Deep learning models perform poorly on tasks that require commonsense reasoning. The underlying cause is that reasoning often necessitates some form of world-knowledge or reasoning over information not immediately present in the input. How can we collect human explanations for commonsense reasoning to improve AI decision making? This talk focuses on language-related use cases for customer service, search, question answer, self-help, and consumer finance.