We’ve been sort of stunned by ChatGPT’s recent exploits, which not only suddenly forced people to adjust their methods but solidly moved AI from the future to the present. There has been much going on in this field, which should also include robots as they are now truly manifestations of AI. This post is the first of a three-part series which will break for the March 3rd jobs report and in the unlikely event that something else about jobs and the economy seems more important and urgent. So now, in chronological order, we start.
First is only a statistic, shared by Emerging Tech Brew
citing The Wall Street Journal on September 21st. In 2021, there were 243,000 industrial robots
implemented in China, which was “just about equal to the amount installed by
every other country on earth combined.” Not really shocking, as China has been adding
far more industrial capacity than elsewhere, but noteworthy as robots, as sort
of anti-human-work, mean that its overall strategy of competing with cheap
labor is over.
It's always too soon to make conclusions on such matters,
but Farhad Manjoo maintained in the October 7th New York Times
that “In the Battle With Robots, Human Workers Are Winning.” Indeed, when Manjoo asked “weren’t humans
supposed to have been replaced by now – or at least severely undermined by the
indefatigable go-getter robots who were said to be gunning for our jobs?,” he
missed how many people have already been displaced, and that AI and robots are
not necessarily comprehensive, and suggested that because widespread,
broad-based job elimination has not already happened it never will. In radiology, a high-skill field now being
largely automated, while it is reasonable that “even if computers can get very
good at spotting certain kind(s) of diseases, they may lack data to diagnose
rare conditions that human experts with experience can easily spot,” there is
no reason why a group of such practitioners cannot be reduced, with remaining
employees doing more specialized diagnoses for more patients. Robots will improve and proliferate on timelines
of which we cannot be certain.
Not all new automata are highly intelligent, as shown in the
imaginative title situation in “Meet Your New Corporate Office Mate: A
‘Brainless’ Robot” (John Yoon and Daisuke Wakabayashi, November 17th,
The New York Times). The authors
chronicled a solution for humans being wary of what data such things wandering
workplace halls may be collecting, which could be Naver’s devices, “completing
mundane tasks like fetching coffee, delivering meals and handing off packages,”
skilled at using elevators without interfering with people, and represented as
doing only those tasks. This piece
showed well how maximum capability is not be the only robotic goal.
At the other extreme, we have “MIT researchers creating
self-replicating robots with built-in intelligence,” by Paul Best in Fox
Business on November 27th.
They are “swarms of tiny robots” able to “build structures, vehicles, or
even larger versions of themselves.”
This one, though being designed and tested, “will likely be years”
before implementation. Also scary was
“San Francisco Considers Allowing Use of Deadly Robots by Police” (Michael
Levenson, The New York Times, November 30th). The idea here was first implemented in the US
by Dallas police, who in 2016 “ended a standoff with a gunman suspected of
killing five officers by blowing him up with a bomb attached to a robot.” The real issues here are ethical, not
logistical – exactly what situations if any would justify their use – and will
need to develop.
We would like to know “How AI is conquering the business
world” (Guy Scriven, The Economist, December 10th). The author saw not giant steps but an
accumulation of small tasks, mastered one after another. When enough of these responsibilities are
eliminated, job consolidation can proceed.
That publication issued the unbylined “The new age of AI” in the same
edition, saying “artificial intelligence is at last permeating swaths of the
business world.” Examples here included
John Deere’s “fully self-driving” farm machines, tools that propose finishing
sentences (as in the version of Microsoft Word I am using here), reducing data
center energy consumption, rerouting impeded deliveries, sweeping floors,
writing first presentation drafts, and generating computer code, all now
incorporated into live production settings.
The piece mentioned Nick Bostrom’s observation that “once something
becomes useful enough and common enough it’s not labeled AI anymore,” and
predicted “an explosion of such “boring AI.””
That may be much of artificial intelligence’s near-term
future – but hardly all. For the first
articles of 2023, see the next post in this series.
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