Friday, December 28, 2018

Herman Kahn’s Great Transition: 42 Years Later It’s Coming True, Quaternary Economy and All

In 1976, the Hudson Institute, now a multicity conservative think tank, released The Next 200 Years, a look at major trends in population, work activities, and general prosperity around the world.  Often described as intended to refute Malthusian projections such as Paul Ehrlich’s Population Bomb and The Club of Rome’s Limits to Growth, it took the opposite view that physical resources, such as mineral wealth and food-producing ability, would greatly increase, and that the number of people in the world, then extrapolated to reach 25 billion or more within two centuries, was in fact having an anomalous surge that would fully return to long-term historical levels by 2176.  Per Institute founder and primary author Herman Kahn, the spiking number of people in 1976 was only part of “The Great Transition,” which would also include a per-capita Gross World Product, similar to GDP, rising from $1,300 to $20,000.

Although we are still 158 years short of that point, it is clear that Kahn’s predictions were outstandingly accurate.  We have gone from “the population explosion” being a worldwide worry to most highly developed countries actually losing people and others with vastly reduced birth rates.  The prices of commodities, from oil to copper to wheat, are either about the same in constant dollars or lower, helped by not only improved extraction processes but by discoveries of almost unimaginably large amounts of accessible minerals.  Starvation is much rarer, with the number of people living on $1.90 or less per day below half of that in 1987. 

On overall economic activities, this book has also been prescient.  Human beings have gone through a progression, starting with extraction (farming, fishing, mining, or taking other resources) and moving on to manufacturing (making other things from these resources) and then services (doing things for each other).  In total employment, extraction peaked around 1900 and manufacturing in 1943.  The number of people working in services is still growing, but may soon not be in the most developed places.

All of that leads to one question:  what will come next?  Following the nomenclature often used with services as tertiary business activity, following extraction as primary and manufacturing as secondary, the following phase would be “quaternary.”  If you look that up online now, you see a common view that it refers to research, consulting, and high-level planning.  That is reasonable, but such activities have one flaw preventing them from deserving that title – unlike the previous three, they cannot possibly provide jobs for most working people.

That brings us back to The Next 200 Years, which uses quaternary to describe unpaid things done for their own sake.  If tertiary activities are done for others, quaternary ones are done for the people doing them.  Per Kahn, they are “often constituting what we now more or less consider leisure activities” and “could include” rituals, “demanding religions,” reading, writing, painting, composing, games, “gourmet cooking and eating,” hunting, boating, discussion, “acquisition and exercise of nonvocational skills,” and, if financially unjustified, “many public works and public projects.”  As services become less and less labor-intensive, which has happened for decades now, quaternary activities will not only keep people active but will be, as paid employment has generally been, a main source of their identities.

The catch, of course, is that these quaternary activities do not provide the means for living.  Whether or not that is implicit in the recent discussion on guaranteed basic income, they go well with it.  Guaranteed income will be necessary someday, and the time people do not spend working or seeking work will be freed for quaternary activities.  How we can persuade the rank and file of Americans to choose more active pursuits than watching television and absorbing entertainment, both of which are held over from the days when work left people physically exhausted, is another problem, but the opportunity will be there.  Kahn called “the transition to a society principally engaged in quaternary activities” “the third great watershed in human history,” and expected it to be nearly complete worldwide by 2176, the same time when the higher population percentage increase will end. 

Will the practice of quaternary activities come to pass?  That is already happening.  The extent that they become people’s main occupations will depend on, among other things, where we go with guaranteed income.  That will be debated more and more over the next twenty years.  With another depression or Great Recession, we will see that jobs are permanently going away, so people, like it or not, will need to find something else to do with their lives.  That is where we are going.  We don’t know much about what life will be like for our grandchildren’s grandchildren, but it’s silly to imagine them working service jobs as if it were the 1980s.  Bet on Herman Kahn’s quaternary activities – it’s the most likely future we have. 

Thursday, December 20, 2018

A Year-End Wrap-up on Today’s Hottest Jobs-Related Topic: Artificial Intelligence

Yes, in amount of recent press, AI has gone past guaranteed income, driverless cars, minimum wages, and even robotics.  It’s sort of an oxymoron, as it still seems to use only algorithms, which forces its developers to assume that what knowledge they want must be linear. 

