AI in the Time of Corona

The coronavirus pandemic has created an extreme environment that is challenging machine learning (ML) models trained on previously seen observations. Businesses with live production models are facing issues as these models make incorrect decisions based on data they have never encountered before. This article discusses the challenges faced by AI/ML models during such black swan events and provides best practices to build resilience in production AI/ML during outlier events and extreme environments. These include tracking and identifying outlier events, deciding on a model fallback plan, finding look-alike events, building a diverse portfolio of models, and understanding the uncertainty of model predictions when performance cannot be improved.