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.

This Morning’s Report: Good Jobs News for Almost Everyone

 

The Bureau of Labor Statistics Employment Situation Summary came out of embargo 17 minutes before I wrote this sentence.  From a national economic perspective It was everything we could have hoped for.

Net new nonfarm payroll employment once again blew away its published estimates, reaching 303,000 instead of 200,000.  Seasonally adjusted and unadjusted unemployment fell 0.1% and 0.3% respectively, to get to 3.8% and 3.9%.  The total jobless count was off 100,000 to 6.4 million, of which those out for 12 months or longer remained at 1,200,000.  The unadjusted number of people working increased over a million, to 161,356,000.  There were 94,814,000 claiming no interest in a job, down 66,000.  Those working part-time for economic reasons, or keeping such positions while looking unsuccessfully for full-time ones, lost 100,000 to 4.3 million.  The two measures of how common it is for people to be in jobs or one step away, the employment-population ratio and the labor force participation rate, each improved 0.2%, realizing 60.3% and 62.7%.  Average private nonfarm payroll hourly wages rose more than inflation, 12 cents per hour, to $34.69. 

The American Joh Shortage Number or AJSN reversed course from last month, falling over 700,000 as follows:

The largest change sources this month were the unemployed, people not looking for a year or more, and those discouraged, contributing 329,000, 264,000, and 125,000.  Compared with a year before, the AJSN gained 462,000, more than that from higher official joblessness.  The share of the AJSN from that was 36.4%, down 0.4% from February.

Except for the second-to-last line, do you see anything bad about the above?  I don’t, except that some will focus on the lowered probability of interest rate cuts soon.  That is understandable, but let us hope that stocks will be more affected by the formidable strength and robustness of our economy.  These additional workers will spend.  Again we added vastly more jobs than our population increase could absorb, added people to the labor force, continued pay increases at a clearly justified level, and reduced the count of those wanting to upgrade to full-time.  Unemployment is still higher than it was a year ago, per the report “in a narrow range of 3.7 percent to 3.9 percent since August 2023,” and the 1.2 million still looking after a year or more could improve.  But those are distractions, and at least interest rates, where they are, appear fully justified.  The turtle stretched and took a large step forward. 

Artificial Intelligence Today: Combating Problems, and Drawing on the Morrow

As market capitalization surges and the press tells us about more and more noncurrent things, what is happening with AI now?  Mostly it is causing trouble. 

In “The AI Culture Wars Are Just Getting Started” (Will Knight, Wired, February 29^th), we got a recap on and views of difficulties in the front of the news several weeks ago.  As I documented in my last AI post, Google and Alphabet’s products were showing white male historical figures as female and darker-skinned.  Both CEOs apologized, Alphabet’s internally and Google’s publicly, and Knight suggested one mishap was because “Google rushed Gemini,” but a Mozilla fellow held “that efforts to fix bias in AI systems have tended to be Band-Aids rather than deep systemic solutions,” which makes sense, as fully retraining the products would require great masses of data and money.  Whether either Google or Alphabet were trying to make ideological statements is irrelevant now – they have huge business problems many customers will not tolerate.

“Silicon dreamin’,” in the March 2^nd Economist, was about the situation where “AI models make stuff up,” and asked “Can researchers limit hallucinations without curtailing AI’s power?.”  Such responses can be “confident, coherent, and just plain wrong,” so “cannot be trusted.”  Unfortunately, “the same abilities that allow models to hallucinate are also what make them so useful,” and “fine-tuning” them may make nonsense answers more common.  Overall, “any successful real-world deployment of these models will probably require training humans how to use and view AI models as much as it will require training the models themselves.”

Another way artificial intelligence may be making enemies come forward is in “A New Surge in Power Use Is Threatening U.S. Climate Goals” (Brad Plumer and Nadja Popovich, The New York Times, March 14^th).  With subtitle “a boom in data centers and factories is straining electric grids and propping up fossil fuels,” the piece documented that demand for electricity grew steeply from 1989 to 2007, was mainly level between 2007 and 2022, but is now forecast by companies selling it to trend upwards through 2033.  The main causes are electric vehicles, more manufacturing, and “a frenzied expansion of data centers” with “the rise of artificial intelligence… poised to accelerate that trend.”  While renewable energy sources can cover much of the increase, they cannot reasonably be expected to cover all of it.

