Can we trust Tesla’s Autopilot feature and the organization’s quest for self-driving?
. If the system requires any element of human supervision or oversight, it is simply not self-driving, but rather assisted driving. Nonetheless, Tesla’s technology prowess in system architecture and data capture has perhaps accomplished what others have not yet found feasible and could revolutionize edge case discovery.
One can bemoan regulatory hurdles for slowing progress, but there is a public expectation that technology, sensors and algorithms have been proven to ensure a level of safety. As andiscusses, we have yet to clearly define what success looks like in our race to autonomy. Musk himself states, “it might need to be like two or three hundred percent safer than a person.” He also discusses that the incidents needed to prove safety are rare, requiring a lot of data.
What makes things even more difficult is that it’s easy to count crashes, but it is hard to count near misses and incidences avoided , making the statistical interpretations of where and when a system provides advantages over humans a complex science. Counting incidents per mile as a simple aggregate ignores aspects of risk such as vehicle type, model year, owner profiles, driving location and a host of other factors.
A well-validated estimate of risk associated with Tesla’s Autopilot, now a three and a half-year-old assisted driving system, remains elusive. Although the system has been used for over
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