aviation-regulator

EASA — Concept Paper: Guidance for Level 1&2 Machine Learning Applications

Name: Calibrated Authority rating — EASA — Concept Paper: Guidance for Level 1&2 Machine Learning Applications
Item: EASA — Concept Paper: Guidance for Level 1&2 Machine Learning Applications — public generative-AI policy
Rating: 9
Author: Chris Huber Reitz

9/12Calibrated Authority

“Firstly, learning assurance covers the paradigm shift from programming to learning, as the existing development assurance methods are not adapted to cover learning processes specific to AI/ML.”— EASA Concept Paper: guidance for Level 1 & 2 machine learning applications, Proposed Issue 02 — AI assurance building block · source ↗

Traceability & inspectability

Human authorship & accountability

Disclosure & labeling

Synthetic-identity / fabrication prohibition

Human validation in loop

Evidential-trust emphasis

Posture Balanced Boundary fit · fits Trust-logic Evidential ⚑ twilight framing

Source policy: https://www.easa.europa.eu/en/downloads/137631/en

Machine record: /institutions/easa.json

Cite this

Reitz, C.H. (2026). The Calibrated Authority Index — EASA — Concept Paper: Guidance for Level 1&2 Machine Learning Applications. https://calibrated-authority.chrishuberreitz.com/institutions/easa Quote: “Firstly, learning assurance covers the paradigm shift from programming to learning, as the existing development assurance methods are not adapted to cover learning processes specific to AI/ML.” Source: https://www.easa.europa.eu/en/downloads/137631/en

Index Methodology Manifest JSON atom CC-BY-4.0 · v2026-09-08 · Chris Huber Reitz