The founder of Cruise Automation recently announced their collaboration with General Motors (GM) on the mass production of a “self-driving ready” vehicle. This new model will be based on the Chevrolet Bolt platform and is designed with all the essential features required for autonomous driving, including the capability to navigate, brake, and steer. Currently, around fifty units have been constructed—primarily for the fleet market—with plans for increased production in the future.
While this is certainly a noteworthy achievement, I can’t help but feel that this announcement gives off a competitive vibe, suggesting more of a race to reach a milestone than an actual readiness for a fully functional self-driving vehicle.
Doug Parks, GM’s Vice President of Autonomous Technology and Vehicle Execution, acknowledged the challenges ahead by stating, “There’s still a lot to be done yet.” Indeed, while these cars may be mechanically and electrically outfitted to be “self-driving ready,” they are far from being genuinely autonomously operable.
Creating a vehicle equipped with the necessary components for autonomy is relatively straightforward. Modern automotive manufacturers and tech enthusiasts alike can easily access components like sensors, cameras, LiDAR, navigation systems, and the mechanical parts needed for steering and braking, often available from standard online retailers.
However, the larger issues at play are far more complex. A significant hurdle involves navigating a tangle of regulatory challenges, as governments worldwide must come to consensus and approval—a process that is often bogged down by bureaucratic red tape. Moreover, the need for substantial infrastructure development poses another challenge that is often overlooked in discussions about vehicle technology. The extent of technological advancements and modifications required to rebuild urban infrastructure is enormous.
Perhaps the most formidable barrier, however, is the workforce of tens of thousands of engineers currently engaged at various companies and organizations globally. Their collective goal is to unravel the complexities of Artificial Intelligence (AI), which lies at the core of the entire autonomous driving initiative. Achieving a reliable and controlled level of AI understanding and deployment is paramount before we can even begin to consider the safe, widespread adoption of self-driving vehicles.
But the critical question remains: when will this all happen?
As American AI researcher and writer Eliezer Yudkowsky insightfully pointed out, “By far, the greatest danger of Artificial Intelligence is that people conclude too early that they understand it.”
Could AI ultimately unlock the potential for true full autonomy in driving?
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