Autonomous Vehicles: The Past Three Months

In less than two weeks I will post my current projected numbers of taxi and truck driving jobs, with expected driverless car saturation dates.  To clear the way, here is what has happened since mid-March.

Is it possible to incapacitate an autonomous vehicle with only a bag of flour?  Derrick Rossignol, writing in Nerdist.com (“Trapping a Self-Driving Car is Surprisingly Easy”) on March 21^st, shows how it just might be.  Required is a solid white circle made around the car, with a dotted-line circle just outside it.  

That emphasizes possible problems with software inflexibility, and reminds me of the words of one of my mid-1980s technical school teachers: “debugging never stops.”

For anyone who might have doubted it, autonomous mobility does not preclude accidents caused by others, with one well described in “Google self-driving van involved in crash in Arizona, driver injured” (Elizabeth Weise and Adrian Marsh, USA Today, May 4^th).  Here “a car being driven by a human swerved to avoid another human-driven car and crashed into it.”  The van’s driverless status contributed zero percent. 

Better, though, you don’t agree with that blame assessment than, per “NASA and Uber are getting serious about flying cars” (Fox News, May 11^th), trust the latter company with your safety in a tiny craft up in the air.  However, as Kirsten Korosec put it in the May 22^nd Yahoo Finance “Consumer Trust in Self-Driving Car Technology Has Made a Sudden U-Turn,” people may be losing confidence in autonomous technology in general, with research finding that the April share of “U.S. drivers… afraid to ride in a fully self-driving vehicle” was 73%.  That may be up a bit since the deadly March accident, though with its changed wording and framing of the question in the immediate present it should not be discouraging.  We also saw that “Uber ends self-driving program in Arizona after fatal crash” (Michael Liedtke, Fox Business, May 24^th), a strange decision even for them – what’s the matter with that state, which otherwise has led the way in embracing this technology, in particular?

So what do driverless cars need to achieve to be generally accepted?  Last week I alluded to one answer, per Risk Analysis research, that “Study:  Self-Driving Vehicles Must Be 4 times as Safe as Human Drivers” (Alexa Lardieri, U.S. News & World Report, May 31^st).  Per the article, “autonomous vehicles present their own set of risks, making a “perfectly safe” self-driving vehicle “both technologically and economically infeasible,” but the level named is both reasonable and attainable – not to mention one at which almost 30,000 American lives per year would be saved.  A fine working objective. 

I’m not sure I agree that “Self-Driving Cars Likely Won’t Steal Your Job (Until 2040),” (Aarian Marshall, Wired, June 13^th), but that’s what a “new report” from Securing America’s Future Energy pointed to, and it’s in the ballpark.  Points Marshall made were that “robo-cars won’t disappear the jobs all at once,” but that “it’s time to prep for fewer truckers and cab drivers, right now,” and, conservatively it seems to me, “the economists estimate (driverless technology) might reduce crash costs by $118 billion annually by 2050.”  It’s fitting, then, that the long-time most safety-oriented carmaker has become the first to announce, though perforce tentatively, “Volvo’s 2021 autopilot to lets (sic) drivers eat, sleep and work” (Chris Mills, New York Post, June 25^th), the first production Level 4, per the Society of Automotive Engineers and the National Highway Traffic Safety Administration “capable of performing all driving functions under certain conditions” and in which “the driver may have the option to control the vehicle.”  Will they deliver?

We end with two Motley Fool pieces, “Driverless Tech Will Impact These 5 Industries” (Jeremy Bowman, June 11^th) and “3 Top Driverless Car Stocks” (Chris Neiger, June 20^th.)  I take seriously this company’s recommendations for investment, especially for general information, since the Watergate logic of following the money, and the effort and true progress behind it, well clarifies situations rife with vaporware and overrepresentations.  As often, both pieces are rich with supporting commentary and information; these two printed out to 15 and 14 pages and do not waste that length.  The business areas Bowman identified – auto manufacturers themselves, auto insurance, ridesharing and taxis, gas stations and convenience stores, and hotels and airlines – hardly form an exhaustive list, but are the largest and most obvious from analysis.  He thought that the first and third will prosper in new ways, and the other three might take a beating.  Neiger’s three stocks were General Motors, Alphabet, and Aptiv – an automaker and two gunrunners.  They also are high-quality choices, though nobody knows if they will even make it, let alone be the best. 

