Visual, Interactive, and Explainable Human-AI Collaboration

Intelligence augmentation through mixed-initiative systems promises to combine AI's efficiency with humans' effectiveness. This can be facilitated through co-​adaptive visual interfaces. This talk will outline the need for human-AI collaborative decision-making and problem-solving. I will illustrate how customized visual interfaces can enable interaction with machine learning models to promote their understanding, diagnosis, and refinement. In particular, I will showcase various workflow designs tailored for computational linguistics
analysis. Lastly, the talk will conclude with reflections on current challenges and future research opportunities.