Another Month of What People Are Doing with Artificial Intelligence

The users are finding more and more applications for the most newsworthy technology of the 2020s.…

Nikolas Lanum, in Fox News on March 22^nd, told us that a “Texas private school’s use of new ‘AI tutor’ rockets student test scores to top 2% in the country.”  At Alpha School, “students are placed in the classroom for two hours a day with an AI assistant, using the rest of the day to fucus on skills like public speaking, financial literacy, and teamwork.”  Their ability to work on things they call “passion projects,” and therefore have strong interest in, can explain these results, but for that AI may indeed be the way to go.

We saw also that “AI enables paralyzed man to control robotic arm with brain signals” (Kent Knutson, Fox News, March 30^th).  The experimental achievement started with “sensors implanted on the surface of his brain,” which “recorded neural signals as he imagined movements like grasping or lifting objects,” and “over two weeks, these signals were used to train the AI model to account for daily shifts in brain activity patterns.”  After months of practicing “controlling a virtual robotic arm,” followed by using a “real” one, “he quickly mastered tasks such as picking up blocks, opening cabinets and even holding a cup under a water dispenser.”  Promising, but will take years at best before it can be provided at scale.

The same source told us about “The dangers of oversharing with AI tools” (April 9^th).  While the likes “of ChatGPT have become incredibly adept at learning your preferences, habits and even some of your deepest secrets,” that means their “knowing” so much about you “raises some serious privacy concerns.”  Information they have may be relayed back to their manufacturers, but it is not clear how much damage that actually does.  It may take a known case of someone being badly hurt before we can effectively regulate, or even understand, the true threat.

More tamely, “These AI transcription voice recorders surge in popularity” (Christopher Murray, still Fox News, April 19^th).  With them, users can “record, transcribe and summarize content effortlessly,” using AI’s ability to “transcribe in 112 languages” and “generate comprehensive summaries” – now.  One, PLAUD’s NotePin, is wearable as a pin, a wristband, or a necklace, and, by using encrypted cloud storage, presents no privacy concerns.  The devices are generally low-priced but require paid subscriptions for the AI itself.  This is one use of AI almost certain to continue without existential scariness.

Could we say the same about coworkers who aren’t real?  On that, “Anthropic anticipates AI virtual employees coming in next year, security leader says” (Alex Nitzberg, Fox Business, April 22^nd).  That company is creating “digital AI employees” with “”memories,” parts to play within the business, and company accounts and passwords,” with “much greater autonomy than agents currently do now.”  Yet even Anthropic’s chief information security officer of the title said there are many such unsolved problems, such as “AI employees” being able to “hack the system in which code is merged and tested prior to being rolled out.”  Since this is more of a potential application than a real one, it may not belong in this post at all, but since users can clearly now create bogus employees of some sort, with small but growing capabilities, we should be aware that new names on organization charts may not be Homo sapiens – or anything alive at all, even if they can converse.  Yes, it may not be possible, as author Erle Stanley Gardner once had his character Perry Mason say, to “correspond with a corpse,” but it is with these electronic automata.  So don’t be fooled – or surprised – and that goes for the other four AI functions here as well.

Artificial Intelligence Regulation – Three Months’ Worth

Controlling AI has been more fun for some people than using it or thinking about what it can do.  What’s the story been?

Before the current regime, we watched as the “Biden Administration Adopts Rules to Guide A.I.’s Global Spread” (Ana Swanson, The New York Times, January 13^th).  The “sweeping rules… governing how A.I. chips and models can be shared with foreign countries,” included various limitations on the number of A.I. chips that companies can send to different countries, with no bounds on those going domestically or to “18 of (our) closest partners,” with those “already subject to U.S. arms embargoes” barred, and all others “subject to caps restricting the number of A.I. chips that can be imported.”  There were also rules governing how much American companies can sell chips they have acquired elsewhere.

Is it true that “The Rush to A.I. Threatens National Security” (Heidy Khlaaf and Sarah Myers West, January 27^th, The New York Times)?  The authors claimed that “now that Donald Trump is taken office, the tech industry is moving full steam ahead in its push to integrate A.I. products across the defense establishment, which could make a dangerous situation even more perilous.”  Companies involved in the “slew of new partnerships and initiatives to integrate A.I. technology into deadly weaponry” included OpenAI, Anduril, Palantir, Meta, and Scale AI.  Potential problems include hallucinations, “cybersecurity vulnerabilities,” and data that could manipulate software, issues that the authors did not think could be solved.

