I just read a really interesting Bloomberg Businessweek article about Starsky Robotics. Founded in 2015, the startup is pairing experienced long-haul truck drivers with machine learning experts and programmers to build a new system of trucks that will be autonomous on interstate highways and remote-controlled by humans on surface roads. Almost 8 million jobs in the US are tied to trucking. Max Chafkin and Josh Eidelson write:
Three and a half million Americans drive trucks for a living, making it one of the most common jobs in America. The larger trucking economy—including cargo brokers, truck manufacturers, truck stop waitresses, and so on—accounts for an additional 4 million jobs, according to the American Trucking Associations (ATA), a trade group. A huge proportion of them are threatened by a decade of driverless research coming out of universities and Silicon Valley companies.
A truck traveling hundreds of miles to make a delivery represents an almost ideal application for the latest autonomous driving technologies. Long-haul truckers spend much of their time on interstate highways, where curves are gentle, lanes are well-defined, and pedestrians and bicycles—the bane of any AI vehicle engineer—are prohibited. Trucks are big and heavy, so they’re easier to outfit with special sensors needed to control them. All of this has caused trucking to be seen by automation experts, and in the popular press, as a test case for the impact of AI on employment.
There are many fascinating aspects to this article. The connection between bits-and-atoms reminds me of the way Amazon tackled logistics and the messiness of handling physical packages while eBay was purely in the digital space. The concern for humans and the desire to bridge the gap between the coastal elite programmers and red state truckers. The questions about how machine learning is actually impacting the world in the near term while still thinking about big questions for the future.