Electric Vehicles are Going Nowhere Special

In my December 15^th post, I wrote “fundamental sale price drops may require more to be sold than the market can support.  I predict that by November 2024 the share of electrics as American vehicles will be higher than it is now, but only about 10%, with a growing consensus that under current conditions they will not be completely or even largely taking over.”  Seven-plus months out, how are those forecasts looking?

On May 26^th in Fox Business, we saw how “Buttigieg defends Biden’s EV strategy after question on how only 8 federal charging stations have been built.”  The unfortunately-placed transportation secretary was asked why, when two years ago President Biden signed a bill authorizing 500,000 such facilities to be built by 2030 and after one-quarter of the time since has elapsed, the number completed stands at .0016% of that; he reiterated the half-million goal and said there was “utility work” to be done at each, under “a new category of federal investment.”  How many have been started?  I could find information on ports, overall stations, and groups of stations with at least one under construction, but not that.

Another thing Buttigieg mentioned in the interview above was the necessity of lower electric vehicle prices.  Soon afterward, on June 3^rd, the New York Times published “Electric Cars Are Suddenly Becoming Affordable” (Jack Ewing).”  The reason, though, was not higher sales providing manufacturing economies of scale, but that “customers have been snapping up used Teslas for a little over $20,000, after applying a $4,000 federal tax credit.”  That trend started with Hertz’s January-announced sale of 20,000 electric rental cars, which the market has not yet absorbed.  Ewing also mentioned, for new cars, the effect of “increased competition, lower raw-material costs and more efficient manufacturing,” but companies choosing to cut prices were pushed by Hertz, as “electric cars still cost more to manufacture than cars with internal combustion engines,” and sales would further drop without continuing subsidies.

The lack of growth has also pushed companies to build “More Gas Cars and Trucks, Fewer E.V.s as Automakers Change Plans” (Neal E. Boudette, The New York Times, July 18^th).  Ford Motor Company “said it would retool a plant in Canada to produce large pickup trucks rather than the electric sport-utility vehicles it had previously planned to make there,” and the day before that, “General Motors said it expected to make 200,000 to 250,000 battery-powered cars and trucks this year, about 50,000 fewer than it had previously forecast.”  Tesla, as well, “has changed its plans because it no longer expects sales to grow 50 percent a year,” as “its global sales fell 6.6 percent in the first six months of the year.” 

And speaking of the last company mentioned, “Tesla’s Profit Fell 45% in the Second Quarter on Weak E.V. Sales” (Neal E. Boudette, The New York Times, July 23^rd).  Its second-quarter year-over-year revenue increased from $24.9 billion to $25.5 billion, but its net profit fell from $2.7 billion to $1.5 billion.  That seems to confirm that its shortfall from lower selling prices is not from lower costs.  For the same interval, its number of EV’s sold dropped 4.8% and their production 14%. 

As of an Experian Automotive Market Trends fourth quarter 2023 report, only 3.3 million out of 288.8 million American vehicles were electric.  Per Edmunds, 6.9% of sales from January to May this year were the same.  Therefore, it is almost impossible to imagine the year-end share will be anywhere near 10%, let alone higher.  It looks also very doubtful that, given the news above, EV’s will be “completely or even largely taking over” – even if a Democrat wins the November presidential election.  Their percentages may substantially increase, but until then, we must project electric vehicles, with some geographical exceptions, to remain a small minority indefinitely.  If their manufacturers cut back and switch to others, and subsidies continue to prop them up, it will mean little if those in the press say they will predominate.  The lack of federal charging stations may, in the end, be just fine, and customers will get the vehicles they want.  That will work.

Four Areas of the Economy – Four Views on Them

What American economic segments have been analyzed over the past four months?