What was “The Dangerous A.I. Nonsense That Trump and Biden Fell For” (Zeynep Tufekci, The New York Times, February 5^th)?  “America’s approach to A.I. safety and regulations,” which “was largely nonsense,” as “it was never going to be possible to contain the spread of this powerful emergent technology, and certainly not just by placing trade restrictions on components like graphics chips.”  “Instead… the government and the industry should be preparing our society for the sweeping changes that are soon to come.”  Specifically, “it’s time to harden our networked infrastructure,” “to start thinking clearly about how corporations and governments could use the A.I. that’s available right now to entrench their dominance, erode our rights, worsen inequality,” and determine “what we can do so that this powerful technology with so much potential for good can benefit the public.”  Perhaps regulation, Tufekci seems to be saying, is futile.

Some companies don’t mind that attitude, as “Emboldened by Trump, A.I. Companies Lobby for Fewer Rules” (Cecilia Kang, again The New York Times, March 24^th).  When under Biden “they wanted Washington to regulate them,” citing “the potential to disrupt national security and elections” and the chance to “eventually eliminate millions of jobs,” starting in late January AI companies have made “bold requests of government to stay out of their way,” by saying “it is legal for them to use copyrighted material to train their A.I. models” and “asking for the federal government to pre-empt states from creating A.I. laws.”  The Trump Administration has at least symbolically taken the less-regulation side through executive orders, statements supporting fewer laws, and invoking the value of “America’s global A.I. dominance.”

One form of regulation took effect April 2^nd, as “Deceptive deepfake media now a crime in N.J.” (Associated Press in Advertiser-News North, April 10^th).  New Jersey governor Phil Murphy “signed legislation… making the creation and dissemination of so-called deceptive deepfake media a crime punishable by up to five years in prison,” joining “at least 20 states.”  This version “defines a deepfake as any video or audio recording or image that appears to a reasonable person to realistically depict someone doing something they did not actually do,” and “establishes civil penalties that would permit victims to pursue lawsuits.”  Will the number of violations be small enough to allow enforcement?  Will such laws damage our need to assess veracity ourselves?  Will they turn out to be just adjuncts to others barring child sexual imagery?  I don’t think these questions will be easy to answer.  That makes this example, along with the others here, an artificial intelligence output which we will need to judge, accept, or reject.  It will take a while.

Eleven Observations on All Those Tariffs

As mentioned in a recent post, I have not been covering the day-in, day-out activity with the Trump Administration’s proposed, threatened, scheduled, started, stopped, and discontinued tariffs, as they have changed too quickly to put in a weekly blog with posts that will not be read immediately.  Most if not all seemed to me like negotiation efforts more than parts of any real economic policy. 

Now, though, they seem more permanent.  Reactions from other countries, from Canada and Europe to especially China, have changed from quick concessions to their own levies and threats.  Some may still be withdrawn, and some agreements will certainly take place, but we can’t count on that anymore.

As of Wednesday morning’s “Live Updates:  Asia Grapples With Punishing Tariffs as Its Stocks Sink Again” in The New York Times, “U.S. tariffs on its largest trading partners” listed the following effective or to be effective April 9^th:  China 84%, Mexico 25%, Canada 25%, European Union 20%, Japan 24%, Vietnam 46%, South Korea 26%, Taiwan 32%, India 27%, United Kingdom 10%,  Switzerland 32%, Thailand 37%, Malaysia 24%, Singapore 10%, Brazil 10%, Indonesia 32%, Israel 17%, Colombia 10%, Turkey 10%, Australia 10%.  There are others.  By the time you read this, there will be differences – I recommend either the New York Times or Fox Business for keeping up with changes too frequent for my reporting.

So what do I have to say?  Here are my views.

First, I am against all tariffs.  Not only do they go directly to the bottom lines of consumers, they prompt retaliatory ones which hurt our employment though reduced business profitability, and decrease product quality by reducing or eliminating healthy foreign competition.  Virtually all economists agree.

