Rather than consigning employees to the dole queue, AI and machine learning tools could free people from admin tasks and lead to more fulfilling work.
This excerpt comes from an in-depth article featured in the Guardian as part of their Work Smarter series – a collaboration between SAP Concur and the Guardian. For more great quality content and advice on ways to introduce greater efficiency into your business, visit the Work Smarter hub.
Spare a thought for all those poor cyborgs and androids. When they were merely exterminating the human race, as portrayed in countless sci-fi films, we looked upon them in awe and admiration. But now, faced with the prospect of robots stealing our jobs, we’ve come to loathe them. The effect that AI and machine learning will have on jobs, however, is likely to be more nuanced than many internet scare stories would have you believe.
“We’ve spent way too much time thinking about jobs that computers are going to take away from people, and not nearly enough time thinking about people and computers,” says Prof Thomas W Malone, founding director of the MIT Center for Collective Intelligence and author of Superminds: The Surprising Power of People and Computers Thinking Together. “That is, the new kind of jobs that will be created when computers do some things so much better, faster and cheaper.”
There is clearly a pressing debate to be had about the future of those of us who might lose our jobs due to AI and then struggle to find quality replacement roles. But Malone believes this issue, although important, will be “far less apocalyptic than many people seem to be expecting”. Rather than consigning human beings to the dole queue en masse, AI and machine learning could automate many of the more mundane tasks employees currently have to perform, leaving them free to pursue more fulfilling work.
Take data entry, for instance. Nobody enjoys keying information from invoices and expense claims into a spreadsheet. It’s dull, time-consuming and utterly unimaginative work. So why not let a machine do it? Unlike humans, they don’t get bored or tired, which means errors are far less likely to creep into the expense reporting process. And businesses could also save money by reducing the labour costs associated with these tiresome tasks.
This isn’t another case of wishful future-gazing; it’s already happening today in many businesses. Machine learning algorithms are capable of processing vast amounts of both structured data (such as spreadsheet fields) and unstructured data (such as emails or images) faster than any human being. They learn through a trial and error process, and the more data they access the more accurate they become – to the point where they are able to draw their own conclusions about what should go where, or why “A” doesn’t match “B”.
Machine learning algorithms developed by SAP Concur, for example, access millions of aggregated and anonymised corporate travel and expense transactions on a daily basis. “In Q3 of 2018, we processed more than $115bn [£87bn] in expenses,” says Rachel van der Merwe, director of product marketing at SAP Concur, “so there’s a lot of volume and spend that’s going through our system. That helps this technology become much more accurate.”
This is just a snippet of the whole story. Read the full Guardian article here.