For the July 11^th issue, I look at what major things have changed the path of the autonomous-vehicle industry in the past year – along with the estimates above. 

Simple Answers to Perpetual Questions

Why, despite money supply numbers going well up year after year, is there so little inflation?  Because money, instead of circulating, is pooling up in the largest corporations and many individuals.  That is one result of more and more products being scalable, or one copy costing barely more for a million than for one.  That is the same reason that precious metal, and base metal for that matter, prices are going nowhere – it doesn’t matter how much money is out there if it’s going nowhere.

Why are wages not increasing, despite lower and lower unemployment?  Because latent demand for jobs is still way high – per the American Job Shortage Number (AJSN), we could easily fill 15.9 million new positions, if all knew that getting one was as easy as getting a pizza.  That is also why stories claiming that we are on the verge of a worker shortage, what with all the baby boomers retiring and so on, are wrong – two-thirds of the people who would materialize to fill open positions are not officially jobless.

Why is nationwide productivity falling?  Because disappearing work opportunities are now most likely to be at the high end, with many menial positions resistant to both globalization and automation.  Stock market analysis can be done much better by automata than janitorial tasks. 

Why are driverless car crashes precipitating strong negative reactions while the over 30,000 fatal human-caused ones in this country alone are ignored?  Because people are afraid of change, afraid of the unknown, and afraid of gigantic technology shifts.  Those things attract inordinate fear at best and conspiracy theories at worst.  Not to worry, though, as the level of safety that studies show autonomous vehicles will need for reasonably full acceptance – one-fourth the fatal accident rate of human-driven ones – is well within what will be achieved within the next ten years.

Why are Americans still getting jobs in the information technology field?  Because no courageous large company has led the way with hiring far-cheaper Indians or Russians.  When a Google or Microsoft does that, such positions will quickly disappear from the “Best Jobs of 20xx” lists.

Why do so many people support protectionism?  They don’t, but a few key ones in power seem to feel that way.  We will all pay the price, with many more jobs lost due to higher prices than artificially retained by tariffs, and a lower standard of living nationwide.

Why are 3-D printers not making everything in sight?  Because they are too slow for manufacturing, and they are lacking an application most people can use. 

Why have electric cars not become the norm?  Because, even after 50 years of subsidies and development, recharging needs to be done too often and takes too long, and continuous availability, even if most people don’t truly need it, is highly valued.

How long will it be before the next recession?  Good question.

The BLS Study: Is the Gig Economy Stalling Out?

This week’s jobs-related news featured some surprising and controversial Bureau of Labor Statistics research on non-payroll employment.  First though, a few items on how this section of the workforce does not need to be.

The first was from the April 30^th New York Times, as Noam Scheiber told us that the “Gig Economy Business Model” was “Dealt a Blow in California Ruling.”  That’s not correct, unless those employers never need to “follow minimum-wage and overtime laws and to pay workers’ compensation and unemployment insurance and payroll taxes,” even if, as “industry executives” said, that “tends to cost 20 to 30 percent more.”  Boo hoo!  The second gaffe, by Christina Caron in the same publication on June 12^th, “Cheesecake Factory Is Found Partly Liable in $4.6 Million Janitor Wage Theft Case,” was a well-known company apparently thinking that hiring workers as contractors would allow them to forget about required breaks and hold them, presumably without pay, until “kitchen managers conducted walk-throughs to review their work.”  Those offenses weren’t mitigated much by the vice president of legal services saying “we take matters of this nature very seriously.”  Then we have the old vinegar-turned wine of multilevel marketing now surprising the Atlantic in the April 2018 “Beware of Selling Yoga Pants on Facebook,” which called that old shell game “the social-media gig economy.”  Repeat after me:  Online auspices do NOT constitute new business models!  And nothing in this paragraph is inherent to this way of earning money.

So, back to the BLS paper.  It said, per Ben Casselman’s June 7^th New York Times “How the Gig Economy Is Reshaping Work:  Not So Much,” that “roughly 10 percent of American workers in 2017 were employed in some form of what the government calls “alternative work arrangements,” a broad category including Uber drivers, freelance writers and people employed through temporary-help agencies,” and which “represents a slight decline from 2005,” also a good economic year.

