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A robot moves ore samples around in the assay lab at Newmont Mining’s Carlin gold mine operation near Elko, Nevada, on May 21, 2014. (RICK WILKING/REUTERS)
A robot moves ore samples around in the assay lab at Newmont Mining’s Carlin gold mine operation near Elko, Nevada, on May 21, 2014. (RICK WILKING/REUTERS)

Agenda 2020

Will robots make us all redundant? Add to ...

But I’ve also read Erik’s excellent book on the causes of the stagnation and increasing inequality we’ve seen over the past couple of decades. And I wonder if technology is at the heart of it, or is it really the case that the rich have taken off [in building their wealth] and, in contrast to previous periods, not taken a group of people with them?

What new industries or job categories might we see in the second machine age? What are the opportunities for humans?

EB: I find this question a lot harder than where the technology is going or even which existing jobs it’s affecting. The new jobs that it’s creating are hard to predict, and I think that 150 years ago, many people would have had difficulty predicting the new industries and jobs that ultimately arose.

The way we historically have solved it is we’ve crowdsourced it. We’ve asked hundreds of thousands of entrepreneurs to answer that question, and they’ve come up with a lot of different answers. Some of them are very silly, and some of them are very successful. Henry Ford and Steve Jobs and Bill Gates and many others have come up with entirely new industries that employed a lot of people.

I will make an effort to describe some of the categories. There are some creative tasks and inventing new things – ideation, some people call it – that machines aren’t very good at, at least not currently.

There’s also a set of categories involving interpersonal relationships: motivating people, comforting people, caring for people. These are things that machines have not proven very good at.

A third category is routine motor skills, fine motor control – the kinds of things that a barber or a gardener or a cook or a janitor does. You don’t necessarily think of them as very high-paid or prestigious jobs, but they involve manipulating the world, and machines are still incredibly bad at those kinds of tasks.

So all three of those are categories where we’ll continue to see some job growth. Now, will they continue forever? By 2020, I think [job growth in those categories] will probably be pretty good, but you can imagine machines getting better and better in all three as well.

From a strategic point of view, how can companies get ready for what’s coming, and to what extent must they reinvent themselves?

JG: To yield productivity from any of these new innovations, it can never really be done piecemeal. It requires sweeping changes, so much so that sometimes existing companies just don’t have a chance, and completely new ones built from the ground up end up taking over. This is certainly the case in retail. No bricks-and-mortar retailer has successfully transitioned to an online mode. It had to come from elsewhere – Amazon and others, for instance.

The message for companies is this is going to be a rocky road. It’s not clear that these technologies can be exploited in the ways that people forecast by grafting them onto existing firms.

EB: Technology is changing much faster than the skills we just talked about, and organizational structures are changing. Companies need to learn how to be increasingly data-driven, and I’m seeing the big data revolution affecting more and more ways that people make decisions. We did some research where we found that the companies that were embracing this more data-driven approach on average appear to be about 5 per cent more productive and more competitive than the other firms in their industries.

What are some common misconceptions about robotics and other forms of automation?

JG: My guess is that the same mistakes that have been made in the past will be made again. Despite everybody understanding that there’s such a thing as disruption and Moore’s Law [of exponential computing growth] and exponential change, there’s still a tendency to disbelieve the rate of improvement in technology that can occur. There’s still an underestimation of how quickly those barriers can fall, and all of a sudden you face very low-cost competitors and you don’t know where they came from.

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