The question of liability is a fascinating issue that can be answered with the classic phrase every lawyer learns in law school: ‘it depends’. Nevertheless, the current reality seems to be that the closest human tends to be blamed. For example, an article by Bloomberg, published in May 2019, describes an ongoing lawsuit, where a Hong Kong businessman lost over $20 million after trusting a large amount of his wealth to an automated investment platform. Without a legal framework to sue the technology, the businessman decided to blame the nearest human: the man who sold him the automated platform.
Although this is the first case concerning automated investment losses that has come to light, it is not the first one involving questions about algorithms’ liability. In 2018, Uber was testing a self-driving car in the United States that collided with a pedestrian and led to the pedestrian’s death. The car had been in autonomous mode at the time of the collision, and a safety driver had been sitting in the driver’s seat. The case went to court and a year later, Uber was cleared of criminal liability. However, the safety driver could still face a charge for vehicular manslaughter. The presented examples suggest that humans may be used as a ‘liability sponge’, as researcher Madeleine Clare Elish puts it, absorbing legal responsibility in cases that involve AI, regardless of the extent of their involvement in the course of events. This seems to be the direction we are headed towards in the handling of liability issues when AI is involved. A potential risk of this direction is that it may create uncertainty and hinder development of AI based products. Legislators and governmental institutions should therefore provide guidance on the matter to help innovators feel more secure when navigating the minefield-like world of liability.