  Building models from data is an integral part of the majority of data science
workflows. While data scientists are often forced to spend the majority of the
time available for a given project on data cleaning and exploratory analysis,
the time available to practitioners to build actual models from data is often
rather short due to time constraints for a given project. AutoML systems are
currently rising in popularity, as they can build powerful models without human
oversight. In this position paper, we aim to discuss the impact of the rising
popularity of such systems and how a user-centered interface for such systems
could look like. More importantly, we also want to point out features that are
currently missing in those systems and start to explore better usability of
such systems from a data-scientists perspective.
