Hidden inequalities: using position generators to capture gender gaps on micro-tasking platforms
Presenter: Prof Paola Tubaro (National Centre for Scientific Research (CNRS), France)
Around the world, myriad
workers perform micro-tasks on online platforms to fuel the digital
economy. Short, repetitive and little paid, these 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
are accessible to anyone with basic skills, and may even be
particularly favourable to women owing to non-disclosure of workers’
profiles and the possibility to work from home.
Nevertheless, this form
of crowd-work fails to fill gender gaps and may even exacerbate them. I
demonstrate this result in three steps. First, legacy inequalities in
the domestic sphere turn micro-tasking into
a ‘third shift’ that adds to already heavy schedules. Second, the human
capital of male and female micro-workers differ, with women less likely
to have received training in science and technology fields. Third,
their social capital differs: using a position
generator instrument to capture micro-workers’ access to the knowledge
and advice that may come from contacts with different occupations, I
show that women have fewer ties to digital-related professionals who
could provide them with knowledge and advice to
successfully navigate the platform world. 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.
Prof Paola Tubaro is
Research Professor in sociology and technology at the National Centre
for Scientific Research (CNRS) in Paris. A specialist of social and
organizational networks, she is currently researching
the place of human labour in the global production networks of
artificial intelligence, and the social conditions of platform work. Her
interests also include data methodologies and research ethics.