The scenario where one side achieves decisive technological advantage before the other (fast takeoff) could be more destabilizing than bilateral AGI development because it creates a window where preemptive action appears attractive

RAND has published extensively on nuclear war, arms control, and first-strike dynamics that inform contemporary thinking about AGI arms races and strategic instability

The paper presents eight scenarios organized across two critical axes: (1) whether one actor or multiple actors achieve AGI first, and (2) whether AGI empowers the party that develops it or disempowers both parties simultaneously

The Cold War II scenario assumes both the US and China achieve AGI and are transformed by it while maintaining rough parity and competitive tension, with AGI accelerating but not fundamentally eliminating the competitive bilateral relationship

Reasoning models (models that spend more computational time thinking through problems rather than producing immediate outputs) could reduce AGI development costs if they rely more on inference-time compute than training-time compute, enabling cheaper model advancement

AGI is a general-purpose technology that can be applied across any domain (health, policy, electronics, defense), meaning that even if AGI development is centralized, pressure to deploy it across all sectors will be enormous and difficult to resist

During the Cold War, mutual assured destruction (MAD) was theoretically coherent but both superpowers continuously tried to escape it through first-strike capabilities and technological advantages rather than accepting the logic of mutual vulnerability

AI-enabled military automation could reduce human casualties in military conflicts by replacing human pilots and soldiers with autonomous systems, creating a dynamic where both sides can engage repeatedly without incurring personnel losses unless explicitly escalated

War requires deliberate decision-making by states rather than accidental escalation, though accidents and misinterpretation remain possible, so whether AGI causes war depends on whether states deliberately choose to fight over AGI advantages or other issues

Smith indicates that he has a view on which of the three scenarios the host identified (Cold War II, Authoritarian Advantage, Wild Frontier) is most likely but delays revealing it to the end of the conversation

The paper deliberately avoids assigning probabilities to scenarios because the epistemic uncertainty about AGI development timelines, technical capabilities, and outcomes is too high to produce credible probability estimates

Smith has personal doubts about whether AGI can be controlled as easily as nuclear weapons, suggesting he questions the validity of the 'AGI as nuclear weapons' analogy for proliferation control

AGI development likely requires enormous capital investment, specialized talent, and educational infrastructure that only major countries with large existing tech ecosystems can currently marshal, making widespread global distribution of AGI development unlikely in the near term

Defining AGI and ASI precisely remains contested across the field, with ongoing debates about what threshold constitutes AGI, what it means to perform all intellectually valuable tasks, cost-effectiveness of AI compared to human performance, and whether superhuman intelligence is possible.

AGI's potential impact is so significant that whether it arrives today, 10 years from now, or 50 years from now remains incredibly important and consequential, making timing less critical than acknowledging the magnitude of possible transformation.

The analogy between AGI and nuclear weapons (expensive, controllable, limited to few states) versus internet (cheap, proliferative, benefits from widespread adoption) is useful for understanding scenario variation but imperfect.

In a world where AGI then ASI moves quickly and is very impactful, getting there first can confer a decisive advantage, which is why the single-vs-multiple-developer axis was central—though there are also possible worlds where being first is not actually a large advantage.

The paper deliberately defines AGI at its most capable extent—as intelligent as a human across all economically valuable or intellectual tasks—and ASI as far outperforming humans in every field, while bracketing the robotics/physical-embodiment question by assuming those physical problems are solvable.

There are roughly a hundred analogies people reach for when describing AI under uncertainty (nuclear weapons, electricity, fire, the internet), reflecting how people grasp for analogies amid uncertainty.

Mutually assured destruction in the Cold War held not because both sides were content with it but because neither side could technologically escape it, and both continually tried to escape it (first-strike theories, the missile race) until they realized they could not out-race each other.