Driverless Cars, Their Technology, and a Shift in Where They and It Are Going

In the area of autonomous vehicles, we’re now long after the crash – sort of like the time in “Wooden Ships,” where the two crews met and did things suitable for their post-apocalyptic times, including asking the plaintive question “Who won?”  Although the idea of driverless cars becoming the norm, replacing our current ones as comprehensively as they did to horses, seems headed for the next century at soonest, they are still making their mark.

As for general progress, we got “Super-smart cars” (The Economist, March 15^th).  Now, apparently, “China is leading the rollout of self-driving technology,” though as always what it is really doing and accomplishing is opaque.  Recently, in a huge city, “on a test drive… the car overtook a three-wheeled noodle cart, avoided scooters speeding the wrong way around the street and nailed a U-turn without intervention from humans.”  Yet the “driver did need to take control a few times during the twenty-minute ride.”  So, while “China’s robotaxi experiment is the world’s biggest,” they can still only “operate within approved areas,” so we’re not much further along technically than we were at last decade’s end.

What has been “The slow but steady advance of driverless vehicles” (Ian Rose, BBC.com, March 20^th)?  General Motors and Apple are both now out of that business, leaving Waymo as “the leading US player,” with driverless “taxis in Phoenix, San Francisco, Los Angeles, and Austin.”  Warm weather, for lack of snow and better battery performance, is important in a location now, and getting the cars out is a “slow process,” involving humans driving on certain streets “over and over again.”  But, despite not knowing just how many square miles of these four cities are open to them, this is certainly forward progress.

So agreed Thomas L. Friedman, New York Times columnist, on April 23^rd, in “How I Describe Myself Politically These Days.”  He saw, as an improvement on “lazily bashing billionaires,” a need for Democrats to enlarge “the pie of work by expanding new industries,” which was where robotaxis came in.  In the four places named in the previous paragraph, Waymo “is now racking up a whopping 200,000 paid rides a week.”  He was unconvinced about any Chinese supremacy, as “American technology is still more than competitive and can become even more dominant.”  He said he “can’t think of a more obvious moonshot project to spur advanced manufacturing in America generally than making it our goal to have Waymos or robo-Teslas – or any other brand of self-driving taxis that we can make – operating in every city in America.”  Friedman had much to say about how we could get that going quicker, by refunding tuition on degrees in related fields, allowing “would-be immigrants, especially from China and Russia, that if they have a degree or expertise in” related areas, to “stay as long as they want,” creating a federal “Department of Engineering and Innovation,” and tripling government self-driving vehicle research funding.  Worthy ideas.

On the problem side, we had “California residents enraged by driverless cars forced by regulators to make loud beeping noises” (Alexander Hall, Fox Business, June 1^st).  The issue is that they must “audibly reverse like delivery trucks,” so “they beep as they back out of charging spots, and beep as they reverse to navigate around each other. They beep in the morning as they head out to pick up early passengers, and beep late at night as they return to charge up."  Perhaps that can be cut down…

Friedman also called on Tesla’s CEO to “finally get the Tesla robotaxi that you have been promising for a decade out on the road.”  Less than two months later, we were able to read that “Tesla’s Robotaxi, Long Promised by Elon Musk, Joins a Crowded Field” (Jack Ewing, The New York Times, June 18^th).  It went into service that week in its hometown, though “the busy streets of Austin show that Tesla will face significant competition and other challenges,” such as needing “painstaking experimentation.”  Indeed, nine days later, per Sophia Compton in Fox Business, “Tesla’s newly launched robotaxi service experiences driving issues, traffic problems: report.”  Those included “braking suddenly, speeding, conducting improper drop-offs, entering the wrong lane and driving over a curb.”  How long will debugging take?

Continuing with that company, as reported in the New York Times on July 2^nd again by Jack Ewing, “Tesla Sales Fall as Elon Musk Focuses on Self-Driving Cars.”  Its “greater emphasis on autonomous driving instead of new models aimed at attracting car buyers” is understandably hurting current revenue, which with electric vehicle sales leveling off and even dropping is now anyway unassured to be favorable.  Rolling out the robotaxis, glitches and all, may turn out to be the best decision Tesla makes this decade.  They may need that, as “Tesla, Elon Musk sued by shareholders over Robotaxi claims” (Reuters, August 5^th).  The business and its leader are accused “of securities fraud for concealing the significant risk that the company’s self-driving vehicles, including the Robotaxi, were dangerous,” based on the Austin mishaps.  This case may have a long way to go.