Second, the end does not justify the means.  That is a solid principle, with few if any exceptions.  Even if the administration knows something vast numbers of knowledgeable people on both political sides do not, which I have no reason to think, there should not be any tariffs.

Third, presidential overreach, here and in general, should be checked and balanced by the legislative and judicial branches.  If either one is unwilling to do that, we have a structural problem, or, more likely, the national lack of will has reached people we need to trust the most.  Either requires our attention and action.

Fourth, we still don’t know how long these tariffs will last.

Fifth, for top management at large businesses, uncertainty is as bad as poor business results.  That will pull down their stocks under this administration even if the tariffs go away.

Sixth, Trump has refused to use blind trusts or make his financial moves public.  Is it possible that he or his agents are selling stocks short before announcing tariffs or other moves certain to hurt the market?

Seventh, trade deficits are meaningless when considering tariffs.  They reflect relative richness and number of customers, at which the United States almost always outranks its trading partners.

Eighth, the April 5^th protests were better attended than many expected.  As the tariffs continue, and the administration does other things to attack prosperity, they should continue.

Ninth, maybe the strongest point against gun control is that any invaders would have to conquer not one government but over 100 million armed households, making that in effect impossible with today’s technology.  The same thing goes for people speaking up against our government – the more who do that, the safer they will be.

Tenth, when this is over, and it will end sometime, there will be a reckoning.  Those who did not resist Trump when they had the opportunity and capability will be identified and possibly punished, formally or informally.

Eleventh, my personal investment decision now is to sit tight.  As The Motley Fool said in a recent Facebook message, bear markets don’t destroy wealth – panic selling in bear markets does.  I will not make any stock trades, indefinitely.  If you choose that course too and it turns out to be wrong, at least you won’t die alone. 

The time will come when we have a better government.  In the meantime, keep living, do what you can and have to, keep the faith, and look at least to 2026 and 2028.

March Jobs Data Showed More New Positions Than Expected, with AJSN Giving Latent Demand Down 400,000 to 16.7 Million – No Clear Tariff Effect Yet

A combined published estimate for today’s number of net new nonfarm payroll positions was 138,000.  The result in this morning’s Bureau of Labor Statistics Employment Situation Summary exceeded that by 90,000, a welcome surprise.  Except for one area, the other numbers, though, changed in light and variable ways.  Both seasonally adjusted and unadjusted unemployment were 4.2%, the former up 0.1% and the latter, as we moved to an average employment month, down 0.3%.  The adjusted counts of those unemployed in general and those out for 27 weeks or longer stayed the same, at 7.1 million and 1.5 million.  Those working part-time for economic reasons, or looking for a full-time position while temporarily keeping a shorter-hours one, lost 100,000 of last time’s 400,000 gain to reach 4.8 million.  The two measures showing how likely it is for Americans to be working or one step away, the employment-population ratio and the labor force participation rate, stayed the same and gained 0.1%, to 59.9% and 62.5%.  Average hourly private nonfarm payroll wages rose 7 cents, or close to the inflation rate, to get to $36.00.

The area with the clearest pattern was partial labor force attachment, the second through eighth rows on the chart below.  While the count of those claiming temporary unavailability was up, the other six were down, some substantially, with the group of people saying they wanted work but were not looking for it for the past year showing the largest loss.

The American Job Shortage Number or AJSN, the metric showing how many fresh positions could be quickly filled if all knew they were easy to get, improved by 404,000 to reach the following:

About 300,000 of the loss was from official joblessness, and almost all the rest was from the categories of marginal attachment.  The share of the AJSN from unemployment edged down from 39.8% to 39.0%.  Compared with a year before, the AJSN gained about 400,000, with increases in those unemployed, discouraged, not wanting work, and not looking for a year or more mostly offset by fewer expatriates. 

What does the overall picture look like?  Except for the higher-than-expected number of new jobs, and the mostly seasonal increase in employment, up 868,000, not much happened.  Lower figures in the marginal attachment statuses may start a trend, but they are only down to about where they were a year before.  As it usually does during increased employment months, whether seasonally caused or not, the labor force grew, with 362,000 fewer out of the labor force and 153,000 fewer not interested.  Next time we will see the effect of Wednesday’s announced tariffs, if they are still in place, and other labor-affecting presidential moves.  For now, though, I saw the turtle take a tiny step forward.  I hope that the May report will not be worse.

