ESPANET 2021 – CfA Stream 4: Algorithmic work in health and social care

Call for abstract dello stream  “Algorithmic work in health and social care”, tenuto da Francesco Miele e Paolo Giardullo internamente alla conferenza ESPANET 2021 (31 aug – 3 sept 2021). La conferenza si terrà Online e l’abstract (di massimo 400 parole) dovrà essere inviato entro il 18 aprile 2021 attraverso l’apposita piattaforma online 

In health and social care sector algorithms – the coded instructions through which data are filtered, sorted and processed – have recently attracted the attention of scholars and policy makers (Ruckenstein and Schüll, 2017). The emphasis on the role of algorithms in improving the efficiency of care processes has been followed by an increased interest in the design of algorithmic systems, to ‘take on’ professional tasks. A particular attention has been paid to the role of algorithms in processing big data, making previsions about social and health risks of a specific target population, determining the likelihood of the latter of utilizing specific services, supporting professionals in the delivery of personalizing care plans (e.g. Bates et al., 2018; Kasthurirathne et al., 2020). In order to manage the growing care demands – with particular reference to people who are socially vulnerable and/or have important health issues – algorithms have been often depicted as good allies for reducing public expenditure and assuring the quality of care.

On other topics – e.g. the digitalization of low wage employments – scholars have highlighted the negative implications related to the diffusion of algorithms, underling how algorithmic technologies do not emerge from a vacuum, rather they deliberately implement choices from employers and incorporate their interests and values (e.g. Srnicek, 2019). At the moment, while some computer scientists showed the algorithmic biases in health care (Hu and Chen 2020) only a limited number of studies has explored how algorithms are constructed from a social sciences perspective – encompassing expertise, public policy goals, cultural assumptions from managers and practitioners – and integrated in care processes – interacting with preexisting organizational cultures and practices, professional identities and welfare arrangements (e.g. Schwennesen, 2019). In order to fill this gap, we want to attract theoretical, empirical and methodological reflections – from research areas such as social policy, social work, science and technology studies and sociology of health and illness – about the following (but not limited to) issues:

• Evaluation of the effects of algorithmic technologies (e.g. in terms of cost-effectiveness analysis health conditions, quality of life);
• Algorithms and welfare system arrangements;
• Design processes and the co-construction of algorithms;
• Algorithmic fairness and marginalized groups (how algorithm can contribute at contrasting or exacerbating pre-existing inequalities);
• Algorithms and innovation processes in healthcare and social care organizations;
• Algorithms and integration between health and social care services;
• Algorithms and social research (what methodologies can be used for exploring algorithmic work in health and social care).