Resources & Further Reading

Academic research papers, occupation exposure databases, career frameworks, and monitoring tools

Resources & Further Reading

Primary Resource: Download the Felten-Raj-Seamans Occupation Exposure Database (CSV) for 800+ occupations scored on AI exposure. Use this to benchmark your own assessment. Included in tutorial materials folder.

Academic Research

Felten, E., Raj, M., & Seamans, R. (2024). "Occupational AI Exposure." Journal of Labor Economics.

  • [Link to paper (when published)]
  • The foundational methodology for task-based AI exposure analysis

Acemoglu, D. (2024). "The Simple Macroeconomics of AI."

Brynjolfsson, E., Li, D., & Raymond, L. (2023). "Generative AI at Work: Productivity Effects of AI on Knowledge Workers."

  • Study of 5,000 customer service agents using AI
  • Found 14% productivity improvement for average workers, 34% for low performers
  • [Link: NBER Working Paper Series]

Webb, M. (2024). "The Impact of Artificial Intelligence on the Labor Market."

  • Comprehensive survey of AI's labor market effects
  • Dataset of occupational AI exposure by detailed occupation codes
  • [Link: Stanford HAI]

Career Pivot Frameworks

Books:

  • Range by David Epstein (generalist advantage in AI era)
  • The Squiggly Career by Helen Tupper & Sarah Ellis (non-linear career development)
  • Designing Your Life by Bill Burnett & Dave Evans (career design thinking)

Online Resources:

Tools for Ongoing Monitoring

AI Capability Trackers:

Labor Market Data:

AI Impact Newsletters:

Community & Discussion

  • Reddit: r/artificial, r/MachineLearning, r/cscareerquestions
  • Discord: Join the XPS.org community for ongoing discussion
  • Twitter/X: Follow #AIEconomics and #FutureOfWork