Until recently, the practice of pathology has been entirely “human-driven”. Well-trained pathologists examine all tissues and arrive at diagnoses based on their application of learned criteria and experience. However, it is well-known that the accuracy of human interpretation can be hampered by subjectivity (inter-observer variability), inconsistency (intra-observer variability), and fatigue. Recently, the rise of digital methods in pathology has led to a growing interest in applying artificial intelligence (AI) to aid or even improve on the analysis of medical specimens. For the pathologist, AI has the potential to improve accuracy, productivity, and workflow by allowing the computer do what it does well: consume lots of data, recognize patterns, and perform automated analyses. Objective and reproducible specimen examination, along with