Will there ever be a fully autonomous car? Maybe not. According to Christopher Mims at the Wall Street Journal, predictions of autonomous vehicles’ imminent development have been exaggerated. He writes:
In 2015, Elon Musk said self-driving cars that could drive “anywhere” would be here within two or three years.
In 2016, Lyft CEO John Zimmer predicted they would “all but end” car ownership by 2025.
In 2018, Waymo CEO John Krafcik warned autonomous robocars would take longer than expected.
In 2021, some experts aren’t sure when, if ever, individuals will be able to purchase steering-wheel-free cars that drive themselves off the lot.
In contrast to investors and CEOs, academics who study artificial intelligence, systems engineering and autonomous technologies have long said that creating a fully self-driving automobile would take many years, perhaps decades. Now some are going further, saying that despite investments already topping $80 billion, we may never get the self-driving cars we were promised. At least not without major breakthroughs in AI, which almost no one is predicting will arrive anytime soon—or a complete redesign of our cities.
Even those who have hyped this technology most—in 2019 Mr. Musk doubled down on previous predictions, and said that autonomous Tesla robotaxis would debut by 2020—are beginning to admit publicly that naysaying experts may have a point.
“A major part of real-world AI has to be solved to make unsupervised, generalized full self-driving work,” Mr. Musk himself recently tweeted. Translation: For a car to drive like a human, researchers have to create AI on par with one. Researchers and academics in the field will tell you that’s something we haven’t got a clue how to do. Mr. Musk, on the other hand, seems to believe that’s exactly what Tesla will accomplish. He continually hypes the next generation of the company’s “Full Self Driving” technology—actually a driver-assist system with a misleading name—which is currently in beta testing.
A recently published paper called “Why AI is Harder Than We Think” sums up the situation nicely. In it, Melanie Mitchell, a computer scientist and professor of complexity at the Santa Fe Institute, notes that as deadlines for the arrival of autonomous vehicles have slipped, people within the industry are redefining the term. Since these vehicles require a geographically constrained test area and ideal weather conditions—not to mention safety drivers or at least remote monitors—makers and supporters of these vehicles have incorporated all of those caveats into their definition of autonomy.
Even with all those asterisks, Dr. Mitchell writes, “none of these predictions has come true.”
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