We investigate the use of a machine learning (ML) algorithm to identify fraudulent non-existent firms. Using a rich dataset of tax returns over several years in an Indian state, we train an ML-based model to predict fraudulent firms. We then use the model predictions to carry out field...

Algorithms (in some form) are already widely used in the criminal justice system. We draw lessons from this experience for what is to come for the rest of society as machine learning diffuses. We find economists and other social scientists have a key role to play in shaping the impact of...

We consider an environment in which there is substantial uncertainty about the potential negative external effects of AI algorithms. We find that subjecting algorithm implementation to regulatory approval or mandating testing is insufficient to implement the social optimum. When testing costs...