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Robots are no longer a sci-fi fantasy. In fact, we are focusing more on analysing exactly how many jobs could be destroyed by the coming wave of automation, rather than on how to actually fix the problem.

More than half of the Internet users believe that within 30 years machines will advance to the point of performing most activities currently done by humans. But a conclusion in a new paper on the potential effects of robotics and AI on global labour markets from the US think tank, the Center for Global Development, says its impossible to know how exactly many jobs will be destroyed or disrupted by new technology.

The paper's authors, Lukas Schlogl and Andy Sumner, add that it's fairly certain there are going to be significant effects – especially in developing economies where the labour market is skewed toward work that requires the sort of routine, manual labour that's so susceptible to automation. Think unskilled jobs in factories or agriculture.

Schlogl and Sumner think the effects of automation on these and other nations are not likely to be mass unemployment, but the stagnation of wages and polarisation of the labour market. Basically, there will still be work for most people, but it'll be increasingly low-paid and unstable; without benefits such as paid vacation, health insurance, or even pensions. On the other end of the employment spectrum, meanwhile, there will continue to be a small number of rich and super-rich individuals who reap the benefits of increased productivity created by technology.

All these changes might lead to a decline in job security and standards of living for many, which in turn could lead to political dissatisfaction. Some suggest we might have seen the early impact of this, in the US, there are cities where jobs are at risk of automation, more likely to vote Republican.

However, Schlogl and Sumner give an overview of proposed solutions to these challenges but seem sceptical that any will go far enough. One solution they call "quasi-Luddite" – measures that try to stall or reverse the trend of automation. All these include taxes on goods made with robots (or taxes on the robots themselves) and regulations that make it difficult to automate existing jobs. It is challenging to measure these implementations in an "open economy", because if automation makes for cheaper goods or services, then customers will naturally look for them elsewhere; like outside the area covered by such regulations.

Another related strategy is to reduce the cost of human labour, by driving down wages or cutting benefits. "The question is how desirable and politically feasible such strategies are," say Schlogl and Sumner, which is a nice way of saying "it’s not clear how much you can hurt people before they riot in the streets."

The other solution, which they call "coping strategies", tend to focus on one of two things: re-skilling workers whose jobs are threatened by automation or providing economic safety nets to those affected. Schlogl and Sumner suggest that the problem with retaining workers is that it's not clear what new skills will be "automation-resistant for a sufficient time" or whether it's even worth the money to retain someone in the middle of their working life. To retain someone is also more expensive and challenging for developing countries where there is less infrastructure for tertiary education.

All this leads Schlogl and Sumner to conclude that there’s simply not enough work being done researching the political and economic solutions to what could be a growing global crisis. "Questions like profitability, labour regulations, unionisation, and corporate-social expectations will be at least as important as technical constraints in determining which jobs get automated," they write.

There are still so many questions to ask and research to do before we can confidently say "Robots will take over everything, as we know it."

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