ALGORITHMIC WOMEN’S WORK: THE LABOUR OF NEGOTIATING BLACK-BOXED REPRESENTATION
Keywords:Gender, algorithms, identity, targeting, black-boxing
This paper argues that under the proprietary logics of the contemporary web, the ‘algorithmic identities’ (Cheney-Lippold, 2017) created by platforms like Google and Facebook function as value-generating constellations that unequally distribute the burdens of being made in data. The paper focuses on a particular identity demographic: that of the algorithmically inferred 'female', based in the 'UK', 'aged 25-34', and therefore deemed to be interested in 'fertility'. Though other algorithmic profiles certainly exist (and generate their own critical problems), I will use this particular template of subjectivity to explore issues of representation, black-boxing and user trust from a gendered perspective.
Combining online audience reception with political economy, I analyse two ad campaigns - for Clearblue Pregnancy Tests and the Natural Cycles Contraceptive app - to understand how the algorithmically fertile female comes to exist, both at the level of the database and at the level of ad representation. I argue that black-boxing occurs at two stages in this process: firstly when the subject is computationally constituted as female (ie in the database) and secondly when the user herself is delivered the ads informed by her algorithmic identity (ie at the interface). This black-boxing creates 'algorithmic imaginaries' (Bucher, 2016) for the user wherein the burden of being made a fertile female in data is experienced as a form of immaterial and emotional labour. Some algorithmic constitutions can therefore be considered a form of algorithmic women's work; work that potentially generates distrust in targeted advertising.