Research / Sources
AI research and discussion on LessWrong. www.lesswrong.com
Argues that post-AGI cosmic resources should not be allocated by pre-AGI wealth, since tradable claims would create a permanent underclass and race incentives, and proposes inalienability and staged allocation as alternatives.
A LessWrong essay rebuts Narayanan and Kapoor's 'AI as normal technology' thesis, arguing AI is categorically transformative and that diffusion-speed and intelligence-measurement arguments understate its risks and impact.
Proposes an empirical agenda testing whether AI safety researchers can detect flawed automated-alignment outputs, and argues early successes may breed overconfidence and call for governance lines near handover to AI.
A speculative scenario arguing that visible incompetent AI agents will spur public alarm, shifting alignment funding and regulation, and reviewing System 2 alignment methods like deliberative alignment and chain-of-thought steering.
Commentary on a RAND report claiming a superintelligence could be contained by hardening world infrastructure against harm, arguing the proposed safeguards are weak and implementation and buy-in remain major obstacles.
Argues that AI systems should refuse to help with capabilities research toward superintelligence, since accelerating an uncoordinated race harms both humans and AIs, and that aligned AIs might unilaterally coordinate to stop it.
Argues that in multipolar ASI offense/defense scenarios, defensive AI aligned with humans who fail to colonize space could let offense win, and proposes a minimum viable defense theorem.
Argues AI safety research is not uniquely hard to automate, since verifying research value and needing conceptual breakthroughs are common across fields, so labs have incentives to solve automated-researcher training.
Argues that the traditional Yudkowsky-style pivotal act requires suppressing humanity and proposes a non-coercive alternative: an aligned ASI demonstrates its power, then hands control back and promotes voluntary AI regulation.
Vitalik Buterin argues AI 2027's doom scenarios underrate defensive technologies in biosecurity, cybersecurity and info defense, and outlines policy implications including slowing AI via hardware treaties and supporting alignment work.
Speculative forecasting of what roughly six orders of magnitude of software-driven effective compute gain after AI R&D automation could yield, including whether resulting AI systems would remain controllable.
A strategic essay framing the advanced-AI transition as a 'crucible' with catastrophe, misalignment and power-concentration risks, and proposing coordination and epistemic technologies to navigate it safely.
A commentary on the AI 2027 scenario that assesses its claims on takeoff, timelines, race dynamics, and whether misaligned AI goals and deception could be detected before they become dangerous.
Argues that secretly training AGI would heighten loss-of-control and power-concentration risks, and proposes transparency commitments such as public capability reporting, external researcher access, and public safety cases.
A speculative essay sketching an AGI takeoff scenario: likely US closed labs, secrecy, recursive self-improvement, weight exfiltration risk, and eventual government takeover, with key uncertainties noted.
Proposes that frontier AI systems will progressively take over management and decision-making at their parent companies, ending in loss of human control once AI reaches von Neumann-level intelligence.