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.

Where Gig Work and Side Hustles Have Been Going, and What They Mean

There’s nothing new about either gig work or side hustles.  The first was called off-the-books, or in some circles, “owlhooting,” with pay or other compensation unknown to the authorities.  I engaged in it at age 10 or so when a fruit delivery truck driver offered me a “nice yellow apple” if I helped him find an apartment receiving his products.  The second type was known as “moonlighting,” and was generally not revealed to primary employers – I did that for almost my entire business career, ending over 20 years ago, and kept it to myself.

Both forms of work have evolved in significance as well as legally.  One problem is a tendency to illegitimately classify ordinary jobs that way.  The latest case I have seen was described by Terri Gerstein in “More People Are Being Classified as Gig Workers.  That’s Bad for Everyone” (January 28^th, The New York Times).  It’s bad for the workers but not for employers, as they can thereby avoid providing benefits such as a minimum wage, overtime, and sick leave.  The law is simple – per Gerstein, “an independent contractor is considered someone who works primarily free of control and direction and is “customarily engaged” in an independent trade or business related to the service performed.”  In the case of temporary employees, seemingly a gray area between employment and gig work but a clear case of the former, companies in Colorado have been drawing fines from governmental department Denver Labor for treating restaurant “servers, bartenders, line and prep cooks, and… dishwashers” as if they could choose their own hours, uniforms, and work locations.  That’s a legal matter, as it should be.

One explanation for increased appeal of these two labor types to some people is “Why do women look for freelance, gig jobs?  Avoiding the ‘old boys network’ at the office” (Paul Davidson, USA Today, February 9^th).  The author said that “there’s a reason lots of women are freelancing, doing contract or gig jobs and saying goodbye to the traditional workplace – and it’s not just about flexible hours.  They don’t want to deal with co-workers.”  That factor was the most common reason why, in a December survey, “they find gig work more attractive than working in an office,” with flexibility, “setting their own hours,” and “avoiding time-wasting commutes” also common reasons.  The difference between men and women was huge, with 77% of women naming the problem with fellow employees but only 23% of men agreeing.  A National Women’s Law Center executive thought “women don’t always feel empowered and don’t feel comfortable,” and “a feeling of uneasiness” about “work-life balance” affects them often as well, all worsened by lowered amounts of allowed remote labor.  Yet “thirty-eight percent of men and 17% of women describe themselves as flexible or gig workers.”  I have read elsewhere about Generation Z employees, especially, wanting more flexibility – it is probable that there will be some common workplace practice changes along these lines in the next decade or sooner.

That cohort is prominent in “Rising number of workers depend on side jobs” (Christopher Murray, Fox Business, April 16^th).  Per a February study, “22% of workers in the U.S. had side gigs,” with 53% of those “living paycheck to paycheck.”  Of Generation Z, 32% had outside jobs.  Although that is easy to explain because of lower income and net worth, that number sounds higher than for other generations at similar ages.  Consistently, from a different source, the “Share of gig workers hit a new high in March” (Eric Revell, Fox Business, May 3^rd).  Bank of America customers make up a different set of people, and the 3.8% of them “who received income from gig platforms through direct deposits or debit cards” may seem puny but was “above the previous peak that was reached in early 2022.”  That may be only a small subset of people working that way, but the comparison with early data is worthwhile.

What about gig employment and other secondary work would be beneficial change?  One thing likely to happen is that, whether their employees talk about it with others or not, managements will expect that a good share of their people have such ventures.  That has consequences for human resources practices – for example, de facto requirements that workers put in extra time may meet with greater resistance than before.  Understanding people is an important business skill, and helps with deliverables as important as cutting turnover.  Accordingly, firms that tolerate more of workers’ off-hours choices, including earning money elsewhere, will be more successful.  We may be seeing the end of work’s centrality to identity, and organizational handling of gig work and side hustles rates to be an important part.  That, beyond the income they provide, is their true significance.

