Commentary
When I first moved to New York City in the mid-1970s, cab drivers—or “hacks,” as they were called once— were a skilled profession.
Many of them were sole proprietors, and owned their cab and taxi medallion—the costly city license that allowed them to pick up fares hailed on the street. They took pride in their taxis, kept them clean, and many festooned them with family photos, religious icons, custom dashboard decorations, and other objects. These men—and just a handful of women—worked hard and knew the city like you know your Social Security number. They knew the fastest way to get you where you were going by the time of day (“Second Avenue will get you to Wall Street faster than the FDR; it’s morning rush”...) And they knew obscure streets like Freeman Alley, Stone Street, and Hunts Lane. And if you were conversant, they also dispensed some of the best opinions and advice one could garner, gleaned from years of workaday life and speaking to thousands of people a year.
But in the 1980s, taxi medallions soared in value to nearly—and past—the half-million dollar mark and were scooped up by investor groups who leased them to a polyglot corps of independent drivers, mostly recently arrived to New York, who rented the cabs, bought their own gas, and had few other options for work.
Soon the medallion-owning taxi owner/operators sold out and retired or found other work. In the 1980s, you were lucky to find a taxi driver who spoke English, let alone one who knew how to get to Katz’s Deli in the days before the movie “When Harry Met Sally” turned it into an overpriced tourist destination.
Today, anyone with a hack license issued by the NYC Taxi and Limousine Commission, a clean driving record, a late-model vehicle, and a mobile phone can drive for Uber or Lyft and start doing what the old hack drivers took years to learn. They can simply start driving using one of the half-dozen navigation apps one can download for free on their telephone or the apps provided by the ride-share company once they sign up.
And those old taxi medallions that once sold, in their heyday, for over a million dollars? Well, they now sell, often in bankruptcy, for less than a quarter of that. And not a few of the independent medallion taxi owner/operators who bought in at the high end and found themselves desperately upside down on their medallion mortgage, ended up killing themselves; there were three in 2018 alone.
I relate the story of the medallion taxi drivers to highlight an example of how technology can disrupt long-standing businesses and industries. (NYC taxi medallions have been issued since 1937.)
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As artificial intelligence (AI) becomes more prevalent in our economy, it’s important to remember that it could become a massive disrupter of existing businesses. In the service space, especially, it has enormous potential to displace millions of skilled workers.
Or not.
“New” technology is always hyped by its proponents. The Segway, when it was introduced in 2001, was reported by one outlet to be “a more significant invention than the personal computer.” Twenty years later, its leading customers were tour companies whose clients couldn’t walk the mile or more to highlighted destinations and mall cops who were similarly limited. (The Segway even became a feature in the “Paul Bart: Mall Cop” movie comedies.) The original model is no longer produced, and most of the market has been replaced with an array of battery powered scooters.
So, how do we separate the hype from the facts?
I’ll have to leave that to people far smarter than I am. If you had told me 20 years ago that Elon Musk would return a rocket booster from space to land, upright, on a platform at sea, like a rocket landing on Mars in some 1950s’ sci-fi movie, I would have called you a liar. But here we are; Musk has done it. (For a deeper dive into the “hows,” “whats,” “whos,” and “whys,” particularly on the hardware elements of AI, I suggest the article “What Is AI Hardwire?” on VentureBeat.)
If AI lives up to its billing, then millions of clerical, repetitive, and routine jobs will go the way of telephone booths and AAA road maps. It could be a massive disruption, for some, or a massive opportunity for others. We’ll have to wait and see. But adaptation will be necessary to some greater or lesser degree. Luddites seldom (never?) win. The good news is that AI will likely take several years to “learn” the routine, clerical, and repetitive jobs it will likely replace, although higher-paying skills are most likely to be “learned” first.
The Market Effect
I am more concerned about the likelihood markets will see an AI bubble and bust, much as we saw in the “dot-com” boom and bust at the flip of this century. Those of us old enough to remember the late 1990s can recall when pretty much any business having a “.com” after its name practically guaranteed an avalanche of investor money being dumped on it. By the time the markets had sorted the likes of Amazon.com and Booking.com from their less viable brethren, billions of investor money had been lost with an enormous effect on the larger macro-economy and the securities markets.I fear there may be a similar boom and bust in AI.
An exchange-traded fund, for example, that invests only in the so-called Magnificent 7 stocks—Alphabet (Google), Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla—is up by nearly 50 percent in less than a year. In addition to the Magnificent 7, AI stocks, who are all involved in AI to a greater or lesser degree, there are a number of “pure play” stocks and start-ups. A number of “silly season,” purely speculative “meme” stocks (i.e., a stock which has gained viral popularity) have been bid up by Wall Street, as well as blockchain digital assets like crypto coins and non-fungible tokens (NFTs)—unique digital assets like artworks.
It’s important to remember that much of this value appreciation has occurred because Federal Reserve policy and Biden administration deficit spending has caused a lot of money to be sloshing around the financial markets. Much of that money—or “excess liquidity”—is looking for a place to nest. If too much of it nests in the aspirational AI, and those dreams come to be dashed, or simply take too long to be realized, it will have an enormous effect on the markets.
For that reason, fund managers and market regulators—as well as the “plunge protection team” (formally, the Working Group on Financial Markets) at the White House—should all be on heightened alert and run robust risk-management strategies to ameliorate market risks.
It will be a massive and crucial undertaking.
They may even want to create an AI algorithm to do it.
