https://www.wiki.ed.ac.uk/display/CIDS/2020+Week+2%3A+Labour+and+workers+rights+in+the+data-driven+e...
On-demand labour platforms have been
digitally transformed, featuring an increasing reliance on data
analytics and algorithmic decision-making. Novel technologies as such
have brought forth unprecedented commercial success, but the
implications for job quality, well-being and worker rights are barely
considered in platforms’ decision-making. In contrast to the massive
volume of data collected or generated by the platform, the information
available to gig workers has been deliberately kept to a minimum. This
asymmetry of information enables the platform to manipulate its
‘human-data capital’ through precarious schemes carefully designed and
displayed. For gig workers, the lack of information squeezes the room to
manoeuvre; they incrementally found themselves working purely for the
platforms, hence diverging from the original intention to have more
flexible work patterns.
Meaningful
data access and/or data portability is crucial for gig workers to
understand their work and arrange it wisely. In the European Union,
there are burgeoning legal regimes facilitating reverse data flows from
platforms to individuals. For instance, the General Data Protection
Regulation allows individuals to request a copy of personal data, or
transmit to other places. Parallel schemes are taking shape in the UK
and other member states that facilitate the porting of non-personal data
for consumers (the Digital Content Directive) as well as professional
users (the Free Flow of Non-Personal Data Regulation). Further to a
sibling paper on these schemes’ applicability in the gig economy, this
interdisciplinary research inquires how large-scale accumulation of
data, coupled with algorithmic decision-making, has affected those
working in the gig economy. Taking Deliveroo as an example, it further
examines how the data can be assessed, aggregated and reused by food
couriers to better their conditions.
With
the evolving legal landscape in mind, we propose a structural response
to algorithmic control over gig workers. Within a platform, a gig worker
may leverage GDPR rights to obtain data of evidentiary value and
contest algorithmic decision-making. Between platforms, a worker may
wish to switch from one platform to another, or dwell on several at the
same time. Data
portability and interoperability are of critical use to ensure these
processes. Beyond platforms, we explore the idea of data-driven worker
science, a conceptual underpinning for worker-side innovations as well
as data-driven organising demands.
