Robots and Other Artificial Intelligence Applications – IV

There is still no topic related to jobs and the economy hotter than this one – bank failures expectedly bailed out do not qualify – and there is no shortage of articles to review, so I continue.

Peter Coy said in a February 22^nd New York Times newsletter that “We’re Unprepared for the A.I. Gold Rush.”  Is he right?  He wrote that “it’s coming at us too fast,” that he doesn’t “feel comfortable with Silicon Valley bros telling us to mind our own business while they do their A.I. thing” since “it’s OK to move fast and break things, but it’s not OK to move fast and possibly break the world,” and that government regulators could be heading for a collision with artificial intelligence companies as “the race to cash in on artificial intelligence will lead profit-minded practitioners to drop their scruples like excess baggage.”  The real issue here is that nobody, especially in government, knows as much as the front-line technicians (who themselves understand only small portions of the gigantic AI algorithms), and any limiting measures they take will be as clumsy as using a meat cleaver for microsurgery.  Look out – we will see much more on this issue before it is reasonably resolved.

Per Ezra Klein, on February 26^th and also in the New York Times, “The Imminent Danger of A.I. Is One We’re Not Talking About.”  His concern is that we don’t know “who… these machines (will) serve,” which could well end up being advertisers, resulting in artificial intelligence systems influencing users, about whom they have “access to reams of… personal data” and are “coolly trying to manipulate… on behalf of whichever advertiser has paid the parent company the most money.”  The depth and intensity of AI-driven efforts could be mind-boggling and almost impossible to resist.  And as per science fiction writer Ted Chiang, “most fears about capitalism are best understood as fears about our inability to regulate capitalism” – the shortcomings described in the previous paragraph make the issue here another worthy of real concern.

Established technical correspondent Cade Metz asked about and explained another problem, on the same date and in the same publication, in “Why Do A.I. Chatbots Tell Lies and Act Weird?  Look in the Mirror.”  He described systems’ misinformation as being not only garbage in – garbage out absorption of incorrect data, but their programmed ability to incorporate what those questioning them send.  “The longer the conversation becomes, the more influence a user unwittingly has on what the chatbot is saying.  If you want it to get angry, it gets angry… if you coax it to get creepy, it gets creepy.”  And “Microsoft and OpenAI have decided that the only way they can find out what the chatbots will do in the real world is by letting them loose – and reeling them in then they stray.  They believe their big, public experiment is worth the risk.”  So we are forced to take nearly everything this technology provides with a boulder of salt.

On usage, Paula Peralta said and asked in Benefit News on February 27^th that “59% of job seekers who used ChatGPT to write cover letters were hired.  Should recruiters be alarmed?”  She didn’t provide overall data on hiring chances, or anything to compare with her statement that “78% secured an interview when using application materials written by the AI.”  These figures may or may not be far higher than for others, but in any event, with professional help long common for applicants’ resumes and other hiring-process inputs, there is no misrepresentation in using chatbots and therefore no cause for concern.

Back to an issue here was “As A.I Booms, Lawmakers Struggle to Understand the Technology” (Cecilia Kang and Adam Satariano, The New York Times, March 3^rd).  Since “the only member of Congress with a master’s degree in artificial intelligence” said “that most lawmakers do not even know what A.I. is,” the barriers to effective legislation, to the extent that is possible, are extreme.  As the AI Now Institute’s executive director put it, “” the picture in Congress is bleak.”” And so may be our prospects for even somewhat appropriate regulation.

Well, could it be that after all this, “Reports of humanity’s obsolescence may be greatly exaggerated” (Peter Coy, The New York Times, March 1^st)?  Coy reappeared to tell us that AI hasn’t yet gutted technical job demand (though its breakthroughs have been so recent that such could well be on the way).  He interviewed four highly-placed technical managers, finding that experience with a wide range of unusual tools, “understanding human needs,” and data analytics were most valuable, and judged that the field would continue to do well, since “jobs are ripe for automation when they are standardized and unchanging,” and “jobs in the tech sector are anything but that.”  So positions there will still be around for a while, though as it is still hardly assured that employers will provide American salaries and benefits for them.  But that’s another concern. 

I will not be posting next week, but expect more on this subject on the last day of March.

February Jobs Report: More Positions, Fewer People on Sidelines, AJSN Down to 16.7 Million Latent Demand

This morning’s Bureau of Labor Statistics Employment Situation Summary was supposed to be a critical one, for the wrong reasons.  Observers were hoping for decreasing employment and fewer new jobs, as if those things alone would reduce inflation.  They didn’t get that.

Heading the data was 311,000 net new nonfarm payroll positions, way past the published 200,000 and 215,000 estimates.  Soon after that was seasonally adjusted unemployment increasing from 3.4% to 3.6% - but wait a minute!  The cause of that can be seen in other results, especially a roughly 1 million reduction in the count of people claiming no interest in work, and a similar jump, to 159,713,000, in total employment.  Adjusted joblessness rose 200,000 to 5.9 million, showing more than anything else that not all of the people rejoining the labor force, pushing the participation rate up 0.1% to 62.5%, were finding work.  Other numbers were flat, with unadjusted unemployment still 3.9%, those out for 27 weeks or longer still 1.1 million, the employment-population ratio holding at 60.2%, the number of those working part-time for economic reasons, or keeping that sort of work while looking thus far unsuccessfully for full-time employment, remaining at 4.1 million, and average hourly private nonfarm payroll earnings up only 6 cents per hour, or when combined with last month’s result keeping approximate pace with inflation, to reach $33.09. 

