The 18th of March 2018, was the day tech insiders had been dreading. That night, a new moon added almost no light to a poorly lit four-lane road in Tempe, Arizona, as a specially adapted Uber Volvo XC90 detected an object ahead. Part of the modern gold rush to develop self-driving vehicles, the SUV had been driving autonomously, with no input from its human backup driver, for 19 minutes. An array of radar and light-emitting lidar sensors allowed onboard algorithms to calculate that, given their host vehicle’s steady speed of 43mph, the object was six seconds away – assuming it remained stationary. But objects in roads seldom remain stationary, so more algorithms crawled a database of recognizable mechanical and biological entities, searching for a fit from which this one’s likely behavior could be inferred.
At first the computer drew a blank; seconds later, it decided it was dealing with another car, expecting it to drive away and require no special action. Only at the last second was a clear identification found – a woman with a bike, shopping bags hanging confusingly from handlebars, doubtless assuming the Volvo would route around her as any ordinary vehicle would. Barred from taking evasive action on its own, the computer abruptly handed control back to its human master, but the master wasn’t paying attention. Elaine Herzberg, aged 49, was struck and killed, leaving more reflective members of the tech community with two uncomfortable questions: was this algorithmic tragedy inevitable? And how used to such incidents would we, should we, be prepared to get?