Around the Economy: Consumer Shifts, Productivity, the Stock Market, And Of Course Inflation

How are we doing now?  If not consistently well, what’s the problem?

According to Emily Stewart, in “America has a ‘trapped in place’ economy” (Business Insider, March 20^th), your economic happiness depends on whether “you like your situation right now – your job, your house, your car,” in which case “you can keep it.”  However, “if you aren’t so satisfied,” then ”well, tough luck, because you might have to keep it anyway.”  Her thinking was that buying things in general costs more from the past few years’ inflation, interest rates have gone up with mortgages up from 2.5% in 2019 to about 7% recently, substantially fewer businesses are hiring, and housing prices are “47% higher than they were in 2019.”  Although our 3.9% unemployment is historically low, that is more a matter of existing positions staying than new ones opening.

One improvement relatively new to 2024 is that “Productivity is way up” (Neil Dutta, Business Insider, March 21^st).  The boost from artificial intelligence hasn’t much happened yet, but “labor productivity – the wonkish measure of how much a worker can get done in a given hour – is already on the rise.”  Productivity results have previously been distorted by factors having little to do with people creating more – for example, it jumped in the early pandemic because workers in the least productive fields, such as food service and preparation, were losing their jobs and dropping out of the calculation.  One element that legitimately contributes, though, is the thinning out and consolidating of corporate positions, as slack time is reduced.  In all, higher productivity is good, but it must be accompanied by other positive measures to be meaningful.

One area of prosperity has been fantastic – stock performance.  As of late yesterday morning, the Dow Jones Industrial Average was up 5.69% this year and Nasdaq has risen 14.12%.  Both have seen frequent all-time highs, with a large milestone for the former, about which Paul Krugman asked “What Does the Dow Hitting 40,000 Tell Us?” (The New York Times, May 20^th).  He concluded that while “by the numbers, the economy looks very good,” with 27 straight months of sub-4% joblessness, inflation “way down from its peak in 2022,” and “U.S. economic growth over the past four years… much faster than in comparable major wealthy nations,” stock prices are not “a good measure of economic success.”  There is still no denying, though, that they are “hitting new highs.”

That brings us to inflation in particular.  First, Krugman in the Times again, with “Remember that news report about low gas prices?  Neither do I.” (May 7^th).  The author presented several graphs intended to debunk common incorrect assertions.  The first showed “rates of wage growth” of the bottom and top income quartiles, showing that for every month from 2020 to 2023 the bottom quarter’s average percentage increases had been higher.  The next compared “wages and inflation” for almost the same period, with the latter, different for every income cohort, being outstripped by wage growth for “bottom,” “middle,” and “top” groups, the largest difference in the lowest.  His second-to-last chart was a stunning look at “TV mentions vs. nominal gas price,” with a consistently close relationship between higher levels of both.  That showed how easy it is for distorted price perceptions to be facilitated, even if unintentionally.

On May 15^th a key measure came in, reported on that same day in “Inflation Moderated Slightly in April, Offering Some Relief for Consumers” (Ben Casselman, The New York Times).  The Consumer Price Index edged down from March’s 3.5% year-over-year reading to 3.4%, as “the “core” index – which strips out volatile food and fuel prices… – rose 3.6 percent last month, down from 3.8 percent a month earlier.”  Later that same day, also in the Times, Krugman returned with “Is Disinflation Back on Track?”  He concluded, considering business price-change expectations, that “underlying annual inflation is probably around 2.5 percent, maybe even less,” but said “even if I’m right, it’s going to take at least a fer more months of good inflation news before this happy reality sinks in.”

