Speaking with Techworld, Bill Ruh – also the CEO of General Electric Digital – warned that there are two major downsides to the oncoming wave of change that will be forced by emerging technologies.

“One is: what jobs are going to get displaced, and which jobs are going to be enhanced?” he asks. “We know that we’ll automate mundane and dangerous jobs – I think that’s absolutely the case. The fact is we don’t know how far that’s going to go.”

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Image: Flickr Creative Commons/mjb

However, he said that it may not be as “negative” as some of the naysayers around automation claim – as some jobs will be “enhanced” by technology rather than replaced entirely.

“These jobs will get augmented – we’re going to see a ton more jobs needed for how people in companies with no digital DNA, they’re going to have to hire a ton of digital-industrial people, so we’re going to see a change in the makeup of jobs. The world is going to have to adapt to that.

“That’s a very uncomfortable place. Change is uncomfortable. But I don’t see it as dire – not all jobs are going away, there will be a lot of creation of new jobs – I don’t think we know how that fully plays out.”

Ruh is well placed to provide this insight. General Electric provides much of the industrial machinery that shapes our world, and it is increasingly providing the analytics software to make the most of the data extracted from those machines.

Industrial revolution

For several years now, it has become increasingly evident that many of the ‘traditional’ jobs known to us in the 21st century – whether blue-collar or white-collar – could be threatened by new technologies, if not replaced outright – as 60,000 Foxconn factory workers just have been. The combination of the internet of things, big data, automation, machine learning, and AI is spurring businesses to refer to the present period as the next industrial revolution.

And just like the first industrial revolution which began in England, some soothsayers are, perhaps rightly, proclaiming doom and gloom. Leaps in technology are able to vastly increase productivity but, at the same time, they can be held to account for failing to benefit workers.

Germany has termed the current digital phenomenon as “industry 4.0” – an economy whereby connected machines and systems are creating intelligence across the full business, working together towards autonomous control.

The general principle is that it’s better not to smash, sabotage or turn our backs on the machines – as the luddites did, with reason, more than 100 years ago – but to understand that this change is taking place and formulate a response to it. This will be equally true for businesses, the workforce, and the state itself.

“I think at a country level, and at a company level, this is going to have to be embraced, and the impact will be: there will be winners and losers,” Ruh claims. “Those who embrace it, those who put digital organisations in place, those who find the right talent... the ability to be able to harness it will determine whether you win or lose.”

Human judgement

At the same time, it’s going to be important not to place all of our trust in the machines. Take the propensity for people to Google a question rather than hash out their own response.

“The big risk that people are ignoring is that people will begin to do their jobs where they believe the machine entirely,” Ruh warns. “I will say this: no matter how good the analytics are, or how much insight you get, people still need to be engaged in making the decisions and flying the plane.

“You have to train people not to let the automation be their guide on everything – good human judgment comes into play,” he explains. “I think the idea of human judgment being trained into people so the automation doesn’t become a crutch to what they do is really the difficult scenario we will be dealing with.”

There are times when people will have to understand that the data the machine is working with does not make sense – and bad data will lead to a bad judgment call. “I think that we’ve got to be cognizant that the machine is not all powerful,” Ruh says.

What next?

“Look, I think general-purpose machine learning has a place and on the industrial side we think it’s going to be e-machine learning, but there’ll be physical models,” Ruh explains.

One of these physical models will be the ‘digital twin’ – the idea that for every machine borne out from every factory, there will be a shadow, mirror image of that product in the digital realm. And these will be able to speak with one another to create new systems, to optimise themselves and each other.

“We’re already seeing that where we have twins of wind turbines and wind farms, we’re seeing the ability to generate 20 percent more electricity with less maintenance than you would have had otherwise,” Ruh says.

“I think the future is even to the point where a human being might be born with a digital twin. And this will allow us to do real preventative maintenance. With a digital twin, we’ll be able to predict not only machine maintenance, but preventative health for humans.”

“I think we’re probably 20 years out – the human machine is much more complicated than any of the others.”