Human-Machine-Learner Interaction: The Best of Both Worlds

Paste the appropriate copyright statement here. ACM now supports three different copyright statements: • ACM copyright: ACM holds the copyright on the work. This is the historical approach. • License: The author(s) retain copyright, but ACM receives an exclusive publication license. • Open Access: The author(s) wish to pay for the work to be open access. The additional fee must be paid to ACM. This text field is large enough to hold the appropriate release statement assuming it is single spaced in a sans-serif 7 point font. Every submission will be assigned their own unique DOI string to be included here. Abstract This position statement presents a notional framework for more tightly integrating interactive visual systems with machine learning. We posit that increasingly, powerful systems will be built for data analysis and consumer use that leverage the best of both human insight and raw computing power by effectively integrating machine learning and human interaction. We note some existing contributions to this space and provide a framework that organizes existing efforts and illuminates future endeavors by suggesting the categories of machine learning algorithm and interaction type that are most germane to this integration.