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High(4)

High quality. Established institution or organization with editorial oversight and accountability.

Rating inherited from publication venue: RAND Corporation

A RAND webinar examining AI's impact on labor markets, identifying which occupations are most exposed to automation or transformation, relevant to AI governance and deployment policy discussions.

Metadata

Importance: 38/100videoeducational

Summary

This RAND webinar, presented by researchers Tobias Sytsma and Melanie Zaber, explores whether AI constitutes a fifth industrial revolution and which jobs are most likely to be replaced, reshaped, or expanded by AI-driven technological change. It draws on data-driven research identifying occupations exposed to AI and discusses policy interventions to ease the transition for workers and employers.

Key Points

  • Examines whether AI represents a transformative 'fifth industrial revolution' comparable to prior technological upheavals.
  • Uses data-driven methods to identify which occupations are most exposed to AI-driven automation or augmentation.
  • Discusses how AI may replace some jobs, reshape others, and expand new categories of work.
  • Considers policy and institutional mechanisms to smooth the transition for workers and employers.
  • Based on related RAND research published in 2023 on AI and labor force exposure.

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AI and the Future of Work

A transcript for this video is available via YouTube. The transcript and captions are auto-generated and have not been edited.

Tobias Sytsma, Melanie A. Zaber, Rachel Slama

 VideoPublished Dec 18, 2024

 

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Will artificial intelligence (AI) be the fifth industrial revolution? Which jobs are most likely to be replaced, reshaped, or expanded by technological change? What might help smooth the “AI revolution” for workers and employers alike? RAND’s Tobias Sytsma and Melanie Zaber tackled these questions and more in a webinar focused on their research findings.

 

 

 

 
 

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Related Content

 

 
 
 

 

 
 

 
 

Research

Artificial Intelligence and the Labor Force: A Data-Driven Approach to Identifying Exposed Occupations

Oct 11, 2023

Topics

 
Data Analysis

Labor Markets

Machine Learning

United States

Workforce Management

 

Document Details

Copyright: RAND Corporation

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Resource ID: 784eef9a7c56fc92 | Stable ID: sid_qxkTAX5gp4