The High-Speed Stag Hunt (Video)

What happens when AI agents start making trust decisions at millisecond speeds? This video explores the collision between game theory’s classic Stag Hunt and the relentless pace of algorithmic decision-making — and why going faster might mean cooperating less.

Can machines learn to trust each other — and us? As AI systems increasingly handle negotiations, economic transactions, and strategic choices at speeds no human can match, they face a fundamental dilemma: play it safe with a small guaranteed win, or risk everything on collective cooperation for a far greater reward.

This is the Stag Hunt, a game theory scenario that cuts deeper than the famous Prisoner’s Dilemma. The video breaks down the difference between the two, then turns to the real question: what happens when AI agents cycle through these decisions thousands of times per second? The uncomfortable answer is that speed tends to favor caution — defaulting to the “hare” strategy of safe, mediocre outcomes rather than the coordinated pursuit of the “stag.”

The video explores whether algorithmic trust is even possible, and what it would take to build digital social contracts that prevent a “flash crash” of human cooperation. As automation accelerates, the stakes keep rising: are we building a future of isolated, self-interested agents, or can we still coordinate for something greater?

Source: The High-Speed Stag Hunt