Ethics review of machine learning in children's social care


Date of publication:  30 Jan 2020 Author:  Leslie, D., The Alan Turing Institute Holmes, L., Rees Centre, University of Oxford Hitrova, C., The Alan Turing Institute Ott, E., Rees Centre, University of Oxford Publisher:  What Works for Children’s Social Care Publication type:  Newsletter / Review / Bulletin

This report presents a thorough and detailed consideration of the issues of machine learning, and how it sits in a children’s social care context. 

It tries to make clear what principles should be followed to use machine learning in an ethical way in children’s social care. It also delineates some barriers – about data quality, representativeness, and availability – which will heavily curtail the number of circumstances in which these tools can be ethically deployed – at least in the current context.

The review is intended to be a guide, and a spur to further debate and discussion.

Key recommendations

  • The responsible design and use of machine learning models in children’s social care should be mandated via national standards.
  • Open communication between social workers and data scientists across local authorities should be encouraged to improve the national knowledge.
  • Local authorities that develop machine learning applications should engage with citizens to gain consent for their use.
  • The use of data science should be refocused away from individual risk and towards exploring “deeper social-structural problems” driving rising social care demand, and also be focused on promoting better outcomes for families and strengths-based approaches.
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