Human Vs AI: Where Will Blame Lie in Autonomous Vehicle Accidents?

Responding to the publication yesterday of media reports into the causes of the fatal accident in March involving an Uber autonomous vehicle and a pedestrian in Tempe, Arizona, Nigel Brook, partner with global law firm Clyde & Co, said:

“An autonomous vehicle has to interpret its changing surroundings so as to navigate roads while avoiding collisions. But can the AV’s systems rapidly distinguish between a ‘false positive’ such as plastic bags blown by the wind from a real threat? If the systems are too ‘neurotic’, the ride will be jerky and uncomfortable; too relaxed, and the car could fail to react to real danger. This is one of the fundamental challenges faced by all AV developers, not just Uber.

“Training the algorithms currently requires millions of miles of driving – and there are commercial pressures on the various companies competing to be first to market.

“This incident could also prove to be a test for regulators, and for local authorities hosting trials. For example, should they insist that two people are always present in the vehicle rather than one? Would this make it any safer in practice?”

Commenting on the challenge of interpreting data, Brook added:

“There are lots of things humans find very easy and machines find very hard – such as picking one type of object out of a bucket containing multiple objects. Through years of experience, our brains develop an impressive ability to process images and work out what is happening without any conscious thought. Machines struggle in this regard – and this is where the real challenge lies.”

Clyde & Co has published a serious of white papers on the development and implications of autonomous vehicles. Its Manchester-based Casualty team works for many of the UK’s leading insurers in managing vehicles accident claims.  

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