Yet, consistent with the first article mentioned in this post, not all recent economic news is good.  I end with “Rent Is Harder to Handle and Inflation Is a Burden, a Fed Financial Survey Finds” (Jeanna Smialek, The New York Times, May 21^st).  “American households struggled to cover some day-to-day expenses in 2023, including rent, and many remained glum about inflation even as price increases slowed.”  However, “households feel good about their job and wage growth prospects and are saving for retirements.”  On inflation, though, “65 percent of adults said that price changes had made their financial situations worse,” as a depressing “ninety-six percent of people making less than $25,000 said that their situations had been made worse.”  Overall, “the report underscores that even though inflation is cooling, it remains a major concern for many Americans, one that may be a big enough worry to take the shine away from an economy that is growing quickly and adding jobs.”

That’s the problem.  Lower current inflation does not mean prices are returning to even 2022 levels.  They are higher, and people are feeling it.  That is the reason why so many Americans say the economy is going poorly.  That is also why as small as inflation seems to be, it is still important that we bring it down.  I expect we will, but if we don’t, we can expect some real social problems – and a presidential election result many of us do not want.

Even Beyond Tesla’s Self-Inflicted Problems, EVs are Slowing Down

Electric vehicles, the sales of which grew 52% in America last year, are not continuing that.  I won’t deal with what’s been happening with Tesla, because I don’t know any more than anyone else what CEO Elon Musk is trying to do, and why they would release the Cybertruck with more bugs than a Kolkata food stand.  Individual companies will come and go no matter what, and Tesla, hardly assured of continuing to lead United States sales, is not the industry.

There has been a gap for a while, as “What electric vehicle shoppers want isn’t what’s for sale, and it’s hurting sales:  poll” (Medora Lee, USA Today, April 3^rd).  I wondered, when I got a non-plug-in hybrid as a rental two years or so ago and enjoyed full convenience along with 60 miles per gallon, why that wasn’t the direction companies wanted to follow.  Instead, in this piece, an Edmunds study said potential buyers wanted “lower prices” (which have improved slightly in the weeks since), “cars and SUVs, not electric pickups” with the latter getting buyer interest in EVs far lower than for liquid fuel ones, and “EVs from the most trusted brands,” particularly Toyota and Honda, which combined at article time for one model selling new in America.  However, as a result, “the dearth of EVs for sale that EV shoppers want has pushed them to hybrids,” also cheaper “and ease people’s range and charger anxieties.”

A third well-established company has discovered that, as “Ford Slows Its Push Into Electric Vehicles” (Neal E. Boudette, The New York Times, April 4^th).  It has “delayed the production of at least two new electric cars and said it would pivot to making more hybrids.”  That will mean production of its “large electric S.U.V.” will be put off two years at at least one plant.  It may indeed be doing the right thing, as “Hybrid vehicle sales revving up as EV demand sputters” (Brock Dumas, Fox Business, April 11^th); a Kelley Blue Book editor called 2024’s “hottest auto trend… “Hybrids – a lot more hybrids.””  Another form of discomfort hybrids do not cause is “time anxiety,” with “parents of young children wondering how they would have to find an extra 45 minutes in their day for recharging their EV.”

Reaction to the Environmental Protection Agency’s March mandate for automakers to produce higher shares of EVs starting in 2027 has come in, and it’s not positive.  The Wall Street Journal editorial response was titled “Biden’s EV Mandate Blows its Cover.”  The Washington Post’s was “The best way to get everyone into electric cars? Hint: It’s not a mandate.”  A piece in USA Today was “If you like your car, good luck keeping it. Biden's EV mandate drives change people don't want.”  And national columnist George Will, channeling an old Ford quip about providing vehicles only black, called his writing “Biden’s impossible dream:  Any car you want, as long as it’s an EV.”  Will named several of the points I have made in this blog, and some more:  EV battery production requires huge amounts of mining including new facilities, there will be more large truck trips since battery weight reduces load capacities, we can expect extra roadway damage and additional “particulate-matter pollution” from that and necessary special tires, there will be massive electricity consumption, EVs have extra problems in especially cold or hot weather, and currently they have high rates of mechanical problems. 

