Hidden inequalities: the gendered labour of women on micro-tasking platforms

Around the world, myriad workers perform data tasks on online labour platforms to fuel the digital economy. Mostly short, repetitive and little paid, these so-called ‘micro-tasks’ include for example labelling objects in images, classifying tweets, recording utterances, and transcribing audio files – notably to satisfy the data appetite of today’s fast-growing artificial intelligence industry. While casualization of labour and low pay have attracted sharp criticisms against these platforms, they appear gender-blind and accessible even to people with basic skills. Women with care or household duties may particularly benefit from the time flexibility and the possibility to work from home that platforms offer. So, are these new labour arrangements gender equalizers after all?

In a new paper co-authored with Marion Coville, Clément Le Ludec and Antonio A. Casilli, we demonstrate that this new form of online labour fails to fill gender gaps, and may even exacerbate them. We proceed in three steps. First, we show that legacy inequalities in the professional and domestic spheres turn platform-mediated micro-tasking into a ‘third shift’ that adds to already heavy schedules. Both working fathers and working mothers experience it, but the structure of the other two shifts affects their experience. Looking at their time use, it turns out that men dedicate long and uninterrupted slots of time to each activity: their main job, their share of household duties, leisure and micro-work. They tend to do all micro-tasks in a row, usually at night after work or in the morning before starting. Instead, women have more fragmented schedules, and micro-work during short breaks, here and there, eating into their leisure time. This is one reason why they earn less on platforms: they have short slots of time available, so they cannot search for better-paid tasks, and just content themselves with whatever is available at that moment.

Time use of typical female (left) and male (right), micro-workers, both of whom have a main job in addition to platform micro-tasks, and dependent children.

Second, we submit that the human capital of male and female data workers differ, with women less likely to have received training in science and technology fields.

Highest educational qualification (left) and discipline of specialization (right) of men and women micro-workers. Data collected in France, 2018 (n = 908).

Third, their social capital differs: using a position generator instrument to capture workers’ access to the informational and support resources that may come from contacts with people in different occupations, we show that women have fewer ties to digital-related professionals who could provide them with knowledge and advice to successfully navigate the platform world.

Gender assortativity index for each occupation in the 48-item position generator that measures respondents’ social capital. Each panel represents respondents’ choices, ordered from lowest (negative) to highest (positive) degree of similarity. Top panel: female respondents, bottom panel: male respondents. The bars corresponding to digital and computing occupations are hatched.

Taken together, these factors leave women with fewer career prospects within a tech-driven workforce, and reproduce relegation of women to lower-level computing work as observed in the history of twentieth-century technology. 

The full paper is available in open access here.

It is part of a full special issue of Internet Policy Review on ‘The gender of the platform economy‘, guest-edited by M. Fuster Morell, R. Espelt and D. Megias.

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