What’s the big change here?  In the first quarter I wrote that autonomous technology was taking the cash by moving to primary use as an enhancement for human-driven cars.  Now the driverless side is resurgent.  That may go back the other way as soon as later this year, depending on how it performs in robotaxis, but it may not.  There is now more reason for optimism about driverless vehicles than there has been for years, maybe five or six of them.  Stay tuned – there may be more, even much more.

New Jobs Down, Unemployment Up, Other Factors Generally Worse Including AJSN Showing 17.8 Million Latent Demand

Did this morning’s Bureau of Labor Statistics Employment Situation Summary show tariffs, which have recently sunk in, affecting the job market?

The data showed that, for once, we gained fewer net new nonfarm payroll jobs than the published estimate I saw – instead of 115,000 it was 73,000.  Despite little seasonal difference, adjusted and unadjusted unemployment both worsened, 4.2% from 4.1% and 4.6% from 4.4%.  The seasonally adjusted jobless count rose 200,000 to 7.2 million, with those holding that status for 27 weeks or longer gaining the same amount to 1.8 million.  The two statistics showing how common it is for Americans to be working and officially unemployed, the labor force participation rate and the employment-population ratio, each dropped 0.1% to reach 62.2% and 59.6%.  Those working part-time for economic reasons, or keeping shorter-hours positions while looking unsuccessfully for longer-hours ones, jumped 200,000 for the second straight month, to 4.7 million.  Average private nonfarm payroll hourly wages were up 12 cents, slightly more than inflation, getting to $36.44.

The American Job Shortage Number or AJSN, the measure showing how many new positions could be quickly filled if all knew they would be easy and routine to get, gained over 300,000 to the following:

That increase was entirely explained by higher unemployment, with everything else, including a substantial fall in those discouraged and a sizable rise in the number of people wanting to work but not looking for it for a year or more, collectively almost breaking even.  The share of the AJSN from official joblessness was 39.6%, up 1.3%.  Compared with a year before, the AJSN was virtually unchanged at 30,000 lower, with a higher estimate of the number of American expatriates offset mostly by gains in the effect of those not looking for a year or more, unemployment, and not wanting jobs at all.

How did this month turn out?  Not well.  I’m unconcerned about gaining only 73,000 jobs – that’s about what our population can absorb, so it isn’t a loss.  It’s that unemployment and participation rates fell too much between the similar times of mid-June and mid-July.  Other results around the margins, such as on working part-time for economic reasons and still looking after half a year, point to a labor market worse than the front-line numbers show, not that those were impressive here either.  And yes, we must charge the tariffs for some of this poor showing.  On the good side, about 100,000 fewer stayed out of the labor force, and the odd situation with two marginal attachment categories seems to be over.  Yet if the latest tariff pronouncements materialize, we may well see similar worsenings in August.  In the meantime, I feel if anything charitable to declare that the turtle went nowhere.  

What Artificial Intelligence Has Been Succeeding At – II

Got three new articles possibly pertinent to this topic this week – two were negative or sort of, so will set them aside and add only the last to my pile.

According to Eric Revell in “Goldman Sachs announces firmwide launch of AI assistant” (Fox Business, June 23^rd), this generative AI tool, “tailored to meet the needs of workers in various specialties across the firm,” is intended to “positively impact” their “daily tasks.”  The piece doesn’t get any more specific than that, so we’ll hold off on praising it more.

Also too general, but firmer in the present tense, is “Salesforce boss reveals the stunning amount of work now handled by AI” (Aislinn Murphy, Fox Business, June 26^th).  Salesforce’s CEO “revealed the software company uses artificial intelligence (AI) technology to perform a good deal of its work,” in fact “30% to 50% of” it.  He said the company “has experienced roughly 93% accuracy in its own technology and its work with customers,” but he seems happy with that.  Can his workers catch that 7%, and, including that, how much time and money does the company save?