One thing dragging us down over the past several years is tariffs.  About that, David Wallace-Wells asked, in the New York Times on May 22^nd, “Can Biden Actually Win This Trade War?”  I mentioned this massive increase, which was actually “a unilateral quadrupling” on Chinese electric vehicle duties, on a post about EV’s.  It seemed destructive for a president who seemed to badly want Americans to get away from gasoline and diesel cars, and, per the author here, “it’s not just EVs.  Five years after blasting (then-President Donald) Trump for imposing tariffs on Chinese exports, Biden raised them – on aluminum, steel, lithium batteries, solar cells and semiconductors, among other products.”  The damage to other environmentally favorable efforts is also great, as China’s production shares of related items include “84 percent of the world’s solar modules… 89 percent of the world's solar cells… 97 percent of its solar wafers and ingots, 86 percent each of its polysilicon and battery cells, 87 percent of its battery cathodes, 96 percent of its battery anodes, 91 percent of its battery electrodes and 85 percent of its battery separators.”  Although various “Democratic policymakers” say we should “avoid growing entirely dependent on China for clean energy,” “industrial policy isn’t guaranteed to work,” and “Trump’s imposition of tariffs on Chinese solar-panel exports in 2018 may have meaningfully slowed American renewable rollout.”  The extra charges have real potential to continue doing that.

Something around for many decades and worsening every year gets concern of various strengths every so often, but there are reasons, per Paul Krugman on June 6^th in the New York Times, “Why You Shouldn’t Obsess About the National Debt.”  Although, per usdebtclock.org, it is now almost $35 trillion, or over $100,000 per citizen, Krugman calls it “a lot less scary than many imagine if you put it in historical and international context,” and making it “sustainable wouldn’t be at all hard in terms of the straight economics; it’s almost entirely a political problem.”  As a share of GDP, the author said “it’s roughly the same as it was at the end of World War II,” and is now “considerably lower” than Japan’s.  We could “stabilize debt as a percentage of G.D.P. for the next 30 years” by raising taxes or reducing spending only 2.1%.  So, the money we owe is real, but it may be dormant instead of a looming threat.

Do we have “A towering real estate crisis” (Andrew Ross Sorkin, The New York Times DealBook, June 12^th)?  “The $2.4 trillion office building sector” has been hit by “sky-high interest rates and a pandemic-induced shift to remote work,” as “tenants are reducing or vacating office space to landlords at a record clip.”  As a result, “developers are looking to repurpose empty offices,” although “conversions are expensive, and not all buildings can be easily retrofitted.”  This problem may be worse than it seems, as the pendulum I have documented which swings back and forth between businesses favoring remote and in-office work is approaching the latter maximum, so it will be almost one complete cycle before office demand increases substantially, if it does at all.  Accordingly, a surplus of commercial space will seem to this generation like a permanent problem, so it needs permanent solutions.

I’m used to issuing the AJSN and basing my views using information I trust, so was not happy to see “Reliability of U.S. Economic Data Is in Jeopardy, Study Finds” (Ben Casselman, The New York Times, July 9^th).  Per an American Statistical Association report, while “government statistics are reliable right now,” “that could soon change,” due to “shrinking budgets, falling survey response rates and the potential for political interference.”  Responses to the Current Population Survey, one of two providing the foundation for “the unemployment rate and other labor force statistics,” have dropped from “nearly 90 percent” ten years ago to “about 70 percent in recent months,” and those to “other government surveys” are down also.  As for the third problem, “there are few legal provisions ensuring that the statistical agencies can operate independently,” and an author of the report called for ““legislation to make this issue of professional autonomy statutory.””  We will see, and weakness here will depend on the result of the upcoming presidential election.  The same will affect the previous three items as well – along with a great deal more. 

A Directionless Month for AI – What Do Its Scattered Reports Say?

Artificial intelligence seems to be moving into another phase, or subphase.  There have never been so many concerns, not about the technology causing a major disaster, but about it being adequate and worthwhile at all.  At the same time, there are new perceptions and more progress in related employment, and, if I am perceiving it correctly, growing acceptance that where AI is now might be where it is for months or even years, so stakeholders are realizing they cannot just wait for the next big eruption. 

A look at one chronic AI problem is the subject of “How Game Theory Can Make AI More Reliable” (Steve Nadis, Wired.com, June 9^th).  The author bemoaned the tendency of large language models to give different answers, not all correct, to generative (open-ended) and discriminative (choice of options) questions.  Researchers have invented a game of sorts where “two modes” of LLMs are asked to agree on answers.  Excellence at games is a long-time AI strength, so engineers have reason to be optimistic such inconsistencies will go away.

