The Other Side of Automation

It seems to us that a magnificent new product made in Silicon Valley is announced every day in the press, on television, and via social media outlets around the world.  From an historical perspective, there’s no doubt that many of these innovations have improved the productivity of governments and the profitability of corporations, and they’ve enhanced the lives of everyday, garden-variety folks like you and us. But we wonder if we aren’t approaching a point in time when advances in AI (artificial intelligence) and robotics will destroy jobs faster than the economy can replace them.

In the near future, self-driving cars, SUV’s, trucks, and buses will be cheap and reliable enough to be sold in volume. Driving will be safer, and commuters will be more entertained and less stressed, but operators of commercial vehicles will be made obsolete because their vehicles won’t need them anymore.

According to the Bureau of Labor Statistics (BLS), there are 2.4 million commercial truck drivers in the United States who on average make about $50,000 per year. In the near future, those jobs will be lost to automation.

The BLS estimates that 7.5 million retail jobs will be lost to automation. More than half of retail workers are women who make about $23,000 per year.

A recent report by the McKinsey Global Institute forecasts that as many as 73,000,000 American jobs may be lost to automation by 2030. If their forecast is in the ballpark, then the US economy will lose a number of jobs that’s approximately equal to 45% of the nation’s current workforce. (See Note 1.) But the McKinsey report isn’t as foreboding as it would seem at first glance, because it also suggests that an overhaul of the economy could more than offset the 73,000,000 job losses.

Here’s the rub: The overhaul would have to rival or exceed the magnitude of our transformation from an agriculture-based economy to the Information Age, which took 165 years. This time, though, we have twelve years, which means we have to move fourteen times faster than we did last time.  (See Note 2.)

We on The Other Side have a few questions:

1) Is the overhaul a training/retraining problem (as they suggest), a social problem, a political problem, a financing problem, or some combination?

2) If politicians are even remotely involved, what are our chances?  Dodd-Frank wasn’t passed until after the Great Recession. Our bridges, ports, railways, and highways are crumbling, but as of this writing Congress has yet to bring an infrastructure renovation bill to the floor of the House or Senate. When was smoking in public places outlawed? Was it before or after millions of Americans died from lung cancer?

3) Who’s going to pay for the retraining of the existing labor force: the public sector, the private sector, or the displaced workers themselves? We expect it’ll be all three, but will government move quickly enough (see the above), will corporations be more disposed to retrain their employees than hire trained ones, and how much money will the unemployed have to invest in retraining themselves?

4) What’s the real-world scale of the problem? How many bus drivers, bank tellers, and baristas will have to be taught to program computers, mine data, and repair robots, how long will it take, and what percentage of them will make the grade?

We could go on, but you get the point.

Unemployment during the Great Depression peaked at 25% in 1933.  In the absence of another cataclysm or two, we’re confident that the unemployment rate won’t come close to 25% in the next ten to twenty years. But we’re just as confident that the pace of job destruction will far exceed the economy’s capacity to compensate for the losses––and no one will do anything about it until it’s too late.

At South by Southwest this year, Elon Musk said, “Mark my words: AI is far more dangerous than nukes, by far, so why do we have no regulatory oversight? This is insane!”  (See Note 3.)


1) According to Wikipedia, 161,000,000 Americans held part or full time jobs in the US at the beginning of 2018.  Seventy-three million divided by 161 million is 45.3%.

2) One-hundred and sixty-five divided by twelve is 13.75.  We rounded up.

3) The quote from Elon Musk was from ZDNet, a high-tech website. We didn’t change a word, but we did edit the punctuation.

4) A roomful of statisticians and economists at the Bureau of Labor Statistics could model the most probable outcomes, but they’d have to base their forecasts on so many assumptions that every politician, private-sector economist, and talk-show pundit could find at least five to dispute—for one news cycle. The next day, they’d be arguing about something else. We have two bits of advice for the BLS: a) forget the model, and b) tell your kids to get degrees in robotics.

5) The Apex Child is a novel about this very problem. Fair warning: it’s longer than this article.



