For Work / Against Work
Debates on the centrality of work

"Economics of Artificial Intelligence: Implications for the Future of Work"

by Ernst, Ekkehardt; Merola, Rossana; Samaan, Daniel (2019)


AbstractThe current wave of technological change based on advancements in artificial intelligence (AI) has created widespread fear of job loss and further rises in inequality. This paper discusses the rationale for these fears, highlighting the specific nature of AI and comparing previous waves of automation and robotization with the current advancements made possible by a widespread adoption of AI. It argues that large opportunities in terms of increases in productivity can ensue, including for developing countries, given the vastly reduced costs of capital that some applications have demonstrated and the potential for productivity increases, especially among the low skilled. At the same time, risks in the form of further increases in inequality need to be addressed if the benefits from AI-based technological progress are to be broadly shared. For this, skills policies are necessary but not sufficient. In addition, new forms of regulating the digital economy are called for that prevent further rises in market concentration, ensure proper data protection and privacy, and help share the benefits of productivity growth through the combination of profit sharing, (digital) capital taxation, and a reduction in working time. The paper calls for a moderately optimistic outlook on the opportunities and risks from AI, provided that policymakers and social partners take the particular characteristics of these new technologies into account.

Key Passage

New, AI-based digital technologies may allow larger segments of the labor market to improve their productivity and to access better paying occupations and, thereby, may help promote (inclusive) growth. This requires, however, that a certain number of policies are put in place that support the necessary shift in occupational demand, maintain a strong competitive environment to guarantee diffusion of innovation, and keep up aggregate demand to support structural transformation. At the same time, AI applications raise the potential for productivity growth for interpersonal, less technical occupations and tasks, leading to higher demand for such work, which is likely to dampen the inequality trends observed over recent decades. A particular challenge arises for developing countries when they are part of a supply chain that forces them to adopt capitalintensive technologies despite an abundance of underutilized labor. Here, AI-driven automation might further drive up informality unless governments ensure a widespread adoption and diffusion of digital technological change beyond the supply chain sectors. In other words, the productivity-enhancing potential of AI is real but the specific characteristics of this new technology require policy responses that differ from those given during previous waves of technological change to generate shared benefits for the world of work. (p.5)


Artificial Intelligence, Machine Learning, Political Economics, The Future Of Work, Economics, Technilogy


Future of Work, Economics, AI and Computerisation

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