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

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


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 tropical diseases taking a toll on their survival, they fostered extractive—rather than inclusive—institutions, designed to fleece locals and enrich an elite. Such geographies saw a reversal of fortune, with once-wealthy countries pushed into poverty by colonial rule. 

An example would be India. On the contrary, where settlers could survive and multiply easily, they set up inclusive institutions that assured their multitudes key rights—to property and justice, critically. The US is an example of such success. Academic rigour, however requires more than studying history. 

To back their observation with a theory that could explain why unfair set-ups persist, the laureates proposed a game-theory model with an extractive elite ranged against the masses. 

Countries where the latter cannot push their rule-makers to institute equitable rules and better resource allocation get trapped in poverty, while reforms spell win-win payoffs where the jinx of mutual distrust is overcome.

That inclusive institutional frameworks hold the key to prosperity is the big message of the 2024 prize. Since equal rights underpin the evenly shared prosperity needed for the rise of an economy, democracy and the rule of law are crucial. 

True, this is easier said than done; reforms are often resisted by beneficiaries of unfair systems who fear losing privileges. Yet, today, it’s in the context of AI that institutional set-ups deserve scrutiny. As Hinton has warned, AI could worsen global disparities. 

Not just through unequal access to the productivity boost of AI, but also via its large-scale takeover of jobs that poorer folks do, apart from greater gaps in military power as AI gets increasingly weaponized. We will need restraints not just on human conduct, but even on AI. Getting the rules right has grown as a challenge.



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