As I am sure applicants have suspected for a while, “Welcome to Your Job Interview.  Your Interviewer Is A.I.” (Natalie Rocha, The New York Times, July 7^th).  It does telephone screenings, and in one recent example, after admitting it was “not a human,” it could pose questions about qualifications but “could not answer most of (the interviewee’s) questions about the job.”  Its efforts, despite “a friendly tone,” “felt hollow.”  Nothing deceptive here, as other employment-search tasks such as assessing resumes, have long been done by software.  Interview-giving capability “started taking off last year,” and can customize, based on the answers it gets.  Perhaps AI can also do something decades neglected – telling candidates without being asked when they have been dropped from consideration.

How about “Effortless golf with AI smart caddie that follows you” (Kurt Knutsson, Fox News, June 26^th)?  Yes, it’s a robot, the Robera Neo, “designed to follow you around the course, carrying your clubs effortlessly and freeing you up to concentrate on your swing.”  Having used “GPS to map out the course,” it requires only sporadic efforts to guide it, and looks like little more than a golf bag on a manual cart.  It costs only about $2,000, and shipping is supposed to start this month.

On the medical front, a “Paralyzed man speaks and sings with AI brain-computer interface” (Kurt Knutsson, Fox News, July 1^st).  “It translates the brain signals that would normally control the muscles used for speech, allowing users to “talk” and even “sing” through a computer, almost instantly.”  It requires “four microelectronic arrays, surgically implanted in the part of the brain responsible for producing speech,” which “pick up the neural activity that happens when someone tries to speak.”  It can also “recreate the user’s own voice, thanks to a voice cloning algorithm trained on recordings made before the onset” of the patient’s medical condition.  “So far, it’s only been tested with one participant,” so it will not be available soon.

Finally, we saw “How A.I. Is Transforming Wedding Planning” (Alix Strauss, The New York Times, July 12^th).  Instead of using new technology, this ChatGPT technique seems to coordinate and focus existing capabilities by determining what weddings would need, starting with “an Excel document listing 200 suggestions, including ideas from blog posts, Reddit and Google Crowdsource.”  It does a wide range of work on this project, including choosing and communicating with vendors, creating a seating chart “taking into account guests’ commonalities and family dynamics (!),” and providing ideas for the likes of “designs, layouts, and types of tables.”  This is all sort of a combination of a good wedding-planning book and ability to do individual tasks, with more sophistication than a program could have done, say, ten years ago.  And it will only get better.

What can we say about these 11 AI accomplishments?  They are a mixture of solid proofs of concept needing fleshing out, in-progress functionalities, and groupings of previously known skills.  They are heaviest in the medical field, and close in other technical areas.  Interestingly, as AI has been thought of primarily as an office and writing tool, it has had the least unqualified success with that.  We should all hope that its penchants for deceit and hallucinations will not find their ways into the likes of the brain-to-speech application above.  Maybe when it creates ideas, instead of implementing them, it is at its best.  Some smart people are like that, so it is fitting that this artificial but sometimes massively strong intelligence, the most extreme form of idiot-savantism we have seen, is that way too.  We still know precious little about how AI will turn out for humanity, and in which ways.  All we can do is to keep working and, with open minds, keep understanding.

What Artificial Intelligence Has Been Succeeding At – I

Unlike how AI has been floundering in offices, it’s been doing well elsewhere.  In Part I of this three-month rundown, you may wish to take note of the fields in which it has been triumphant and perhaps wonder how its threats and hallucinations don’t seem to be a factor there. 

First, “Artificial intelligence transforms patient care and reduces burnout, physician says” (Kennedy Hayes, Fox News, April 13^th).  The AI variety is “called ambient listening,” which “surveys show” “thousands of physicians across the country are using.”  This technology is like an enhanced transcriptionist, doing that with patient conversations in any of various languages, and adding a summary, with “a system of checks and balances” between doctors and software.  Hundreds of physician-employing organizations now use it, and it may soon be employed for other health professionals as well.

In another victory, “AI system restores speech for paralyzed patients using own voice” (Kurt Knutsson, Fox News, April 16^th).  Though not yet in production, in research “an AI-powered system… restores natural speech to paralyzed individuals in real time,” using “brain-computer interfaces.”  It uses electrodes and “electromyography sensors” on surfaces of the brain and face, and “learns to transform (mental activity) into the sounds of the patient’s voice.”  The author said it represents “key advancements” in “real-time speech synthesis,” “naturalistic speech,” and “personalized voice.”

