Designing Intelligent Automation based Solutions for Complex Social   Problems
  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. 
Sanjay Podder, Janardan Misra, Senthil Kumaresan, Neville Dubash,   Indrani Bhattacharya
stat.ML cs.CY