White-collar jobs threatened by automation
The ‘information revolution’ is set to bring immense change for white-collar workers, just as the industrial revolution saw sweeping changes across the workforce.
Speaking to ifa’s sister publication, Fintech Business, professor of artificial intelligence at the University of NSW Toby Walsh discussed the impact technological automation will have on employment and financial services.
One of the impacts professor Walsh said we need to worry about is the impact technology will have on employment.
“The chief economist of the Bank of England said [last month] that he thought about 50 per cent of jobs in the UK are under threat of automation,” he said.
“We used to think that it was going to be the blue-collar jobs, the people working in factories, that were most under threat. And that’s certainly been the case – if you go to a car factory a robot’s doing the painting, a robot’s doing the welding.
“But now middle-class, white-collar jobs are under threat.”
Professor Walsh pointed to the example of finance journalism, where a majority of financial reports that now go down the wire are written by a computer with “quite plausible and readable paragraphs of text”.
Pointing to financial services specifically, he said it is one of the industries where consumers have precipitated the changes.
“I can’t remember the last time I went and actually used a real person and a real cash register,” Professor Walsh said.
“Then there’s the fact that we used ATMs from a very early age. We bought into the idea that these things could be automated.
“We do the same thing now in supermarkets, airport check-ins. You can see that the service people are on the way out,” he said.
The rise of robo-advice could help reduce the significant advantages enjoyed by wealth people and institutions, he added.
“With artificial intelligence and these sorts of technologies you will be able to get better advice for less money. So it will help us all do better,” Professor Walsh said.
“There’s no reason to believe that you can’t build a trading algorithm that would trade as well as a very good individual.
“It’s a great area to play in because you have all this wonderful historical data, so you can train algorithms very well.”
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