As opposed to what many people thought, “Your A.I. Radiologist Will Not Be With You Soon” (Steve Lohr, The New York Times, May 14^th).  It seemed a good forecast that AI’s algorithmic abilities would far surpass human radiologists’, but “in recent years” at the Mayo Clinic, the technology has been used instead “to sharpen images, automate routine tasks, identify medical abnormalities and predict disease,” and “can also serve as “a second set of eyes.””  It has not been good enough to “advise other doctors and surgeons, talk to patients, write reports and analyze medical records,” or assess what results “might mean for an individual patient with a particular medical history, tapping years of experience.”  As a result, “a recent study from the American College of Radiology projected a steadily growing work force through 2055.”

Onto the more controversial area of education, we saw “How Miami Schools Are Leading 100,000 Students Into the A.I. Future” (Natasha Singer, The New York Times, May 19^th).  One way was to have them critique the tool’s requested “Kennedyesque text” using the students’ knowledge from studying that president’s speeches.  Another was for them to train AI models themselves on specific topics, something also requiring understanding they had acquired in the class.  A third was having students try “to break A.I.,” by posing “the most inappropriate questions you can imagine,” and hoping to “prompt the chatbots to produce racist, violent or sexually explicit responses.”  Perhaps that’s the way for people to learn to understand how AI functions, and with it, its limitations, while gaining true experience working with it.

On scholarship, “A.I. Is Poised to Rewrite History.  Literally.” (Bill Wasik, The New York Times, June 16^th).  With its penchant for making up facts, unchecked AI could pollute the stream of historical records.  Yet here, historians have found ways it could help without going too far, such as by identifying formerly obscure participants and by summarizing works in ways provoking new insights.  A research assistant with a good if strange mind can be plenty useful – if nothing it writes ends up in final versions unverified. 

That brings us back to how artificial intelligence is serving in offices.  It can be beneficial, if its shortcomings are known and minimized.  That may be the answer there.  See at least five more of its recent achievements next week.

This Morning’s Jobs Report and AJSN: Some Readjustment, A Chunk of Seasonality, More Latent Demand, and Real Progress

The latest Bureau of Labor Statistics Employment Situation Summary was supposed to feature 100,000 to 110,000 net new nonfarm payroll positions, a higher unemployment rate, and possibly some real tariff effects.  None of those things happened.  The new jobs once more far exceeded estimates with 147,000.  Seasonally adjusted joblessness dropped 0.1% to 4.1%.  The rest of the numbers looked for all the world like an ordinary good month, with the usual differences between May and June being dominant.

With that, unadjusted unemployment rose from 4.0% to 4.4%.  The count of adjusted unemployment fell 200,000 to 7.0 million, with those out long-term, or for 27 weeks or longer, up 100,000 to 1.6 million.  There were 100,000 fewer people working part-time for economic reasons, or maintaining short-hours arrangements while looking for longer ones, reaching 4.5 million.  The two measures of how common it is for Americans to be working or officially jobless, the labor force participation rate and the employment-population ratio, lost 0.1% and held to get to 62.3% and 59.7%.  Average hourly private nonfarm payroll earnings tacked on 6 cents, a bit less than inflation, to $36.30. 

The American Job Shortage Number or AJSN, the measure showing how many new jobs could be quickly filled if we knew they would be easy to get, rose 650,000:

The largest changes were from unemployment, which almost covered the difference, from the number of discouraged, up a way-high 302,000, and from a reversal of last month’s jump in those not available to work now, which lost 332,000.  Compared with a year before, the AJSN gained 255,000, with the shrunken count of American expatriates more than offset by additional people wanting work but not looking for it for a year or more, discouraged, and unemployed.  The share of the AJSN from official joblessness gained 1.9% to 38.3%. 

How can I summarize this month’s data?  It was better than the usual seasonal worsening, with 482,000 more employed unadjusted, 927,000 fewer out of the labor force, and 815,000 fewer not interested.  Tariffs are still not clearly causing any disruption, and, with our president’s emphasis on making trade deals, may never.  Once again, the number of net new positions was far higher than we have any right to expect.  The turtle took a substantial step forward.

Artificial Intelligence’s Effect on Getting Jobs – The Reverse of What Many Expected?