Artificial Intelligence: This Month’s Fine Progress, Real and Potential

From March 6^th to March 20^th, there was a string of articles – two about areas of true AI achievement, one questioning what may or may not have happened earlier this year, and two trying to persuade us about its ability to reach certain lofty heights. 

In the first, we saw how “Taco Bell shows off AI ‘coach’ following massive digital tech investment” (Pilar Arias, Fox Business, March 6^th).  Already, “about 500 Taco Bell U.S. locations have AI voice technology to take drive-thru orders,” up from 100 nine months before, and its Byte software, at least partially in use at 25,000 Taco Bell and KFC restaurants, “is widely scaled and enables operational consistency and restaurant manager efficiency,” including “online and mobile app ordering, point of sale, kitchen and delivery optimization, menu management, inventory and labor management, and team member tools.”  We will look for information no later than next year on how well that is working out.

The other told us, about a patient, that “A.I. Saved His Life by Discovering New Uses for Old Drugs” (Kate Morgan, The New York Times, March 20^th).  The wife of a man “battling a rare blood disorder” and looking at near-certain death contacted a doctor they had met, who used an AI model to propose “an unconventional combination of chemotherapy, immunotherapy and steroids previously untested.”  The patient was “responding to treatment” within a week, and within months was healthy enough for the “stem cell transplant” he needed to put him into remission.  In other cases as well the technology can provide “a systematic way” of assessing “a treasure trove of medicine that could be used for so many other diseases,” which a Harvard Medical School professor called an “enticing alternative” for treating rare afflictions.  Other successes include an AI proposal to use isopropyl alcohol inhalation for nausea which “worked instantly,” ADHD-dedicated amphetamines to help “periodic paralysis in children with a rare genetic disorder,” a drug used for Parkinson’s helping “patients with a neurological condition” to “move and speak,” and more.  This immensely valuable sort of thing, assimilating existing information on side effects, which in these cases were desirable, and other medication properties, more voluminously than humans could do, may be a perfect task for AI.

“How long will the DeepSeek euphoria last?” (Don Weinland, The Economist, March 15^th).  The author said that in that case “many China watchers are now trying to figure out what is real and what is froth,” as “it is worth keeping in mind that China is prone to asset bubbles,” and tension between China and the US could mean that “some of the green shoots might be short-lived.”  We still don’t have the well-established truth about DeepSeek’s asserted ability to produce AI modules at a small fraction of what other companies have paid, and until we do, any comments about its future are premature.

The first tall peak was the subject of “Lila Sciences Uses A.I. to Turbocharge Scientific Discovery” (Steve Lohr, The New York Times, March 10^th).  Per Lohr, “the big, inspiring A.I. opportunity on the horizon, experts agree, lies in accelerating and transforming scientific discovery and development.”  Well, there are others, one of which we will rediscover in the next paragraph.  The Cambridge, Massachusetts startup in the title “had worked in secret for two years to build scientific superintelligence to solve humankind’s greatest challenges.”  It has “already… generated novel antibodies to fight disease and (has) developed new materials for capturing carbon from the atmosphere,” and “turned those experiments into physical results in its lab within months, a process that most likely would take years with conventional research.”  As a result, “many scientists” think “that A.I. will soon make the hypothesis-experiment-test cycle faster than ever before,” and it “could even exceed the human imagination with inventions.”  Although “the early projects are still a long way from market-ready products,” the company “will work with partners to commercialize the ideas emerging from its lab.”  So there is plenty more to do, and while seeing reason for real optimism, comprehensive success is still an unknown amount of time away.