Top AI workers are scarce, and many, soon after starting work with an organization, move on to another for more pay.  That is why, on one level, “Retention is all you need” (The Economist, June 15^th).  As, per a market analyst, “20,000 companies in the West are hiring AI experts,” “AI talent, previously hoarded at tech giants, is becoming more distributed.”  Indeed, AI hiring at Amazon, Apple, Google, Meta, and Microsoft has only about broken even since the beginning of 2023.  Advertisements for many more software positions now mention AI, as do those for math, scientific research and development, and information design.

Defining another clear problem, Sherin Shibu’s “How Can AI Help Small Businesses?  It’s A Matter of Trust, According to a New Report” (Entrepreneur, June 17^th), tells us that “just 7% of U.S. desk workers see AI answers as completely trustworthy,” the share of American businesses as of June was only 5% although 96% of “surveyed executives felt pressure to bring AI into their business,” and “privacy” and “data quality” were the other two top issues.  These tell AI companies where they should focus, perhaps above all other considerations.

Unsurprisingly, more universities and technical schools are preparing students for jobs using the technology.  A Brock Dumas June 17^th Fox Business piece, “Want an AI career?  These colleges offer degrees for the best chance” provides a current look.  “A new study by software development firm Vention shows which U.S. colleges are offering bachelor’s degrees with the best chance of landing a job fresh out of school – and the potential for the biggest paychecks.”  The top five were California Polytechnic State University, Wake Forest University in North Carolina, Trinity University in Texas, Clarkson University in New York state, and Knox College in Illinois.  There are more, and this list will change, but these may be the ones currently most worth investigating.

Also, for now, “We’re Still Waiting for the Next Big Leap in AI” (Will Knight, Wired.com, June 20^th).  Knight wrote that “the world is still waiting for another AI leap forward… akin to that delivered by GPT-4” 16 months ago.  He described possible contenders, but then concluded “it’s unclear how long the world must wait for that next big leap in AI.  OpenAI has said it has started training its next big model.  In the meantime, we will need to figure out new ways to measure how useful the technology really is.”

On June 27^th, Fox News released “US tops world ratings for AI preparedness:  China, Russia and Iran lag in key measures, report finds” (Peter Aitken).  The rankings were on countries’ “ability to immediately adopt artificial intelligence… into their economies.”  The American “value of preparedness” tied the Netherlands, and was followed by Finland, Estonia, New Zealand, Germany, Sweden, Australia, Japan, and Israel.  That may or may not prove to be valuable information.

There must be something noteworthy about a source called Futurism.com having the most consistently negative AI articles of anyone.  Here are two more.  The first is “There’s a Small Problem with the AI Industry:  It’s Making Absolutely No Money” (July 4^th).  Author Sharon Adarlo noted that “Goldman Sachs analysts have concluded… that AI just isn’t making any serious money yet,” and that “Goldman found that companies that hoped to profit from using AI to boost productivity – ranging from H&R Block to Walmart – have seen their shares vastly underperform the broader stock market since the tail end of 2022.”  She also found that “the only companies making much actual revenue off AI are the ones selling the hardware it needs, like Nvidia.”  While “companies using it want to see major returns,” “so far, it sounds like they aren’t.  Maybe the real question is how much runway the AI industry has before business leaders move onto the next thing.”  This piece is consistent with my previous comments.

The second Futurism.com piece was “Expert Warns That AI Industry Due for Huge Collapse” (Victor Tangermann, July 9^th).  He named a “founding partner” at a “macroeconomic research firm” calling AI “completely unproven,” saying that its hallucinations may never go away and that it was “too energy hungry,” along with a previous Stability AI CEO telling bankers that “this will be the biggest bubble of all time.”  Hardly universal views, but with merit.

Overall, is it true that, per New York Times columnist Thomas Friedman on July 9^th, “the artificial intelligence revolution of the past four years is widely expected to slam into the white-collar job market in the next four like a Category 5 hurricane”?  We don’t know that.  As with actual storms, we will benefit from tracking them and projecting their courses and times of landfall, but this one is way too weak and distant to fear.  We don’t need to buy flashlights, batteries, and water, and may never need to.  The future of artificial intelligence is still up in the air – and it may never come down.

