Advancing AI Research and Applications by Learning from What Went Wrong and Why

This special issue of AI Magazine is dedicated to the proposition that problems populate the path to insight, implying that experiences and lessons learned should be shared. In this view, problems are signposts, not roadblocks, which guide us towards better solutions. Bugs, surprises, and anomalies also become powerful instructional tools that reveal assumptions, expose design flaws, and chart the boundaries of current technology. This perspective motivated our work on this special issue. When researchers publish success stories, we commonly leave process out of the narrative.