The GOP v. Democrats, Round 3: Jobs

This is the third and final article in a series of three that examine the relative economic performance of Republican and Democratic administrations since the end of the Second Industrial Age. If you haven’t already done so, read the first and second articles, which compare federal debt and stock-market performance since the proximate end of the Second Industrial Age. Spoiler alert: the underdog Democrats defeated the overdog Republicans in both instances, and neither outcome was a close call.

In this piece, we attempt to determine which party has been the better “job creator” over the last four decades. As in the last two episodes, there are a number of metrics that can be used to measure relative job creation, but the simplest, most widely understood, and least obscured by a growing economy is the unemployment rate.

The incoming and outgoing unemployment rates by administration were as follows:

President Party In Office Incoming Outgoing Change
Jimmy  Carter Dem 1977-81 8.5% 8.0% -0.5%
Ronald Reagan GOP 1981-89 8.0% 5.6% -2.4%
George HW Bush GOP 1989-93 5.6% 7.8% 2.2%
Bill  Clinton Dem 1993-01 7.8% 4.1% -3.7%
George W Bush GOP 2001-09 4.1% 8.6% 4.5%
Barrack  Obama Dem 2009-17 8.6% 4.9% -3.7%

On average, the unemployment rate increased from 5.9% to 7.3% during the last three Republican administrations. On average, the unemployment rate decreased from 8.3% to 5.7% during the last three Democratic administrations.

Another way to gauge the difference: The unemployment rate increased by an average of 24% during the average Republican administration; it decreased by an average of 32% during the average Democratic administration.

That’s a difference of tens of millions of jobs over the last forty years.

Full disclosure: From February 2017 to February 2018, US unemployment decreased from 4.9% to 4.4%. The trend line suggests, however, that the unemployment rate will be materially higher by February of 2021, or maybe The Donald is channeling Ronald Reagan. We’ll know in a few more years.


(1) The unemployment data are from Bureau of Labor Statistics.

(2) The comparison assumes that each incoming president was responsible for the economy from the first day of February after his inauguration until the first first day of February after his successor’s inauguration, which is why incoming and exit figures are identical.


Trickle Down: The Lost Alternative

At one time or another, most of us have heard the phrase “trickle-down economics.” It is, in the conservative mind, the best way to stimulate the economy, thus it was the basis for the 2018 tax reform bill authored by Congress and signed into law by the president. But, before we on The Other Side can accept that “trickle-down” works admirably well, we are compelled to examine how it works, if for no other reason than we aspire to be sentient.

In an economic context, “trickle down” means that tax incentives aimed at the wealthiest of the economy will work their way down to the middle and lower classes. However, a tax break for a wealthy man, or more rarely a woman, is discretionary. He can spend it on an American-made business jet or a Norwegian yacht. She can invest the money in an asphalt plant in Pittsburgh or a cement factory in Vietnam. He can buy a thousand acres of farmland in Nebraska or in Surinam. She can invest in an American hedge fund, or Eurobonds, or bitcoin.

Moreover, the wealthy need never be in a hurry because, well, they’re wealthy. Hence the phrase “trickle down,” which, to review, means that a lot of money is given to the wealthy in the form of tax breaks, and then it trickles down to the middle and lower classes, except for the parts that are invested overseas or put aside for a rainy day, possibly in the Caymans.

It would seem from a cursory examination of trickle-down economics that there’s room for improvement, if only in theory. Let’s imagine for a moment that instead of giving another tax break to the wealthy, Congress voted to cut taxes for the middle class and to increase subsidies like food stamps and Medicaid for the economically disadvantaged. Unlike the rich, the lower classes don’t have any money to save, and the middle classes don’t bother (with few exceptions). Instead, they spend it on essentials like heat, healthcare, video games, and pop tarts, and they can’t afford to wait.

In other words, the money enters the economy quickly, and then it gushes up the economic food chain: from the retail stores to the companies that own the retail stores, to the hedge funds that own most of the stock in retail store companies, and on to the men and women who invest in hedge funds. In the end the wealthy get it anyway, but at least the middle and lower classes had it for a while––and pop-tart sales skyrocketed.

Sadly, the phrase “gush up” sounds too much like vomit. It never caught on, which explains why the rich get all the tax breaks.