AI is not a race - hn Reader

October 19, 2026 ☼ The Intersection ☼ technology ☼ geopolitics ☼ information age

A few drivers could well race each other on the highway, but nothing stops other motorists from getting to their own destinations in their own time.

Mint This is from The Intersection column that appears every other Monday in Mint.

If you are a company raising capital it is in your interests to hustle investors into signing cheques to buy into the idea that whoever gets to artificial general intelligence (AGI) first will have an eternal global monopoly. If you are country whose economy depends on such companies, your might see it in your interests to declare that AI is indeed a race. Or if you derive prestige by demonstrating that you have technology comparable to what the incumbent superpower has, then you too have an interest in announcing that you are a challenger in the AI race. None of this, however, means that artificial intelligence technology is a race. A few drivers could well race each other on the highway, but nothing stops other motorists from getting to their own destinations in their own time.

When confronted with evidence that the atomic and space ‘races’ of the previous century neither stopped new entrants nor conferred decisive advantages, proponents of a new race argue that this time it is different because AI can build better AI, and recursive self-improvement sets this techology apart. This argument is strong, but must satisfy a few conditions to be persuasive. The compounding must be disproportionate, be faster than the pace at which it leaks to others and must escape the law of diminishing marginal returns. The hype from genuinely impressive achievements is currently standing in for real proof that we could have an AI to end all AIs.

A race must fulfil all three conditions: one, there must be a definite finish line; two, crossing it first must entail a big reward; and three, this should not be available to other finishers. None of these are true in the case of AI. Some claim AGI is the finish line, but few can define what it means. It is unclear if the first to reach that yet-to-be-defined mark will be the only one to reap the benefits, not least because most people will be satisfied with any one of the lesser models available to them. We are likely to find that AGI, if and when we approach it, is more a moving horizon than a finish line. Those who think they are running a race might discover that they are actually on an accelerating treadmill.

What’s wrong with calling it a race? Won’t the feverish competition drive innovation? Well, it would be one thing if it were only private investors putting their money into these ventures. What is happening is that governments around the world are allocating public funds, land, water and energy resources to participate in the race. Those resources might be better utilised — to achieve economic growth, national power and prestige — if clearer thinking prevailed.

The race metaphor gives the subject a strong security and geopolitical colour: generals, spooks and politicians gain undue influence on technical and economic decisions. We are already seeing this today in the policies of yards, fences, export controls and sanctions, hitting not only AI but the technology sector as a whole.

The security state displaces the regulatory state. Competition watchdogs and safety regulators are pushed aside. It is amusing to hear regular headlines of AI labs postponing the release of their next model due to concerns over safety. The United States does not allow aircraft manufacturers, pharmaceutical companies or even packaged food makers put products in the market before safety certification. If AI labs get a pass, it is because the race metaphor allows them to get away with it.

India should reject the notion of an AI race. There is a case for publicly-financed AI development, not because India sees itself in a race with the United States and China. Public policy should focus on rapid adoption and diffusion, which are the pathways of advantage for India. Fellow Mint columnist Rahul Matthan calls it absorption. “We have been made to believe that those who build the most advanced AI models will reign over those who do not,” he writes in a new essay for ORF, yet “the value of a new technology is only ever realised when it is deployed into the world.” This is the most important point as far as India is concerned. His “absorption frontier” is the point at which a sector has reorganised itself enough to turn abundant intelligence into productive gains. It took decades for electricity to get there. AI will be faster, but public policy can accelerate the process. Countries that have built digital public infrastructure, he argues, have already laid down the first layers of the frontier. India should build the infrastructure for absorption that will remain long after the bubble is gone.

Sharma’s essay captures how the mechanics of the end of the AI bubble might play out. (The boom is likely to continue long after the burst. No pun intended.)

In this month’s Foreign Affairs, Ruchir Sharma reminds us that “The economist William Nordhaus has shown that only two percent of the value created by innovations of the past, including railroads, airlines, and the Internet, went to the companies that built these networks. The rest went to the consumers and businesses that used the inventions.”

Tailpiece: “Aisa to aadmi life mein do hi time bhagta hai…Olympic ka race ho ya police ka case ho” - Anthony Gonsalves

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