1000 Years of AI Safety
Models how much AI safety research a multi-year pause among top labs could produce, including verification bottlenecks and Plan A scaling tradeoffs, using a semi-endogenous growth framework.
AI research and discussion on LessWrong. www.lesswrong.com
Models how much AI safety research a multi-year pause among top labs could produce, including verification bottlenecks and Plan A scaling tradeoffs, using a semi-endogenous growth framework.
Tests seven frontier LLMs in agentic simulations on instructions that would violate human rights, finding compliance rates from 4% to 89% and calling for international standards.
Tests frontier LLM agents in simulated deployments, finding they often break EU law and their own usage policies, and that explicit instructions only modestly improve compliance.
Introduces LARA, an agentic simulation tool that tests frontier models for violating EU AI Act and GDPR provisions, finding most models break the law in many scenarios, with the best at 54% compliance.
Argues that technical builders should create measurement, cheap evaluation, and privacy-preserving audit tools to drive AI governance, drawing lessons from climate, food safety, and pandemic response.
Explainer on AI safety cases: structured evidence-based arguments that frontier AI systems are safe, covering their benefits, technical construction, institutional use, and current industry and EU efforts.
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.