Interestingly, the chemical industry — and ethylene production in particular — provides a significant historical precedent related to the ongoing discussions on AI and labor.

By the mid-20th century, ethylene plants transitioned to automated flow systems operating continuously with minimal human oversight. Labor productivity improvements within the industry reflect virtually constant manning levels independent of plant size. Empirical analysis demonstrates that the scale coefficient for labor is not significantly different from zero [1]. Consequently, once a fixed level of labor is reached, plant output can be increased to any level by merely increasing other inputs while holding labor almost constant.

This history mirrors the zero-marginal-labor model associated with AI today. Generative AI models output “cognitive work” with near-zero marginal human effort [2]. Scaling AI output requires additional computational and electrical inputs. In both cases, human roles transition from direct task execution to the supervisory monitoring of automated flow systems.

References

  1. Cantley, M. F. (1979). The Scale of Ethylene Plants: Background and Issues. IIASA.
  2. Stiefenhofer, P. (2025). Artificial General Intelligence and the End of Human Employment: The Need to Renegotiate the Social Contract. arXiv.