We’ll start our set of dispatches from the last seven months of 2018 with one from a series called “Dispatches.”  This entry by Henry Kissinger, who, if he penned this himself, is one of the world’s best 95-year-old writers, is titled “How the Enlightenment Ends” and was published in the June 2018 Atlantic.  Kissinger was concerned that our “new, even sweeping technological revolution” has “consequences we have failed to fully reckon with” – a sentiment around since at least George Orwell in the 1940s, even if some of the problems he mentioned, such as “the ability to target micro-groups” causing politicians to be “overwhelmed by niche pressures,” are newer.  He warned of the dangers of “an AI program that is acting outside our framework of expectation,” especially one that learns much quicker than humans and can “surpass the explanatory powers of human language and reason,” and considered the nature of consciousness, which in one of many views comes from computations and is thus present in pocket calculators.  As opposed to the historical Enlightenment, in which the situation was the opposite, Kissinger wrote that we now have “a potentially dominating technology in search of a guiding philosophy.”  Well selected and well refined insights.

In the June 20th New York Times, Steve Lohr asked “Is There a Smarter Path to Artificial Intelligence?  Some Experts Hope So.”  The author first hinted at a rising problem, that “a growing number of A.I. experts are warning that the infatuation with deep learning may well breed myopia and overinvestment now – and disillusionment later,” a view which may be driven as much by concerns about the politically incorrect conclusions the deep learning, or massive data analysis, systems Lohr discussed sometimes reach.  Although they seem to “learn” by identifying commonality, such schemes are ultimately only based on computations, running faster but not making intuitive human-style connections, and indeed, per Lohr, “deep learning comes from the statistical side of A.I.”  That theme was also the point of Melanie Mitchell’s “Artificial Intelligence Hits the Barrier of Meaning,” on November 5th in the same publication, which said that “today’s A.I. systems sorely lack the essence of human intelligence:  understanding the situations we experience, being able to grasp their meaning,” and pointed out how vulnerable such schemes, which may need to learn from the beginning when only small things are changed, are to hackers.      

One section of artificial intelligence has hit a roadblock, as Julie Creswell reported on June 20th, also in the New York Times, that “Orlando Pulls the Plug on Its Amazon Facial Recognition Program.” That police-department effort, powered by Amazon’s two-year-old Rekognition product, was ended in the wake of protesters rightfully concerned that it could be used to track them “or others whom authorities see as suspicious, rather than being limited to individuals who are committing crimes.”  This won’t, though, be the end of large organizations vacuuming up millions of faces and attaching them to credit reports, medical files, purchasing histories, cell phone records, and so on, and it is unrealistic to think your face will not be with your name in plenty of huge databases within ten years.  There will be good and bad aspects to what is already the means to attach a personal history to a high share of facial photographs, making everyone an even faster and sharper data analyst than Penelope Garcia on CBS’s television show Criminal Minds.  Even if such technology is legally restricted, it will still be used.

Moving on to human resources issues, we have, also in the Times, “A.I. as Talent Scout:  Unorthodox Hires, and Maybe Lower Pay” (Noam Scheiber, December 6th).  That piece showed how companies can use a baseball-style Bill James or Moneyball system to identify winning job candidates lacking conventionally expected credentials, for whom, per a Columbia economist, the organization “doesn’t seem to have to compete… as much.”  A fundamental improvement over the long-time use of automated scanning for key words on resumes, the service Eightfold can look for related but not identical experiences.  One drawback Scheiber named was that people might feel “a sense of unfairness… if a computer were to make hiring, firing and promotion decisions” – that made me laugh, as those verdicts, when made by humans, have been notoriously erratic since long before the first computer was made.  Just as modern technology can put chubby or awkward-throwing but superbly hitting players into major-league careers, it can do the same for those with credentials slightly off balance in cubicle jobs.

