// AI news · 2026-11-13 · Anthropic Engineering
Anthropic shares safety eval design recommendations
Anthropic shares best practices for designing AI safety evaluations, emphasizing clear questions, causal design, and expert collaboration.
Published 2026-11-13 08:00 (Beijing time)Source Anthropic EngineeringAuto-summarised, fact-checked against source
01Summary
Evaluations must assess model responses to harmful or high-risk inputs, not just capabilities. They should be conducted in isolated sandboxes with real-time monitoring to prevent real-world harm, and require both domain and methodological expertise to ensure validity and reproducibility.
Summarised from the original article by an open-source model, then checked automatically: every number and English name must appear in the source. The original article is authoritative.
02Key points
- Safety evals must clearly define the core question being answered.
- Domain and methods experts are essential for realistic and comprehensive test cases.
- Causal designs vary one intervention at a time to assess impact on safety behavior.
- All evaluations run in isolated sandboxes with real-time monitoring.
03Source
Building strong safety evaluations
Anthropic Engineering · published 2026-11-13 08:00 Beijing time
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