Decision Support Systems, Social Justice and Algorithmic Accountability in Social Work: A New Challenge

Abstract

Social work, health, education, income support and criminal justice departments have, through the adoption of electronic information systems, amassed an enormous amount of data about citizens in the developed world. Using relatively new techniques for data extraction and analysis, referred to as big data, these data are now being used to develop algorithmic decision support systems (DSS). These developments have occurred mainly in child welfare services across the world but there are also developments in criminal justice. DSS may, in certain circumstances, make incorrect recommendations to decision-makers, or recommendations which perpetuate the social prejudices that disadvantage service users. Clearly this is antithetical to social justice and it follows that there will be an increasing role for social workers as advocates, as more DSS are implemented. There is, however, a dearth of literature that would inform social workers about how, why and when the recommendations of DSS should be challenged. The aims of this article are therefore to provide some insights into current examples of DSS, propose principles to be applied to try to avoid DSS from perpetuating social injustice and to describe how social workers might apply these principles to challenge recommendations.

Keywords:

• big data
• decision support systems
• algorithmic accountability

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Australian Research Council.

Notes on contributors

Philip Gillingham

Philip Gillingham is ARC Future Fellow at the University of Queensland, Brisbane, Australia. Correspondence to: Philip Gillingham, School of Social Work and Human Services, University of Queensland, Brisbane, Australia. Email: [email protected]