Several people responded to how this result came about.  First was in this same article, with Casselman writing that “separate data released by the Federal Reserve this month” replaced the 10% with “nearly a third,” a finding echoed by “private-sector studies.”  The BLS study, also per Casselman, did not include those with regular-job equivalents employed by outside agencies, or those “selling products online or working erratically as a freelancer.”  He also quoted a former BLS commissioner saying that “we’re not asking the right questions,” and noted that “income-generating activities that people might not consider “work,” like renting out a home on Airbnb,” were not included.  In “What gig economy?  Fewer working as freelancers, contractors than believed” (Paul Davidson, USA Today, June 7^th), we got a Staffing Industry Analysts report result that 29% of the American labor force “performed contingent work in 2015,” and news that the BLS data did not include people with “side hustles” as well as conventional jobs.  That exact phrase also turned up in the headline of Daniel B. Kline’s June 10^th Motley Fool piece; “Side hustles are changing how people plan for retirement” related how these additional propositions were on the rise, as I predicted six years ago, and usually undertaken to pay off debt.  That’s nothing new – in decades past they were called “second jobs” – but are facilitated, not dictated, by opportunities using modern technology.

John Younger’s June 11^th Forbes “The Death Of The Freelance Revolution Is Greatly Exaggerated” made a different point.  It acknowledged the inferior-good nature of most gig assignments, but mentioned an opposite proposition, “lawyers, doctors and other highly skilled professionals” who “earn as much, on average, as standard employees,” even if they tend to get less in benefits, and of whom “nearly eight in 10 say they prefer being an independent contractor to being an employee,” some of which was also cited by Casselman.  There are likely more of these than there were 13 years ago. 

What can we conclude from this study and those writing about it?  Clearly it missed two-thirds of the data it was supposedly trying to capture.  Working on the side is becoming more common, and may be closer to the spirit of the gig economy than being employed full-time, temporarily, while seeking a W-2 position.  To conclude that fewer, not more, people are earning money through these modern-setting temporary-help propositions, we need more of a breakdown.  And when, not if, the next recession hits, we will all be able to see the value, for many, the gig economy truly has.  

Artificial Intelligence: Our Choices - II

As described in my May 25^th post, the development and implementation of artificial intelligence (AI) is growing, expected to be massive, and is bringing numerous old and new issues to the forefront.  What ten observations, attitudes, and adjustments would serve us best?

First, AI evolution will be a process of discovery about us and the world.  What do human beings really want?  Do we truly make decisions of our own volition?  Do we ultimately want more than our own comfort and enjoyment?  If we discover that all objective knowledge stems from algorithms, what will that eventually mean to us?  These questions and many more may someday be answered by progress in this field.

Second, while autonomous vehicles represent the largest single change we anticipate facing in the 21^st century, their technology is only a subset of AI, which is like a massive computer system with driverless cars only one of its applications.

Third, accordingly, AI, itself, presents a multicentury-level challenge.  Its significance is hard to overestimate.

Fourth, because of data mining discoveries, some of our core values and wishes, such as the inherent equality of groups of people, may get the most serious nonideological challenges they ever have, and may even be essentially proven false.  If such happens, after and during a long time of denial, large sections of our belief systems will be overturned.  We need to prepare for that. 

Fifth, AI may seem brilliant, but as with other computer applications it is intrinsically totally stupid.  It has no common sense and no idea of what it is doing.  The ancient data processing law of garbage in, garbage out applies with AI as much as it ever has, with bad assumptions or instructions capable of causing totally false conclusions. 

Sixth, while we can debate the dangers of research into artificial general intelligence, it is wrong to try to suppress progress on the narrow version.  As its scope is limited, it will serve us without threatening to take over.

Seventh, we need to avoid hating or attributing conspiracies to AI simply because it is major change.

Eighth, we must think flexibly about AI, and deal with its problems using logic instead of ideology.  It will leave neither conservative nor liberal philosophies unscathed, so we, as individuals as well as collectively, need to consider the values of both sides when assessing and dealing with it.

