While noting that this is the most likely scenario for the next 10 to 15 years, Messrs. Keep and Brown also consider two potential longer-term scenarios. Perhaps AI will lead to even more pervasive and fundamental transformations in the nature of work, making it difficult for even those with higher education to find a good job. Beyond that, some have suggested that in the more distant future we might see an even more radical, science-fiction-like transformation: the end of work as we’ve long known it.

The authors argue that considering such a spectrum of possibilities will help us better prepare for what’s essentially an unpredictable future. In that spirit, their paper discusses three different labor-market scenarios: labor scarcity, job scarcity and the end of work.

Labor scarcity

In this scenario, new positions and professions will emerge to replace any eliminated by new technology.

Investments in the skills required to meet these challenges are the key source of individual opportunity, social mobility and economic welfare. This is especially important for workers without a four-year college degree who’ve disproportionately borne the brunt of automation. Post-secondary education and training venues, such as community colleges or industry-specific training programs, are likely to be most relevant and accessible to these workers. However, existing education and training programs won’t be enough given the demands for lifelong adult learning.

“People will need to adapt continuously and learn new skills and approaches within a variety of contexts,” the authors write.

Job Scarcity

Previous technological innovation always delivered more long-run employment, but things can change. Some fear that a new era of automation enabled by ever more powerful and capable computers could work out differently.

It could be that new technologies only enhance the skills of a relatively small proportion of the workforce, they write. Indeed, the larger trend is one of a tech-led “redesign of existing jobs.” Here, “much of the knowledge content is captured in software,” leading to the automation of a wide range of occupations, including managerial roles.

This scenario reminds me of “Why Software is Eating the World,” a 2011 essay by Marc Andreessen published in The Wall Street Journal that predicted software was poised to take over large swaths of the economy.  Entrepreneurial companies all over the world are disrupting established industries with innovative AI-driven software solutions. More businesses and industries are being run on software and delivered as online services.

“Job scarcity points to a significant mismatch between an expanding supply of educated and skilled workers and a scarcity of high-quality job opportunities, primarily resulting from the routinization and segmentation of job roles rather than technological unemployment,” the authors write. A relatively small number of highly skilled, educated professionals and managers will develop the necessary algorithms, digital systems and business models, while a much larger number of less skilled workers will be needed to implement the procedures and managerial tasks which have been captured in algorithms and software.

The End of Work

In a 1930 essay, English economist John Maynard Keynes wrote about the onset of “a new disease” he named technological unemployment, that is, “unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.”

Such an end-of-work scenario assumes that decades from now, most economic activity will be handled by super-smart machines developed and supervised by small groups of highly skilled professional and technical workers.

“It would represent a profound dislocation for the education and training system…where for the past three decades or more the focus has been on the role of education in equipping individuals to perform effectively in a changing labor market,” Messrs. Keep and Brown write.

Instead, the aim of education “would be to help people gain the skills to live fulfilling lives, with the judgment and knowledge to be capable of addressing the complex problems that humanity will face.”

“Moreover, although the technical and knowledge requirements of what people do for a living may change, the social context in which people interact, network, and produce will remain,” they continue. “Social skills are more difficult for smart machines to develop.” Finally, “all three theories see a need for educational reform and a greater focus on lifelong learning,” the authors conclude.

Irving Wladawsky-Berger worked at IBM from 1970 to 2007, and has been a strategic adviser to Citigroup, HBO and Mastercard and a visiting professor at Imperial College. He’s been affiliated with MIT since 2005, and is a regular contributor to CIO Journal.