====== Anton Korinek ======
**Anton Korinek** is an economist known for research on the economic implications of artificial intelligence and automation, particularly focusing on labor market disruption and technological singularity scenarios. His work examines how advances in AI-driven research and development could accelerate technological progress with significant macroeconomic consequences.

===== Research on AI Automation and Economic Growth =====
Korinek has authored research exploring the economic dynamics of automating artificial intelligence research itself. His work investigates scenarios where improvements in AI capabilities enable automation of software development and research processes, creating potential feedback loops in technological advancement (([[https://www.nber.org/|National Bureau of Economic Research - NBER Working Papers]])). 

The research concludes that under specific calibration assumptions, automating software research and development combined with modest automation gains (approximately 5%) in other economic sectors could produce rapid, potentially explosive economic growth within a relatively short timeframe—estimated at approximately six years under empirically grounded parameter assumptions. This analysis draws on established economic modeling techniques applied to technological change and productivity growth.

===== Methodology and Economic Framework =====
Korinek's analytical approach grounds theoretical models of automation in empirical data about current productivity levels, automation capabilities, and economic parameters. The research employs standard macroeconomic growth models extended to account for endogenous technological change—where the rate of innovation itself becomes a variable dependent on economic inputs and resource allocation (([[https://www.journals.uchicago.edu/doi/10.1086/260845|Romer, P. - "Endogenous Technological Change" (1990]])). 

The specific modeling of AI research automation reflects concerns raised in the broader economics of AI literature about recursive self-improvement dynamics and their potential macroeconomic effects. Rather than treating automation as exogenous, Korinek's framework models how automating the research process that generates further automation creates feedback mechanisms that could amplify growth rates (([[https://www.brookings.edu/articles/the-economics-of-artificial-intelligence/|Agrawal, A., Gans, J., Goldfarb, A. - "The Economics of Artificial Intelligence" (2019]])). 

===== Implications for Economic Policy =====
The research raises important questions about economic preparedness for scenarios involving rapid technological change driven by AI capabilities. The analysis suggests that policy frameworks designed for conventional technological progress may be inadequate for scenarios involving automation of the innovation process itself. Key policy considerations include labor market transitions, income distribution effects, and macroeconomic stability during periods of accelerating growth.

The work contributes to an emerging literature examining how AI systems capable of improving their own design could generate qualitatively different economic dynamics than historical technological transitions (([[https://www.nber.org/system/files/working_papers/w30915/w30915.pdf|Korinek, A., Stiglitz, J. - "Artificial Intelligence and Its Implications for Income Distribution and Unemployment" (2021]])). 

===== Academic Context =====
Korinek's research sits within the intersection of labor economics, macroeconomics, and technology economics. His contributions address gaps in traditional economic analysis regarding transformative technologies with potential for recursive improvement. The work acknowledges uncertainties inherent in modeling far-future scenarios while maintaining quantitative grounding in current data and established economic theory.


===== See Also =====

  * [[claude_cowork|Claude Cowork]]
  * [[ethan_mollick|Ethan Mollick]]
  * [[anton_osika|Anton Osika]]

===== References =====