|The DIKW Hierarchy|
In David Weinberger's fascinating Too Big to Know, he taught me about the Data, Information, Knowledge, Wisdom hierarchy, which apparently is so commonly referred to that it is better known by it's acronym, DIKW. It's one of those ideas whose power derives from its staggering simplicity. Stated briefly (or, if you prefer, extensively on wikipedia), the idea is that information is more valuable, and more scarce, than raw data, and the same goes for knowledge and wisdom.
The hierarchy says a lot about the perfectly valid concern that the influx of modern technology in medicine is ultimately dehumanizing.
As someone who has could be accused as proselytizing med tech, the hierarchy gave me pause at first. Our fancy gadgets stand to create a data deluge that leaves little room for knowledge and wisdom, which are the stock and trade of medicine. A wealth of information certainly is no substitute for knowing what to do with the information, when, and to what purpose. Those who wonder if more technology is really the answer for medicine must not be casually dismissed as narrow-minded Luddites.
But there is a less obvious application of technology, and this is nicely illustrated with the DIKW hierarchy. Some of our new tools not only collect and dispense more data and information, but transform these into knowledge, any maybe one day, wisdom.
An example is IBM's Jeopardy master computer, Watson, currently being engineered to assist physicians. This tool is interesting because it turns information into knowledge. Far from overwhelming doctors with information, and even farther from attempting to replace doctors, Watson aims to help doctors by reducing the information they're faced with by converting it to knowledge. Ideally, a doctor working with Watson can spend more time turning knowledge into wisdom, and spend less time calculating information from data, or synthesizing knowledge from information.
My guess is that patients would prefer to have their doctor impart wisdom rather than manage data. To the extent that our tools promote this end, we should be optimistic about the future of tech in medicine.
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