“AI augmentation that makes workers more productive can reduce the number of workers needed to produce a fixed amount of output,” Peng explains. “But by lowering the cost per unit of output, it might also increase demand for what they produce enough to generate a net increase in their employment.”
This is an example of Jevons paradox, an economic phenomenon first identified in the 1800s, when increased efficiency in the use of coal actually raised total coal consumption. The boost in efficiency lowered the effective price, prompting more industries to choose coal as their fuel source.
Until recently, it has been difficult to distinguish between occupational roles where AI will substitute for workers and where it will augment them. Indexes that economists have been using to see where AI capabilities and human abilities overlap have been agnostic on the question of substitution versus augmentation. Several recent studies, though, have begun to tease out the difference, Peng writes.
How AI complements humans in certain roles
Occupations with similar AI exposure can differ in their degree of AI complementarity—that is, the degree to which AI can complement a human rather than substitute them. Customer service representatives and interior designers both face AI exposure, for example. But the work of interior designers requires more unstructured tasks and more frequent physical presence at worksites—things that cannot be fully automated. In other words, the AI complements the human in interior design, giving the profession a higher augmentation score.
Which jobs are most at risk of being replaced by AI?
When jobs are sorted in this way, it shows that professionals such as telephone operators, insurance claims clerks, and bill collectors face the highest substitution risk. By contrast, roles such as education workers, judges, and construction managers offer the highest AI augmentation potential.