Research / Sources
AI research and discussion on LessWrong. www.lesswrong.com
Analyses China's AI safety regulation, including the non-binding Framework 3.0 on loss-of-control risks, CAC model filing gaps, content-focused enforcement, and a court opinion on developer liability.
Proposes pacing AI development, meaning interventions that moderate its pace, as a dedicated research field, covering incentives, regulatory and technical tools, and the full lifecycle of interventions.
An essay defending Anthropic CEO Dario Amodei's proposal for coordinated frontier AI slowdown and regulation, arguing for embedded independent evaluators and distributed trust rather than trust in labs.
Analyses US federal statutes and executive powers that let the president unilaterally influence or control frontier AI companies, and the limits imposed by Congress and courts.
An essay arguing that AI safety policy needs legal practitioners who can implement regulation, using GDPR's Data Protection Officer failures as a warning and describing efforts to train such people in AI safety.
Argues that a global AI pause is nearly impossible because treaties come after warning shots, AI is dual-use, there is no capability ceiling, defection is hard to detect, and no clear warning shot may occur.
An informal LessWrong argument that personal computers already have enough power for AGI, so preventing AGI would require restricting both hardware and research, which the author considers near impossible.
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 falling costs of weapons-capable AI will cause proliferation of mass-destruction capabilities, surveying offensive uses in bio, chemical, cyber, drone and mirror-life weapons and superintelligence risks, with policy to follow.
Analyses the EU GPAI Code of Practice as a legally enforceable frontier AI safety framework requiring threat modelling, external evaluations, safety officers, and incident reporting for AGI companies.
A lawyer argues that an AGI ban must define precise, ex ante precursor capability thresholds with strict liability, rather than outcome-based definitions, drawing on nuclear treaties and EU AI Act precedents.
Proposes and reviews a conditional international AI safety treaty with compute thresholds, mandatory model audits, and AISI-led pause authority to address loss-of-control risks from advanced AI.
Argues that governments will likely seek to control AGI and limit its proliferation, weighing the alignment benefits of fewer actors against risks of centralized power and a worsened race dynamic.
Proposes forecasting questions on frontier AI governance, including lab safety-commitment reneging, US third-party testing requirements for if-then commitments, and mandated deception audits, with operationalizations of CBRN thresholds.