The Economics of Work with Ben Zweig19 Aug

Deena Mousa - What AI Means for the Developing World

The standard debate about AI and jobs is a rich-country debate. But for billions of people in low- and middle-income countries, the stakes and the story look completely different.

In this episode, Ben sits down with Deena Mousa, program officer at Coefficient Giving and writer on AI and global development, to explore what gets missed when we only think about AI's impact through a Western lens.

Topics covered:

Why there are still so many radiologists, and what the gap between benchmark performance and real-world clinical performance tells us about AI adoption more broadly
How automation demand works in reverse: why making scans faster and cheaper expands the complexity of what radiologists are asked to do, not just the volume
Why low-income countries are in a fundamentally different situation with both their access to AI and how it can address their needs.
The service export threat: why the BPO and outsourcing sectors in countries like the Philippines and India may face a more immediate AI disruption than any manufacturing sector
Why "supply creates its own demand" doesn't automatically work for development, and the Malawi example of why breakout growth is the exception, not the rule
The difference between low-income and middle-income countries, and why bundling them into "LMICs" obscures the very different things they need to do
Why some Western social progress movements can inadvertently harm the workers they're meant to protect

About Deena Mousa: Deena Mousa is a program officer at Coefficient Giving, formerly Open Philanthropy, where she focuses on the intersection of AI and global development. She writes on Substack about how transformative technology reshapes economic opportunity across the world.

Check out Deena’s substack

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