Responsible AI materials from standards, risk frameworks, regulator guidance, consultations, and legal sources.
Risk-based AI governance is ready for immediate standardization. Security, privacy, transparency, incident response, recovery, training-data practices, terminology, and taxonomy are near-term standards candidates. TEVV procedures can be standardized now, but TEVV metrics and scientific validity stil...
ViewLifecycle AI governance: what NIST and the EU AI Act together require The NIST AI RMF and its Playbook treat AI governance as a **full lifecycle control system** spanning govern, map, measure, and manage, with supporting practices such as documentation, testing, monitoring, supplier oversight, and d...
ViewQ1. A project team is building an AI system inventory. Which item belongs in the inventory according to the NIST sources? - A list of the system's artifacts, such as incident response plans, data dictionaries, source code links, and AI actor contact information - A marketing summary of the model's b...
ViewArticle 50 transparency duties for generative AI compliance Article 50 of the EU AI Act creates **binding transparency duties** for AI interactions, synthetic content, deepfakes, and certain public-interest text. The Commission’s draft guidance is meant to help providers and deployers implement thos...
ViewNIST’s July 2024 AI standards priority list makes a sharp split: some governance topics are ready to standardize now, while others still need foundational work before teams can rely on them.[[cite:1]][[cite:2]] Ready-now areas include terminology and taxonomy, TEVV methods and metrics, provenance an...
ViewEU AI Act mapping: evidence status I found the attached EU AI Act page at the European Commission digital strategy site, but the available search pass returned no extractable evidence from that source, so I cannot responsibly provide a substantive jurisdiction-aware mapping from the material on hand...
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