
This episode discusses automation versus augmentation, featuring insights from MIT economists Daron Acemoglu and David Autor, and researchers Tim Bresnahan, A.J. Agarwal, Avi Goldfarb, and Joshua Gans.
The conversation highlights the task-based approach proposed by Acemoglu and Autor, which views jobs as bundles of tasks that can be augmented or automated.
In contrast, the systems-level perspective from Bresnahan and his colleagues suggests that significant changes occur at the system level, affecting labor and capital demands.
The episode emphasizes the importance of understanding how companies making large investments can lead to new supply and demand dynamics.
Both frameworks are presented as useful for different questions, with a growing belief in the relevance of the systems view.
Automation and augmentation are analyzed through task-based and systems-level perspectives by leading economists.

The systems view has more to say.AI is shifting systems and industries, not just automating tasks.