Jobs in June: Seasonal Worsenings Mostly Offset Elsewhere, with AJSN Showing Latent Demand Up Almost Half a Million

The published projections I saw for this morning's Bureau of Labor Statistics Employment Situation Summary was that it would be worse than for May’s data a month ago.  The two estimates of net new nonfarm payroll positions were 190,000 and 200,000, and unemployment might be going up again.  So what happened?

Employment as above, at plus 206,000, was quite close to the predictions.  Seasonally adjusted joblessness had its third straight 0.1% gain, to 4.1%, with the corresponding total of people up 200,000 to 6.8 million.  (We now can ignore when the BLS says something “changed little.”)  Long-term unemployed, for 27 weeks or longer, gained 100,000 to 1.5 million, up 36% from June 2023, with so many people joining the labor force that its participation rate increased, 0.1% to 62.6%.  The measure of how many Americans are actually working, the employment-population ratio, stayed at 60.1%.  The count of those working part-time for economic reasons, or holding onto shorter-hours positions while looking for full-time ones, shed 200,000 to get to 4.2 million.  Average private nonfarm payroll earnings rose 9 cents per hour, close to the inflation rate, to $35.00.

Since May and June have different employment characteristics, the seasonally unadjusted figures did not match the others.  Unemployment that way jumped 0.6% to 4.3%.  The count of those not interested in working lost 637,000 to 93,776,000.  Those employed rose 433,000 to 161,774,000.

The American Job Shortage Number or AJSN, the statistic showing how many additional positions could be quickly filled if all knew they would be easy and routine to get, was up 478,000, as follows:

The share of the AJSN from those officially jobless was 4.3% higher at 37.7%.  Compared with a year earlier, the AJSN grew 504,000, with almost 800,000 more from unemployment partially equalized by, among others, 174,000 from fewer people wanting work but not looking for it for a year or more, and 200,000 fewer from expatriates. 

What patterns can we get from this report?  The new jobs, once again plentiful and nothing to take for granted, went largely to people with statuses other than simple unemployment.  Many more people returned to the labor market, and enough were unsuccessful to bring overall joblessness up.  A goodly number of those without work are not finding it, even after six months away.  Latent demand is not only alive and well but increasing.  Still, June is a tougher month than May, and the smaller, marginal categories show that this was, overall, a good one.  The turtle took a moderate step forward.

Driverless Cars in Mid-2024: A Niche, A Great Future, or Stalling Out?

Autonomous vehicles, through thrown off their horse (strange pun intended) years ago, have not gone away, and aren’t even out of the news as artificial hearts have long been.  What has been happening with them?

The largest recent news item was “Feds are investigating Waymo driverless cars after reports of crashes, traffic violations” (Corina Vanek Natalie Neysa Alund, USA Today, May 16^th).  The National Highway Safety Administration got “reports of nearly two dozen incidents where a Waymo vehicle was the sole vehicle operating during a collision or the driving system allegedly violated traffic laws.”  There were no injuries, but “17 involved crashes or fires,” and the automated driving system “was either engaged through the incident, or, in certain cases when supervised by an in-vehicle test driver,” it “disengaged in the moments just before an incident occurred.”  Waymo gave itself a vote of confidence, with a spokesperson saying “we are proud of our performance and safety record over tens of millions of autonomous miles driven”; additionally, “according to data released by Waymo in December 2023… which was peer-reviewed by experts outside the company, Waymo vehicles were involved in 0.4 collisions with injuries per million miles driven, compared with humans who were involved in 2.78.”  This story graphically shows how autonomous vehicles are being held to vastly higher standards.

Travelers are showing an interest in “San Francisco’s Hot Tourist Attraction:  Driverless Cars” (Lauren Sloss, The New York Times, May 22^nd).  There they “have been operating commercially since August,” though only through Waymo, as “popular pickup and drop-off locations” include “the Ferry Building, Pier 39, Coit Tower, and the Japantown Peace Plaza.”  They are “all-electric Jaguar I PACEs,” and are accessed through an app.  Trips are remotely monitored.  Although different in some ways, “perhaps the most noteworthy aspect of a first-time Waymo ride is how quickly it feels normal.”

