Open Guest Lecture: Predicting their futures - Think Family as a case study

Predicting their futures: Think Family as a case study

Increasing pressures on local authorities to utilise reduced workforce and economic resources in child and family welfare contexts and drivers emanating from serious case reviews of child deaths where services have not identified children at risk have coincided with the rise in techno-solutionism in child welfare particularly related to data linkage and predictive analytic modelling of risk. The increasing possibilities of artificial intelligence/ machine learning in these systems are driving a huge expansion in the use of data-driven systems as pre-emptive solutions to directing scant human resources in targeted ways:

Targeting families for intervention

Targeting families for intervention in an attempt to pre-empt social problems and enhance children’s well-being and outcomes is accepted by local authorities as socially valuable, and as potentially both saving costs and generating funds in constrained budgetary conditions (Edwards et al., 2022: 273).
Debbie Watson and her colleagues have been investigating a data linkage and predictive model called Think Family in Bristol, UK and this session will consider what they have learnt about the drivers, assumptions and impacts of this system on children and families in the city.

Supports radical interdisciplinary research

Debbie Watson is Professor of Child and Family Welfare and Director of the Brigstow Institute which supports radical interdisciplinary research across and beyond the University. They champion the use of co-produced research and the importance of critical making in research. She is also co-investigator in the ESRC Centre for Sociodigital Futures and part of the leadership team heading up impact and engagement. Debbie’s research in the Centre is focused on Caring Futures where she is leading an interdisciplinary project to understand the impact of predictive analytic AI systems in child welfare contexts. This involves research with five community groups across Bristol engaging young people in creative technology workshops considering data harms and AI and working with colleagues in engineering to conduct system analytics on the Think Family database and risk model currently in use in Bristol.

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