Summary

Data science presents a new and promising frontier for social work both in methodology and in ensuring data justice and equity. Within social work, text documentation and social media are popular forms of non-traditional data, but other forms, such as imagery and connectivity data, also provide new opportunities. Administrative data linkages, particularly within the realm of child welfare, are a common approach to data use. Methodologically, natural language processing and machine learning are some of the widely applied techniques; however, computer vision, combined with spatial analysis, presents areas with significant potential. Various fields or substantive areas in social work leverage data science to predict risk and utilize algorithmic decision-making. Data science has been used around the world in both data rich and data sparse countries. Social workers are called upon to take action and take part in the conversation of data justice and equitable deployment. Professionals in social work are encouraged to have a thorough understanding of and employ a diverse range of data science tools.