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.  

April: Another Good Jobs-Data Month, as AJSN Drops Another Half-Million to Show We’re Now 15,800,000 Jobs Short

Once again, the American employment situation improved, though not in the ways we expected.

Again we didn’t make the projected increase in net new nonfarm payroll positions.  It was 204,000, and we missed that by 40,000.  But, once more, the other numbers more than compensated.

The big news was the headline seasonally adjusted unemployment rate ending its six-month stay at 4.1% in the good direction.  Its current 3.9% is the lowest it has been since December 2000, and came with a 300,000 cut in the number of officially jobless people, to 6.3 million.  The unadjusted rate also reached a long-term low at 3.7%, the difference showing that April is an above average month for jobs.

The worst of this morning’s readings were in the labor force participation rate and employment-population ratio.  These measures of how common it is for Americans to be working went down, falling 0.1% apiece to 62.8% and 60.3% respectively.  Although both greatly improved earlier this year, these have now given back about half of that gain, a seemingly unusual result given unemployment’s drop.  The count of the long-term jobless, those without work for 27 weeks or longer, stayed the same at 1.3 million, as did the number of people working part-time for economic reasons, or holding on to short-hours propositions while unsuccessfully seeking full-length ones, still at 5.0 million. 

The American Job Shortage Number or AJSN, which shows in one figure how many new positions could be filled if all new that getting one were as easy as ordering a pizza, also improved more than the season would indicate (the AJSN is unadjusted), down 492,000 from March as follows:

The nature of the drop, though, tells us why the two percentage indicators of working-likelihood worsened.  While latent demand from officially jobless people fell 665,000, over a quarter of that was offset by a 238,000 rise in the number wanting employment but not looking for it for a year or more.  There were also increases in the counts of those currently and temporarily unavailable and those claiming no interest in jobs, though the discouraged category fell more than 10%. 

Compared with a year before, the AJSN is down just over 800,000, with over two-thirds of that difference coming from reduced official unemployment and the rest more or less from an annual cut, despite this month’s worsening, in those wishing to work but not trying for 12 months or longer. 

The monthly AJSN decrease, and more so the annual one, is another outcome in support of the interpretation, accurate I believe, that our employment situation is still improving.  Jobs growth is only sitting around the 130,000-140,000 needed to cover our population increase, but with other numbers tending to improve, even with their advances in the past few years, that is good enough.  Once again, the turtle took a small but significant step forward.