Algorithmic
Management: Features, Impacts, Legal Issues.
What's the Current State of Play?
AIDA
PONCE DEL CASTILLO (Senior Researcher at
European Trade Union Institute)
L'INCONTRO SI TERRÀ IN PRESENZA E
ONLINE
SEDE
FISICA: Centro Nexa su Internet e
Società, Politecnico di Torino, Via Boggio
65/a, Torino (1° piano). Suonare al citofono
"Portineria" - Seguire le indicazioni
segnalate dai cartelli apposti all'ingresso e
lungo il percorso. (Per maggiori informazioni
su come raggiungerci clicca QUI)
STANZA VIRTUALE: https://didattica.polito.it/VClass/NexaEvent
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Data-driven
management or algorithmic management is
the materialisation of how AI models
are deployed in the context of employment, and
how they coordinate it differently from the
traditional employer-worker relationship.
Technically, it is one of the most disruptive
forms of technological change and a defining
feature of the platform business model, which
is increasingly colonizing standard work
settings (Baiocco et al., 2022; Jarrahi et
al., 2021; Parent-Rocheleau & Parker,
2022).
The way
algorithmic management works and is deployed
is controversial because of its so-called ‘black
box’ characteristics. In this talk, I
will first outline some of these
characteristics, in particular the high
dependency on the collection of personal and sensitive
data of workers, riders, couriers, etc.
I will describe how data fuels the model. I
will also talk about how it interferes, in an
almost invisible but pervasive manner, with
work organisation and working conditions, and
impacts individual workers. I will share a
possible working definition (Ponce Del
Castillo & Naranjo, 2022).
The ‘Directive
to Improve the Working Conditions in
Platform Work’ put forward by the EU
Commission in December 2021 contains a chapter
on algorithmic management, with rights and
obligations. The proposals bring
accountability to digital labour platforms and
provides workers with GDPR-like rights, for
example transparency provisions regarding the
use of algorithms by digital labour platforms,
rights for workers regarding automated
decisions, their right to access their data
and to ask for reviews of such decisions.
In a
second and final part, I will map how
algorithmic management impacts three
different dimensions: (1) the subordination
relationship; (2) work organisation
and (3) the individual worker. I will
present some concluding remarks around the
interconnection of, on the one hand, labour
law and, on the other, privacy
and data protection, which requires an
ad hoc legislative response.
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