AI Evaluations, Evaluationsor "Evals", focus on experimentally assessing the capabilities, safety, and alignment of advanced AI systems. These evaluations can be divided into two main categories: behavioral and understanding-based.based.

(note: initially written by GPT4, may contain errors.errors despite a human review. Please correct them if you see them)

Current challenges in AI evaluations include include:

• developing a method-agnostic standard to demonstrate sufficient understanding of a model, model
• ensuring that the level of understanding is adequate to catch dangerous failure modes, and modes
• finding the right balance between behavioral and understanding-based evaluations.

See also:

• Interpretability (ML & AI)
• AI Risk