17 million flexible jobs in 2016 and more than 21 million drivers earned their income on the platform from June 2016 to June 2017 (Didi, 2016; Didi Institute of Policy Study, 2017). Taxi drivers do not belong to the category of “new jobs,” despite the fact that a great majority of taxi drivers in China also work on the Didi platform (Chen, 2017a). The two reports highlight the company’s contributions to jobs-creation particularly in regions and sectors where China’s national development strategy for economic restructuring has brought about staggering figures of unemployment. These regions include the heavy-industrial sectors of the rust-belt provinces in northeastern China Take the 2016 report as an example; other than the vague number of 17 million and 5 million job opportunities for laid-off factory workers, the report revealed few details on specific work conditions or if the income earned through the platform accounted for living wages. The China Internet Network Information Center (CNNIC)—China’s authoritative agency on statistics about Internet use—cited Didi’s jobs-creation number (17 million) word for word in its annual report on China’s state of platform economy (CNNIC & Internet Society of China Sharing Economy Committee, 2017). In the absence of other figures or reports on drivers’ work conditions, CNNIC echoed the rhetoric of jobs creation and did not delve into the challenges facing drivers in the ride-hailing platforms.

China is hardly alone in the short-circuiting of platform narratives. This process is dangerous because it allows the language and figures of jobs creation, and more importantly, the framing of the platform’s contributing role in the economy, to travel in a narrative package from the private company to the governmental report. But the governmental report also serves as the reference for scholars and policy-makers. Without incorporating alternative perspectives and narratives on the relationship between platform technologies and workers and development, the governmental report may be at risk of losing its public accountability, which further prevents counter-narratives from surfacing into the mainstream conversations on how accomplish the goal of fair and decent digital work.

Works Cited

Chen, J. Y. (2017a). Technologies of control, communication, and calculation: taxi driver’s labor in the platform economy. In P. Moore, M. Upchurch, & X. Whittaker (Eds.), Humans and machines at work: monitoring, surveillance and automation in contemporary capitalism (pp. 231–255). London: Palgrave Macmillan.

CNNIC & Internet Society of China Sharing Economy Committee. (2017). Report on the Development of the Sharing Economy in China. Beijing.

Didi. (2016). Job Creation – VALUES. Retrieved September 5, 2017, from http://www.didichuxing.com/en/values/job-creation

Didi Institute of Policy Study. (2017). New Economy, New Jobs: 2017 Research Report on jobs on Didi Chuxing. Beijing, China: Didi Institute of Policy Study.

Pasquale, F. A. (2015). The Black Box Society: The Secret Algorithms That Control Money and Information. Cambridge: Harvard University Press.

Rosenblat, A., & Stark, L. (2016). Algorithmic Labor and Information Asymmetries: A Case Study of Uber’s Drivers. International Journal of Communication, 10, 3758–3784.

 

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