What "good" is measured against
Standards & Frameworks
The formal standards, management systems, and governance frameworks that AI deployments are audited and certified against.
8 entries, newest first
ISO/IEC 27566-1:2025 — Information security, cybersecurity and privacy protection — Age assurance systems — Part 1: Framework
The first international standard for age assurance systems, establishing a technology-neutral framework and shared vocabulary for age-related eligibility decisions. It distinguishes age verification, age estimation, age inference, and successive validation, and describes core system characteristics including functionality, performance, privacy, security, and acceptability.
General-Purpose AI Code of Practice (EU AI Act, Articles 53 and 55)
Voluntary code of practice published 10 July 2025, drafted by 13 independent experts through a multi-stakeholder process (1,000+ participants) facilitated by the EU AI Office, to help providers of general-purpose AI models demonstrate compliance with EU AI Act Articles 53 and 55. It has three chapters — Transparency, Copyright, and Safety and Security — the first two applying to all GPAI providers and the third only to providers of models with systemic risk. The Commission and AI Board confirmed it as an adequate voluntary compliance tool; signatories (23+, coordinated via a Signatory Taskforce chaired by the AI Office) gain reduced administrative burden and greater legal certainty.
ISO/IEC 42005:2025 — Information technology — Artificial intelligence (AI) — AI system impact assessment
Guidance standard from ISO/IEC JTC 1/SC 42 for organizations performing AI system impact assessments focused on individuals and societies that can be affected by an AI system and its foreseeable applications. It covers how and when to perform assessments, at which stages of the AI system lifecycle, and how to document them. It operationalizes the impact-assessment requirement embedded in ISO/IEC 42001 and complements ISO/IEC 23894's risk-management guidance.
Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (NIST AI 600-1)
Companion profile to the NIST AI Risk Management Framework identifying twelve risks unique to or exacerbated by generative AI — including harmful content, human-AI configuration risks, and mental-health-relevant harms — and enumerating ~200 suggested actions mapped to the AI RMF's Govern/Map/Measure/Manage functions. Widely used as the de facto US reference for generative-AI risk programs.
IEEE 7014-2024 — IEEE Standard for Ethical Considerations in Emulated Empathy in Autonomous and Intelligent Systems
An IEEE standard providing guidance and actions for the ethical development, deployment, and decommissioning of autonomous and intelligent systems that identify, simulate, or respond to human affective/emotional states ('emulated empathy'). Developed over five years by IEEE's Empathic Technology working group under the Society on Social Implications of Technology.
IEEE 2089.1-2024 — IEEE Standard for Online Age Verification
Establishes a framework for the design, specification, evaluation, and deployment of online age-verification and age-estimation systems, including privacy, data-security, and information-management requirements for the age-assurance process. Second standard in the 5Rights-based family after IEEE 2089-2021.
ISO/IEC 42001:2023 — Information technology — Artificial intelligence — Management system
The world's first certifiable AI management system standard (AIMS), developed by ISO/IEC JTC 1/SC 42. It specifies requirements for establishing, implementing, maintaining and continually improving an AI management system within any organization that provides or uses products or services utilizing AI systems. It exists to give organizations an auditable, ISO-harmonized-structure framework for responsible AI development and use, analogous to ISO 27001 for information security.
IEEE 2089-2021 — IEEE Standard for an Age Appropriate Digital Services Framework Based on the 5Rights Principles for Children
IEEE SA standard establishing processes by which organizations make digital products and services age appropriate, built on the 5Rights Foundation principles and grounded in the UN Convention on the Rights of the Child. It guides organizations through the development, delivery and distribution lifecycle to identify child-specific risks and embed age-appropriate safeguards. It is the reference design standard behind age-appropriate-design regulation (e.g. the UK Children's Code) and directly applicable to conversational AI services children can access.