An Electronic Social Worker?

From City Limits:

In two separate studies, published in Children and Youth Services Review in 2004 and in the Temple Law Review last year, Schwartz and colleagues analyzed data from thousands of cases of child abuse and neglect nationwide. A neural [computer] network was asked to predict which cases would meet the “harm standard,” the most serious classification of abuse. Ninety percent of the time, the system accurately predicted risk – which the researchers knew because of the actual outcomes – with very few false positives or false negatives. In other words, the neural network was able to determine which variables were most closely associated with child abuse, then identify the cases matching those variables. The first study concludes, “Neural networks…are tools that could help to increase accuracy, reduce errors, and facilitate more effective decisions in child welfare and child protective service organizations.

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