Towards Human Centered AutoML
This is an incremental position paper discussing interface improvements for AutoML to aid data scientists in time-constrained projects.
The paper addresses the problem of limited time for model building in data science by proposing a user-centered interface for AutoML systems, aiming to improve usability and incorporate missing features from a data scientist's perspective.
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.