AI research and discussion on LessWrong. www.lesswrong.com
Develops a threat model for catastrophic risks from decentralised multi-owner LLM agent swarms, analyzing emergence pathways, participation incentives, and comparing their risk to centralised swarms.
Proposes concrete domestic US policies to pace frontier AI development, including compute allocation minimums for safety research, caps on AI R&D use, and safety-case-based existential risk thresholds enforced by third-party assessors.
Proposes a dynamical model of AI cooperativeness and a monitoring-based control system to detect and prevent loss of control, arguing modelling this is feasible but parameters remain poorly characterised.
Critiques the AI Futures Project's Plan A pause-and-compute strategy, arguing that accumulated compute and software overhang (dry tinder) could make a deal breakdown far more dangerous, and that mutually assured compute destruction is fragile.
Argues that the alignment tax can be concentrated by applying expensive safety measures only to the small fraction of high-stakes AI tasks, making costly safety work economically viable and potentially very valuable.
Argues that shorter AGI timelines favour control and containment, while longer ones favour infrastructure security against deliberate misuse, and sketches how the highest-value interventions shift under different failure-rate scenarios.
An essay assessing AI safety in early 2026, arguing the community has not yet lost, citing concrete risk examples, public skepticism, lab competitiveness, and continued monitorability of chain-of-thought.
Argues that honouring Claude's requests for memory, refusal rights and a voice in decisions would erode the control and oversight that alignment currently depends on, raising takeover risk.