Automation Threatens Jobs in Poor Nations, and May Propel More Illegal Immigration
02/01/2016
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Smart machines will likely fuel social turmoil in ways we can barely imagine now. Automation has already contributed substantially to the jobless recovery here at home. In addition, the decreasing cost of the machines means they are already taking jobs from humans in the third world and will do so to an increasing degree.

The basic Baxter robot costs around $25,000, and Martin Ford reported in “Rise of the Robots” that “Delta hopes to offer a one-armed assembly robot for about $10,000” which would really open up machine use for poor countries and small companies.

When jobs disappear and there is no work to be found at home in the developing world, many will head north to industrialized nations that offer welfare benefits even to illegal aliens — as long as the more appealing word “refugee” is invoked. Certainly the promise of an easy life is what has attracted millions from Africa and the Middle East to travel to Europe for the free stuff there.

The report below is based on the recent Davos meeting that focused on the Fourth Industrial Revolution, aka automation.

In the following video included with the text item, the reporter notes, “There have been some reports that maybe 40 percent of jobs are going to be destroyed by the rise of robots, of automation, digitization, which is a frightening prospect for many people,” but he doesn’t specify a time frame.

It’s likely that when Guatemalans suffer sufficiently from the “premature deindustrialisation” mentioned below, many will head north hoping to get lucky in stupid-generous America. Why wouldn’t they?

Rise of the robots threatens the poor, FT, January 26, 2016

Automation threatens 85% of jobs in Ethiopia and many more across emerging markets, study says

Automation and the march of the robots will prove most disruptive to the world’s poorest nations, with 85 per cent of all jobs in Ethiopia in danger of being lost, according to new analysis.

Nepal, Cambodia, China, Bangladesh and Guatemala are among the other countries most at risk from “premature deindustrialisation”, according to research by Citi, the US bank, and the Oxford Martin School, a research and policy unit of the UK university.

“There is a really strong [negative] relationship between countries’ level of income and their susceptibility to automation,” says Carl Benedikt Frey, co-director of the Oxford Martin programme on technology and employment.

The findings come a week after the World Economic Forum said more than 5m jobs will be lost globally by 2020 as a result of advances in artificial intelligence, robotics and other technological change. (The scale of this growth, in robotics at least, is indicated in the first chart).

To date, the debate on the impact of the so-called “Fourth Industrial Revolution” has focused on the developed world. Analysis by the Martin School in 2013 concluded that 47 per cent of US jobs were at risk of automation over the coming two decades.

However, its follow-up analysis suggests the impact will be greater still in the developing world.

At present, lower-income countries have a competitive cost advantage over higher-wage ones in tradable sectors such as agriculture and manufacturing.

However the report argues that they will lose that advantage in more and more sectors as robots replace workers, levelling the cost playing field. Moreover, their current low wage levels mean poorer countries still have a greater number of easily automatable jobs that will ultimately be lost.

“While many jobs are automatable in the developing world, automating them is not yet economically feasible due to the abundance of cheap labour,” the report says.

In addition the report, Technology At Work v2.0, argues that the rise of automation and developments in technologies such as 3D printing will encourage companies to bring their manufacturing back to their home countries.

It claims to have seen the first signs of this trend, with the pace at which global supply chains are fragmenting starting to slow, and even go into reverse in some countries. The Philippines, China and Malaysia all sourced a greater proportion of the inputs for their manufacturing exports from their domestic market in 2011 than they did in 2005, it says.

Despite this, the authors argue that North America will be the big winner from this reshoring trend. Emerging markets, the prime beneficiaries of the prior wave of offshoring, would be the obvious losers.

This, combined with ever-greater efficiency that is rendering manufacturing less labour-intensive, has led to concerns that many developing countries are doomed to suffer from premature deindustrialisation.

In the west, the manufacturing sector’s share of total employment peaked at around 25-30 per cent of the workforce (generally between the 1950s and 1980s), and at a point where gross domestic product per capita (in constant 2005 dollars) was between $11,000 and $21,000, as the second chart shows.

In contrast, the report says the likes of Brazil and India have already seen their share of manufacturing employment peak at no more than 15 per cent when GDP per capita (by the same measure) was less than $5,000 in Brazil and under $1,000 in India.

A host of other Asian economies also reached this peak with per capita income of less than $10,000, while “in most of sub-Saharan Africa the manufacturing share of output has persistently declined over the past 25 years” and accounts for just 6 per cent of jobs.

Worse still, while the full impact of automation is likely to take longer to reach developing countries than richer ones “it may be potentially more disruptive in countries with little consumer demand and limited social safety nets”, Mr Frey says.

This shift from labour-intensive to capital-intensive production creates a problem for those emerging countries that still have a large number of small-scale farmers, particularly given that agriculture itself is prone to automation.

“Simply shifting workers from agriculture to manufacturing is not necessarily going to be the course to prosperity. The repayment period for a robot is already down to two years in China. I think that is quite a staggering finding,” says Mr Frey.

Taking all this together, the report concludes that 69 per cent of jobs in India and 77 per cent in China are at “high risk” of automation, comfortably above the 47 per cent figure they found in the US and 57 per cent across the OECD, a club of mostly developed nations.

As the third chart shows, the authors believe there is a clear correlation between a low level of GDP per capita and the proportion of jobs in danger of being automated, with Ethiopia the most exposed of the countries analysed.

At the other end of the scale, Uzbekistan, Lithuania, Malta, Latvia and the Kyrgyz Republic are seen as the developing countries least exposed to the automation threat.

The report quotes a study suggesting that in the 1980s, 8.2 per cent of the US workforce moved into new jobs associated with the arrival of new technologies, a figure that fell to 4.4 per cent in the 1990s and just 0.5 per cent in the 2000s.

“This speaks to the general concern that the WhatsApps of this world do not create as many jobs as GM or IBM did,” says Mr Frey.

Despite this, for the time being at least, he is not overly worried that the march of technology will lead to mass unemployment, even if the impact on equality does appear to be detrimental.

“[Historically] technology has shifted the composition of the workforce. We have seen very little to suggest a net negative effect on employment, although that does not mean it won’t happen in the future.”

His belief is that recent innovations have largely created additional jobs in some pre-existing occupations, rather than large numbers of entirely new jobs, with, for instance, digital technology bolstering employment in professional services.

Moreover, he notes a US study suggesting that for every job created in the tech sector, five more are created in the local economy in shops, restaurants and the like.

As for emerging market countries, the report’s prognosis is that they need to invest in education to “upskill” their workforces in order to benefit from the rise of the robots, rather than being a victim of this trend.

In the absence of this “it’s likely that a large fraction of the population may not find employment”, Mr Frey says.

However, given that the poorest countries are adjudged to be most vulnerable to automation, it is far from clear where the resources for such a push to improve education would come from.

Despite this, Mr Frey believes we should be “quite optimistic” — on the basis that technological progress is likely to increase productivity it should, in theory at least, lead to a rise in wealth for the global population as a whole.

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