On the user side, we were asked to “Keep these tips in mind to avoid being duped by AI-generated deepfakes” (Fox News, March 21^st).  Such things of ever higher quality have been in the news for months, and “video and image generators like DALL-E, Midjourney and OpenAI’s Sora make it easy for people without any technical skills to create deepfakes – just type a request and the system spits it out.”  Such things “may seem harmless,” “but they can be used to carry out scams and identity theft or propaganda and election manipulation.”  Fewer of these now have “obvious errors, like hands with six fingers or eyeglasses that have differently shaped lenses” or “unnatural blinking patterns among people in deepfake videos.”  Advice here was “looking closely at the edges of the face” for skin tone inconsistent with elsewhere on the person, “lip movements” not agreeing with audio, unrealistic teeth, and “context,” showing “a public figure doing something that seems “exaggerated, unrealistic or not in character,” or not corroborated by “legitimate sources.”  Generally, we need to be more skeptical about photos and video clips of all kinds – that will happen remarkably quickly.  In the meantime, though, “Fretting About Election-Year Deep Fakes, States Roll Out New Rules for A.I. Content” (Neil Vigdor, The New York Times, March 26^th), such as advertisers being required to disclose AI-generated content.  There are now, per Voting Rights Lab, “over 100 bills in 40 state legislatures.”

Beyond these and other troubles, how much AI is out there in corporate settings?  In “Meet your new copilot” (The Economist, March 2^nd), we learned that, despite massive company valuations, “big tech’s sales of AI software remain small.”  Specifically, “in the past year AI has accounted for only about a fifth of the growth in revenues at Azure, Microsoft’s cloud-computing division, and related services.”  As well, “Alphabet and Amazon do not reveal their AI-related sales, but analysts suspect they are lower than those of Microsoft.”  Two different consulting firms were not taken with current usage, as one said, “it will take at least two years to “move beyond the hype,” and another determined that “adoption of AI “has not necessarily translated into higher levels of productivity – yet.””

Per Oxford Languages, “morrow” is an “archaic” word meaning tomorrow, “the time following an event,” or “the near future.”  I have seen “drawing on the morrow” used as recently as the last half-century to mean getting a questionably justified advance.  I propose we use it that way for artificial intelligence progress.  AI may turn out to be a gigantically important business product, but it isn’t yet.  No matter how much its producers’ stock is worth, we can’t give AI credit for what it may or may not accomplish someday.  That would be drawing on the morrow.  That’s not how we want to deal with reality.

Five Weeks of Cars: Autonomous, Electric, Teledriven, and a Governmental Push for Change

The article flow on automobiles is getting less concentrated.  Instead of the late-2010’s emphasis on driverless vehicles and the early 2020’s on electric ones, we’re seeing variety, and at least one sort-of-new concept.  What’s turned up recently?

As if it wasn’t sputtering enough, we found out from Jordyn Grzelewski in Tech Brew on February 16^th that “AV sector hits latest speed bump with Waymo incident in Phoenix.”  On December 11^th, a Waymo robotaxi “struck a pickup truck as it was being towed “across a center turn lane and a traffic lane,”” followed by another Waymo automated taxi doing the same thing.  The company described it as an “unusual scenario,” due to their algorithms misfiguring which way the truck on the hook was likely to go.  Another situation where self-driving vehicles need to be programmed to deal with situations easy for humans to comprehend. 

In Fox Business on February 26^th, Sunny Tsai told us how “Teledriving company Vay brings new transportation option to streets of Las Vegas.”  It uses “remote drivers,” who, from their workstations, in this case deliver vehicles to renters and retrieve them the same way afterwards.  It clearly could be used for other propositions, such as taking over from automatic operation when driverless cars or trucks get into predicaments.  This technology could find its niche, which could end up being something vastly different from what Vay is doing with it.

On February 27^th, we looked on as “Apple Kills Its Electric Car Project” (Brian X, Chen, The New York Times.)  “A secretive product that had been in the works for nearly a decade,” it involved another category as well, as the company had “plans to release an electric car with self-driving abilities.”  As was the case in the automotive industry a century ago, there is certain to be a great winnowing of involved companies – it seemed surprising, though, to happen to a player this large, which had been working on its product since before self-driving seemed inevitable.  Indeed, “the cancellation is a rare move by Apple, which typically doesn’t shelve such public and high-profile projects.”  On the rationale, unfortunately, “Apple declined to comment.”  If something leaks out, we may learn more about EV’s true robustness.

