Kurt is the founder and CEO of Semantical, LLC, a consulting company focusing on enterprise data hubs, metadata management, semantics, and NoSQL systems. He has developed large scale information and data governance strategies for Fortune 500 companies in the health care/insurance sector, media and entertainment, publishing, financial services and logistics arenas, as well as for government agencies in the defense and insurance sector (including the Affordable Care Act). Kurt holds a Bachelor of Science in Physics from the University of Illinois at Urbana–Champaign.
There’s a little secret that ontologists know that should make insurance companies, and that makes quite a few other people sweat more than a little bit. That secret is simple — insurance is not really all that complicated if you get all the quasi-standards out of the way.
Most people are uncomfortable with the idea that they can be programmed, a discomfort that can very quickly escalate to full blown denial. Yet there is ample evidence to show that such programming is remarkably (indeed, entirely too) easy, and anyone who is involved in media, social media, advertising or organized religion can generally lay out most of the basics. Call the people who engage in this social programming “social programmers”, or for brevity, “sogrammers”.
Recently, I wrote a tribute to the late Futurist Alvin Toffler, who passed away last week at age 87. In many respects, he is considered the father of business futurism, and his notions (along with others such Michael Naisbitt and Faith Popcorn) helped to lay out the big trends that tend to influence events over decades.
A General Artificial Intelligence is one that has achieved sentience. Sentience means, in effect, that it is aware of itself, is capable of multiple levels of recursive abstraction, and in general will not be programmed so much as taught. Arguably, a GAI is a specialized AI that can feel existential angst.
Suppose that jobs went away. Not all jobs, mind you, but many, perhaps upwards of 90%. Some of those are in hard-manual labor territory, like coal mining. Some are in the services industry such as driving a taxi. Some are in high tech, like programming. Not a few will be in areas such as sales and management, politics or journalism. What happens next?
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