Productivity and Wages: What Was the Productivity–Wage Link in the Digital Revolution of the Past, and What Might Occur in the AI Revolution of the Future?
Por um escritor misterioso
Last updated 22 setembro 2024
Wages have been spreading out across workers over time – or in other words, the 90th/50th wage ratio has risen over time. A key question is, has the productivity distribution also spread out across worker skill levels over time? Using our calculations of productivity by skill level for the United States, we show that the distributions of both wages and productivity have spread out over time, as the right tail lengthens for both. We add Organization for Economic Co-Operation and Development (OECD) countries, showing that the wage–productivity correlation exists, such that gains in aggregate productivity, or GDP per person, have resulted in higher wages for workers at the top and bottom of the wage distribution. However, across countries, those workers in the upper-income ranks have seen their wages rise the most over time. The most likely international factor explaining these wage increases is the skill-biased technological change of the digital revolution. The new artificial intelligence (AI) revolution that has just begun seems to be having similar skill-biased effects on wages. But this current AI, called “supervised learning,” is relatively similar to past technological change. The AI of the distant future will be “unsupervised learning,” and it could eventually have an effect on the jobs of the most highly skilled.
How Artificial Intelligence Could Widen the Gap Between Rich and Poor Nations
Artificial intelligence and income inequality: Do technological changes and worker's position matter? - Goyal - 2020 - Journal of Public Affairs - Wiley Online Library
What Can Past Technological Revolutions Tell Us About Today?
What Happened to the Wage and Productivity Link? – Outside the Beltway
How digital transformation is driving economic change
Artificial intelligence and unemployment in high-tech developed countries: New insights from dynamic panel data model - ScienceDirect
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