I just returned from the 2016 ACM Intelligent User Interfaces conference which was held in Sonoma, California. As I’ve previously written, we at the VACLab had a paper published as part of the proceedings which described our work on Adaptive Contextualization (AC). The core theory behind AC is that we can use intelligent user modeling and analysis to combat the emergence of selection bias during visualization-based data selection. By quantifying bias and making it visible through the user interface, users are more informed about the underling quality of their data.