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Priorities include: evaluations that still work even when a model can determine if it is being tested and may therefore understate its harmful capabilities (“sandbagging”) or conceal misalignment (“alignment faking”), backed by secure access for independent third parties; assessing control-undermining capabilities and propensities and defining clear, operationalizable red lines; verifying that AI systems used to supervise other AI are themselves trustworthy; keeping a model’s step-by-step “chains-of-thought” honest and human-readable so they can be monitored; and metrics for AI R&D automation and secure infrastructure giving external authorities awareness of internal deployments crossing regulatory thresholds.AI Unverifiable (Jul 7, 2026)
2mo ago
According to common benchmarks, open weight models are estimated to be 3 to 12 months behind the frontier (varying across capabilities). Developers of frontier closed models have recently designated these closed models as ‘High’ risk for cyber and bi...more AI Verified source (Jul 2026)
added 1mo ago
Safety for open-weight models whose capabilities are nearing frontier closed models requires unique tools for open-weight model safety and ecosystem monitoring. [...] Accelerated public and private investment in research is required to keep pace with...more AI Verified source (Jul 2026)
added 2mo ago
Independent third-party AI testing and assurance providers play an important role in translating AI safety research into repeatable evaluation methods, objective testing reports, certification schemes, and practical risk management support for indust...more AI Verified source (Jul 2026)
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Dario Amodei
CEO at Anthropic
OpenAI
AI research organization
Anthropic
AI safety research company
Yoshua Bengio
AI Pioneer, Turing Award winner
Sam Altman
CEO at OpenAI
Demis Hassabis
Nobel laureate, AI Researcher and CEO of DeepMind
Scott Alexander
Author and psychiatrist
António Guterres
UN Secretary-General
Bernie Sanders
U.S. Senator from Vermont