Nobel for a prosperity theory: Let’s talk about it in the context of AI

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Subscribe to enjoy similar stories. Artificial intelligence (AI) has been the broad theme of this year’s Nobel awards.

The 2024 prize in Physics went to John Hopfield of Princeton and Geoffrey Hinton of the University of Toronto for laying the foundation for AI advances, while the Chemistry award was shared by University of Washington biochemist David Baker, for protein-design work using digital tools, and Demis Hassabis and John Jumper of Google’s DeepMind for the development of AlphaFold, an AI tool that can predict protein structures based on its genetic code. This year’s prize for Economics, though, took on a question that the advent of AI lends urgency to: Why are some countries rich and others poor? The prize was shared by Daron Acemoglu and Simon Johnson of MIT with James Robinson of the University of Chicago “for studies of how institutions are formed and affect prosperity." The views of Acemoglu and Robinson are rather well known, set out as they were in their 2012 book, Why Nations Fail.

The answer is that extractive institutions prevail over inclusive ones. Institutions are broadly defined as the rules or restraints that govern human interaction; rich or poor is judged by a nation’s output per head; and the persistence of gross inequality between nations is borne out by data: The per-capita GDP of the richest 20% countries is about 30 times that of the poorest 20%.

The trio was honoured for showing that much of that gap can be explained by persistent differences in economic and political institutions. For this, they had to show a causal link beyond mere correlation.

On the empirical front, they looked at the impact of colonization on countries under foreign rule. Where colonizers found it hard to settle, with