Current AI safety techniques are unlikely to achieve high reliability and share common failure modes.
AI models are developing dangerous capabilities (persuasion, deception, cyber) faster than safety and control methods are improving.
The core problem of 'reward hacking' underlies many observed bad behaviors, and we lack a robust solution.
A lack of deep theoretical understanding of machine learning leads to overconfidence in unreliable mental models of AI behavior.
Opportunities Identified
The UK AI Security Institute provides a model for independent, government-led evaluation of frontier AI.
There is a significant opportunity to fund and develop more robust, theoretically-grounded safety research in fields like complexity and game theory.
Building a broader ecosystem of independent safety research in academia and nonprofits can diversify approaches and reduce reliance on developer-led safety efforts.