  Deciding effective and timely preventive measures against complex social
problems affecting relatively low income geographies is a difficult challenge.
There is a strong need to adopt intelligent automation based solutions with low
cost imprints to tackle these problems at larger scales. Starting with the
hypothesis that analytical modelling and analysis of social phenomena with high
accuracy is in general inherently hard, in this paper we propose design
framework to enable data-driven machine learning based adaptive solution
approach towards enabling more effective preventive measures. We use survey
data collected from a socio-economically backward region of India about
adolescent girls to illustrate the design approach.

Machine Learning;Computers and Society