By 2050, driverless cars and mobility as a service will grow into a $7 trillion worldwide. So if the millions of people making decisions on the road, how will A.I. handle that? Driverless cars have many benefits and from 2035 to 2045 consumers will regain up to 250 million hours of free time that was previously spent from behind the wheel, $234 billion in public costs will be saved by reducing accidents and damages due to human error, and driverless cars can eliminate 90% of traffic fatalities – saving 1 million lives every year. But in cases of a crash, how will driverless cars determine whose life is to be spared?
Driverless cars “must decide quickly, with incomplete information, in situations that programmers often will not have considered, using ethics that must be encoded all to literally” said Noah J. Goodall, Senior Research at the Virginia Transportation Research Council. In a global study, most people preferred A.I. to swerve rather than stay on course, spare passengers over pedestrians, and that the A.I. should save as many lives as possible in any case. Participants were most likely to spare the life of a child, and least likely to spare animals and criminals.
Driverless cars will save lives, but programming them to do so could slow their adoption and cost many more lives. Real life applications grow even more complex – in an accident that causes injuries but not fatalities, should A.I. distribute injuries evenly, harming more people less severely, or should it consider the likelihood and severity of potential injuries, or should it take into account the quality of life affect of resulting injuries, or should the A.I. have to decide if it is better to hospitalize five or should it kill one?
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Infographic Source: Cybersecurity Degrees