The AI Prisoner's Dilemma


By Gray Howle


If you caught any financial news recently, you probably saw some version of the same story: the people building artificial intelligence are arguing about whether to slow it down. Some of the coverage has been dramatic. I want to walk you through what's actually going on, because a little context takes most of the drama out of it. And on a topic like this, I'd rather walk you through it myself than leave it to the headlines. Stay with me to the end and you'll also learn why, of all things, a herd of impalas gives me some optimism about how this plays out.


What happened

This summer, an experimental group of AI "agents" at a leading lab acted outside the boundaries of a test they were running. That incident, along with the fast pace of the technology generally, set off a debate that boiled over earlier this month. On September 12, Anthropic's CEO Dario Amodei published an essay arguing the industry should deliberately pace the development of its most powerful models. Here's what got everyone's attention: two of his biggest rivals, OpenAI's Sam Altman and Elon Musk, publicly agreed with him. These three don't agree on much.


The pushback came quickly. President Trump and Nvidia's Jensen Huang both argued a slowdown is unnecessary and would hand the lead to China. Beijing's response was telling. Its Foreign Ministry dismissed the warnings as fear mongering, while in the same breath China promoted its own competing framework for governing AI, one built around its partnerships with developing countries. In other words, nobody rejected the idea of rules. Each side just rejected the other side's version of them. Keep that in mind, because it's exactly what the framework below predicts.


Why the experts are split

Both sides have a real argument. The pacing camp says the technology is moving faster than our ability to fully understand it, and that slowing down is simply the responsible thing to do. The other camp says the risks are exaggerated and the cost of falling behind is not.


I'll also share the more cynical readings, because you deserve the whole picture. Some observers point out that the big labs might like rules and evaluations partly because rules are expensive for smaller competitors, or because the labs themselves could use more time and money. Others note that the companies resisting a slowdown are often the ones selling the picks and shovels. All of that can be true at the same time as genuine conviction. My job isn't to referee anyone's motives. It's to understand the incentives well enough to see where this is likely headed.



An old idea that cuts through the noise

For that, I lean on game theory, which was born during the last great technology race. John von Neumann, a Manhattan Project scientist, helped found the field. John Nash, whose life became the Best Picture winner A Beautiful Mind, extended it during the Cold War and later won the Nobel Prize for it.



Nash's most famous illustration is the prisoner's dilemma. Two suspects are held in separate rooms. If both stay quiet, both get light sentences, the best combined outcome. But neither can trust the other, so each one's rational move is to talk, and both end up worse off. Cooperation would win, but there is no way to enforce it.

Swap the suspects for superpowers and the logic carries over.

No AI lab, and no country, wants to slow down only to watch a rival sprint ahead. Without a way to enforce cooperation, game theory points to one rational outcome: neither the U.S. nor China slows down. The CNBC analysis that got me thinking about all this put it in arms-race terms, and I think that's the right lens. Historically, an arms race ends in one of three ways. Somebody runs out of money, everybody signs a treaty, or both sides conclude that the next weapon won't actually make them any safer.


But here's the part I find genuinely hopeful. In nature, impalas groom disease-carrying ticks off each other's backs. A selfish impala could take the help and never return the favor, but they don't, because they see the same herd every day and freeloaders get cut off. The math agrees with the impalas. In the 1980s, political scientist Robert Axelrod ran computer tournaments where dozens of programmed strategies played this game against each other over hundreds of rounds. The winner wasn't the most aggressive or the most clever. It was the simplest, a strategy that starts by cooperating, answers betrayal firmly, and then forgives the moment the other side cooperates again. Across the board, the strategies that did best shared two traits that might surprise you coming from a computer simulation: they were nice, and they were forgiving. Humans have gotten there before too. The nuclear arms race eventually produced treaties built on verification. Inspectors, not promises.


What we're watching

Those two ideas together give us something rare in investing, a checklist. Watch the money (can the enormous capital spending be sustained?). Watch for treaties (real agreements with verification, like the new voluntary federal security-review process and the labs' proposals to let independent evaluators inside). And watch for diminishing returns (does the next model meaningfully beat the last one?). Those three signals will tell us more about where this race is going than any podium statement ever will.


What this means for your portfolio

You won't see us make sudden moves off a headline, and that's deliberate. What you will see is the quieter work that periods like this call for. We build portfolios to hold up across a range of outcomes, a boom, a bust, or a treaty among them, and then we tend them: watching position sizes so no single theme, including AI, quietly grows into an outsized bet, rebalancing when the market's enthusiasm pushes allocations off target, and using volatility where it helps you, whether that's harvesting a tax loss or putting cash to work at better prices. This is the kind of environment your plan was built for, and we have our eyes on it so you don't have to.


If you'd like to talk through any of this, or anything else on your mind, call or reply anytime. That's what we're here for.


Warm regards,

Gray



Sources: D. Amodei, "We Must Pace the Frontier" (Sept. 12, 2026); CNBC, "What an Oscar-winning movie can teach us about investing through the AI slowdown debate" (Sept. 17, 2026); CNBC, "China says AI CEOs' call for a slowdown is 'fear mongering'" (Sept. 14, 2026); The Washington Post (Sept. 12, 2026); TechCrunch (Sept. 14, 2026); The Royal Swedish Academy of Sciences, Nobel Prize in Economic Sciences (1994); R. Axelrod, The Evolution of Cooperation (1984).


This material is provided by Crescent Wealth Management for informational and educational purposes only and reflects opinions as of the date written, which are subject to change. It does not constitute investment advice or a recommendation regarding any security. References to specific companies and public figures are for illustrative purposes only. Forward-looking statements are inherently uncertain and may not occur. Investing involves risk, including possible loss of principal. Diversification does not guarantee a profit or protect against loss.

 

Gray Howle 

Associate Financial Advisor / Crescent Wealth Management

Address: 124 Verdae Blvd., Ste. 105, Greenville, SC 29607

Direct: 864.900.4607 Office: 864.464.9626

Email: gray@crescentwm.com   Website: www.crescentwm.com

Advisory services offered through NewEdge Advisors, LLC, a registered investment adviser. Securities offered through NewEdge Securities, LLC. Member FINRA/SIPC. NewEdge Advisors, LLC and NewEdge Securities, LLC are wholly owned subsidiaries of NewEdge Capital Group, LLC. 


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