Even more optimistic was New York Times technology columnist Kevin Roose, as he showed in that publication’s “Why I’m Feeling the A.G.I.,” published on March 14^th and in the Sunday, March 16^th print edition.  He wrote “I believe that very soon – probably in 2026 or 2027, but possibly as soon as this year – one or more A.I. companies will claim they’ve created an artificial general intelligence, or A.G.I., which is usually defined as something like “a general-purpose A.I. system that can do almost all cognitive tasks a human can do.””  That means “we are losing our monopoly on human-level intelligence, and transitioning to a world with very powerful A.I. systems in it.”  “Powerful A.I.” will also “generate trillions of dollars in economic value and tilt the balance of political and military power toward the nations to control it.”  Reasons he names for his position are that “the insiders are alarmed,” “the A.I. models keep getting better,” and “overpreparing is better than underpreparing.”  This viewpoint harkens back to two years ago, before most people came to see AI’s doubts, impediments, and shortcomings more clearly.  There have been recent calls for those producing the technology to focus more on specific applications, some as strong as those described in the first two pieces here, and less on the hope of AGI, and this piece does not cancel them out.  Therefore, we have controversy between experts, and the rest of us don’t know either.  When we get much closer, then, I will keep you posted.  In the meantime, this may have been the best all-around month for AI since February 2023.

Autonomous Vehicles, Starting and Stopping – Where Are They Going Now?

We’re way past any idea that driverless cars will soon become the norm – but they are still progressing, in the taxi niche and elsewhere.  What have they shown us in the past 3½ months?

Where one large automaker’s products won’t be going is to give rides for hire, as “G.M. Will Stop Developing Self-Driving Taxis” (Jack Ewing and Eli Tan, The New York Times, December 10^th). They will still work on autonomous vehicles, as General Motors “said it would fold its Cruise subsidiary, which was working on that project, into its main operations, allowing formerly separate development teams to jointly develop fully autonomous vehicles for private owners.”  Although “the decision removes G.M. from a business that some in the industry believe could someday be worth hundreds of billions of dollars,” the company’s CEO “suggested that the payoff was too far in the future to justify the expense,” and said it “would focus on technology that will allow vehicles sold to consumers to steer, accelerate and brake without driver intervention under certain conditions.” 

Recent mishaps include “Passenger in Waymo self-driving car gets stuck circling parking lot while trying to make flight” (Pilar Arias, Fox Business, January 7^th).  The man called Waymo customer support, who fixed the problem in “just over 5 minutes” whereupon the vehicle delivered him to the airport.  The piece did not say if, as the passenger asked, the car had been hacked.

In further expansion, we have “Uber offering driverless rides in major Texas city” (Daniella Genovese, Fox Business, March 4^th).  Uber can offer Austin customers “a Waymo fully autonomous all-electric Jaguar I-PACE vehicle, which will allow them to travel across 37 miles in the area.”  Those two companies “joined forces in 2022 to bring autonomous rides to the public.”  To get such service, “riders till first have to opt in” to it, and those “who request an UberX, Uber Green, Uber Comfort or Uber Comfort Electric could be matched” with such a vehicle, which they can choose to accept.  “When the car arrives, riders will be able to unlock the vehicle, open the trunk, and start the trip in their app.”  It will cost the same as the usual amounts for these four Uber variations, and, in case you were wondering, users “won’t be prompted to tip.”

As well, a “Fleet of Amazon-backed self-driving taxis will soon hit the Las Vegas streets with public rides” (Sunny Tsai, again Fox Business, March 6^th).  “Ten years in the making,” they will be provided by Zoox, and “don’t look like standard cars,” as “they have four seats inside the vehicle, and riders face each other, sitting in rows of two.”  They “will be able to call their taxi on an app,” and “rides will be competitively priced to other existing offers.”  All of that could become a standard for additional service expansions.

Most recently, we merged automata, driverless vehicles, and freight capacity, as a “New delivery robot can haul 2,200 pounds of your stuff” (Kurt Knutsson, Fox News, March 9^th).  It looks like a truck with two rear ends, with its “194 cubic feet of cargo space” designed to be “modular,” so “it can be customized to suit various business needs.”  Although the article used the present tense throughout, it did not mention areas or specific locations where these are in use.  Let’s hope it really is, and that the progress shown in the last four articles here – I include the second, since the problem resolution time was so short – represents what we will continue to see.

Artificial Intelligence: Three Months, Six Different Facets

Since mid-December, except for the DeepSeek brouhaha AI has been relatively quiet.  There have been small expansions here and there, and sales of chips for it have stayed strong.  It has neither crapped out nor exploded.  Here are some looks at various views of it.