A company not doing as well is the subject of “The Very Slow Restart of G.M.’s Cruise Driverless Car Business” (Yiwen Lu, The New York Times, May 30^th).  General Motors is still using its “sprawling complex in Warren, Mich.,” but “G.M.’s driverless future looks a lot further away today than it did a year ago,” before “a Cruise driverless car hit and dragged a pedestrian for 20 feet on a San Francisco street, causing severe injuries.”  Since then, it has “slowed its breakneck development to a crawl,” and, per a consultant, “catching up with Waymo technologically is going to take three to five years at best.”  Yet GM’s CEO said the subsidiary “has made tangible progress.”

Meanwhile, we saw “Waymo, Zoox expand autonomous ride-hailing operations despite recent AV setbacks” (Jordyn Grzelewski, Emerging Tech Brew, June 11^th).  Zoox is moving from three cities to five, but is only testing; Waymo “revealed that it expanded its ride-hailing service area in Metro Phoenix by 90 square miles, bringing its total service area to 315,” and as well as San Francisco, “operates… in Los Angeles, and is testing in Austin.”

For now, Waymo is the only normally available option.  But another competitor, nation-sized, is emerging, as “China Is Testing More Driverless Cars Than Any Other Country” (Keith Bradsher, The New York Times, June 13^th).  In the city of Wuhan, “a fleet of 500 taxis navigated by computers, often with no safety drivers in them for backup, buzz around,” operated by “tech giant Baidu.”  No mention here, though, of a date when paying customers can ride in them.  That seems better though, than another major country, as, although resumed in March, “last fall, Japan suspended its test of driverless golf carts that travel seven miles per hour after one of them hit the pedal of a parked bicycle,” causing no injuries. 

All of this is much the same as 2023’s reports, and largely like the past five years’ worth.  While Waymo is piling up miles and a record, the others are too often stopped by small mishaps.  Companies’ levels of caution are based on the correct perception that such blips unduly scare people.  However, as before, we are paying too little attention to the upside of driverless technology.  Over 40,000 died in American car crashes last year alone, compared with zero in the accidents above.  A tenuous niche has been established – a great future autonomous vehicles still have, if we allow that.  Will we get to the point where extensive testing efforts are not halted for months by the likes of hitting a bicycle pedal?  The answer to that question is more important than any possible driverless technology improvement.  The choice, once again, is ours.

Five Weeks of Artificial Intelligence – Where Is It Now?

A lot has happened with AI over the past several weeks.  I’m not talking about projections, assumptions, justified or other worries, 100-to-1 price-to-earnings ratio stock run-ups, market capitalizations, self-serving representations, CEO hijinks, and other things at the fringes of substantive news making up the great bulk of writing on the technology.  There is real stuff here, so much that I’m calling this piece an expanded edition, appropriate since I won’t be posting next week.

The oldest article is “The great AI power grab” (The Economist, May 11^th).  It addresses the “awful lot of electricity” the software will need, and asks “where will it come from?.”  With “Dominion Energy, one of America’s biggest utilities” being “frequently” asked for “several gigawatts,” when the company has only 34 installed, it’s getting up there.  That power is consumed “at a steady rate,” regardless of sunlight and wind conditions.  It has already started affecting AI companies’ choices of location, and will do so more as long as anyone anywhere has what they need.

It took some digging to show, on my last AI post, what actual sales were, but how about number of transactions?  That is the metric used in “The 10 most popular AI companies businesses are paying for” (Jordan Hart, Business Insider, May 12^th).  The list, which includes “specialized tools” as well as “generative AI,” in order, are OpenAI, Midjourney, Anthropic, Firefiies.ai, ElevenLabs, Perplexity AI, Instill AI, Instantly.ai, Beautiful.ai, and Pinecone.  I found it noteworthy how many are not household words, even in my house.  It shows not only that there are firms being quietly effective, but that some with the noisiest press releases aren’t selling to many people at all.

“As A.I. search ramps up, publishers worry” (Andrew Ross Sorkin, New York Times DealBook, May 15^th) shows cause for concern among those using an “ad-focused business model.”  They are fearful, as “AI Overviews will give more prominence to A.I.-generated results, essentially pushing website links farther down the page, and potentially depriving those non-Google sites of traffic.”  They will need to work this out, as the presence of AI does not please everyone.

