This paper defines pro-worker technologies, including artificial intelligence (AI), as technologies that make human skills and expertise more valuable by expanding worker capabilities. It presents a conceptual framework that distinguishes among five categories of technological change. 

AI’s capacity to automate work and displace workers is substantial. But AI also has transformative potential to act as a force-multiplier for human skills and expertise by expanding worker capabilities. This potential arises from AI’s capacity to collaborate with workers, enabling them to be more effective at their existing tasks, tackle new tasks and acquire new expertise.

A conceptual framework for pro-worker AI

1. Labour-augmenting technologies make workers more effective at the tasks they already do. 
2. Capital-augmenting technologies make machines better, cheaper or faster at performing their current tasks. 
3. Automating technologies directly reshape the division of labour between workers and machines by substituting machinery or algorithms for tasks that were previously performed by workers. 
4. Expertise-levelling technologies enable a new set of workers to perform tasks that previously demanded expertise from another domain(s). 
5. New task-creating technologies create new human tasks.

The paper outlines nine ways that public policy could channel advances in AI in a pro-worker direction. 

1. Shaping pro-worker AI in health care and education
2. Building AI expertise in government
3. Using grant-making to support worthwhile AI investments
4. Fostering competition for excellence
5. Rebalancing the tilted investment playing field in the tax code
6. Fostering private sector competition
7. Harnessing worker voice
8. Discouraging 'expertise theft'
9. Loosening up licensure.