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Friday, October 13, 2017

Automation on our own terms

Benedict Dellot and Fabian Wallace-Stephens
Medium.com
Originally published September 17, 2017

Here is an excerpt:

There are three main risks of embracing AI and robotics unreservedly:
  1. A rise in economic inequality — To the extent that technology deskills jobs, it will put downward pressure on earnings. If jobs are removed altogether as a result of automation, the result will be greater returns for those who make and deploy the technology, as well as the elite workers left behind in firms. The median OECD country has already seen a decrease in its labour share of income of about 5 percentage points since the early 1990s, with capital’s share swallowing the difference. Another risk here is market concentration. If large firms continue to adopt AI and robotics at a faster rate than small firms, they will gain enormous efficiency advantages and as a result could take excessive share of markets. Automation could lead to oligopolistic markets, where a handful of firms dominate at the expense of others.
  2. A deepening of geographic disparities — Since the computer revolution of the 1980s, cities that specialise in cognitive work have gained a comparative advantage in job creation. In 2014, 5.5 percent of all UK workers operated in new job types that emerged after 1990, but the figure for workers in London was almost double that at 9.8 percent. The ability of cities to attract skilled workers, as well as the diverse nature of their economies, makes them better placed than rural areas to grasp the opportunities of AI and robotics. The most vulnerable locations will be those that are heavily reliant on a single automatable industry, such as parts of the North East that have a large stock of call centre jobs.
  3. An entrenchment of demographic biases — If left untamed, automation could disadvantage some demographic groups. Recall our case study analysis of the retail sector, which suggested that AI and robotics might lead to fewer workers being required in bricks and mortar shops, but more workers being deployed in warehouse operative roles. Given women are more likely to make up the former and men the latter, automation in this case could exacerbate gender pay and job differences. It is also possible that the use of AI in recruitment (e.g. algorithms that screen CVs) could amplify workplace biases and block people from employment based on their age, ethnicity or gender.
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