Is AI MAD?: Game theory & why collaboration is so challenging

The nuclear arms race and our current AI challenges

Game theory is a mathematical framework used for analyzing strategic interactions between rational decision-makers.

In the Cold War, this framework was used to model the behavior of the United States and the Soviet Union as they decided whether to build up or reduce their nuclear arsenals. At this time both the US and the USSR were engaged in an arms race, each building up their nuclear supplies to deter the other from launching a first strike.

Situations like these can be modeled using the Prisoner’s Dilemma, a classic game theory scenario where two parties may either choose to cooperate or defect. Where they choose to cooperate (in this case, disarm), both countries agree to reduce their nuclear weapons. Where they choose to defect (in this case, to arm), both countries secretly continue to build up their nuclear arsenals.

The dilemma arises because although mutual cooperation (disarmament) would be the best outcome for both, both fear that the other might defect (continue arming), which leads both to choose to defect. This results in a suboptimal outcome where both continue to arm and the tensions and potentially dangerous outcomes continue to rise.

The threat of Mutually Assured Destruction (MAD)

As both superpowers developed second-strike capabilities (the ability to retaliate even after a nuclear attack), the concept of Mutually Assured Destruction (MAD) emerged. This meant that any nuclear attack by one would result in the total destruction of both.

The payoff matrix modeling in this scenario showed that the best strategy for both was to avoid a first strike, as any attack would lead to catastrophic retaliation. This then led to the realization that continued armament would lead to mutual destruction, which fast-tracked the development of several arms control treaties.

Game theory, therefore, assisted with understanding the strategic decisions of the US and the USSR during the Cold War. By recognizing the destructive potential of continued armament and through a series of treaties, the nuclear arms race was eventually de-escalated, leading to a more stable and secure world.

Is AI MAD?

The issue with the AI race is that it is progressing more gradually. There is currently no obvious alarming event (like MAD) to compel parties to negotiate treaties. This could make the AI race more dangerous in terms of the potential outcomes. It’s particularly concerning because that AI development is currently driven by techno-optimists and profit-seekers rather than ethicists.

In his book Nexus, popular historian and New York Times bestselling author Yuval Noah Harari delves into the race to develop artificial intelligence (AI) and identifies it as one of the most pressing challenges of our time. The competition, which Harari likens to a high-stakes game, reveals how nations and companies are increasingly driven by the promise of unprecedented advantages—economic strength, military power, and technological dominance.

Harari believes that the AI race comes with risks that cannot be overlooked. With the relentless push to lead in AI, he says, there’s been a tendency to sideline ethical considerations and safety protocols, a trend Harari refers to as ‘prioritizing speed over responsibility’. This mindset, he warns, could be the very factor that drives humanity towards unforeseen and potentially catastrophic outcomes.

The rapid race to develop artificial intelligence (AI) is often also now analysed through the lens of game theory. As game theory identifies strategic interactions among competing players, it provides an illuminating framework for understanding the dynamics at play in the AI race.

In this context, each player (nation or corporation) is compelled to act independently, driven by the fear of being outpaced. This scenario also resembles the "prisoner's dilemma," where the rational choice for each competitor—to accelerate AI development without constraint—results in a collectively irrational outcome: increased risk of destabilization.

Collectively these choices increase risks to humanity, as premature deployment of AI systems could lead to unforeseen consequences or destabilization.

Managing the tension between collaboration and competition

In our research as outlined in our book The Innovation Race, we further explore these pressures. We examine how innovation often creates tensions between collaboration and competition. We argue that without a cooperative framework, innovation efforts can devolve into destructive rivalries.

In an age where the stakes couldn’t be higher, fostering trust and establishing global AI ethics and safety standards may be the only path forward. But putting up a pretence of collaboration or not committing fully to it can unwittingly become a slippery deception. Even if everyone might say they want the same ‘progressive yet safe' outcome, there can end up being deeper factors that threaten this.

There is typically a breakdown of collaboration when the cost-to-benefit ratio becomes too high. A common perspective can also be a fear of being left behind, with the mindset of: "If we don't build it (AI), someone else will, so we may as well go first!"

With so much at stake, adopting a balanced and cooperative approach to AI is more crucial than ever. Before entering this latest chapter of the ‘innovation race’ (with the new 'AI' entrant) and assuming we can control it, we must first address a fundamental question: “If there are compelling reasons both to collaborate and not to, under what conditions will collaboration occur? And how can we ensure those conditions are in place to support mutually beneficial and sustainable development?"

Are you prepared to make responsible decisions about new innovations such as AI?

by Andrew Grant and Gaia Grant (PhD) (C) Share this article from https://tirian.com/articles/6788/

Would you push the red button?

There are good reasons to cooperate – and good reasons not to do so – we are left with a question without an obvious answer: under what conditions will people cooperate? The answer matters a great deal to anyone trying to create an environment that fosters cooperation, from corporate managers and government bureaucrats to parents of unruly siblings. Learn about Tirian's "The Collaboration Concept" "Program, where the participants become their own social experiment. 

See Andrew Grant discuss  The Collaboration Concept workshop: Video  |  Simulation/Workshop/Keynote: 

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