Let’s Admit It: We’re a Long Way from Using Real ‘Intelligence’ in AI

By John Harney – For anyone worrying about machines taking over the world, I have reassuring news: The idea of artificial intelligence has been overcome by hype.

I don’t mean to belittle AI’s promise or even its existing capabilities. The technology allows organizations to put data to use in ways we could only imagine not that long ago. It’s revolutionized the way executives approach strategic planning. But very often lately—when I’m in meetings, reading research papers or listening to an expert’s presentation—I can’t shake the feeling that to many people, terms like “AI,” “machine learning” and “cognitive computing” have become answers unto themselves.

Today, solutions providers put statements like “AI-driven” or “harnessing the power of machine learning” at the core of their sales pitch. The buzzwords are certainly getting through. One colleague tells the story of a client calling “to make sure AI was included” in their data analysis project. Business people have been sold on the notion that today’s cutting-edge systems analyze data in a black box, then spit out reliable insights. How? They just do.

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Busting A Buzzword: Semantic Search

By Katrina Kibben – DataScava’s non-semantic search was featured in a piece by the renowned RecruitingTools news blog.

“What we really need, and I only know one company that does this (shout out to TalentBrowser, powered by DataScava, and founders Janet Dwyer and John Harney) is a completely customizable white box ‘profile’ search built on input and personalized rules that you the user control, not a black box semantic search engine that thinks it knows what you ‘really mean.’ Profile search allows you to specify many individual topics in a search, with thresholds (minimums) to be met by each topic. This twofold process bubbles the best candidates right to the top.”

Here’s the full report http://recruitingtools.com/semantic-search/

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