We end on a pessimistic note from Timothy Egan, in the December 7th New York Times.  As before, we’ve known about threats from “The Deadly Soul of a New Machine” for a while, but it isn’t the whole story.  Yes, October’s Lion Air flight disaster may have been caused by an excessively dominant, in effect faulty, “advanced electronic brain,” but such things have saved many more lives than that, and saying that one driverless-car pedestrian death means that “there shouldn’t be any rush… to hand over the steering wheel to a driver without a heartbeat,” and that a good summary for artificially intelligent devices is “Our invention.  Our folly,” is out of touch with the reality of what such systems are doing now, let alone how they will perform when bugs that caused both disasters are removed.  We don’t need naivete, but we can also do without looking only at the worst.  Artificial intelligence is still only algorithmic, and will continue to present problems, but it is still overwhelmingly positive.  As for its future, stay tuned. 

Friday, December 14, 2018

Autonomous Vehicles: Six Slow Months

I last published on this topic June 28th, wrapping up the previous 12 months, and July 11th, with projections on the shares of vehicles reaching certain technological points in the USA and elsewhere and the number of trucking and cabdriving jobs in relation to today’s.  I have established that forecast as a regular annual feature, but didn’t want to get caught up in the often-daily updates in the field I had seen for the previous year.  So what has happened since then?

One noteworthy thing is the lack of news itself.  Companies have been much quieter about their progress, with the largest stories concerning business instead of technical moves.  The promises have softened, especially, as we will see, those from the formerly loudest participant.

One company reached a real milestone in the summer, as “Lyft’s self-driving vehicles have performed 5,000 passenger rides in Las Vegas” (Cohen Coberly, TechSpot, August 22nd).  Although all were in the limited and almost linear area of the Strip, it’s still an impressive accomplishment, especially with no accidents and a stunning 4.96 out of 5 passenger feedback record with comments calling the trips “amazing” as well as safe. 

On the regulatory front, our federal government showed again that it can be helpful and set guidelines without unreasonable or heavy-handed interference.  In “US Department of Transportation updates autonomous car rules,” from Engadget on October 4th, Natalie Behring showed us changes to voluntary, not mandatory, principles, including allowing automata to legally constitute “drivers” and announcing an intention to drop requirements for devices, such as pedals and steering wheels, such systems don’t need.  That approach has drawn disagreement from the private, consumer-advocating Center of Auto Safety, but is certainly the long-run winner.

I thought we had more insights into the recent slowdown in “Through All the Hype, Self-Driving Cars Remain Elusive” (Norman Mayersohn, The New York Times, November 27th), but this article, after noting the likes of “self-driving vehicles, despite being the subject of breathless media reports and in automakers’ strategies, remain years from being available to private owners” (which we know, as the first wave of them will be put in fleets instead), and quoting a Stanford transportation lecturer as saying that “few start-ups actually understood the commitment required to create a complete vehicle” (but none in the past year have tried), listed companies not only specializing in different technical areas but taking varying business approaches, from concentrating on easy environmental conditions to planning to deal with all of them, from partnering with one automaker to offering products to all, and starting with taxi service, intracompany runs, or other fixed-route shuttles.  Mayersohn revealed ten of these concerns, some familiar from the literature but several not, which showed how much forceful, widely-varied work is still ongoing.

In the December 5th Arizona Republic, Ryan Randazzo told us about his progress-assessing project, “We followed Waymo’s self-driving cars around Arizona for 170 miles:  Here’s what we saw.”  The latter, though clouded by his uncertainty on whether the vehicles, all of which had safety drivers, were actually in driverless mode, included extreme caution while approaching a major accident site, perhaps excessively slow turning in some intersections, sluggish lane changing causing some missed turns, and what seemed like unusually conservative driving in general.  Randazzo’s findings cast a positive light on Waymo, which has already shown itself to be one of the soberest and most measured autonomous-technology providers – it seems appropriate to err on the side of caution, and problems such as not getting into the proper lane in time will clearly be attacked and solved.  Remembering that all know that such vehicles are not at all being touted as finished or even commonly available should remove any concern about this piece’s discoveries.

