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 Indeed, when Manjoo asked “weren’t humans supposed to have been replaced by now – or at least severely undermined by the indefatigable go-getter robots who were said to be gunning for our jobs?,” he missed how many people have already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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