How robots will change the world

Will robots take over?

No but they might steal your job. The rapid advances in artificial intelligence (AI), sensor development and other areas mean that robots are acquiring a range of skills from diagnosing disease to driving cars to understanding natural language that used to be the preserve of humans. That doesn't mean that robots are about to become self-aware and take over, like Skynet in the Terminator films.

In real life, robots and AI remain tools, not overlords. But the threat of economic dislocation is real and growing. "We are approaching the time when machines will be able to outperform humans at almost any task," reckons Moshe Vardi, professor of computer science atRice University in Texas. "Society needs to confront this question before it is upon us: if machines are capable of doing almost any work humans can do, what will humans do?"

Is that a bit overblown?

Not necessarily. The point is that AI machines don't need to be more intelligent than humans to transform the job market and society. They only need to be intelligent enough to make using them more efficient and cost-effective over the long run. Google's announcement that its DeepMind technology had defeated one of the world's highest-ranked champions at the ancient Chinese strategy game of Go made headlines earlier this year a striking example of the advances being made. The reason that the feat was so remarkable, according to Martin Ford, author of the prize-winning book Rise of the Robots, was that "the system largely trained itself to do so".

Subscribe to MoneyWeek

Subscribe to MoneyWeek today and get your first six magazine issues absolutely FREE

Get 6 issues free

Sign up to Money Morning

Don't miss the latest investment and personal finances news, market analysis, plus money-saving tips with our free twice-daily newsletter

Don't miss the latest investment and personal finances news, market analysis, plus money-saving tips with our free twice-daily newsletter

Sign up

Why's that so significant?

Because it is "machine learning" the branch of computer science that studies how computers can learn, analyse and make predictions dynamically, without being explicitly programmed to do so that is driving the explosion of applications in robotics and software automation. Everyday examples of applications that draw on machine learning include spam filtering, search engines, and personal assistants such as Siri, Cortana and Google Now.

"The near-term future is likely to be transformed not by general purpose robots or AI systems, but rather by a nearly limitless number of specialised applications," says Ford. Collectively, these systems are likely to span the economy, "ultimately consuming nearly any kind of work that is on some level routine and predictable".

How will this work?

Until now, the type of robots most familiar in a work environment are the expensive, high-precision industrial machines often used to perform repetitive, pre-programmed tasks on manufacturing assembly lines. In the future, robots (and "cobots" that work alongside humans in industrial settings) will become cheaper, more flexible, and able to adapt to their surroundings. Examples include Tug (a robot that moves supplies round hospitals), Savioke (which handles deliveries to hotel rooms) and Locus Robotics (which operates in warehouses).

Who stands to lose their jobs?

Vast swathes of the industrial and services sectors, and white-collar workers whose jobs involve routine information analysis and manipulation. Automation and the march of the robots will hit the rich world hard, and the poorest countries even harder. Research by the Oxford Martin School and Citi, for example, found that 47% of jobs in the US were at high risk of automation or "computerisation" over the next two decades.

However, the researchers found that the figures for developing countries are likely to be even higher, naming Nepal, Cambodia, Bangladesh, Guatemala and Ethiopia as examples of highly exposed countries, along with China (77% of jobs affected). This is based on the prediction that the rise of automation and other technologies, such as 3D printing, will mean more firms bring manufacturing back to their home countries, leaving developing nations at risk of "premature deindustrialisation".

What will the consequences be?

If we fail to start adapting, it means grim times ahead, and intense socio-political struggles over resources. As Stephen Hawking put it last year: "Everyone can enjoy a life of luxurious leisure if the machine-produced wealth is shared, or most people can end up miserably poor if the machine owners successfully lobby against wealth redistribution."

In his forthcoming book Homo Deus: A Brief History of Tomorrow, the historian Yuval Noah Harari predicts the rise of what he calls the "useless class". That's the coming class of aimless and jobless humans who don't know what to study because they have no idea what skills will be needed by the time they've finished; who can't find work because there are always cheaper and better robots; and who spend their time taking drugs and sitting around with VR screens strapped to their faces.

Harari is alive to the charge that people have been predicting the rise of the machines for at least 200 years (see below). "It's basically the boy who cried wolf. But in the original story of the boy who cried wolf, in the end, the wolf actually comes, and I think that's true this time."

Reasons to cheer the robots

From the Luddites to Keynes, people have worried aboutmass technological unemployment for centuries, saysThe Economist. But even if a wave of automation sweepsthe world, total employment may not fall. Innovation couldslash prices and thus stimulate incomes indirectly andboost demand for new jobs elsewhere.

So when we hearof robots taking our jobs, "the reaction should be to cheerrather than sneer", agrees Chris Giles in the FT. Yes, thewave of innovation might affect employment but it standsto boost productivity and growth. "This would enableeveryone to be better off so long as public policy toolswere devised to ensure a fair distribution of the spoils."