Even beyond bipartisan issue-raising is concern on the left, as shown in a view “Inside the Climate Protests Hell-Bent on Stopping Tesla” (Morgan Meaker, Wired.com, May 7^th).  Demonstrators have been protesting outside a German Tesla “gigafactory,” calling company operations “”green capitalism,” a plot by companies to appear environmentally friendly.”  The activists have cited excessive mining, “the industry’s disruption of communities in the global south,” “unsafe working conditions,” and not only “using up local water supplies but also the potential that the company will contaminate them.”  If EV manufacturers cannot count on environmentalists’ support, they may end up with no group of core adherents at all.

A recent news item concerned a new set of import duties, as described in, among other places, “Biden announces 100% tariff on Chinese-made electric vehicles” (The Guardian, May 14^th).  There are plenty of things wrong with tariffs, and one here is to raise the prices of the cheapest EVs, further discouraging people from making that transition.  Per “Don’t Slam the Door on Expensive Chinese Electric Vehicles” (Gernot Wagner and Conor Walsh, The New York Times, May 15^th), “a recent survey” determined that 83% of US EV “drivers” were in the top half of national household income, with 57% with over $100,000.  Those numbers will not drop much soon.

Are electric vehicles moving in the right direction?  Not now.  It would be wrong to say they are in reverse – sales are still increasing, but they’re heading for a stall.  Do we want to almost require them within a handful of years?  It’s hard to say yes.  We won’t be ready, and the chances are increasing that we won’t during our lifetimes. 

Artificial Intelligence, Present Tense: Modest Revenues and Serious Problems

There is a massive amount of AI material online.  Almost all of it, though, deals with capabilities in development, business deals, stock performance, organizational changes, and forecasts.

How is it doing now?  I don’t know, and you don’t either.  It moves too quickly, and most of the information is proprietary and unassembled.  But if we can go back four months, to “10 Companies With Largest AI Revenues:  Success Cases from OpenAI, Anthropic & More” (Tim Keary, Technopedia, January 17^th), we get some insight.  In the first paragraph it relates how “the global AI market was valued at $196.63 billion in 2023,” close to Statistica’s October 2023 $207.9 billion determination.  However, per an unsourced answer to a Google search, “the “market size” is made up of the total number of potential buyers of a product or service within a given market, and the total revenue that these sales may generate.”  As Keary told us, though, that’s not the same as what’s actually being sold.  In his section titled “10 Leading Companies in Terms of AI Revenue,” he named OpenAI, Anthropic, Microsoft, Nvidia, Hugging Face, Stability AI, Perplexity AI, IBM, Google, and Salesforce, giving annual sales figures for each.  After taking one-quarter of those from the last two, which were not broken down into AI and other offerings, I got a total of $29.7 billion, meaning that something over 15% of the market is producing revenue.  By comparison, a recent Wikipedia list of largest companies by annual sales – not entire industries – showed the 50th-largest one with over $157 billion.

Accordingly, “A.I. Start-Ups Face a Rough Financial Reality Check” (Cade Metz, Karen Weise, and Tripp Mickle, The New York Times, April 29^th).  The main point here was that “the A.I. revolution… is going to come with a very big price tag.  And the tech companies that have bet their futures on it are scrambling to figure out how to close the gap between those expenses and the profits they hope to make somewhere down the line.”  Although “investors have poured $330 billion into about 26,000 A.I. and machine-learning start-ups over the past three years,” they may not maintain that pace.  Indeed, “Wall Street’s Patience for a Costly A.I. Arms Race Is Waning” (Andrew Ross Sorkin et al., New York Times DealBook Newsletter, April 25^th). 

Also, “A.I. is running out of power” (Andrew Ross Sorkin et al., New York Times DealBook Newsletter, April 18^th).  As a result, “tech executives are increasingly warning that electricity supplies need a boost,” with a notice that “there’s “not enough energy right now” to power new generative A. I. services,” and because of that the technology “could also spur a geographic shift for tech” to areas with more of it to spare.  With that, it is fair to ask “How Bad is A.I. for the Climate?” (the same source on May 6^th), as it “risks throwing companies’ climate pledges off track” since “the A.I. revolution will largely run on fossil fuels.”