Ninth, the potential AI-caused mass employment-opportunity elimination means we need to start discussing possible jobs-crisis solutions.  We’re seeing that now with guaranteed basic income, but need more there, along with more serious debate on assured government employment, payments for online content contribution, shorter working hours, and a more widespread use of ad hoc or “gig” jobs.  True, these are mainly solutions for future problems, but we may need one or more of these as soon as the 2020s.

Tenth, on the nonpolitical issue of dealing with artificial intelligence, we need to remember we are Americans and work with those of other backgrounds and beliefs.  For once.  Yet again, our choice is between living together as brothers and perishing together as fools.

May Was Another Fine Employment Month, Though the AJSN Gained 135,000 – We’re Now Short 15.9 Million Jobs

The strength of several, maybe most, of the past year’s Bureau of Labor Statistics Employment Situation Summaries has been debatable.  This morning’s, though, was not.

It started with an official adjusted unemployment rate down again, this time to 3.8%, an 18-year low.  It continued with a drop from 6.3 million to 6.1 million jobless, a 100,000 cut in the number of long-term unemployed (out 27 weeks or longer) to 1.2 million, and a similar decline in those working part-time for economic reasons, or keeping less than full-time work while thus far unsuccessfully seeking that, to 4.9 million.  Even the average private nonfarm payroll wage got in the act by gaining 8 cents per hour, more than inflation, to $26.92.  The unadjusted unemployment rate fell once more, to 3.6%.  The only loser was the labor force participation rate, off 0.1% to 62.7%, offset by the employment-population ratio’s same-amount gain to 60.4%. 

It may seem strange, then, that the American Job Shortage Number or AJSN, the one-figure measure of latent employment demand, increased, in this case 135,000, as follows:

The reason for the gain, though, is easy to understand.  The count of those claiming no interest in working often falls back during strong employment times, and from April it lost almost a million.  The missing people who did not find jobs moved into statuses with higher latent demand rates, most likely not looking for a year or more and temporarily unavailable to take a position.  Gains in those two categories affected the AJSN more than the reduction in unemployment, which, followed by the 5% share of those not wanting work, subtracted the most from the metric. 

Compared with May 2017, the AJSN is down about 800,000.  Almost all of that is from the official jobless drop, with decreases in the sum of those not looking for a year or more and those in institutions, in the services, and off the grid also contributing improvements of over 100,000.  Only the best estimate of the number of American expatriates, up 700,000 over the May-to-May year, raised the AJSN a comparable amount.

As before, there can be little argument that May was a strong American employment month.  What we need to stay aware of, though, is, that with only 32.5% of the AJSN’s value coming from those officially jobless, the first month since before the Great Recession in which it was less than one-third, the massive majority of people likeliest to start working again are not in that category.  Otherwise, the turtle took a solid step forward. 

Artificial Intelligence: Our Choices - I

In some ways, this is an old topic.  At least as far back as the 1960s, many people have been concerned that computers, robots, and other technology manifestations have potential to do more harm than good.  It’s now 50 years since the cutting-edge machine HAL was graphically and effectively portrayed in 2001:  A Space Odyssey, killing a crew member to follow its highest-priority directive of mission success, and 34 since The Terminator reinforced the dangers of what one of its characters accurately called “autonomous goal-seeking programs.”  Since then it has crept into the mainstream, with products such as Amazon Echo Show and Google Home, taking over small household tasks for millions, constituting large jumps in the past year.  Sixty-five-million-people Great Britain has a chance, per Jeremy Kahn in the October 14^th Bloomberg.com, to add the equivalent of $837 billion to its economy with it over the next 17 years, and the potential in the United States is far higher. 

Even more than with driverless vehicle technology, artificial intelligence has attracted efforts to regulate and limit it.  As Andrew Burt put it in “Leave A.I. Alone” (The New York Times, January 4^th), “December was a big month for advocates of regulating artificial intelligence,” with local and national bills setting the stage for its control.  Yet such governing has not actually happened.  The best sources now on how we should deal with it are the commentators.  Here are two.