That company recently crossed another line, as “Ex-Google driverless car firm Waymo begins charging for self-driving car rides in Arizona” (USA Today, also December 5th).  It is not a general offering, but only for “pre-approved passengers in the Chandler, Arizona area.”  Meanwhile, as I alluded to before, “Uber plans smaller, more cautious self-driving car launch” (Heather Somerville, Reuters, again December 5th).  This is the first sentence I’ve seen with both “Uber” and “cautious,” but seems to be what came off their drawing board after their real but grossly overemphasized fatal March accident.  Their tests will resume at speeds under 25 miles per hour in dry daytimes with not one but two “employees” in front seats, with no plans for passengers and “no firm start date.”  That may be so unadventurous as to make Uber uncompetitive.  However, Somerville’s reporting of this announcement was more positive than what Rachel England wrote in Engadget’s December 6th “Uber puts self-driving cars back on the road in scaled-down test,” including the statement that “current employees have anonymously claimed that Uber is taking shortcuts to hit internal milestones.”  If that were to be documented and to have demonstrably bad consequences, it could finish Uber off, not only in the autonomous-vehicle realm but eventually as a business.  It is now more important than ever that we differentiate between what Uber is doing and the progress and safety of others. 

Four conclusions stem from the events above.  First, the limited rollouts and smaller set of immediate future implementations mean that we are behind schedule, maybe six months back of what my July projections anticipated.  Second, the Waymo model of operating in smallish, well-mapped and defined areas which can expand with time may become established as the way driverless technology reaches the general public.  Third, the wide variety of companies and methods is good for the long run, as some will be successful and most will not, but may mean further delays in the next year or so.  But fourth, if people working in this field maintain or reimplement their 2017 levels of intensity, there can be no doubt that driverless vehicles will, indeed, become the norm.

Friday, December 7, 2018

Neutral Jobs Data? No, November’s Was Good – The AJSN, Now Down 200,000 to Latent Demand of 15.5 Million, Shows Why

My first thought as I went through this morning’s Bureau of Labor Statistics Employment Situation Summary was that November was a flatline month.  Nonfarm payroll employment gained 155,000, over the level needed to absorb our population gain but not much.  The break-evens included seasonally adjusted unemployment (3.7%), unadjusted unemployment (3.5%), the labor force participation rate (62.9%), and the employment-population ratio (60.6%), arguably the four most important jobs figures the BLS publishes.  Average hourly nonfarm payroll wages didn’t do anything either, gaining 5 cents per hour, or just about the inflation rate, to $27.35.  The two other major data points were mixed, with the count of people working part-time for economic reasons, or holding on to short-hours positions while thus far unsuccessfully seeking full-time ones, up 200,000 to 4.8 million, and the number officially jobless for 27 weeks or longer off 100,000 to 1.3 million. 

Given all that, especially with the last two statistics not an input to it, I expected the American Job Shortage Number or AJSN, which shows latent demand for American work, to have stayed virtually the same.  However, it lost 200,000, improving as follows:

Half of the drop was from lower official unemployment.  The other half came from one of the numbers of marginal labor-force attachment above.  The count of people saying they wanted to work but had not looked for it during the previous year fell 136,000 from October, which meant their group’s latent demand fell about 109,000.  The other smaller factors almost held, with a 45,000 rise in those temporarily in school or training and a 120,000 gain in “other” offset by 53,000 fewer calling themselves discouraged. 

The AJSN’s year-over-year comparison was also strong.  In November 2017, there were 636,000 more unemployed and almost 1.5 million more counted as non-civilian (in the armed forces), institutionalized, and unaccounted for (off the grid), with changes in the other components small and mixed, resulting in a 660,000 drop.  

You may read from other sources that this jobs report was disappointing.  I don’t see that.  More new positions than our rising population needs, even if they were below some estimates, is, as we will find out with the next recession, nothing to take for granted.  The smaller categories above are straightening themselves out, with people settling into a robust employment market but with more realistic views of whether it could help them personally.  Otherwise, we broke even.  As to why November wasn’t better, the answer may be that we are simply running out of room.  We can always use many more jobs, but barring something on the scale of a national infrastructure project, there is no reason for us to get them.  Given that, this is hardly a shabby place to hang out.  And yes, while it was small, the turtle did indeed take another step forward.