Impact data analyst at Google DeepMind. Interested in AI, economics, complexity, metascience, research methods, science-fiction.
Juan Mateos-Garcia
Loading...
All this highlights the need to consider AI economic impacts holistically, and to create incentives and infrastructure to reproduce AI economic impact analyses regularly to track longer term impacts via improved capabilities and job redesign.
They use LinkedIn job ads to measure firm-level AI adoption and occupation / task distribution, and embedding distance to ONET tasks to quantify exposure. They use instruments to reduce selection biases and mitigate mis-measurement (read the paper for full details)
The results are consistent with their hypotheses: AI drives firm growth, occupations with high mean exposure to AI decline but this is often more than offset by complementarities and productivity growth. Big AI impacts with different signs lead to small aggregate changes.
In their model, AI displaces an occupation if its mean task exposure to AI is high, and augments it if its exposure dispersion is high (some tasks are exposed to AI and others untouched). They also consider impacts on labour demand though AI-powered firm growth.
"Artificial Intelligence and the Labor Market"
Nice analysis of LinkedIn data to estimate the impact of AI on jobs between 2010 and 2023.
It illustrates the complexity of AI economic impacts: what exposure taketh away, complementarities and productivity giveth.
www.menakahampole.com
"Artificial Intelligence and the Labor Market"
Nice analysis of LinkedIn data to estimate the impact of AI on jobs between 2010 and 2023.
It illustrates the complexity of AI economic impacts: what exposure taketh away, complementarities and productivity giveth.
www.menakahampole.com
