Self-Driving Cars Are Corporate FOMO

Ford is already lowering expectations for self-driving cars. This should give investors and techies pause while raising deeper epistemological questions.

  1. Tempering expectations isn’t isolated to Ford. Waymo has done the same. Tesla hits stationary objects. We’re not there yet. According to Waymo, we’re decades out.
  2. Lyft and Uber’s valuations only make sense if autonomous vehicles are just around the corner. As it stands, they both are losing billions a year.

This is in stark contrast to the average person believing fully automated cars are a foregone conclusion. Capitalism is supposed to prevent these vast inefficiencies and weed out obvious frauds — I can see no description more apt for Uber and Lyft’s valuations.

Corporate FOMO

Scammers dressed as MBAs have been using the fear of missing out (FOMO) to get consumers to spend more money for decades. You buy something because you’re afraid of either falling behind socially (wearing last season’s fashion) or because of an artificial scarcity (“limited edition”).

And yet the MBA clad scammers didn’t realize that marketing tricks work on them too. Thus we see a feedback loop with hucksters like Elon Musk continually upping the ante. After all, you don’t get billions of dollars in other people’s money to build a slight improvement over cruise control.

A tweet proclaims the inevitability of fully autonomous cars: meaning you hop in, take a nap and wake up across town. Tech journalist quote the tweet, which was originally marketing hype, to write a myriad of stories about self-driving cars being just around the corner. The second wave of journalism quotes the first stories as irrefutable evidence. Now there’s VC money to be had. Thus you need to invoke the lore of autonomous vehicles to unlock funding. Then the tech journalists quote the next wave of VC funded “founders” whose entire livelihood depends on keeping the autonomous driving saga alive. Meanwhile the actual “autonomous cars” that we’ll get are nothing like the hop in and take a nap thing we were expecting.

If it were just the flunkies and tech wannabes that bought into the hype, that’d be one thing. Instead, full on FOMO has engulfed the automotive industry. Serious investors talk about throwing money in companies that could only become profitable if fully self-driving cars are worked out. This goes for everything from taxis to delivery.

When I casually mention my lack of enthusiasm for self-driving cars among people in the tech bubble, I get blank stares and nervous laughs. I might as well be a flat-earther.

Howard Hughes and deep-sea mining

The story of Howard Hughes and the Glomar Explorer is more than a fascinating tale of Cold War spycraft. The CIA needed to build a massive ship without revealing that the true purpose of the operation was to raise a sunken Soviet submarine. An eccentric magnate known for overly ambitious projects came in handy. Howard Hughes would ostensibly build the Glomar for deep-sea mining.

This isn’t a case of the technology not panning out. It was never real. That didn’t stop the media and other companies from catching wind of the operation and jumping on the bandwagon. Corporate FOMO.

Unlike bubbles such as Bitcoin, the early dot-com era or tulips, this was always fake. To quote from a BBC story:

To convince them that Howard Hughes was genuinely interested in nodules, executives were despatched to conferences on ocean mining where they described in detail their plans to harvest the rocks.

“We made ocean mining seem a lot more credible,” Sharp says. “We really misled a lot of people and it’s surprising that the story held together for so long.”

The cover was so good that it prompted US universities to move to start courses in deep sea mining and it also whipped up the share prices of the companies involved. “People thought, ‘if Howard Hughes is into it, we need to be too’,” says Sharp.

It’s easy to laugh this off, but there’s something serious about human nature here. Real experts failed to sniff out bullshit. We should be humble about our own abilities to filter signal and noise. In fact we should learn to be far more skeptical of just about everything.

No harm, no foul. Right?

Let’s say that fully autonomous vehicles are a complete pipe dream for at least the next decade or two. The money spent didn’t go into a blackhole, jobs were created and the technology can be spun off into usable pursuits. If VCs want to subsidize my taxi fair, what’s the harm?

Not so fast.

Self-driving cars are trying to solve a real transportation problem. Instead of a civic discourse about infrastructure, improved public transportation, and urban planning that would eliminate the need for cars altogether, billionaires are gambling on getting even richer. The opportunity cost has been enormous, and many people have stopped working on these other problems because of the belief that self-driving cars in the next few years is an inevitability.

Looking at all of the VC money, resources, talent, and energy being thrown at the blockchain and even less useful “innovations” is even more depressing.

The role of healthy skepticism

Even the best and the brightest are subject to the fallacies and weaknesses of the human brain. A brilliant scientist can still fall for group think and FOMO.

Both corporate and government led innovation are vital for society. But that’s not an excuse for irrational exuberance. Those of us in tech need to respect skepticism instead of deriding it as a sign of Luddism.

As people taking part of the public discourse, we need to be more demanding of journalists. Are they quoting a marketer as if he were a scientist? Is an accepted opinion coming from a hype-based feedback loop or actual research?

One of the best heuristics for filtering out hubris in tech is to ask whether some hyped technology is trying to solve a political problem. An even better heuristic to sniff out bullshit is to ignore whatever tech journalists are calling disruptive.

There’s plenty of real innovation going on out there, but it’s behind the scenes. I’m loath to praise Amazon, but their approach to machine learning has far more to offer than whatever Tech Crunch is talking about this week.