# The Adversarial Rationality Blindspot in AI Existential Risk Mitigation > Reevaluating geopolitical game theory and the assumption of irrationality among international actors in the face of existential AI threats. **Published:** June 26, 2026 **Author:** PSEEDR Editorial **Category:** risk **Content tier:** free **Accessible for free:** true **Editorial format:** analysis **News quality eligible:** true **Source count:** 1 **Word count:** 1078 **Tags:** AI Safety, Game Theory, Geopolitics, Existential Risk, AI Governance **Canonical URL:** https://pseedr.com/risk/the-adversarial-rationality-blindspot-in-ai-existential-risk-mitigation --- In discussions surrounding existential AI risk, safety advocates frequently model geopolitical adversaries as irrational actors who would prioritize short-term competitive advantage over their own survival. A recent analysis from [lessw-blog](https://www.lesswrong.com/posts/ah5JMgJmEGJuxh79v/why-are-adversaries-assumed-to-be-incapable-of-responding-to) highlights this cognitive blindspot, pointing out the logical contradiction of believing AI poses a literal existential threat while assuming adversaries will ignore it. PSEEDR examines this assumption through the lens of game theory, contrasting the prevailing multipolar trap narrative with historical precedents of adversarial cooperation to assess the viability of multilateral AI safety treaties. ## The Utility Function of Self-Preservation The core observation from the lessw-blog post centers on a persistent double standard in how existential risk is communicated and modeled. When evaluating conventional geopolitical threats-such as a scenario presenting a twenty percent probability of a direct kinetic strike or nuclear exchange-analysts universally assume that state actors and political figures will follow basic self-preservation incentives. They will negotiate, de-escalate, or implement safeguards to avoid their own destruction. However, when the threat vector shifts to artificial general intelligence (AGI), this assumption of rational self-interest evaporates. The source notes that cooperative action to prevent an AI-driven catastrophe is often dismissed by safety advocates as an unrealistic expectation of universal selfless love. Instead of modeling adversaries as rational agents seeking regime survival, critics implicitly assign them a utility function of simply being the bad guy. This framing assumes that adversaries will pursue AI supremacy even if it guarantees their own disempowerment or destruction, a stance that contradicts foundational principles of statecraft and realpolitik. ## Deconstructing the Multipolar Trap Narrative The prevailing pessimism in AI safety circles is largely driven by the concept of the multipolar trap, often modeled as a high-stakes Prisoner's Dilemma. In this framework, multiple actors are racing to develop AGI. Even if all actors recognize the existential danger of an unaligned system, the fear that a rival might achieve a decisive strategic advantage incentivizes defection-continuing reckless development-over cooperation. While this game-theoretic model is mathematically sound under specific conditions, it relies heavily on the assumption that verification is impossible and that the payoff for defection outweighs the penalty of mutual destruction. PSEEDR analysis suggests this model may misrepresent the actual payoff matrix of existential AI risk. If the threat is truly existential, the penalty for defection is absolute zero (extinction), which alters the equilibrium. The assumption that adversaries cannot respond to AI risk conflates the difficulty of establishing trust with an inherent inability to recognize a shared threat. ## Historical Precedents for Adversarial Cooperation To evaluate whether adversaries can respond rationally to existential threats, we must look at historical precedents, most notably the Cold War. During the nuclear arms race, the United States and the Soviet Union were locked in an intense ideological and geopolitical struggle. Yet, the recognition of Mutual Assured Destruction (MAD) forced both superpowers to the negotiating table. Treaties such as the Non-Proliferation Treaty (NPT), the Strategic Arms Limitation Talks (SALT), and the Anti-Ballistic Missile (ABM) Treaty were not born out of altruism or universal selfless love. They were pragmatic, self-preserving responses to a technology that threatened both regimes equally. If advanced AI systems pose a comparable or greater threat to state control and human survival, the historical baseline suggests that adversarial states are highly capable of recognizing the danger and establishing binding frameworks to mitigate it, provided the threat is credible and mutually understood. ## Implications for International AI Governance Recognizing adversaries as rational actors capable of self-preservation significantly expands the policy space for international AI governance. Currently, much of the AI safety discourse focuses on unilateral containment, export controls, and domestic regulation, operating under the assumption that international agreements are futile. If we discard the irrational adversary fallacy, bilateral and multilateral safety treaties become viable strategic objectives. This shift implies that diplomatic efforts should focus heavily on establishing shared epistemic foundations-ensuring that all state actors have a common, scientifically grounded understanding of the existential risks associated with unaligned AGI. Furthermore, it elevates the importance of developing robust, verifiable mechanisms for monitoring AI development. Just as nuclear treaties rely on the International Atomic Energy Agency (IAEA) to inspect uranium enrichment facilities, an international AI treaty would require technical infrastructure to monitor large-scale compute clusters, track advanced semiconductor supply chains, and verify compliance with training run limitations. ## Limitations and Open Questions in Cooperative Models Despite the theoretical viability of adversarial cooperation, significant limitations and open questions remain. The lessw-blog source correctly identifies the cognitive bias against adversary rationality but does not provide specific mechanisms for how cooperation would function in practice. A primary limitation is the verification problem. Unlike nuclear weapons, which require massive, highly visible industrial infrastructure to produce fissile material, AI development is fundamentally a software and data challenge. While current frontier models require highly visible data centers and specialized hardware, future algorithmic efficiencies could reduce these requirements, making clandestine development easier to hide. Additionally, the timeline for AI capability jumps may be too compressed for traditional diplomatic treaties to form. Nuclear non-proliferation frameworks took decades to negotiate and refine; the window for establishing global AI governance may be significantly shorter. Finally, trust-building mechanisms in the digital domain are historically weak, as evidenced by the ongoing prevalence of state-sponsored cyber espionage. ## Synthesis The assumption that geopolitical adversaries are inherently incapable of responding to existential AI risk represents a critical failure of strategic imagination. By defaulting to a model where rivals act as irrational agents driven solely by a desire to be the bad guy, the AI safety community artificially restricts the scope of potential solutions. Transitioning from this cartoonish modeling to rigorous, game-theoretic analysis reveals that self-preservation remains the most powerful incentive in international relations. While the technical challenges of verification and the compressed timelines of AI development pose severe hurdles, acknowledging the rational self-interest of all global actors is a necessary first step toward constructing functional, multilateral frameworks capable of averting a shared catastrophe. ### Key Takeaways * AI safety discourse often relies on a flawed assumption that geopolitical adversaries will act irrationally and ignore existential threats to pursue short-term AI supremacy. * Modeling adversaries with a utility function of 'being the bad guy' contradicts foundational game theory and historical precedents of state self-preservation. * Historical examples, such as Cold War nuclear non-proliferation treaties, demonstrate that intense geopolitical rivals can cooperate when faced with mutually assured destruction. * Recognizing adversary rationality expands AI governance policy beyond unilateral containment to include bilateral and multilateral safety treaties. * Significant limitations remain regarding the technical feasibility of verifying AI development treaties compared to traditional nuclear infrastructure. --- ## Sources - https://www.lesswrong.com/posts/ah5JMgJmEGJuxh79v/why-are-adversaries-assumed-to-be-incapable-of-responding-to