From Our Swindon Correspondent:
No, This Simply isn’t Right
From The Guardian
We have now lived through what one might call Automation 1.0. The paradigmatic example is car manufacturing. Henry Ford’s production line metamorphosed into Toyota’s “lean machine” and thence to the point where few humans, if any, are visible on an assembly line. Once upon a time, the car industry employed hundreds of thousands of people. We called them blue-collar workers. Now it employs far fewer. The robots did indeed take their jobs. In some cases, those made redundant found other employment, but many didn’t. And sometimes their communities were devastated as a result. But GDP went up, nevertheless, so economists were happy.
Now we’re embarking on Automation 2.0. This is largely driven by technologies employing machine learning (ML) and big data, what we misleadingly call “artificial intelligence”. The types of job it targets are different from those addressed by Automation 1.0: they have some cognitive content but also a lot of routine. We call them white-collar jobs. And the new machines can often do them adequately or well.
It’s rather worrying that someone who is a professor of public understanding of technology at the OU can get this so wrong.
Sure, computers powering robots in car factories wiped out jobs doing welding and painting, but they also wiped out a great deal of other work around the same time or slightly earlier. People who hand typed bank statements, people who calculated interest. The typing pool was destroyed by word processors, the people in bank branches because of ATMs and direct debits. Bank managers became far less of a critical job as we got the computers doing credit scoring.
The reason this wasn’t noticed in organisations like banks or local authorities is that the service sector was expanding at the same time and organisations got the typists doing something else instead. And while manufacturing actually expanded under Mrs Thatcher (in value), it wasn’t at the same sort of rate.