Something often mentioned these past two-plus years of intense AI news has been what it will do to employment.  First, many were claiming that a massive shedding of office jobs was imminent, which was premature at best.  How about more recently?

“I’m a LinkedIn Executive.  I See the Bottom Rung of the Career Ladder Breaking.”  So said Aneesh Raman in the May 19^th New York Times.  His case was that “there are growing signs that artificial intelligence poses a real threat to a substantial number of the jobs that normally serve as the first step for each new generation of young workers.”  That’s nothing new – such positions have been getting higher for decades, from my onetime father-in-law starting his illustrious pharmaceutical career in the 1950s by sweeping up the lab, through the steady attrition of what were once called “secretaries” at AT&T through at least the 1990s, and continuing with more and more bottom-level positions requiring excellent computer user skills this century.  Raman talked about “advanced coding tools” replacing “writing simple code and debugging,” and similar things happening with document review at law firms and “automated customer service tools” at “retailers.”  True, these trends are coinciding with poorer employment rates for new college graduates, but he said “we haven’t seen definitive evidence that A.I. is the reason for the shaky entry-level job market.”  The author also failed to mention that even if we “reimagine (entry-level work) entirely,” there will be fewer such positions.

Next, Leif Weatherby’s exposition that “A.I. Killed the Math Brain” (The New York Times, June 2^nd), that “the largest problem… is not the college essay, the novel or the office memo.  It’s computer code.”  Tracking with Raman, he noted “that at major A.I. companies, the hiring rate for software engineering jobs have (sic) fallen over the course of 2024 from a high of about 3,000 per month to near zero.”  He recommended that “young students… study language and mathematics,” to be able to audit AI output, which would be “also a way to deepen our humanity in the face of these strange machines we have built, and to understand them.”

The same events, with an additional cause, were described by Paul Davidson in USA Today’s June 5^th “Tech job openings vanish as AI, tariffs change hiring landscape.”  In a different view from the first piece, “AI… is increasingly prompting technology companies to hire fewer recent college graduates and lay off more employees, according to economists and staffing firms.”  Per the most recent Bureau of Labor Statistics Employment Situation Summary, we have still been gaining plenty of jobs, but “from April 2022 to March 2025, the unemployment rate for recent college grads – aged 22 to 27 – shot up from 3.9% to 5.8%,” compared with only 3.7% to 4.0% for everyone.

On the other side, we saw “A.I. Might Take Your Job.  Here Are 22 New Ones It Could Give You” (Robert Capps, The New York Times, June 17^th).  The author dispensed with AI being ready to write news stories, as “in freelance journalism… you aren’t just being paid for the words you submit.  You’re being paid to be responsible for them:  the facts, the concepts, the fairness, the phrasing” (italics Capps’s), even though “commentators have become increasingly bleak about the future of human work in an A.I. world.”  He named, as his 22 positions, AI auditors, AI translators, trust authenticators, AI ethicists, legal guarantors, consistency coordinators, escalation officers, AI integrators, AI “plumbers,” AI assessors, integration specialists, AI trainers,  AI personality directors, drug-compliance optimizers, AI/human evaluation specialists, enhanced product designers, article designers, story designers, world designers, human resources designers, civil designers, and differentiation designers, all defined in the text.  Although we should ask how many of these will be needed, AI’s deficiencies will indeed call for many to mop up for it – how about AI janitors?

“AI Is Taking Over Jobs; Is Yours at Risk?” (Autumn Spredemann, The Epoch Times, June 17^th).  Unfortunately vague about events in the past, expected in the immediate future, and projected by 2030, the author still clearly claimed that positions already losing headcount included 4,000 in May 2023, and “26 percent of illustrators and 36 percent of translators had already lost work because of generative AI.”

Last, “A ‘White-Collar Blood Bath’ Doesn’t Have to Be Our Fate” (Tim Wu, The New York Times, June 24^th).  Wu had been hearing “a lot of talk in recent weeks about” such a thing, “a scenario in the near future in which many college-educated workers are replaced by artificial intelligence programs that do their jobs faster and better.”  He said it wouldn’t be determined by “fate,” if “companies like Anthropic and Open AI” decide to use their products to enhance instead of supplant workers.  However, since “any technology – from the stone ax onward – replaces some human work in the course of augmenting it,” we will not end lost jobs with any AI-using strategy.

