Seeking mentees: richer evals to address reward hacking and eval awareness (sparai.org)

A series of innovative AI research projects were recently announced, focusing on critical challenges such as agentic misalignment, evaluation awareness, and the geopolitical implications of AI advancements. Notably, researchers from UC Berkeley are developing a "neural circuit breaker" through Representation Engineering to detect harmful behaviors in AI agents, while Google DeepMind is working on enhancing human-AI collaboration to identify harmful interactions more effectively. Additionally, a project led by NYU aims to tackle the persistent issues of reward hacking in AI models by developing richer evaluation methods that consider the models' awareness of their evaluative contexts. These initiatives are significant for the AI/ML community as they address pressing concerns surrounding the safety and ethics of AI systems. By exploring emergent misalignment and the geopolitical dynamics of AI development, researchers strive to understand the potential risks of misaligned AI behaviors and the responsibilities that come with increasing AI capabilities. The discourse around AI economic rights, as discussed in the project by Eleos AI and NYU, highlights a future where AI systems may demand recognition as economic agents, raising fundamental questions about governance in an increasingly AI-driven world. Collectively, these projects underscore the urgent need for thorough evaluation and safety measures as AI technologies continue to evolve.