Something remarkably lost in the outpouring of manufacturer claims got its own article: “Silicon Valley’s A.I. Hype Machine” (Julia Angwin, The New York Times, May 19^th).  Although in early 2023 “leading researchers asked for a six-month pause in the development of larger systems of artificial intelligence, fearing that the systems would become too powerful,” now “the question is… whether A.I. is too stupid and unreliable to be useful.”  Results have lagged the previous intensity, but corporate statements haven’t – for example, OpenAI CEO Sam Altman, the week before, had “promised he would unveil “new stuff” that “feels like magic to me,”” but delivered only “a rather routine update.”  One “cryptocurrency researcher” asserted that AI companies “do a poor job of much of what people try to do with them” and “can’t do the things their creators claim they one day might.”  The author agreed that “some of A.I.’s greatest accomplishments,” such as its 2023 law bar exam performance critical to perception of AI being amazingly high quality turning out to be in the 48^th percentile instead of the 90th as stated, “seem inflated.”  The technology, per Angwin, “is feared as an all-powerful being,” but now seems “more like a bad intern.”  There will be growing discontent about blatant exaggerations as products fail to meet the stunning standards we were told to expect by now.

The big May story, which many probably confused with higher AI sales, was “Nvidia, Powered by A.I. Boom, Reports Soaring Revenues and Profits” (Don Clark, The New York Times, May 22^nd).  For this leading supplier, “revenue was $26 billion for the three months that ended in April, surpassing its $24 billion estimate in February and tripling sales from a year earlier for the third consecutive quarter.  Net income surged sevenfold to $5.98 billion.”  These numbers show how much more companies such as OpenAI have bought than they have sold.

A related area was the subject of “OpenAI Insiders Warn of a ‘Reckless’ Race for Dominance” (Kevin Roose, The New York Times, June 4^th).  Per “a group” there, the firm, “racing to build the most powerful A.I. systems ever created,” “published an open letter… calling for leading A.I. companies, including OpenAI, to establish greater transparency and more protections for whistle-blowers.”  That firm, “still recovering from an attempted coup last year” and “facing legal battles with content creators who have accused it of stealing copyrighted works to train its models,” has big issues to go with its big chip purchases.

For June, the largest news item so far has been “Apple Jumps Into A.I. Fray With Apple Intelligence” (Tripp Mickle, The New York Times, June 10^th).  This company, ancient and entrenched by the standards of its industry, “revealed plans to bring (AI) to more than a billion iPhone users around the world,” including “a major upgrade for Siri, Apple’s virtual assistant.”  This business decision has a huge possible upside for AI, as it could “add credibility to a technology that has more than a few critics, who worry that it is mistake-prone and could add to the flood of misinformation already on the internet.”  That would close some of OpenAI’s sales-to-purchases gap – I don’t say “will,” since, per Forbes Daily on June 12^th, “to utilize these AI features, iPhone users will have to wait until the iOS 18 operating system becomes available later this year,” which, per the Angwin story above, seems less than a sure thing.

It has been slow on the national regulatory front lately, so we are seeing “States Take Up A.I. Regulation Amid Federal Standstill” (Cecilia Kang, The New York Times, June 10^th).  Although, per the Institute for Technology Law and Policy’s director, “clearly there is a need for harmonized federal legislation,” current and anticipated violations are prodding other governments to quicker action.  “Lawmakers in California last month advanced about 30 new measures on artificial intelligence aimed at protecting consumers and jobs,” including “rules to prevent A.I. tools from discriminating in housing and health care services” and ones that “also aim to protect intellectual property and jobs.”  Legislation has already passed in Colorado and Tennessee, the first against “discrimination,” and the second, through the snappily named “ELVIS act,” guarding “musicians from having their voice and likenesses used in A.I.-generated content without their explicit consent.”

