As stated by the article, The Data Science Behind Self-Driving Cars, self-driving cars were science fiction only a decade ago. It is no surprise how quickly technology evolves and advances. Within the span of 18 months, Google launched and developed its self-driving car project. Soon after Tesla joined, building automated features into their vehicles and Uber and Lyft started investing in making ride sharing autonomous. In order to simulate a human brain, self-driving cars use highly detailed maps of street features, sensors and cameras such as LIDAR, cloud communications, and sensory inputs into the vehicle’s machine learning algorithms. Self-driving cars have a lot of positive aspects, some including the reduction of car accidents, improving road safety, environmental benefits and fuel-efficiency, and easing traffic. However, self-driving cars do have their limitations as well. The largest one being the millions of truckers, cabbies, and drivers that will eventually be put out of work as autonomous cars start replacing humans. In addition, self-driving vehicles are vulnerable to hacking because of the advanced computers they contain or could potentially malfunction. What I find most interesting is who is to blame when a self-driving car has an accident. As these cars increase in popularity, the question of legal liability remains. From the legal responsibilities of the driver and the issues of over trusting drivers and system misuse to the legal responsibilities of the car maker that built the self-driving car, self-driving cars have a long way to go before they become a part of our everyday lives.