The China Syndrome

Industrial robots: thousands of new firms, or mass unemployment?

Will industrial robots sweep aside millions of human jobs, or create thousands of new smart businesses? Chris Middleton contrasts the automation of China with the emergence of ‘PAL’ organisations.

Last year, China bought 66,000 industrial robots. That might not seem like a huge number for a country of over a billion people, but when you consider that each of these machines can do the jobs of 15 or more full-time employees, the impact begins to look more significant: it means that 66,000 robots could potentially do the work of one million people.

China purchased one-quarter of all the industrial robots manufactured in 2016. So, using these figures, we could make a reasonable claim that manufacturing jobs alone may be falling to the machines at a rate of four million a year worldwide. By 2019, 1.4 million new industrial robots will be installed in factories around the world, according to the International Federation of Robotics.

On the face of it, that’s 21 million human jobs being replaced by machines in just two years. Society isn’t prepared for these kinds of statistics, and people are understandably worried about the damage that mass automation could do to employment and the social fabric. But is the reality so simplistic? 

Between 2010 and 2015, US car makers also installed more than 60,000 industrial robots and the number of human workers rose by 230,000 in that sector, according to UK-RAS, the organisation for robotics research in the UK. This runs counter to the perception that industrial automation equals mass unemployment.

And this doesn’t include the new enterprises that spring up in a technology’s wake; consider how many new businesses the internet and mobile phones have created in the past quarter century.

But one thing is certain: the adoption curve of robotics and AI can only get steeper. Industrial robots are no longer dumb, single-purpose machines; they’re becoming programmable platforms that can carry out a range of increasingly complex tasks. In this way specialist human processes that have evolved over years – even centuries, such as farming – can be replicated with an app. Few industries are immune to the march of the machines.

The Chinese equation

In China, the human population is falling, even as the machine population grows. China is industrialising fast to further its ability to manufacture goods faster and cheaper than the West, but also automating faster than any other economy to retain its value proposition. Costs are rising as a new urban middle class booms within its borders, just as it did in the UK during the industrial revolution.

Robots promise to keep those costs down, or so China believes. This is the reason that many industries are automating, often without considering the human consequences.

At the moment, China is a long way behind countries such as Germany and Sweden in terms of its robot density – the number of robots per 10,000 human workers. Sweden has a robot density of 200 and China’s target is 150. In China’s case, however, that means a strategic goal of up to 650,000 robots, each doing the work of 15 or more people – 10 million jobs – while perhaps creating 2.5 million new ones (using the US car makers’ example).

The rise of the machines, then, can be boiled down to simple maths – if you ignore the potential impacts on human society. On the face of it, the figures suggest that within large manufacturers, automation may create 2.5 skilled jobs for every 10 unskilled jobs it replaces.

Similar processes will happen across many industries. Robotics, drones, smart IoT devices, and autonomous vehicles are already beginning to transform social and health care, critical infrastructure maintenance, transport, law enforcement, the military, and more.

But even this is not the full scale of the challenge to human society – or the business opportunity, depending on your perspective. Thanks to Moore’s Law and similar effects, robots can only get smarter, faster, more efficient, and cheaper, and will eventually begin building and upgrading themselves. Industrial robots may become 20 per cent cheaper over the next five years and 20-30 per cent more efficient, according to Boston Consulting, although there are already examples of a single platform upgrade reducing an automated task’s duration from minutes to seconds.

Inevitably, China itself is starting to manufacture industrial robots, too, so within a decade these machines may be available at half the cost of current models. By then, each robot may be a fully customisable platform that’s able to do the work of 20 or more people – without falling sick, taking a holiday, or starting a family.

All of this poses a real challenge to developing economies that want to follow China’s example by creating new human jobs and wealth, lifting millions out of rural poverty. For unskilled workers, at least, the future doesn’t look bright.

And, of course, robots can be software, too: back- and front-office applications that automate business functions in sectors as diverse as the media, or financial and legal services, often enhanced by a mix of AI, big data, analytics, and enterprise asset management. So it’s not just blue-collar jobs that are falling to the machines, but also white-collar careers – not to mention post-industrial jobs, such as call centre work. What happens to local employment opportunities if the UK’s one million call centre workers are replaced by chatbots, for example?

A new world of opportunity

Yet despite the sometimes alarming statistics, robotics, AI, and automation are not the zero sum game that apocalyptic thinkers and tabloid newspapers like to imagine: they also create human jobs and open up opportunities for new types of lean, smart business. As long as organisations focus on deploying the technologies strategically to enhance and complement human society, rather than tactically to sweep workers aside and slash costs.

