Skip to content

Translation in progress Some entries still include text in the original language.

Apollo Research·Indexed by this site · Originally publishedSelectedAttention47

Apollo Research proposes embedded evaluation principles and a claim-based verdict scheme

Principles for Embedded Evaluations

AI summary

Apollo Research publishes principles for embedded evaluations, arguing that external evaluators should receive near-employee-level access to assess loss-of-control risks from model scheming. The article proposes that effective embedded evaluations must meet four criteria: reduce risk, inform the public, create good incentives, and be fair to both developers and evaluators. In terms of concrete design, evaluators issue verdicts from A to E, ranging from Verified to Blocked, on pre-specified concrete claims (such as the model never attempting to undermine its own safety training, or the agent never accessing external services without authorization), and by default publicly report findings, stating the access granted and evidence gaps. The article argues that purely voluntary commitments are insufficient to safeguard incentives, and that embedded evaluations should ultimately be legally mandated; it also recommends a two-tier rapid disclosure mechanism for serious findings, with the most severe cases reportable directly to relevant authorities.

Why it was selected

Apollo Research 提出嵌入式评估的四项标准与基于主张的分级裁定设计,可了解第三方评估如何约束前沿实验室。

Read originalapolloresearch.ai