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Thursday, December 07, 2017

Kaiser Fung on the Limitations of AI

Colleague Kaiser Fung  on on hype and limitations of AI today.   Some useful thoughts.  In his always interesting Junkcharts blog.  I too have lived through several waves of AI hype, seeing it from an enterprise perspective.   Points to a number of studies.  In part this does depend on your definition of AI.

Primer on the limitation of current AI

Today, I turn attention to another Technology Review article in the same special AI issue, the important article by Rodney Brooks on the limitation of the current AI systems, driven by the "deep learning" "revolution." Brooks was the head of MIT's CSAIL lab, and an expert in AI who has lived through several waves of AI hype.

Brooks frames his content differently, titling the piece "The Seven Deadly Sins of AI Predictions." He opens with the breathless forecasts published by various media outlets, predicting that AI (computers) would wipe out the job market for human beings in a broad range of industries, in some cases, in a matter of 10 or 20 years. He then describes seven fallacies that have led these hype-meisters astray. Read the whole article here. Some of these dire forecasts: Oxford/Yale, McKinsey. [PS. I do not understand why those technology leaders who claim to believe in these forecasts do not immediately stop their AI programs for the public good.]

Brooks calls these predictions "ludicrous." He points out that there have been zero realistic demonstrations of robots that can take over grounds and maintenance work even though the forecasters claim that 90% of such jobs would disappear in 10 to 20 years. For the rest of us, who are not knee-deep in AI research, it's simple to validate Brooks's viewpoint: just make a call to your favorite service provider (your bank, your credit card provider, your health insurer, for example); subject yourself to the AI "chatbot" for even five minutes. 

In debunking the hype, Brooks outlines several key limitations of the current AI systems, built on the deep learning revolution (discussed in the prior post).   .... " 

( See also his previous piece on this, pointed to in the above) 


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