• Chris

You've Seen This Movie Before

“As medical education thinks about competencies for physicians, ML [machine learning] should be embedded into information technology and the education in that domain,” said co-author Priya Sinha Garg, MD, associate dean ad interim for Academic Affairs at Boston University School of Medicine.


I couldn't agree more, though I'd expand that to include ALL technical and business competencies, including law, engineering, information technology, business management, marketing, advertising, and so on.


Of course, as is always the punchline with "shoulds," machine learning (for our purposes, you can substitute 'artificial intelligence,' if you prefer) is no where in the curriculum for medical students, nor is it anywhere near the curriculum for most disciplines, save for the ostensible creators of machine learning algorithms, Computer Scientists.


Dr. Garg and her colleagues published this finding in the latest issue of npj Digital Medicine, a good digest of which is found here.


Peter Elkin, MD, of SUNY-Buffalo notes that “One caveat that we should all keep in mind is that poor quality data can limit these methods’ ability to create highly accurate predictive analytics,” which is why NOT teaching this technology and its applications to medical student poses a real problem for the use of machine learning itself. Without humans to teach them, the algorithms are either not very useful, or sometimes downright dangerous.


When technology is considered to be the sole purview of specialized technologists, it often fails to take in to account the practical impact of being released to the general public. You've seen this before: social media engines are run almost entirely on algorithms, developed by brilliant minds in Silicon Valley, but disconnected from actual people who would eventually come in to contact with them. The result has been--as you might notice from the millions of people angrily staring at their phones all day--a mess.


All technology needs to be people-centric, and in the case of technology applied to medicine, that should read "patient-centric." Machine learning backed by big data and cloud computing IS entering medicine, and indeed it is already there, from insurance companies to surgical suites. The way to ensure that it is a net positive to patients, however, is to expand the knowledge of how to develop and work with these systems to everyone affected. In this case, it's physicians, but you can just as easily make the case that everyone should become more technologically proficient, even if only to understand the strengths and weaknesses and when to rely on your own sense, rather than the machine's.


The Wrecking Crew understands this, and ensures that all of our technology solutions begin and end with the people most affected by it. When you do that, not only will you have a great solution, but one that is accepted and used by the people who need it most.

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