The Promise and Limitations of Artificial Intelligence

The Promise and Limitations of Artificial Intelligence

The Promise and Limitations of AI - Almost everyone who talks about Artificial Intelligence, nowadays, means training multi-level neural nets on big data. Developing and using those patterns is a lot like what our right brain hemispheres do; it enables AI's to react quickly and – very often – adequately. But we human beings also make good use of our left brain hemisphere, which reasons more slowly, logically, and causally.

Almost everyone who talks about Artificial Intelligence, nowadays, means training multi-level neural nets on big data. Developing and using those patterns is a lot like what our right brain hemispheres do; it enables AI's to react quickly and – very often – adequately. But we human beings also make good use of our left brain hemisphere, which reasons more slowly, logically, and causally.

I will discuss this "other type of AI" – i.e., left brain AI, which comprises a formal representation language, a "seed" knowledge base with hand-engineered default rules of common sense and good domain-specific expert judgement written in that language, and an inference engine capable of producing hundreds-deep chains of deduction, induction, and abduction on that large knowledge base. I will describe the largest such platform, Cyc, and will demo a few commercial applications that were produced just by educating it as one might teach a new human employee.

But it is important to remember that human beings' "super-power" is our ability to harness both types of reasoning, and I believe that the most powerful AI solutions in the coming decade will likewise be hybrids of right-brain-like "thinking fast" and left-brain-like "thinking slow". That is the only path I see by which we will overcome the current dangerous inability of deep-learning AI's to rationalize and explain their decisions, and will make AI's far more trusted and – more importantly – far more trustworthy.

Anyone who understood this abstract and found it interesting should find my actual talk similarly accessible – and hopefully interesting!

ai datasciecne machinelearning

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