In the first article of our conversational AI series, we explored how the proliferation of voice assistants and messaging platforms are giving way to a new era of user interfaces (see the sidebar, "A five-part series on conversational AI"). Whether it's in the car, a phone, or a smart home device, nearly 112 million US consumers rely on their voice assistants at least once a month--and that number continues to grow.1 These can range from the mundane, such as misinterpreting a request for ordering a roll of paper towel, to the more troubling error of providing a harmful health recommendation (or conversely, providing an accurate, but difficult to interpret recommendation).2 Despite the uptick in adoption of voice-enabled virtual assistants, designing effective products is a nontrivial endeavor. Virtual assistants often deal with multiple, sometimes complex scenarios that require understanding a range of queries to which users expect a quick, accurate, and easily interpretable response.