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The Regional Impact of Automation

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The Regional Impact of Automation

The key is not to try to shut down change but to become better at adapting to it. After all, it's not the strongest or most intelligent of a species that survives, but the one most adaptable to change.

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A fundamental part of both Brexit and various other populist-style movements around the world is the clear divide between large cities and smaller towns. While big cities tend to do okay out of globalization, the smaller towns have struggled to find their niche in such a global marketplace.

The vote for Brexit, the election of Trump, and various other rejections of the establishment have been calls to correct matters, but the medicine seems unlikely to correct matters. What's more, a recent paper from MIT suggests that those same small towns are likely to bear the brunt of any impact technology will have on the labor market.

Regional Automation

The central hypothesis is that automation is more likely in roles with repetitive tasks playing a major part, and such lower skilled roles tend to be concentrated more in smaller towns than larger cities.

The researchers came to this conclusion after analyzing both what kind of roles and skills are most prevalent in smaller towns (and larger cities), and then what roles are most at risk from automation. Big cities tend to disproportionately offer work for people doing cognitive and analytical tasks, which are harder to automate. By contrast, smaller towns have a disproportionate amount of routine work, which is more vulnerable.

"Big cities provide greater opportunities for synergies among creative, highly technical people, and that's why they attract them," the authors say. "The other dynamic is that cashiers and waiters are less idle in big cities than small cities, so large cities need fewer of them in proportion to their size."

The report is interesting because it tries to steer clear of absolute predictions on jobs likely to be impacted by technology and instead makes relative comparisons between regions.

"For us, the question is: How can we anticipate future changes, not just related to robotics but also machine learning, algorithms, chatbots, and voice recognition, which are going to disrupt people who are in white-collar occupations as well [as in blue-collar jobs]?" the authors conclude.

A similar report was published last year by the UN Conference on Trade and Development. It was looking at the impact very much from the perspective of the developing world. Similarly to the MIT paper, it argued that most of the disruption will be in low-skilled work, and with that in mind, it argues that most of this disruption will occur in the developing world.

"The increased use of robots in developed countries risks eroding the traditional labor cost advantage of developing countries," the report states. "Adverse effects for developing countries may be significant."

Adapting to Change

This perhaps shouldn't be surprising because, as far back as the 1700s, thinkers like Henry Martyn were comparing globalization with new technologies, as the benefits (and disruption) are similar in both.

He suggested that by using a tool (a sawmill, in his case), we could perform the work of 30 men with the labor of two men.

Now, of course, we could employ those 30 men instead, but that would be a waste of human resources. The same is true for most technologies, and hopefully, readers of this blog would agree that we shouldn't go back on technological development.

Martyn went on to compare this with globalization and suggested that if another country can produce textiles (for instance) more efficiently than we can, then it is akin to having a new technology to do likewise, and we should jump at such an opportunity and instead deploy our resources to trade with that nation in areas that we can excel.

The key, therefore, is not to try to shut down change but to become better at adapting to it. After all, Darwin himself may or may not have said that "it's not the strongest of the species that survives, not the most intelligent — but rather, the one most adaptable to change." That is now the challenge facing societies across the world.

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