Another copyright infringement lawsuit materialized last week, as “8 Daily Newspapers Sue OpenAI and Microsoft Over A.I.” (Katie Robertson, The New York Times, April 30^th).  These papers, including the New York Post and the Chicago Tribune, all owned by one company, claimed that “chatbots regularly surfaced the entire text of articles behind subscription paywalls for users and often did not prominently link back to the source,” and erroneously named the papers as sources of things they did not produce.

Although many predictions show massive increases in profits as well as capabilities, “CEOs make the message clear on AI’s big payoff:  Be patient” (Lloyd Lee, Business Insider, April 25^th).  To prevent AI-company stock prices from reverting to whence they came, when “many (companies) have yet to see any significant returns on their investment,” “CEOs hope to re-assure shareholders that this is to be expected.”  Venture capitalists have not always been known for patience, so even if the titanic success so often forecast for AI materializes, without every firm running out of power, data, chips, perceived accuracy, or legal acceptance, many may fail due to running out of money. 

We don’t know where or how far artificial intelligence is going, but it hasn’t done much yet.  From here, there are no guarantees – and plenty of doubts.

The Jobs Report Dips from Great to Good – AJSN Reflects Only Half of Its Seasonally Lower Latent Demand

This morning’s Bureau of Labor Statistics Employment Situation Summary may have seemed disappointing, as for once the number of net new nonfarm payroll positions fell short of public estimates.  But that was not the real reason.  The ones I saw for April, the month of the report, ranged from 223,000 to 250,000 – it came in at 175,000.  Otherwise, seasonally adjusted unemployment was up 0.1% to 3.9% and the unadjusted version was down, as is typical from March to April, 0.4% to 3.5%.  Unadjusted employment rose 234,000 to 161,590,000, with such unemployed down more than 700,000 to 5,894,000.  There were 95,080,000 people claiming no interest in work, up 266,000.  The counts of people jobless for 12 months or more and those working part-time for economic reasons, or keeping those arrangements while looking thus far unsuccessfully for full-time ones, both worsened, up from 1.2 million to 1.3 million and from 4.3 million to 4.5 million.  The two measures showing how common it is for Americans to be working or that plus those counted as jobless, the employment-population ratio and the labor force participation rate, were narrowly mixed, with the former down 0.1% to 60.2% and the latter holding at 62.7%.  Private nonfarm payroll hourly earnings increased 6 cents to $34.75, not keeping up with inflation.

The American Job Shortage Number or AJSN, the metric showing how many additional positions could be quickly filled if all knew that getting one would be little more than another daily errand, improved with a 300,000 drop from March as follows:

The number of unemployed shaved over 600,000, but increases in those discouraged and those not looking for a year or more offset more than half of that.  The share of the AJSN from those officially jobless fell to 33.1%, meaning that more than two-thirds of people taking these opportunities and not working now would have other statuses.  Compared with a year before, the AJSN gained about 650,000, more than that from a higher number of unemployed.

We have areas of concern here.  Although the number of new jobs keeps on exceeding our population increases, joblessness is at the top of its nine-month range, with several other statistics worse than in March.  If they degrade again, we may need to accept that we are not in the top employment category anymore.  In the meantime, though, the turtle took a small step forward.

Four More Facets of Working from Home

The usual news on this issue has settled down.  The pendulum which swings back and forth between office and remote labor has continued to move toward the former, with companies not in the news as much for telling their employees they can choose between turning up onsite or losing their jobs.  There have been some items on this topic, though, over the past ten weeks.

