What are Evals in AI?

Evals (Evaluations) are systematic tests and assessment frameworks designed to measure AI model capabilities, safety, alignment, and performance across specific tasks, domains, or behavioral criteria.

Evals provide objective measurement of AI system capabilities, identify potential risks or limitations, and ensure models meet required standards before deployment in production environments.

Evals work by creating standardized test suites that probe different aspects of AI behavior, from factual knowledge and reasoning to safety alignment and potential harmful outputs, providing quantitative scores and qualitative insights.

Safety evals might test whether an AI refuses harmful requests, while capability evals measure performance on math problems, coding tasks, or reading comprehension across various difficulty levels.

Connected to AI Safety, Model Testing, Benchmarks, Quality Assurance, Risk Assessment, and AI Alignment research.