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From Tesla, a parable of data collection

Data centre

The interior of the Tesla Model S offers a glimpse of the data-rich driving environments of tomorrow. (Tesla Motors)

In the ping-pong battle between the New York Times’ John M Broder and Tesla Motors’ irrepressible chief executive, Elon Musk, a remarkable fact was taken for granted.

Stemming from Broder’s fraught drive between Washington, DC and Boston in the purely electric Model S sedan, during which the reporter suffered multiple bouts of battery-range anxiety, reams of data were collected by the vehicle on everything from throttle pressure to battery depletion. Musk has refused to release this data, but the fact that a passenger vehicle would collect it at all underscores a change in what we trust our cars to do.

Passenger vehicles can and will collect very specific data on our driving habits. This data can be stored, analysed and used to ascertain fault in accidents, speeding cases and manufacturers’ gas mileage claims; it can also be used to take proactive measures to avoid collisions. Some of this data collection and processing ability exists already, but it is nowhere near as robust as it will soon become.

First, a look at the data-driven tools already used by passenger vehicles.

Technology as a tool

Adaptive cruise control uses radar and sensors to determine the distance from a driver's car to the one in front of it. When it receives that information, it determines whether the car should maintain its speed or slow down. Systems like Volvo's City Safety accident prevention system are further evolutions of this, able to sense obstacles and apply brake pressure to avoid or lessen the impact of collision. Both systems apply information culled from a car's surroundings and in a stopping or slowing scenario.

In coming years however, cars will communicate with multiple vehicles in their vicinity, exchanging speed data, assessing possible risks and using algorithms to avoid, and calculate the risk of, collisions. Cars will not merely collect data about themselves, they will collect data about everything around them to help drivers make decisions. In some cases, cars will make the decision for them.

The question that may nag at motorists is how implicitly such technology can be trusted. This reckoning is already at hand in the form of so-called autonomous vehicles. Google's autonomous cars collect reams of data and manoeuvre based on that information. The company’s engineers have done such a thorough job of controlling for various factors that the vehicles have never had an accident under computer control.

Drivers already put an enormous amount of trust in their vehicles and for the most part our cars perform their tasks extraordinarily well. Whether this trust endures as cars take over more functions from drivers remains to be seen.

The human experience
Anyone who has ever booted up a computer or opened an app knows that the data presented is not always accurate. Our computers and smartphones freeze, our apps crash and our files get corrupted. The same applies to our vehicles. Technology has already made cars safer and more efficient, but as more data technologies migrate into the car, there will be more possibilities for misreporting of information or just plain failure.

That is why every Google car has a manual override, and why autonomy will be gradually integrated into vehicles. Technology, in other words, will not be allowed to trump a driver's ability to make decisions, at least not for the foreseeable future.

For now, we can choose to trust data when we can assess it accurately, or discard it when we think it is wrong. But in a few years, presuming data collection has become better honed, disputes like the one between Tesla and the New York Times may not even have the opportunity to surface.