1 link tagged with all of: existential risk + long term forecasting
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Rigorous models of the distant future inevitably produce extreme outcomes rather than mundane ones, because when you run any consistent logic far enough, the world either reaches a stable endpoint or crashes—and stable endpoints in a post-human future look radically different from today.
- Qualitative models (like "AI gets smarter faster than humans") can show you the direction of change but not timing, forcing you to extrapolate to logical endpoints that seem implausible.
- Quantitative models work well for near-term prediction but break down over long timescales, so forecasters must instead ask what stable state a system converges to rather than what happens at a specific date.
- The only meaningful stable states for civilization are either transformative superintelligence scenarios (Matrioshka brains, uploaded minds, von Neumann probes) or civilizational collapse—there's no middle ground when you follow the logic to its conclusion.
long term forecasting
+ stable endpoints
+ extrapolation
+ superintelligence
existential risk
+ modeling