Despite the problems described in the first piece here, we learned that “California officials give Waymo the green light to expand robotaxis” (Sarah Al-Arshani, USA Today, March 3^rd).  It will now be allowed to have them in Los Angeles County and San Mateo County, expanding from San Francisco.  There is still controversy, though, as several local legislators have expressed reservations, describing the decision as “irresponsible” and “dangerous.”

Given competition across borders, we want to learn “How China Is Churning Out EVs Faster Than Everyone Else” (Selina Cheng, The Wall Street Journal, March 4^th).  Per the author, “Chinese automakers are around 30% quicker in development than legacy manufacturers, industry executives say, largely because they have upended global practices built around decades of making complex combustion-engine cars.  They work on many stages of development at once.  They are willing to substitute traditional suppliers for smaller, faster ones.  They run more virtual tests instead of time-consuming mechanical ones.  And they are redefining when a car is ready to sell on the market.”  That sounds good, but is it all true?  Are they getting advantages from cutting corners in ways that business laws and practices would not allow elsewhere?  Is it possible that they are putting forward massive amounts of scale and effort, such as multiple identical factories, that would be capital-prohibitive in the West?  Could they be substantially losing money or getting huge subsidies?  We must be able to answer these and related questions before we can give them credit in context.

The news Wednesday, in the New York Times, was headlined “Biden Administration Announces Rules Aimed at Phasing Out Gas Cars” (Coral Davenport).  Well, according to the text, not quite.  They want to “ensure that the majority of new passenger cars and light trucks sold in the United States are all-electric or hybrids by 2032.”  The piece acknowledged that only 7.6% of American car sales were electric (not clear whether that included hybrids), and the regulation’s target, just eight years off, was 56% for all-electrics and another 16% for hybrids.  These “rules are expected to face an immediate legal challenge by a coalition of fossil fuel companies and Republican attorneys general,” could be hampered by the need for over 1.8 million additional “public charging stations,” and was initiated when “growth in sales of electric vehicles is slowing.”  This edict is almost certain to be cancelled or postponed – we’ll get a better view of which it will be, and what else happens with vehicles, during this critical year.

Jobs Report: New Ones Drifting Away from Other Outcomes; AJSN Shows Latent Demand 100,000 Lower at 17.0 Million

I clicked on the Bureau of Labor Statistics Employment Situation Summary with February’s data, knowing only that it showed another flashy nonfarm payroll employment result, 275,000 net new positions on estimates of 175,000 and 200,000.  Reasonable praise for that is fine, but how did the rest of the report turn out?

Seasonally adjusted unemployment gained a substantial 0.2%, with the unadjusted version up 0.1%, to 3.9% and 4.2% respectively.  The adjusted count of jobless soared 400,000 to 6.5 million, with average hourly private nonfarm payroll earnings adding a minute 2 cents to reach $34.57.  Other results stayed even or were varying amounts of better.  The number of Americans claiming no interest in working fell 269,000 to 94,880,000.  Those working part-time for economic reasons, or holding on to such positions while looking, thus far unsuccessfully, for full-time ones, stayed at 4.4 million.  The labor force participation rate remained 62.5% but the employment-population ratio improved 0.1%, down to 60.1%.  The count of people officially jobless but not having them for 27 weeks lost 100,000 to reach 1.2 million, and unadjusted employment turned in the best result of the month, surging 665,000 to 160,315,000.

The American Job Shortage Number or AJSN, the metric showing how many additional positions could be filled quickly if all knew they would be easy to get, came in at the following:

 

The share of the AJSN from people officially unemployed gained 1.2% on rising joblessness to 36.8%. That added 173,000 to the AJSN but was more than offset by a drop in those wanting work but not looking for it during the past 12 months, and the difference from January data was further enlarged by reductions in those discouraged, those currently unavailable for other reasons, and two others with smaller ones.  Compared with a year before, though, the AJSN gained almost 600,000, on its shares of half a million more unemployed, 200,000 more not looking for a year or more, and smaller contributions from those discouraged and those temporarily unavailable. 

Some improvements, some worsenings, some break-evens.  I was glad to see the count of people working getting better along with the almost monthly large jobs gain, which it hasn’t always, and the reduction in those claiming no interest.  But with that 3.9% we aren’t burning any barns.  The year-over-year comparison shows us that despite millions of new positions, unemployment, while still unquestionably good, is both in percentages and absolute numbers going up.  It’s not enough to add positions if more are on benefits.  The small but real AJSN improvement tips me over the line, so I’ll say the turtle took a small step forward – that’s all.