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Can Predictive Algorithms Assist Decision‐Making in Social Work with Children and Families?
Author(s) -
Gillingham Philip
Publication year - 2019
Publication title -
child abuse review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 41
eISSN - 1099-0852
pISSN - 0952-9136
DOI - 10.1002/car.2547
Subject(s) - work (physics) , decision support system , social work , computer science , social support , key (lock) , service (business) , data science , knowledge management , psychology , computer security , marketing , business , artificial intelligence , engineering , social psychology , political science , mechanical engineering , law
Decision support systems (DSS) which incorporate algorithms trained using administrative data have been promoted as the next promising development in initiatives to improve and assist decision‐making in social work with children and families. In this article, research and grey literature about DSS designed, and in some cases implemented, in the USA, the Netherlands, Australia and New Zealand are analysed to assess the extent to which they are currently able to meet this promise. The challenges of developing DSS for social work are identified and ideas are suggested to overcome them. © 2019 John Wiley & Sons, Ltd. Key Practitioner Messages Decision support systems (DSS) are being developed for social work with children and families and they may transform how decisions are made with important consequences for both service users and the profession. Current DSS are mostly not very accurate in their predictions and further work is required in their development and on the data used to train the algorithms. The next stage in the development of DSS will require long‐term commitment by social workers to work in collaboration with data scientists and researchers. It will also be expensive. Social workers need to lead the debate about whether DSS are worth the investment.‘Decision support systems are being developed for social work with children and families and they may transform how decisions are made’