prize winning economist Jan Tinbergen (1974) argued that skill-biased technological progress – with its consequences for income inequality – necessitates an important role for education in mediating the demand for higher-order skills.

However, since about 1980, it is argued that educational supply is no longer meeting educational demand. Since much of the disconnect is because of skill-biased technological change, this has been referred to as the race between education and technology (Tinbergen 1974; Goldin and Katz 2010). Education no longer seems to have mediating effects. If there is no change in the supply of education – its quality, that is – then the net effect could be a rise in inequality. Those with lower levels of education and especially lower quality of schooling will be at a distinct disadvantage.

# **The Automation Challenge**

In 2017, the Japanese insurance company, Fukoku Mutual Life Insurance, replaced 34 human insurance claim workers with IBM Watson Explorer (McCurry 2017). The Artificial Intelligence (AI) will scan hospital records and other documents to determine insurance payouts, factoring injuries, patient medical histories, and procedures administered. Automation of these research and data gathering tasks will help the remaining human workers process the final payout faster. Fukoku Mutual will spend $1.7 million to install the AI system, and $128,000 per year for maintenance. The company saves roughly $1.1 million per year on employee salaries by using the IBM software, meaning it hopes to see a return on the investment in less than two years. Watson AI is expected to improve productivity by 30 percent.

Though an isolated case, it is not expected to be the last. What is also interesting is that it is highly educated, white collar workers who are being targeted. The immediate cost savings are also reason to believe we will see more of this in the years to come.

As already mentioned, technological change heralds a renewed race between the supply and demand for schooling, or between education and technology. The ability of workers to compete is handicapped by the poor performance of education systems in most developing countries (Barro and Lee 2015). The returns to schooling are high in most developing countries, and growing skill premiums are evident in much of the world (Montenegro and Patrinos 2014). In high-performing economies, such as those in East Asia, we may have reached the limits of the industrial model and what once worked for developed countries may not work for developing countries. Automation implies deskilling in many aspects and a need for new skills for many (Bentaouet Kattan, Macdonald and Patrinos 2018).

The coming automation – robots, machines and artificial intelligence (AI) – will become increasingly capable. More and more jobs will become targets. Therefore, the risk or perceived risk that your job is likely to be automated will increase.

That is not to say that all AI is negative. There are proponents who say that increased automation and AI will solve many of our problems. The collective intelligence of humanity will increase, and we will live longer, healthier and more satisfying lives (Kurzweil 2005). In a 1930 essay, the economist John Maynard Keynes argued that automation will lead us to a life of leisure because of increases in productivity and a 15-hour work week.

4