The carmarker reckons it can use big data and new technology to predict where car crashes will occur before the accident happens.
What it means: There are lots of good things about cars: they ferry us around with speed, comfort and convenience. But there are lots of bad things about cars as well, not least that they are the reason that 1.25 million people lose their lives every year. Car crashes also injure a further 20-50 million people.
The consequence is not only untold grief and suffering, but economic losses: families losing their main income source, say, or high healthcare bills (which in countries without government-provided services can push people into poverty). Even non-harmful accidents have severe consequences; the cost of car repairs or losing their main mode of transport can cause serious financial hardship to many people. Almost two-thirds of Americans would have to go into debt to cover an unexpected $500 expense. And for people who use their car to get work, sending it to the garage could mean they lose their job.
Now the carmaker Ford says it can reduce the economic and social impact of car crashes by equipping vehicles with data-collecting sensors and combing through the readings for “accident black-spots”. These aren’t necessarily places where accidents have already happened, but perhaps a place where lots of vehicles brake suddenly, suggesting that it could be a blind spot for oncoming traffic. Ford has already tried its idea out with a van fleet in London. Presumably the idea is to sell its findings to groups who have an interest in improving road safety: like local councils and governments.
…So where next? Not only do economic ideas shape the institutions and communities we live in, they also influence our own ideas of personal success – be it earning well, achieving a ‘Dr.’ or ‘CEO’ at the front of our label, or living a sustainable life. But what with the speed at which technology is transforming our economies, we can barely predict what ‘s in store for our economies and where we’ll fit in…