One of the largest problems so far in health care is the most important thing in regards to AI/ML. Data. Yes, electronic health records now exist which is a huge step up from the paper charting of the not so distant past. However, the large EHR companies have multiple inputs for data that are not easily accessible and often times in multiple different forms. A lot of times, the necessary and clinically relevant information is not in a check-box or numerical format, but is free-text with myriad ways of describing a feature that may be hard to quantify. Additionally, often times the purpose behind charting, or put in AI/ML terms “collecting and transcribing data,” is for billing purposes, which further complicates the problem of having good data. My $0.02 is that ML methods like NLP will become more useful for chart digging purposes and trying to collect and organize data in meaningful ways. Most of a physician’s time now is currently spent charting, so the most likely applications of AI/ML will be in automating annoying tasks that physicians do not like to do in the first place. What will happen is that physicians that do not incorporate AI/ML in the future will be replaced by physicians that do use AI/ML to augment their clinical decision-making. Medicine, in my opinion, is a field in which physicians will continue to be people for the long-term future.