First, though, I address something my regular readers may have wondered about.  Why have I not been posting on the actions of the Trump administration, many important to American jobs and the American economy?  The answer is simple: they are changing too quickly.  We have gone back and forth on tariffs, job cuts, and foreign policy so swiftly that recounting those actions, and their reversals, is not suited to a weekly blog.  I sense that President Donald Trump is using them as bargaining tools more than for true policy changes, so the actions of other countries and other organizations, along with his choices of responses, will determine what will become permanent, what is temporary but briefly implemented, what is temporary without execution, and what turn out to be only threats.  For various reasons, I do not think the quantity and intensity of these edicts will continue for anywhere near a four-year presidential term, so we will be able to assess their significance, when the roller coaster slows down or stops, sooner.  In the meantime, I recommend reading the New York Times, if you want to keep track of the daily situation.

Back to the topic, the first piece here is “Business leaders commiserate over scaling roadblocks at AI Summit” (Patrick Kulp, Emerging Tech Brew, December 12^th).  You might think that a conference three months ago would be ancient AI history, but no, it doesn’t move that fast.  The “scaling” was more about selling, “failure to launch,” or a need to “fully commercialize” AI, as two conference presenters put it.  Progress can be slower than some may have thought, as well; for example, it may seem conceptually easy to book airline flights, but that “is still four or five years off.” 

“Why Does OpenAI Need So Much Money?”  This query, placed by Cade Metz on December 17^th in the New York Times, is in response to the company consuming $10 billion in the 18 months starting early 2023, and expecting to do the same with $10.6 billion ending in mid-2026.  The reasons are needing “enormous amounts of data” calling for “larger and larger amounts of computing power from giant data centers,” thereby using chips and electricity which are scarce in the quantities it requires.  And it may get even more expensive, as OpenAI “chases the dream of artificial general intelligence” (AGI), potentially “a machine that can do as much as the human brain, or more.”

Progress announced by a certain Chinese firm has not shrunk these numbers, and even if it was honestly represented, it may never, as “DeepSeek Doesn’t Scare OpenAI, Thanks to the ‘Jevons Paradox’” (Talmon Joseph Smith, The New York Times, February 14^th).  That holds “that as a resource becomes more efficient to use, demand will increase.”  It dates from 1865, when it applied to coal, and has a “decent track record” since then.  As we will see, not all pressures on AI are pushing it up, but this one has real potential to do that.

What does it mean when the “Microsoft CEO Admits That AI Is Generating Basically No Value” (Victor Tangermann, Futurism, February 22^nd)?  The executive, Satya Nadella, “has had it with the constant hype surrounding AI,” and, per the author, “argued that we should be looking at whether AI is generating real-world value instead of mindlessly running after fantastical ideas like AGI.”  The CEO also asked that “when we say this is like the Industrial Revolution, let’s have that Industrial Revolution type of growth.”  As “OpenAI’s top AI agent… still moves at a snail’s pace and requires constant supervision,” Nadella’s statement “could be seen as a way for Microsoft to temper some sky-high expectations.”  Yet he, himself, agreed during the previous month to invest $80 billion in the Stargate industry project.  So maybe, as bizarre as that sounds, it doesn’t mean much at all.

Per a Goldman Sachs-connected survey, “A majority of small businesses are using artificial intelligence” (Kennedy Hayes, Fox Business, February 27^th).  The majority found was 69%, and most found it was saving both time and money.  I do not know the minimum size of these ventures. 

Yet one business application has its enemies, as shown in “Interviewing on AI:  Tech companies love AI.  Just don’t try it to use it to get a job at one” (Dan DeFrancesco, Business Insider, February 28^th).  Amazon has been whining that “AI tools give candidates an “unfair advantage,” and that it doesn’t allow Amazon to evaluate their “authentic” skills, according to “guidelines” given to its internal recruiters.  Too bad, so sad.  Sorry if that is harsh, but companies, especially those of Amazon’s caliber, use plenty of proprietary technological methods to assess, consider, and reject candidates.  Fair is fair for jobseekers to use software of their own.  More power to them – and more power to everyone understanding, comprehending, and assessing the true merits of artificial intelligence.