The March 31^st Economist titled a 12-page “special report” “GrAIt Expectations,” which started with the observation that “artificial intelligence is spreading beyond the technology sector, with big consequences for companies, workers and consumers.”  It touched on data mining, a perfect application for this technology as while it seems intense it is truly only computational, but, in only the second body-text paragraph, jumped the rails by naming a consulting company, Accenture, using it to “pick the best candidates,” something no machine, or human for that matter, can consistently do.  I liked better the section’s supply-chain-progress heading “In algorithms we trust,” which is still what artificial intelligence is all about, even if modern-day computing power can do such things as determine optimal multi-stop routes, for which, with 25 locations to visit, there are 15 septillion possibilities, and replace human customer service representatives with automata in many ways better.  The set of articles touched on a rapidly brewing artificial-intelligence controversy, or what we will do with information such as identifying sexual orientation, detecting unusual opinions, and potentially determining that members of certain groups may be, in general, less suited for specific employment or financial treatment.  It was relatively easy for medical scientists to disregard Nazi-experiment findings, since they were less valuable, but if the latest and most powerful data mining resource were to “determine,” for example, that even when controlling for income, family background, credentials, and every other variable it can find, blacks are less successful at engineering jobs, we would have hard decisions to make.

The second piece is Tad Friend’s May 8^th New Yorker “How Frightened Should We Be of A.I.?”.  In this remarkably stunning and comprehensive piece, Friend started with the difference between “artificial narrow intelligence,” which harmlessly powers everything from Roombas to refrigerators, and “artificial general intelligence,” the potential 2001 or Terminator-style version, with prospects alarming even to the likes of Elon Musk, Stephen Hawking, and Alan Turing.  The strictly algorithmic nature of artificial narrow intelligence, limited or not, has shown that intuition, long believed to be necessary for success in Go, is at least sometimes computational and therefore within the range of computers, including the one that beat a major champion at that game two years ago. 

That intuition finding puts one thing into doubt.  That is the expectation that many tasks will always require live people.  Friend cited computer scientist Larry Tesler as saying that “human intelligence “is whatever machines haven’t done yet.””  As an atheist might say that religion as commonly practiced fills in only current gaps, that with today’s knowledge people no longer think that God moves planets, it could be that only our failure to understand how to reduce all human abilities to if-A-then-B thinking is stopping us from seeing that artificial intelligence can someday handle anything.  Indeed, computers are already, per Friend’s citations and examples, passing the Turing test by writing in the style of petulant 13-year-olds and otherwise pretending to vary from the linear sequences we expect of them.

Three classic philosophic issues come forth as well in Friend’s article.  The presence or absence of free will, or people choosing their actions themselves, may be solved by further artificial intelligence achievements.  The same is true of the differences between feelings and logical thoughts.  The question of whether we would want to make our planet “into a highly enriched zoo environment that’s really fun for humans to live in” may thus force itself on us.  There is much more here, and I recommend anyone with interest in these topics to read it – it is at  https://www.newyorker.com/magazine/2018/05/14/how-frightened-should-we-be-of-ai .

After a one-week break for the latest employment situation, I will continue this topic on June 8^th with artificial-intelligence-related observations for employers, employees, and the rest of us. 

Robots and Guaranteed Income – Two Halves of a Puzzle?

Here are two strongly jobs-related topics on which I have written over 10,000 words.  We know by now that robots and other mechanical systems are continuing, irregularly, to replace human employees across a wide spectrum.  We also know that universal basic income, if we consider the issues of incentive to work (which I think is both illusory and not a problem anyway) and how to pay for it (much but hardly all would come from ending existing social programs such as food stamps) to be nonfatal, is one of the few conceivable solutions to the long-term jobs crisis.  As we will see, these areas are connected. 

Although it is silly to maintain that robots will create more jobs than they cost, there are some real opportunities.  Per Mike Duffy, Keystone Automation founder and CEO, as quoted in Dave Gardner’s “Trends in Technology: Robotics” in the July 2017 Northeast Pennsylvania Business Journal, implementation of automata is more important in many business areas than its development, requires more skill than most of the positions it will replace, and now there is a shortage in industrial automation graduates.  Most of the time I consider highly specialized bachelor’s degrees too risky, as they leave their holders poorly placed if they cannot find employment in their tiny fields, but robotics is guaranteed to be strong for many decades to come.  Despite a steady flow of career recommendations for software development, I rate physical automation opportunities more long-lasting, as they must be implemented and maintained locally.  If this is not now one of the hottest four-year and two-year majors, it should be.

