What do Watson, House, and our Education System have in Common?


As I was reading articles about Watson winning Jeopardy, I was thinking about one of my wife’s favorite TV shows; House. The main character, Dr. Gregory House–played brilliantly by Hugh Laurie, is an emotionally unstable genius who leads a team of physicians in a diagnostic unit at a fictional teaching hospital in Princeton, New Jersey.

In most episodes of House, the diagnosticians torture this viewer, the patient, and the patient’s family, with a game much like Jeopardy when each of the experts draw on their memory over days and weeks to match symptoms with disease and therapy. As if this isn’t painful enough for someone who has been focused on applying semantic technologies to improve healthcare efficiencies, the team invariably nearly kills the patient multiple times during the diagnostic Q & A before House has an epiphany when his pain-killer addicted mind finally connects the dots between Jungian philosophy, tropical parasites, chemical toxicity, and/or genetic disorders to miraculously save the patient (usually).

I have actually found myself talking over the TV at times (very rare otherwise), suggesting some version of “put those symptoms in a database”, or “structure your data and stop torturing your patients and viewers”, and “save a million dollars per patient in unnecessary healthcare costs”.

Of course this frustration comes only after a half-century of witnessing our education system—and by extension our society, favor memorization techniques rather than the more essential understanding of how to improve, innovate and solve problems. Most of our challenges as individuals, organizations, a planet, and species depend not only on the quality of data far beyond the abilities of any single human expert–or even group–that would be best categorized as hubris, but rather the integrity of the collective knowledge, and more importantly what we do with it, aka the decision process.

While a sharp memory is essential in solving real-world problems such as diagnostics in highly complex environments, memory is a task that is much better performed by computer networks than humans, particularly with properly structured data sourced and updated from human experts. Unfortunately, the vast majority of institutions can no longer afford Watson, House, or our education system, which is among the best arguments for the semantic web.

In the real-world, Dr. Gregory House and his team would be employing Watson for diagnostics to free up time for improved therapy, research, and caring for additional patients.

Mark Montgomery
Founder & CEO
Kyield
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About Mark Montgomery
I am a technologist, serial entrepreneur, business consultant, recovered VC, and inventor with interests that are both broad and deep across multiple disciplines, including organizational management, computing, communications, economics, sociology, science and nature, among others. For the past several years I have been founder and CEO of Kyield, which offers a distributed operating system for achieving optimal yield of executable knowledge across large data networks. The patented AI system core acts to unify networks with adaptive data tailored to each entity with continuous predictive analytics designed to significantly reduce ongoing costs while accelerating productivity, and generally make life more satisfying and productive for knowledge workers and their organizations. We provide popular free white papers, use case scenarios, and other information at http://www.kyield.com .

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