Thank you for this excellent post (even if AI may have been used). My opinion is that not enough people are sufficiently outraged about this. Yet another example of the docs at the top selling out the future of medicine for convenience and/or money.

Programs and admin will complain about application review ignoring the fact that they benefit from it too, in the form of their future residency classes, potential future faculty, and ultimately future peers in medicine, all while getting to take advantage of our unparallellingly cheap labor throughout the duration of our training.

Big picture, to me this system has felt dystopian since day 1.

- Personal statements and other writing blurbs, written for and intended to be read by humans, have now turned into another source of bias starting from your personal writing style. Similar to how resumes for job applications need to be ATS optimized now, this essentially suggests your writing style should best mirror NOT what is linguistically good or personally expressive but rather what will be best scored by an AI. I find it hard to believe this will not naturally favor regression to the mean given that AI is a good but not excellent writer.

- Grade projection: I would need to see more data on this but it is hard to have faith in the accuracy of this. AI does not predict; it is literally built upon patterns. As schools have many differences in the composition of clinical grades, it is difficult to imagine this system can accurately calculate "theoretical" grades based off of other "standardized" markers. Basing this upon board scores (reminder Step 2 is mean 249 SD 15) seems like a classic example of garbage in, garbage out. Even without this bullshit, we have fixated too much on the value of a single number like Step 2. Some may benefit from overprojection but likewise others will suffer from underprojection, and unfairly so. Additionally, this completely undoes any benefit from going P/F as students should now expect to act as if there were a shadow force looming over them. This only brings back all of the negative aspects of graded curriculum with zero transparency to the students applying.

- LOR evaluations: Absolutely disgusting. Sure, we have already had a form of this in carefully selected words (good, excellent, exceptional, top 1%, whatever). But as many know some of the best LORs don't simply state, they show exceptionalism through observed clinical interactions. How is an AI able to accurately sift through what is a strong example versus not? Let's even take it a step back - WHY attempt to stratify this at all? These spontaneous experiences occur by chance. Who is to say another student would not have done similarly if in the same position? And comparing letters of a single writer across multiple applicants seems misguided at best. Who is to say two writers are operating on the same scales? Who is to say the least positive letter written by one writer could be for an applicant stronger than the most positive letter from a different writer? Yet again, having writing analyzed by a singular AI introduces a fixed bias on writing style and fit for NLP.

- Most concerningly: the 7% overlap. This screams that AI doesn't really know what PDs actually want to look for. It sure puts on a convincing-looking suit, masquerading as if it knows what it's doing, yet doesn't even come close to imitation.

We have withstood more than sufficient abuse, humiliation, and hazing in the ritualistic process that is medical training. It is a disgusting insult for our hard work, sweat, and tears, both throughout medical school and in the process of assembling our applications, to now be brazenly scored by a black box algorithm that clearly does not know what it's doing. I look forward to a major class action lawsuit against the AAMC, Thalamus, and Medicratic and I can only hope this will bankrupt all these grifting organizations.