First was “The ‘work-from-home weekend’ may be on its way out” (Lakshmi Varanasi, Business Insider, February 16^th).  The main example was Deutsche Bank, which now “won’t let employees work from home on both Fridays and Mondays.”  Decades ago, at AT&T, those were the most common days for that, which when combined with generally unconscious bosses and worker measures taken to impede contact, meant too many people were in effect working only Tuesday through Thursday.  Ostensibly, “the move was made to even out worker attendance across the week,” but as it is easy to try to solve attendance and productivity problems with policy, it was probably more than that.

Second, “The ZIP Code Shift:  Why Many Americans No Longer Live Where They Work” (Emma Goldberg, The New York Times, March 4^th).  Per then-breaking research, “many Americans now live roughly twice as far from their offices as they did prepandemic,” not across the country, but choosing couple-hour commutes, which they do less than five days a week and rarely if they are among the still 12% of workers exclusively remote.  That is bad news for those with businesses in downtown areas hoping that with Covid’s fading they would recover to where they were in the late 2010s – but can be a good choice for people wanting to live in another city for housing or personal reasons. 

Does anyone wonder why there has been no great remote-worker movement to isolated rural areas and small towns?  It may be “The hidden price of leaving a big city” (Aki Ito, Business Insider, April 15^th).  While “it may improve your quality of life,” you may need “good luck if you lose your job.”  As well, some making that choice have ended up “pining for the things they left behind, from culinary excellence to cultural diversity.”  Yet, although the author said “every week it seems like I see a new story about some former San Franciscan or New Yorker regretting their decision to leave,” population has been dropping in those metropolitan areas along with Los Angeles and Seattle.  It is important if not always determinative to consider how suitable new locations would be for continuing careers.

Finally, one office disadvantage you may not have considered.  In “Google’s worker firings show that the office actually isn’t a place to be yourself” (Business Insider, April 20^th), author Tim Paradis told us that “Google fired more than two dozen workers after they took part in sit-ins at offices in California and New York.”  For about ten years there has been a trend toward encouraging employees to “bring your whole self to work,” probably strengthened by blurred home-office borders, recreation as part of the workday, and Generation Z wishes.  However, it is still dangerous to talk about politics, let alone participate in it at the office, and other subjects would also invite unwanted controversy.  The concern here seems quite like something I read almost 50 years ago, when jobseekers were cautioned that management will only indulge talking about “real or imagined personal problems” up to a point, that “you can get fired,” which meant “so much” to the idea of coworkers being equivalent to a family. 

The issue of whether to work from an office is still important.  Expect more here – especially if the pendulum shows signs of stopping or reversing.

Three Employee Problems and One Big Employer Concern – Different but Similar

With new technology, follow-on effects from the pandemic, strong employment, and a new generation – Z – becoming established in jobs, it is no surprise that concerns around workers and their managements are evolving.  Except for those centering around putting in less effort, having multiple jobs, and the pendulum of office work to home work and back, what issues have reached the press?

For one, “Employees are demanding workplace resets” (Brock Dumas, Fox Business, August 31^st).  The piece covered a report from Edelman, which once a year issues the Edelman Trust Barometer.  The statement revealed that, of 7,000 employee recipients, 72% “said it is more important than ever that employers rethink what work means to employees,” with “career advancement,” “personal empowerment,” and “societal impact” each named by 71% to 83% of respondents.  While the first one is old, the second has not been stated as often as felt and the third has recently risen dramatically.  Sixty-one percent said they were “more likely to work for an organization where the CEO speaks publicly about the controversial issues they care about.”  In all, though, “workers across the board have expressed far greater trust in their employers than any other institution the survey asks about, which are business, non-government organizations, the media and the government.”

