Why deep learning won't give us level 5 self-driving cars

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. "I'm extremely confident that level 5 [self-driving cars] or essentially complete autonomy will happen, and I think it will happen very quickly," Tesla CEO Elon Musk said in a video message to the World Artificial Intelligence Conference in Shanghai earlier this month. "I remain confident that we will have the basic functionality for level 5 autonomy complete this year." Musk's remarks triggered much discussion in the media about whether we are close to having full self-driving cars on our roads. Like many other software engineers, I don't think we'll be seeing driverless cars (I mean cars that don't have human drivers) any time soon, let alone the end of this year. I wrote a column about this on PCMag, and received a lot of feedback (both positive and negative). So I decided to write a more technical and detailed version of my views about the state of self-driving cars. I will explain why, in its current state, deep learning, the technology used in Tesla's Autopilot, won't be able to solve the challenges of level 5 autonomous driving.