From Our Swindon Correspondent:
No, This Simply isn’t Right
From The Guardian
[perfectpullquote align=”full” bordertop=”false” cite=”” link=”” color=”” class=”” size=””]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.[/perfectpullquote] [perfectpullquote align=”full” bordertop=”false” cite=”” link=”” color=”” class=”” size=””]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.[/perfectpullquote]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.
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"We" (who do they mean, Guardian writers, OU professors?) don't need to do anything. We can't predict or plan for things which are going to happen. Progress, they used to call it before that word lost some of its meanings. Occupations come and go. So what. Who thirty years ago could have seen app programmer as a job? Who now is looking around for the expected android robots when the real automation is right there on your phone? By which I mean, don't worry about this future, there isn't a damn thing you can do but hang on for the ride.
(The invisible hand will sort it out.)
This is largely driven by technologies employing machine learning (ML) and big data, what we misleadingly call “artificial intelligence”.
That part, at least, is correct. (Meaning 'I agree'.)
Luddites at the Guardian, who would have thought. We could increase the number of jobs needed by banning tractors and beasts of burden, there-bye creating a huge demand for people to plough by hand. That would have the beneficial side effect of causing mass starvation leading to a reduction in CO2 emissions and an even sharper fall in sales of the Guardian.
Just wait until someone produces a robot that sits on the toilet most of the day, has bad attitude (and hygiene) and just moves a pen from one side of a desk to the other.
Local authority employees will be decimated (not just the 10% factual definition either).