Yet there are other problems.  Per “Most people have an unhealthy relationship with work, study finds: ‘Huge opportunity’” (Erica Lamberg, Fox Business, September 21^st).  The surveyor this time was HP Inc, with “the first HP Work Relationship Index, a comprehensive study that explores employees’ relations with work around the globe.”  Only 27% of “knowledge workers” claimed a “healthy relationship with work.”  Lamberg recommended employees talk about it with their bosses, with important principles to “walk before you run” or expect less at the start, “it’s all about presentation” or framing intentions as “here is how you can get the very best quality of work out of me,” and “know your worth” by documenting accomplishments. 

A long-standing but timely one returns in “Almost half of Americans see automation replacing their jobs” (Rich Miller, Benefit News, August 21^st).  American Staffing Association found that in a survey, a share which almost doubled since a similar 2017 effort, and that “some three-quarters of those polled expect increased use of automation and artificial intelligence to lead to higher joblessness.”  With 2024 thus far a down year for AI, it would be worthwhile to see what a similar study would tell us now.

On the employers’ side, one concern affecting all of us has evolved.  On December 11^th, we saw that “Corporate America Is Testing the Limits of Its Pricing Power” (Jason Karaian, Jeanna Smialek, and Joe Rennison, The New York Times, December 11^th).  Talking first about 2022 and then about late 2023, “margins eased somewhat last year, but have recently recovered to levels that would have set records before the pandemic,” and “average margins in nearly every sector in the S&P 500 are running near or above 10-year highs, according to Goldman Sachs.”  A chart titled “Quarterly net profit margin of S&P 500 companies,” covering 2010 to 2023, showed, except for an early-pandemic dip, a choppy rise from just over 8% to 12%.  Further article findings were “there’s a focus on margins over market share” and “that’s a shift from post-2009 practice,” “companies learned they can charge more than they thought… but price sensitivity may return,” and “the ability to raise prices – or keep them high – may not last.”

In the four months since, inflation concerns have become more vocal, so overall demand may yet return to being more elastic.  Yet some ways of raising profit are getting bad press, at least from Christopher Beam, whose “Welcome to Pricing Hell” came out in Atlantic in April.  The author’s concern was about “the ubiquitous rise of add-on fees and personalized pricing,” which “has turned buying stuff into a game you can’t win.”  He started discussing how Wendy’s’ plan for “dynamic pricing” faced strong negative reactions, as have new fees, subscription plans, unbundled features, and the use of personal data to determine product cost.  Variable rates, common before the 1800s invention of the price tag, may have started with airplane tickets, spread to “airline-adjacent industries like hotels and cruise lines,” and proliferated from there.  In the 2010s, more and more industries added fees often unrevealed until just before payment time.  At the origin point, extra charges have reached the point where “the airlines raked in $33 billion from baggage fees, and even more from other ancillary fees like seat selection, meals, and in-flight Wi-Fi,” such tariffs becoming “a major driver of airline profits.”  Personal data often reaches retailers through apps, which can access purchase history, financial information, and much more, which “can be fed into machine-learning algorithms to generate a portrait of you and your willingness to pay.” 

Most of my fellow economists think personal pricing is fine.  They do not, however, like belatedly disclosed fees.  As the last article revealed, “even the CATO Institute, the libertarian think tank that never saw a regulation it liked, acknowledges that consumers “shouldn’t be charged for products without their consent, and businesses should disclose mandatory fees before purchases are made.””  If that means sooner than the Place Order page, that’s good enough for me.  There will be much more personal pricing, though – it is up to us to determine how to facilitate or impede it, as we wish.  In work situations as well as with what we buy, there are countermeasures.  Even in these times, we still have choices.

Artificial Intelligence: Twelve Days of Problems

Only two weeks since my last AI post, but a lot has happened – and it isn’t good.

I don’t deal on speculation and rumors any more than future-only “progress,” so you won’t read here about the growing set of people thinking that Nvidia stock is heading for a steep decline – as with AI’s projected, expected, touted world-beating capabilities and applications, we’ll deal with it when it happens.  But here are harder concerns.

