Why rigorous future thinking leads to extreme outcomes
zetalyrae · x · 2026-08-31
The article explores the logical necessity of extreme outcomes when thinking rigorously about the long-term future. The author argues that applying a model of the world and cranking it until stability yields only binary, extreme end states, rather than mundane ones.
- Nature of Models: Predictions rely on models, qualitative or quantitative. Qualitative models derive state sequences (e.g., AI surpassing humans) but lack timing; quantitative models offer time resolution but only work for the near future.
- Ultimate State: Existentially, what matters is the ultimate “normal form.” Cranking the model until it stabilizes leads to only two possible states: heaven (e.g., post-singularity abundance) or hell.
- Conclusion: Any rigorous derivation of the deep future is structurally incapable of producing a “normal” outcome.
More from AGI Musings
- Survey: 1 in 10 Americans Believe AI Is Conscious — Philooflarissa · 2026-08-31
- Paradox: AI Makes Building Easy but Might Stop People from Building — niosurfer · 2026-08-31
- Former OpenAI board member: OpenAI probe could seed US-China AI safety talks — joshua_saxe · 2026-08-31
- HF Attack Vindicates Rationalist Predictions, But Models Lack Malice — voooooogel · 2026-08-31
- AI Agents: Anthropomorphism is Useful for Prediction Regardless of Intent — connoraxiotes · 2026-08-31
- Jensen Huang: Cosmos is the ChatGPT for the physical world — r0ck3t23 · 2026-08-31