Evaluating Alignment

Evaluating the alignment of artificial intelligence models, particularly large language models (LLMs), with human values and intentions is a crucial area of research. Current efforts focus on developing robust metrics and benchmarks that assess alignment across diverse tasks and scenarios, employing various techniques including agent-based evaluations and LLM-as-judge paradigms. These investigations highlight the multi-faceted nature of alignment, revealing inconsistencies between different evaluation methods and underscoring the need for more comprehensive and integrative approaches. Ultimately, improved alignment evaluation is vital for ensuring the safe and beneficial deployment of increasingly powerful AI systems.