This ‘threat or promise?’ aspect of robotics was the subject of a packed summit in London on 4 September 2017: Rise of the Machines, hosted by The Crowd – a kind of TED for sustainability specialists. Delegates were a Who’s Who of blue-chip businesses and government organisations, and they heard presentations by robotics, AI, and business transformation specialists before breaking out to debate questions such as: How will robotics and AI impact on sustainable development goals (SDGs)?

Sean Culey, consultant and executive VP of Manucore, gave the keynote, in which he described the traditional concepts of manufacturing, manual labour, and even ownership being swept aside by a wave of “creative destruction”. Culey says we’re in the trough before the big wave hits, the disruptive crunch-point before future opportunities fully emerge on the crest of new ideas.

The future it brings will be about ‘PAL’ he said: Culey’s acronym to describe businesses that are personalised, automated, and localised, in which a single prototype is as simple to produce as a million finished products, enabled by big data, robotics, the IoT, and 3D printing. He used the example of Carbon, a Silicon Valley startup* that has been developing new lines of shoes for Adidas. Watch this video for more.

Outside the event, Culey set out his PAL vision: Personalised through mass customisation and on-demand manufacturing, combined with devices that remember personal preferences and AI systems that predict what you want before you want it.

“Automated using autonomous vehicles and smart robotics that pick, pack, and produce goods, while Blockchain technology, robotic process automation, and chatbots handle the administration and customer queries. 

“And localised due the reshoring of production to where consumers are located. As the cost advantages of making, storing, and shipping goods locally – and in smaller quantities – grow, the use of smart machines and on-demand manufacturing will become increasingly pervasive. A micro-logistics network, using warehouse robotics and autonomous delivery methods – from drones to mothership vans that contain delivery robots.”

On-demand manufacturing

In Culey’s PAL model, goods will increasingly be made on demand, reducing excess production, transportation, storage, and waste. The sustainability benefits alone will be massive, he said: Currently we ship products halfway round the world, then drive them to large warehouses, store them, then drive them to smaller warehouses or outlets, and finally they’re either picked up by people who drive to that location, or the goods are transported to the consumer.

Meanwhile, factory managers are often measured on line utilisation and throughput, with production running all day, making large quantities of product that often finds its way into landfill. The carbon emissions and waste from this global supply chain are enormous.

Additive manufacturing greatly reduces the by-products and waste from the production process, and machines operate for the cost of electricity, the cost of which continues to fall due to increased efficiencies from solar and other renewable sources.”

More, the industrial internet will see machines that monitor and optimise their own performance, reducing quality defects and highlighting any excessive energy consumption. Transportation will be greatly optimised through increasingly autonomous electric vehicles, directed by intelligent AI routing systems that direct them to move what’s needed to where it’s needed.

Finally, the rise of digitalisation and ‘servitisation’ business models will greatly increase the utilisation rate of logistics assets; while dramatically reducing the costs.”

China: on the wrong path?

In Culey’s future, the China I described at the beginning of this report seems less like a massive object attracting global business through sheer force of gravity, and more like the apotheosis of an ageing industrial strategy: big manufacturing on a massive scale, with global supply chains, waste, and a relentless focus on cost, rather than diffused, personalised, localised innovation. That’s an opportunity for other countries to exploit.

But the mistake that many futurists make is imagining that the old world stops when the new one starts; the reality is messy, unpredictable, complex, full of legacy as much as promise – the 19th Century landmarks among the Shards and creative hubs. Yet Culey is a pragmatist, not a futurist: he is outlining a new ideal for the smart, sustainable, industrialised world that’s emerging both on the fringes and in the centre.

The wider challenge is to ensure that we don’t try to remodel human society after the fact. We need to think today about directing this wave of creative destruction towards societal advantage and sustainable, ethical development, and not just towards narrow, short-term cost-cuts. That demands a buy-side shift of focus, and a change of tack from the analysts and think tanks.

So, how to ensure that robots enhance human society, rather than consign it to the history books (if such things are still being written then)? A simple idea emerged from one of the breakout groups at the summit: why not use the UN’s Sustainable Development Goals to underpin a legal framework to regulate robotics and AI? That was the suggestion of delegate Sherah Beckley, sustainability specialist at Thomson Reuters.

A brilliant idea. Let’s make that happen.


*: A different company, Carbon Roboticsmakes trainable intelligent robots.
• Chris Middleton hosted a panel at the Rise of the Machines summit. See separate report.
• This article was first published by diginomica.
• For more articles on robotics, AI, and automation, go to the Robotics Expert page.

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© Chris Middleton 2017