This is not a workshop about tools. This is a workshop to encourage critical engagement with the choice of machine learning tasks, data collection, data transformations, labeling, categorization and the evaluation of results and how these processes are interconnected. We will discuss and work with case examples to raise important issues: What do we know about the data collections? What choices do we make with regard to selecting and filtering data and what are the implications? What are implicit assumptions?
Participants should expect to walk away with a framework to help them use data responsibly in the context of Machine Learning.