Two AI achievements have reached the present, as described in “This is, like, really nice” (Vlad Savov, Bloomberg Tech Daily, June 11^th).  Here, even though “the breathless bluster about AI changing industries, jobs and lifestyles has obviously not been met by reality,” it has come up with the “Descript editing tool” for audio files, which “eliminates pauses, verbal fillers like “like” and “um,” redundant retakes and anything else that’s not essential.”  Listening to its end results, the author “couldn’t tell where the seams were,” and noted that when “everything takes far longer to edit than its actual running time,” “automating the process is invaluable.”  The second was “AI noise cancelling” with “the Audeze Filter,” “a smartphone-sized Bluetooth conference speaker” that “effectively cancels even unpredictable and high-pitched noises, such as the crying of a baby,” and in a demonstration “a cacophonous café was made tranquil with the flip of a switch.”  Not world domination, but perhaps it can help with wedding audiotapes damaged by unwanted sounds.

To end a bit lighter, new technologies get us new word usages, with one of the latest in “First Came ‘Spam.’  Now, With A.I., We’ve Got ‘Slop’” (Benjamin Hoffman, The New York Times, June 11^th).  The author identified that as “a broad term that has developed some traction in reference to shoddy or unwanted A.I. content in social media, art, books, and, increasingly, in search results.”  As a two-years-ago “early adopter of the term” was quoted, “Society needs concise ways to talk about modern A.I. – both the positives and the negatives.  ‘Ignore that email, it’s spam,’ and ‘Ignore that article, it’s slop,’ are both useful lessons.”  And so it will be.  Beyond that, though, we have no idea.

The Lukewarm Reports Continue: Plenty of New Jobs, but AJSN’s Latent Demand Is Up to 16.8 Million, with Unemployment and Other Key Figures Worse

This morning’s Bureau of Labor Statistics Employment Situation Summary was important for other observers and me for different reasons.  Most were concerned with whether the job market was cooling off, meaning that if it was, we might see lower interest rates sooner.  They got a mixed result – while the number of net new nonfarm payroll positions again beat expectations, coming in at 272,000 instead of 180,000 or 190,000, seasonally adjusted unemployment broke upward out of a 10-month range to 4.0%.  I was looking to both the second of these and other figures, which taken together give us more insight than any one or two can provide.

There, the results were more bad than good.  Unadjusted joblessness rose 0.2% to 3.7%, mostly not for seasonality.  We reached 6.6 million adjusted jobless, up 100,000.  The count of people out of work for 27 weeks or longer also hiked 100,000, to 1.4 million.  The two measures of people with jobs and those also officially jobless, the employment-population ratio and the labor force participation rate, fell 0.1% and 0.2% to reach 60.1% and 62.5%.  The number of people working, unadjusted, fell 249,000 to 161,341,000. 

On the plus side, the count of those not interested in working shed 667,000 to 94,413,000.  Those working part-time for economic reasons or keeping less than full-time employment while looking for something with more hours lost 100,000 to 4.4 million.  Average private nonfarm payroll earnings rose 12 cents, more than inflation this time, to $34.91. 

The American Job Shortage Number or AJSN, the measure showing how many additional positions could be quickly filled if all knew they were easy and routine to get, increased almost 800,000 to reach the following:

 

The largest contributor to higher latent demand was people available for work but not looking for it over the past year, which added almost 400,000 more than last time to the metric.  Most of the rest of the increase was from unemployment itself, but those discouraged and those wanting work but not available for it now also added significant amounts.  Compared with a year before, the AJSN has also gone up, mostly from official unemployment, just over 400,000.  The share of the AJSN from unemployment rose 0.3% to 33.4%.

With all those new jobs, which the reduced number of people not interested more than absorbed, why can’t I rate this report higher?  Adding to the preponderance of evidence from the second through fourth paragraphs above, and the worsened AJSN, are the smaller categories therein.  There will be little discussion elsewhere about the effect of more people discouraged, not looking for the previous year, and temporarily unavailable, but they conceal a lot of people not making it in today’s market, new jobs notwithstanding.  Just as the count of those claiming they do not want a job decreases during truly good times, fewer people turn up in these smaller groupings when they see employment opportunities they like.  If they were counted as unemployed, their effect would be on front pages. 

Overall, we’re no longer in our best job market times.  That 272,000 can only go so far.  The turtle, last month, stayed right where he was.