Whats the point of having a WG if we don’t state what its goals are?
Todd Gifford
“WG-AI-Conformance” isn’t a formal term, but it likely refers to efforts across international organizations to define conformance, testing, and compliance standards for AI systems. Key players include ISO/IEC, IEEE, and the European Union.
🔧 1. ISO/IEC JTC 1/SC 42 – AI Standardization
JWG 2 (Joint Working Group with SC 7)
Focuses on testing methods and conformance assessment for AI systems.Role: Establish technical protocols to ensure AI system behavior matches expected performance and safety requirements.
🗂 Related Standard:
ISO/IEC 42001:2023 – Management system for AI, enabling organizations to design trustworthy AI processes with compliance and oversight.
🧭 2. IEEE P7999 – Ethics Oversight & Conformance
Develops ethics-based assessment criteria for AI governance.
Includes certification mechanisms for individuals and organizations responsible for AI systems.
Goal: Align AI development with human-centered design and transparency.
🇪🇺 3. European Union AI Act (Effective 2024–2026)
High-risk AI systems must undergo conformance assessment under harmonized standards.
Article 47: Requires a formal “EU Declaration of Conformity”.
Systems that pass conformance may receive a CE marking to legally operate in the EU market.
🧩 Conformance Routes:
Harmonized Standards: Developed under CEN/CENELEC.
Common Specifications: Applied if no harmonized standards exist.
✅ Summary Table
Framework
Focus
Conformance Element
ISO/IEC SC 42 (JWG 2)
Technical Testing
AI performance testing, system-level validation
ISO/IEC 42001
Management Systems
Organizational governance & risk management
IEEE P7999
Ethical Oversight
Ethics certification, transparency, fairness
EU AI Act
Legal Compliance
Declarations of Conformity, CE marking
📌 Key Takeaways
Multiple global efforts define what it means for an AI system to be “conformant.”
Testing, ethics, and governance are all critical domains of conformance.
The EU AI Act creates legal obligations; ISO/IEC and IEEE create the technical and ethical scaffolding.
Let me know if you'd like this in a PowerPoint, PDF, or email-ready format, or if you want me to include logos, timelines, or country-specific views
Laura Santamaria
> The goal of this group is to define a standardized set of capabilities, APIs, and configurations that a Kubernetes cluster must offer to reliably and efficiently run AI/ML workloads. This initiative aims to simplify AI/ML operations on Kubernetes, accelerate adoption, guarantee interoperability and portability for AI workloads, and enable ecosystem growth on an industry-standard foundation.
I think it's a bit better than ChatGPT's summary, if I do say so myself :)
May I suggest reading through that document [1] , as well as the discussions around the initial pull request [2], and the dev@ mailing list summary [3], and the related doc where initial discussions started [4], and then coming back to ask some questions?
Thanks!