Driverless Taxi Usage in California Surges Eightfold as AI Nears 'World-Changing' Phase, Predicts Derek Thompson

Journalist and author Derek Thompson recently outlined a phased trajectory for artificial intelligence, predicting that after initial overrating, disappointment, and a speculative bubble, AI will become "world-changing" by the 2030s. Thompson drew a direct parallel to the evolution of self-driving cars, highlighting their journey from early hype to current significant impact. This perspective comes as driverless taxi usage in California has reportedly grown eightfold in the past year, with companies like Waymo expanding their services.

Thompson's baseline case for AI suggests a period where the technology is initially "overrated," followed by "disappointment," then a "bubble," before ultimately transforming the world. He emphasized that this progression mirrors the development of autonomous vehicles, which faced similar cycles of public perception and technological maturation. Airbnb CEO Brian Chesky has reportedly echoed similar sentiments regarding AI's long-term impact.

Recalling the self-driving car narrative, Thompson noted, "In 2015, I heard autonomy was 5 years away from taking over the roads." This early optimism was followed by a period of disillusionment, with self-driving cars being "nowhere" in 2020 and a "huge disappointment" even in 2022. However, he now states, "Now, they're quietly a revolution."

The quiet revolution in autonomous vehicles is evidenced by substantial growth in commercial operations. Driverless taxi usage in California has seen an impressive eightfold increase over the last year, indicating a significant shift in adoption. Waymo, a prominent autonomous vehicle company, is actively expanding its commercial ride-hailing services beyond its established operations in San Francisco, Phoenix, Los Angeles, and Austin.

The advancement in self-driving technology is largely attributed to sophisticated artificial intelligence and machine learning, including the use of transformer models similar to those powering large language models. These AI systems enable vehicles to perceive their environment, predict the behavior of other road users, and make real-time driving decisions. While challenges remain, the steady progress and increasing deployment of autonomous fleets underscore the long-term potential of AI in transforming transportation.