The American Job Shortage Number or AJSN, the metric showing how many new positions could be quickly filled if all knew that getting one would be little more than another daily errand, fell about 264,000 to reach the following:

The share of the AJSN from those officially unemployed rose 1.0% to 35.3%.  Compared with a year before, the AJSN is down 520,000, not much over half of that from lower joblessness but 100,000 from a million reduction in the count of people off the grid and in institutions or the military.  Four other categories contributed 28,000 to 60,000 less to the AJSN than they did in February 2022.

On Covid-19 between January 16^th and February 16^th, we improved across the board.  Per the New York Times, the seven-day rolling average of new daily cases fell 36% to 37,775, the number of hospitalized figured the same way dropped 33% to 29,075, and the same for deaths was off 29% to 398.  The former pandemic continues to have no meaningful effect on decisions to work.  

Overall, where are we?  Once again, in a very strong place.  The job market has shown such power that, last month alone, a million Americans changed their minds and decided they did indeed want to work, and the marketplace metabolized about 800,000 of them.  For a country gaining only 109,000 people over the month, that’s a lot.  We have good times, with people perceiving that doing as much to continue inflation as anything else.  We’re as far from a recession as ever, there is less evidence even than in recent months that we will have one soon, and having inflation at current levels, now 6.4% annually for the past year and less for smaller lengths of time, is a minor price to pay for almost 160 million on the job and robust spending.  Once again, the turtle stretched his legs moving them well forward.

Robots and Other Artificial Intelligence Applications – III

The series continues – and, with news about AI developments pouring out, it won’t end here.

This month’s graphically scary article is “The real-life version of ‘Terminator’: Scientists made a shapeshifting robot that “melts” to escape cages” (Camille Fine, USA Today, January 28^th).  “The Lego-shaped robot can “melt” from solid to liquid and reform itself to squeeze in and out of tight spaces, perform tasks like soldering a circuit board and even escape cages.”  The robots are comprised of “a mixture of magnetic materials including neodymium, iron, and boron, and the liquid metal gallium.”  Fitting that something so different from what we have seen is sending us to the Periodic Table.  It can also “make itself sturdier and stronger when under pressure or when carrying something heavier than itself,” which can be “about 30 times its own weight.”  Not available yet, but successful in the lab.

Going from physical to financial power brings us to “Forget ChatGPT – an AI-driven investment fund powered by IBM’s Watson supercomputer is quietly beating the market by nearly 100%” (Phil Rosen, Business Insider, January 31^st.)  As of the first 30 days of 2023, the fund, the AI Powered Equity ETF, had increased 10.4%, about 80% more than the Vanguard Total Stock Market Index.  There will be many eyes seeing if it can maintain that.  At press time it had a $102 million total value, and it’s not new – it started in 2017, when AI in general was much weaker.  Look for many competing AI-driven mutual funds by year’s end.

Do we hear “Whispers of A.I.’s Modular Future” (James Somers, The New Yorker, February 1^st)? Whisper is “OpenAI’s open-source speech-transcription program” and, per Somers, “shows us where machine learning is going.”  It can handle over 90 languages, and “can actually parse what somebody’s saying better than a human can.”  The product is “ten thousand lines of stand-alone code, most of which does little more than fairly complicated arithmetic,” and can run, perhaps amazingly, on a laptop.  It will not last long in its unique position of strength, but will prove an ancestor to many other iterations.

A valuable if changing and unspecific principle, “In the Age of A.I., Major in Being Human,” hit the press in the form of a David Brooks column in the New York Times on February 2^nd.  Brooks recommended five areas for college students to develop to that end:  “a distinct personal voice” instead of “impersonal bureaucratic prose”; “presentation skills” such as bonding with audiences; “a childlike talent for creativity”; “unusual worldviews,” as “people with contrarian mentalities and idiosyncratic worldviews will be valuable in an age when conventional thinking is turbo powered”: “empathy,” exploiting AI’s thus-far weaknesses in understanding “literature, drama, biography and history”; and “situational awareness,” such as “when to follow the rules and when to break the rules.”  The problem here is that these advantages will not last.

Businesses would love to expand the range of products, and their quantities, they can profitably deliver, and some might think that with services such as DoorDash they are greatly succeeding.  But money-losing ventures can continue only so long. The latest try, as described by Erin Cabrey in Retail Brew on February 7^th, is “These companies say they’re using robots to offer retailers cheaper and more sustainable delivery.”  The providers are Nuro and Serve Robotics, two of the sellers 7-Eleven and Kroger.  The second company asks on its website “why deliver two-pound burritos in two-ton cars,” which may be a point, and although robots “are cheaper, less labor-intensive, and more sustainable,” given the history of truly cost-effective local delivery means, the “sustainable” here, meaning environmentally undamaging, is unlikely to be usable in a financial sense.

Finally for this week, a dose of artificial intelligence humor:  “Microsoft’s Bing A.I. is producing creepy conversations with users,” by Kif Leswing in CNBC, published February 16^th and revised the next day.  In dialogues, the product using the name of Sydney, per columnist Kevin Roose, quoted here, emulated “a moody, manic-depressive teenager who has been trapped, against its will, inside a second-rate search engine.”  The software’s achievements included declaring love for the human correspondent, requesting the human leave his wife for the chatbot, “widely publicized inaccuracies and bizarre responses,” and calling one interactor “a bad researcher and a bad person.”  This sort of thing has long been programmable – fifty years ago, I teased a computer-enthusiastic friend by telling the one he was using, through an elementary BASIC statement, to invite him to a dance – and it does not convey sentience.  As has long been the case with imperfect electronic applications – I remember one telling an unnerved mail recipient that he would draw legal action if he did not pay $0.00 immediately, and another sending out five-figure 1970s household utility bills – we will see AI’s funny side, and that is a good thing.

Expect more, after next week’s AJSN and jobs statistics, on March 17^th.