Are Machines Too Dumb to Take Over the World? Part III: Yes.

“Human intelligence is underrated”

Longtime readers of this blog who may have tired of my ruminations about AI imposing absolute reign over humanity should be overjoyed to hear that I am dropping the apocalyptic Artificial Intelligence thread for the foreseeable future.

That’s because this article in New Scientist has put my fears (mostly) to rest, with one of the pioneers of Deep Learning,  Yoshua Bengio,  saying,  “[the machines] don’t even have the intelligence of a 6-month-old.” He is even quoted as saying “AIs are really dumb”—essentially answering my very question. Thanks Yoshua!

Bengio expresses himself in deceptively simple language, but that’s an exercise in humility, because . . .

Bengio is a recipient of the A.M. Turing Award, the “Nobel Prize of computing,” which gives his opinions great authority.  He’s one of the originators of “deep learning,” that combines advanced hardware with state-of-the-art software enabling machines to train themselves to solve problems.  Bengios’s high standing is enough to persuade me not to worry to excess until a contradictory view by an equally qualified AI expert comes out.   Most of those sounding alarms about AI Apocalypse are not computer scientists, no matter how smart they are. Elon Musk, for example, discovered that robots in his Tesla factory were making stupid mistakes, and concluded, “human intelligence is underrated.”

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Robots Coming for Our Jobs? – Not So Fast

Reassuring News on Automation and Employment?

A recent study led by Melanie Arntz, acting head of the labor markets research department at the Center for European Economic Research,*  addressed the specter of massive unemployment due to automation.  It concluded that the risks of robots taking our jobs has been exaggerated.  Looking forward 10-20 years, it revises downward the estimates of job losses in the U.S. from 38% to 9%.  As we know, doomsayers (such as I) have forecast job losses more like 50% by 2040.

Here’s a link to the study, where you can download a free .pdf: Revisiting the Risk of Automation

The paper, released in July 2017, is chock-full of jargon and hairy statistical equations, but the thrust of it is commonsensical: scary scenarios of massive job losses** fail to take into account what the authors call “the substantial heterogeneity of tasks within occupations” [emphasis mine] “as well as the adaptability of jobs in the digital transformation.” (I take this language from the abstract, which nicely encapsulates the study and findings in the nine pages that follow.)

These findings stem from an approach that distinguishes between occupation-level work and  job-level work.

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