Something I like less, though, Pedro Nicolaci da Costa advocated in the July 15^th Business Insider “A solution to job-stealing robots is staring us right in the face.”  Getting retrained is a good move for many individuals, but it’s not an overall solution, as it only tends to change who gets hired and who does not.  Another positive view turned up in “Can robots help the U.S. get its economic mojo back?” in TechCrunch on September 4^th, as Steve Cousins correctly stated that automata help overall prosperity but oversold it by crediting China’s world-leading robot spending for its unsurpassed national affluence rise, which came first. 

The next month, though, we began to see the direct connection between the two subjects.  In Fast Company’s October 10th “Robot Taxes Are A Good Idea As Long As The End Goal Is Basic Income,” Ben Schiller considered using the first, actually advocated by Bill Gates, to pay for the second.  Schiller wrote that two economists were advocating “taxing the purchase of equipment that replaces routine work” so governments could “transfer “a certain amount to all the agents in the economy, regardless of their occupation or income.”” 

It was only one day later that www.resilience.org published a paper titled “How to Fund a Universal Basic Income Without Increasing Taxes or Inflation.”  The piece cited an Oxford study projecting that “there was a 50 percent chance of (artificial intelligence) outperforming humans in all tasks within 45 years,” and that “all human jobs were expected to be automated in 120 years.”  Further research cited here suggested that guaranteed income of $1,000 per month to each American adult, the exact proposal I made in 2012’s Work’s New Age, “would add $2.5 trillion to the US economy in eight years,” and that a true universal basic income would not “encourage laziness,” a point also in that book.  With so much money pooling up I can’t agree that its movement will help prosperity as much as in times past, but we may indeed be closer to covering payments to everyone than we had thought. 

While I agree that “The Universal Basic Income Is An Idea Whose Time Has Not Come,” (J. David Patterson, The Federalist, October 20), we need to be exploring and testing it.  And indeed we are doing some of that.  Per Frances Coppola in Forbes on October 15th, “The IMF Gives a Cautious Welcome to Universal Basic Income,” a decision influenced by reduced money movement as above and countries’ differences in “transfer systems” or safety nets.  As Coppola perceptively pointed out, such programs could be especially effective in “oil-exporting developing countries,” and whether you consider, for example, Qatar to be developed or developing, there are several like it that could probably pay for such a scheme right now.

Three places have made the news with what they called pilot guaranteed income efforts, but two weren’t.  The city of Hamilton, Ontario, the subject of “Canada tests ‘basic income’ effect on poverty amid lost jobs” (Fox News, November 29^th), is now giving the equivalent of $13,000 to single people and $19,000 for married couples with incomes below $26,000, with amounts reduced for work earnings.  That may or may not be a valid unemployment and welfare arrangement, but it is not universal basic income.  Peter Goodman told us on April 24^th in The New York Times that “Finland Has Second Thoughts about Giving Free Money to Jobless People,” and is ending its program, which was not, as Goodman put it, an “experiment with so-called universal basic income,” but the same sort of “free money” Americans in any state get if and only if they lose their jobs.  The real McCoy, in Stockton, was the one Chris Weller described in the October 18^th Business Insider’s “A California city is launching the first US experiment in basic income – and residents will get $6,000 a year.”  It’s not nearly enough for them to live on alone, but the program will benefit “a select group of residents” for three years.  We’ll watch this one.

We bring automata back with a story about exactly the sort of quixotic 2020 presidential candidate we need to hear from.  In The New York Times on February 11^th, Kevin Roose told us about businessman Andrew Yang, in “His 2020 Slogan:  Beware of Robots.”  Yang expected serious social unrest from both robots and driverless cars, and proposed as a solution what he called a “Freedom Dividend,” or “a monthly check for $1,000 that would be sent to every American from age 18 to 64, regardless of income or employment status.”  In other words, a true guaranteed income.  Look for Yang to influence other candidates, as neither of these issues will go away soon. 

Next week, I will be a long way away and not posting.  I will return on May 25th with commentary and a recap on another issue that won't go away soon - artificial intelligence.