What’s unexpected here?  Until such problems as AI hallucinations somehow go away, the old 2023-ish idea that we will lose great masses of clerical and nontechnical office jobs won’t materialize.  It’s on the technical front now.  It may seem ironic that a product of oversold and overly-beloved STEM work may be the thing to knock its other opportunities off their pedestal, but that’s what we’re looking at now.  We are well and indefinitely into a time, per Weatherby, “in which a computer science degree is no longer a guarantee of a job.”  No matter where AI goes from here, that will continue, and we need to accept it.  Perhaps, also as Weatherby said, we need to bring back the career value of the liberal arts – even in our technology-soaked world.  Don’t rule that out. 

Artificial Intelligence Philosophy and Its Other Huge Issues – A Few Current Views

There is something about AI that gets people to perceive the loftiest concerns imaginable.  Years after it jumped into our consciousness in inaccurate articles about how it aced law school assignments, the depth of its future effects is still highly uncertain. 

We have little trouble identifying the approximate year most forecasts were prepared, whether through drawings, science fiction, or just lists of ideas, as they evolve depending on the technology and priorities of their presents.  How, then, does AI’s future look now?

In “OpenAI CEO Sam Altman rings in 2025 with cryptic, concerning tweet about AI’s future” (Fox Business, January 4^th), Andrea Margolis related how the OpenAI founder claimed the technology was “near the singularity, unclear which side.”  Margolis clarified that Altman was saying one of two things, either that “the simulation hypothesis,” or the trendy but automatically baseless idea “that humans exist in a computer simulation,” is correct, or that it is impossible for us to know exactly “where technological singularity,” or “the point at which technology becomes so advanced that it moves beyond the control of mankind, potentially wreaking havoc on human civilization,” begins.  If he was suggesting that AI might cause singularity, we have no reason to think that’s already happened, but next year could conceivably be different. 

Although Ezra Klein’s “’Now Is the Time of Monsters’” (The New York Times, January 19^th) was telling us that “four trends are converging to make life much scarier” and only one was AI development, it was the largest.  The author cited results on a test “designed to compare the fluid intelligence of humans and A.I. systems” improving with OpenAI’s latest model from scoring 5% to 88%, and wondered if we were prepared, or “even really preparing for” “these intelligences.”  A valid question, though not terrifying on the face of it.

Kevin Roose told us, about a then newly released report, that “This A.I. Forecast Predicts Storms Ahead” (The New York Times, April 3^rd).  The Berkeley nonprofit A.I. Futures Project, which “has spent the past year trying to predict what the world will look like over the next few years, as increasingly powerful A.I. systems are developed,” came out with “AI 2027… that describes, in a detailed fictional scenario, what could happen.”  The piece said that “there’s no shortage of speculation about A.I. these days,” with “warring tribes and splinter sects, each one convinced that it knows how the future will unfold.”  The excerpts here read like those from dystopian disaster novels, and all depend not only on exponential AI progress but on its systems busting their bounds, becoming the equivalent of copiers hopping around their offices and then out of them like giant metal frogs to make images of everything they can find. 

Patrick Kulp described a more sober study on the same general topic in “AI researchers are split on how AI will impact society” (Emerging Tech Brew, April 16^th).  This one, from University College London, asked “more than 4,200 AI researchers” in the summer of 2024 what they thought.  Fifty-four percent “said AI has more benefits than risks, 33% said benefits and risks are roughly equal and 9% said risks outnumber benefits.”  Just over half maintained that “AI research will lead to artificial general intelligence,” and while 29% “were all for pushing its development,” 40% “said AI shouldn’t be developed as quickly as possible.”  As well, “there is more uncertainty among the researchers who are closest to the technology.”  An updated version of this survey could precipitate responses closer to the Berkeley ones, but I don’t think the difference would be massive.

Back to Kevin Roose and the Times, we were asked “If A.I. Systems Become Conscious, Should They Have Rights?” (April 24^th).  A deep idea, but still a novel one, and, with what we know about the workings of consciousness fitting into a thimble, one for the future or maybe never.  Until that changes, we can wait on this issue.  And we should not hold our breath.  Likewise, if we can keep AI tools away from the rest of the world, we won’t have anything to fear.  Let us hope, on huge AI worries, that that becomes the final word.