Self Driving Car Ethics

977 Words 4 Pages
Introduction
A self-driving car (also referred to as an autonomous car, driverless car, robotic car) is a vehicle capable of navigating without a person's input. It can detect its surroundings using various techniques; radar, laser lights, GPS, odometry and computer vision. This car contains advanced control systems that interpret sensory information that consequently identify suitable paths, as well as detecting obstacles and relevant signage. Self-driving cars are already becoming the new street sensation with the leading tech titans Tesla and Google spearheading the innovation (Goodchild, 2012). However, the carmakers have a huge challenge of ethical dilemma of algorithmic morality to address before these cars can be embraced. The reoccurring
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Although, they cannot be perfect and 100% safe. Collisions remain unavoidable bearing the fact that they will be driving at high speeds in the midst of the streets busy with pedestrians, cyclists, and human drivers. For this reason, self-driving cars need to be programmed on how they should respond to scenarios where collisions are unavoidable. We critically look at this tempting analogy in this piece of work. We visit the task faced by those responsible for programming those cars and why the programmers should gear towards saving more lives even at the expense of individuals on board those vehicles (Gogoll & Müller, 2017). We look at legal and moral obligations and essential decision making in the face of uncertainty. Wendell Wallach and Colin Allen wrote when discussing a kind of autonomous vehicle: “…could trolley cases be one of the first borderlines for artificial morality? Systems without drivers put machines in positions to make split-decisions that could have life or death consequences. As the traffic becomes more complex, the likelihood of dilemmas similar to the trolley case going up also increases” (Wallach W, 2009). Economist and psychologist Francois Bonnefon, Azim Shariff, and Iyad Rahwan wrote: Situations of Unavoidable harm, as demonstrated in (our examples of crashes with autonomous cars), bear outstanding resemblance with flagship dilemmas of experimental …show more content…
These algorithms consider the inevitability of crashes and seek to "optimize" the crash. By "optimize," a crash-optimization algorithm enables a self-driving car to decide a crash that would cause the least damage or harm. Crash optimization options have the advantage of reflecting on ethical fixes in contrast to the view from a driver's seat which is guided by reaction and reflex more than

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