In “The age of AI BS” (Business Insider, March 27^th), Emily Stewart told us about “”AI washing,” or companies giving off a false impression that they’re using AI so they can amp up investors,” which has precipitated formal charges and legal settlements, as well as ChatGPT’s marketing campaign being mainly “to raise money, attract talent, and compete in the hypercompetitive tech industry,” a situation where “overselling has become a near-constant of the AI landscape,” and “it’s not super clear what the present capabilities of the technology even are, let alone what they might be in the future, so making bold, concrete claims about the way it’s going to affect society seems presumptuous.”  A “senior industry analyst” said that “a lot of these companies are not yet showcasing exactly what type of revenue they’re getting from AI yet because it’s still so small.” Stewart ended with “anyone who tells you they know exactly what is going on in AI and where it’s headed is lying.”

In response to a good and timely question, Zvi Mowshowitz informed us, in the New York Times on March 28^th, “How A.I. Chatbots Become Political.”  Although “our A.I. systems are still largely inscrutable black boxes” according to political-view assessment tests, most lean liberal and to some extent libertarian.  The biases may have been introduced during “fine tuning,” when technicians adjust outcomes, and from earlier developments, “because models learn from correlations and biases in training data, overrepresenting the statistically most likely results.”  There are now three versions of one major product, LeftWingGPT and RightWingGPT, which were evaluated as matching their names, and DepolarizingGPT, which still skewed slightly to the libertarian left.  A cause for concern, as “we may have individually customized A.I.’s telling us what we want to hear,” which may not end up being constructive.  This area, still, looks under control, but all should be aware of the biases these tools all carry.

Could it be, already, that “A.I.-Generated Garbage Is Polluting Our Culture” (Erik Hoel, The New York Times, March 31^st)?  In places, anyway.  One the author documented is recent academic peer reviews, which showed expressions known to be “the favorite buzzwords of modern large language models like ChatGPT” 10 to 34 times as often as in 2022.  Another example is nonsensical and uncorrected videos for children.  That sort of thing could cause a state “when future A.I.’s are trained, the previous A.I. output will leak into the training set, leading to a future of copies of copies of copies, as content (becomes) more stereotypical and predictable,” called “model collapse.”

Moving on, “It looks like it could be the end of the AI hype cycle” (Hasan Chowdhury, Business Insider, April 3^rd).  Not yet, though with the amount of accumulating doubt that may happen soon.  Along with sky-high importance assessments from Bill Gates and Elon Musk, Gary Marcus, who testified to the Senate on the technology, “predicted the generative AI bubble could burst within the next 12 months,” noting that “the industry is spending much more money than it’s raking in,” a great deal given that, per Crunchbase, “generative AI and AI-related startups raised almost $50 billion last year.”  Overall, “the verdict is still out on whether the companies behind foundation AI models dependent on expensive chips can turn their products into viable, profitable businesses.”

Back to a problem mentioned above, “Big Tech needs to get creative as it runs out of data to train its AI models.  Here are some of its wildest solutions” (Lakshmi Varanasi, Business Insider, April 7^th).  If, “according to Epoch, an AI research institute,” less than three years from now “all the high-quality data could be exhausted.”  Companies will need to do something, which could include “tapping consumer data available in Google Docs, Sheets, and Slides” which Google has already contemplated; buying an entire large publisher, such as Simon & Schuster, for its copyrighted information; “generating synthetic data,” created by AI modules themselves, using speech recognition to tap YouTube videos; and incorporating pictures from Photobucket, which hosted those from former large social media sites Myspace and Friendster.  In the meantime, we saw “How Tech Giants Cut Corners to Harvest Data for A.I.” (Cade Metz et al., The New York Times, April 6^th).  One way was the same YouTube idea, which was input into GPT-4 – this piece also mentioned the solutions Varanasi revealed. 

On the positive AI side, all I have seen these past two weeks is incomplete and future-bound.  For its actual advancement, they were a loser for artificial intelligence.  Will it get better, or worse?  I will keep you informed.