Artificial intelligence capabilities march steadily toward human-level performance, prompting diverse forecasts regarding artificial general intelligence and its profound global power implications. Proposed strategies for managing the AGI transition range from rapid competitive racing and Cold War-style deterrence to a global moratorium, reflecting fundamentally divergent assumptions about future risks and technological trajectories.
This analytical landscape maps competing worldviews from catastrophic intelligence explosion scenarios to perspectives viewing AI as a normal technology whose societal diffusion unfolds gradually over decades. Key variables such as computing power availability, proliferation rates, adoption speeds, and automated AI research capacity will ultimately drive drastically different outcomes. Understanding these foundational assumptions equips decision-makers and researchers to better navigate an uncertain future.
General-purpose technological diffusion rarely follows a uniform velocity across competing state economies, complicating baseline assumptions about artificial general intelligence transitions. Historical parallels drawn from electrification and combustion engine adoption demonstrate that infrastructural bottlenecks and compute allocation determine the actual speed of societal integration more than raw algorithmic breakthroughs.
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