When Carl Benedikt Frey and Michael Osborne, from Oxford University, published their infamous Future of Employment report, they disturbed one very large hornet’s nest. The cry went out, automation will replace jobs, but more and more analysts are saying that AI won’t destroy jobs.
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They claimed that 47 per cent of the workforce were vulnerable to job losses.
The big criticism of the Frey and Osborne study is that they focused on specific tasks and did not pay enough attention to the overall activities a worker might carry out. So, while some of the daily tasks might be automated, this would theoretically free up time to focus on the tasks that were less likely to be automated.
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Multiple studies have drawn that conclusion. For example, McKinsey, concluded that “while about half of all work activities globally have the technical potential to be automated by adapting currently demonstrated technologies, the proportion of work actually displaced by 2030 will likely be lower, because of technical, economic and social factors that affect adoption.” A report from PwC concluded that “up to around 30% of existing UK jobs are susceptible to automation from robotics and Artificial Intelligence (AI) by the early 2030s, but in many cases the nature of jobs will change rather than disappear.” Finally, a report from the World Economic Forum concluded that while machines will do more tasks than humans by 2025, the Robot Revolution will still create 58 million net new jobs in the next five years.
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But speak to people working in AI, or robotics process automation, people who, as it were, are in the front line and you get a different take. Their view is clear: AI won’t destroy jobs.
There seems to be two sides to the ‘robots won’t take jobs’ argument. One side suggests that robots and other automation tools will enable workers to focus more on the aspects of their job that requires more human skills — such as the ability to engage with customers. The other side argues that AI, robotics process automation and robotics will create new jobs.
For example, dealings with the second of those arguments in a recent interview with Information Age, Jeremy Achin, CEO at DataRobot put emphasis on the sheer volume of data that is required, and he made the bold claim that “there will never be enough data scientists.” So, ladies and gentlemen will be required to work with data and understand it, and some of the work will be automated, but that of “trillions of AI systems that will be out there, some of them will be automatically built by machines and some of them will be built by human data scientists, because some of them entail tougher problems to solve.”
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It’s a kind of percentage game: X% of data tasks will require human involvement. Even if this X% is quite low, there will be trillions of such tasks and a small percentage of trillions is still a big number.
He said: “I think we’re going to move this mindset we call automation to an automation mindset.
“Whether you’re a knowledge worker or a data scientist, every single problem you encounter, every single process that you follow, that you do on a day to day basis, you should be looking at it to see where ‘I can use automation’.”
UiPath comes at this from a different angle, it makes the first of the two arguments. Guy Kirkwood, Chief Evangelist recently told Information Age that “one of the big myths of automation is that it replaces jobs, it doesn’t. Most organisations go into automation because they want to reduce headcount, that’s what they base their business case on and they are all wrong, that doesn’t happen.
“What actually happens is they put in automation and then realise that the value of their people, the value of their human capital, is much higher than they thought it was. So, they re-deploy those people, they raise them up the value chain.
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Indeed, on this theme, he cited Karl Nolan, Chief Executive of Generali Link, who made a somewhat choice comment at a recent event, in which he described what happened after RPA was installed at the company: “The mood music has changed. Our people are happier and we now measure the service in terms of compliments rather than complaints.”
Now Alibaba has waded into the debate. Speaking at the CNBC Conference at the Nansha district of Guangzhou, China, Min Wanli, chief machine intelligence scientist at Alibaba Cloud recently said that Alibaba’s goal was to make workers as smart as power machines, he said: “I wouldn’t call it a job loss, it’s a job transformation.”
They are all right, until some day when computers can do absolutely everything we can do, the application of computers will create jobs.
And they will often displace the boring tasks, freeing us up to do the more fun stuff, the stuff involving human engagement.
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And maybe, in a truly ideal world, we can find some happy medium with new tech, so that some of the productivity benefits it brings can be used to create more leisure time.
But the economy is a complex beast. History tells us that there were long time lags between the industrial revolutions of the 18th, 19th and very early 20th Century and a rise in median wages.
Not all displaced workers will have the skill sets to work as data scientists or apply AI to their benefit.
One of the most important tasks facing governments — one furthermore that they are far from grappling with — is to ensure that the fruits of the the fourth industrial revolution ripen sufficiently fast so that we can jump from a pre Al and robotics age into the new age as seamlessly as possible. Disruption of business is to be welcomed, disruption of people’s lives needs to be managed with care.
