  As the production of and reliance on datasets to produce automated
decision-making systems (ADS) increases, so does the need for processes for
evaluating and interrogating the underlying data. After launching the Dataset
Nutrition Label in 2018, the Data Nutrition Project has made significant
updates to the design and purpose of the Label, and is launching an updated
Label in late 2020, which is previewed in this paper. The new Label includes
context-specific Use Cases &Alerts presented through an updated design and user
interface targeted towards the data scientist profile. This paper discusses the
harm and bias from underlying training data that the Label is intended to
mitigate, the current state of the work including new datasets being labeled,
new and existing challenges, and further directions of the work, as well as
Figures previewing the new label.
