… Frontier threats red teaming for national security risks Since we released our blog post on our approach to red teaming AI systems for national security risks, we’ve continued to build out evaluation techniques to measure “frontier threats” areas that may pose a consequential risk to national secur… …
… Department of Energy DOE ’s National Nuclear Security Administration NNSA to assess our models for nuclear proliferation risks and continue to work with them on these evaluations. …
… Governments need time to build the capacity to capture benefits while containing risks, which is why they need to start now. Policy that meets the moment We’ve long argued that frontier AI companies should be transparent about what their models can do and how they’re managing the risks. …
… We provide evidence-based analysis about AI’s implications for cybersecurity, national security, and autonomous systems. …
… Adapting to a new phase of cybersecurity Models with similar cybersecurity skills to Mythos Preview will soon be more broadly available. …
… Three types of risk, three components of defense Security risks to agents fall into one of three categories: User misuse: A user—either maliciously or through carelessness—directs the agent to do something harmful. …
… 54.8% of the threat actors studied used AI to bypass, disable, or tamper endpoint security tools. …
… Evaluations, red teaming, standards, interpretability and other safety research, auditing, and strong cybersecurity practices are all promising avenues for mitigating the risks of AI while realizing its benefits. …
… Within the realm of threat actors seeking assistance from AI, biological risks—and catastrophic risks more generally—are by no means the only concern. …
… But the autonomy that makes agents useful also introduces a range of new risks. …