Three Ways to Think About AI and Jobs

TL;DR

Despite AI advancements in radiology, human radiologists are in higher demand with increased salaries.
Jobs can be categorized as 'strong bundles' (tasks are interdependent and difficult to separate, like trial lawyers) or 'weak bundles' (tasks are easily separable, like recruiters).
The Jevons paradox suggests that increased efficiency through automation can lead to lower prices, increased demand, and ultimately, job growth in some sectors (e.g., automobiles, textiles, ATMs, spreadsheets).
Not all efficiency gains lead to increased demand; for instance, food production became more efficient but farming employment drastically decreased.
A job's susceptibility to AI also depends on whether AI replaces low-expert skills or enhances high-expert skills.
Radiology remains a strong bundle job where AI automates some tasks, but remaining tasks require high expertise, and increased demand due to lower costs (Jevons paradox) keeps radiologists employed.
The long-term impact of AI is hard to predict, as unforeseen technologies can drastically alter entire professions, as seen with the iPhone's impact on banking.

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