Safety · Concept
ECAISA: Epistemic Code for AI Safety and Alignment
Eight-principle epistemic code and disclosure ladder arguing safety research needs different norms than capability science.
Could seed journal and lab standards for preregistration and third-party audit of alignment claims.
Connections
Connections · 6
How this node ties into the rest of the map, and the evidence behind each link.
ECAISA proposes explicit epistemic norms, scoring, and disclosure practices for safety/alignment evaluation work.
+5 growthECAISA proposes epistemic norms and independent verification standards specifically for safety/alignment research quality.
+3 growthECAISA paper appears in the day’s AI safety arXiv cluster.
+3 growthECAISA demands independent verification and worst-case epistemic norms that strengthen evaluation science for alignment.
+3 growthECAISA’s demand for independent verification and worst-case epistemic norms would force earlier repayment of latent safety/security debts.
+3 growthHidden filler-token computation shows why safety research cannot rely on average-case capability metrics or surface CoT traces alone.
+3 growthSignal sources
Signal sources
Dated facts from primary sources in this direction.
In June 2025 the US AI Safety Institute was renamed the Center for AI Standards and Innovation (CAISI), pivoting toward security, standards and adversary-model assessment.
NIST →Anthropic activated its ASL-3 deployment and security standard with Claude Opus 4 on 22 May 2025 — the first real-world trigger of a responsible-scaling tier, focused on blocking bio-weapon uplift.
Anthropic →The International Network of AI Safety Institutes (launched Nov 2024) ran a third joint testing exercise focused on agentic AI systems across cyber and fraud strands.
European Commission — AI Office →