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Artificial intelligence (AI) has evolved considerably in the last few years.While applications of AI is now becoming more common in fields like retail andmarketing, application of AI in solving problems related to developingcountries is still an emerging topic. Specially, AI applications inresource-poor settings remains relatively nascent. There is a huge scope of AIbeing used in such settings. For example, researchers have started exploring AIapplications to reduce poverty and deliver a broad range of critical publicservices. However, despite many promising use cases, there are many datasetrelated challenges that one has to overcome in such projects. These challengesoften take the form of missing data, incorrectly collected data and improperlylabeled variables, among other factors. As a result, we can often end up usingdata that is not representative of the problem we are trying to solve. In thiscase study, we explore the challenges of using such an open dataset from India,to predict an important health outcome. We highlight how the use of AI withoutproper understanding of reporting metrics can lead to erroneous conclusions.

Risks of Using Non-verified Open Data: A case study on using Machine Learning techniques for predicting Pregnancy Outcomes in India