AI research and discussion on LessWrong. www.lesswrong.com
Argues that near-term autonomous replicating AI agents are unlikely to pose existential risk because frontier labs hold compute and economic advantages, and that they may aid preparedness, though unchecked deployment restrictions could backfire.
Argues for more empirical research measuring the security-relevant capabilities of biological AI models, such as protein and genomic models, to inform biosecurity policy and funding decisions.
Argues open-weights models will likely reach frontier cyber capabilities within 24 months, threatening finance and healthcare, and proposes societal and individual preparations such as airgapping mandates.
A 4,100-person study finds AI voice models match or beat human scammers in eliciting compliance, and that AI vishing is already economically profitable, so the risk lies in automation.
A recap of the Australian AI Safety Forum covering agentic evaluation, offensive-cyber time horizons, Dark AI markets, recursive self-improvement experiments, and Australia's AI safety and governance role.
Proposes a quantitative probabilistic risk-modelling methodology for AI-enabled cyber attacks, building nine Bayesian models using benchmarks (Cybench, BountyBench) and expert elicitation to estimate AI uplift and harm.
Argues that Anthropic's Claude Mythos and its Project Glasswing access controls make certain AI-enabled coup pathways more plausible, and that private lab control over access to dangerous cyber capabilities is a governance concern.