The Global AI Standards Repository is the world’s first centralized, transparent notification system that captures AI and Autonomous and Intelligent Systems standards and standards in progress. If you would like to submit an entry, please use the submit button below.

*This is a compilation of user submitted entries. The submitter is responsible for any and all changes/updates to the list of standards.

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Organization Standard Scope Stage Country
IEEE IEEE P7014™ - IEEE Draft Standards Project for Ethical considerations in Emulated Empathy in Autonomous and Intelligent Systems Defines a model for ethical considerations and practices in the design, creation and use of empathic technology, incorporating systems that have the capacity to identify, quantify, respond to, or simulate affective states. In Development Global
IEEE IEEE P7012™ - IEEE Draft Standards Project for Machine Readable Personal Privacy Terms Identifies/addresses the manner in which personal privacy terms are proffered and how they can be read and agreed to by machines. In Development Global
IEEE IEEE P7011™ - IEEE Draft Standards Project for the Process of Identifying and Rating the Trustworthiness of News Sources Provides semi-autonomous processes using standards to create and maintain news purveyor ratings for purposes of public awareness. It standardizes processes to identify and rate the factual accuracy of news stories. In Development Global
IEEE IEEE P7010-2020™- (Standard Now Available) - IEEE Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well-being The impact of artificial intelligence or autonomous and intelligent systems (A/IS) on humans is measured by this standard. The positive outcome of A/IS on human well-being is the overall intent of this standard. Published Global
IEEE IEEE P7009™ - IEEE Draft Standards Project for Fail-Safe Design of Autonomous and Semi-Autonomous Systems Establishes a practical, technical baseline of specific methodologies and tools for the development, implementation, and use of effective fail-safe mechanisms in autonomous and semi-autonomous systems. In Development Global
IEEE IEEE P7008™ - IEEE Draft Standards Project for Ethically Driven Nudging for Robotic, Intelligent and Autonomous Systems Establishes a delineation of typical nudges (currently in use or that could be created). Contains concepts, functions and benefits necessary to establish & ensure ethically driven methodologies for the design of robotic, A/IS incorporating them. In Development Global
IEEE IEEE P7007™ - IEEE Draft Standards Project for Ontological Standard for Ethically Driven Robotics and Automation Systems Establishes a set of ontologies with different abstraction levels that contain concepts, definitions and axioms which are necessary to establish ethically driven methodologies for the design of Robots and Automation Systems. In Development Global
IEEE IEEE P7006™ - IEEE Standards Project for Personal Data AI Agent Working Group Describes the technical elements required to create and grant access to a personalized Artificial Intelligence (AI) that will comprise inputs, learning, ethics, rules and values controlled by individuals. In Development Global
IEEE IEEE P7005™ - IEEE Draft Standards Project for Employer Data Governance Defines specific methodologies to help employers to certify how they approach accessing, collecting, storing, utilizing, sharing, and destroying employee data. Provides specific metrics and conformance criteria regarding these types of uses. In Development Global
IEEE IEEE P7004™ - IEEE Draft Standards Project for Child and Student Data Governance Defines specific methodologies to help users certify how they approach accessing, collecting, storing, utilizing, sharing, and destroying child and student data. Provides specific metrics and conformance criteria regarding these types of uses. In Development Global
IEEE IEEE P7003™- IEEE Draft Standards Project for Algorithmic Bias Considerations Provides developers of algorithms for autonomous or intelligent systems with protocols to avoid negative bias in their code. In Development Global
IEEE IEEE P7002™- IEEE Draft Standards Project for Data Privacy Process Specifies how to manage privacy issues for systems or software that collect personal data by defining requirements that cover corporate data collection policies and quality assurance. In Development Global
IEEE IEEE P7001™ - IEEE Draft Standards Project for Transparency of Autonomous Systems Describes measurable, testable levels of transparency, so that autonomous systems can be objectively assessed and levels of compliance determined. In Development Global
IEEE IEEE P7000™ - IEEE Draft Standards Project for Model Process for Addressing Ethical Concerns During System Design Establishes a process model by which engineers and technologists can address ethical consideration throughout the various stages of system initiation, analysis and design. In Development Global
CIO Strategy Council CAN/CIOSC 103-2™ - Digital Identity and Trust – Part 2: Delivery of Health Care Services Specifies minimum requirements for a user-centric, interoperable health network that securely binds a health care identity to strong digital credentials to facilitate appropriate and user-directed sharing of that identity. In Development CAN
CIO Strategy Council CAN/CIOSC 103-1™ - Digital Trust and Identity – Part 1: Fundamentals Specifies minimum requirements and a set of controls for developing, implementing, operating, monitoring, and governing trust in systems and services that consume and assert digital identity. Published CAN
CIO Strategy Council CIOSC 102™ - Qualification and Certification of Big Data and Machine Learning Personnel Specifies minimum requirements for the qualification and certification of personnel who perform big data analytics and develop machine learning algorithms. Published CAN
CIO Strategy Council CAN/CIOSC 101:2019™ - Ethical Design and Use of Automated Decision Systems Specifies minimum requirements in protecting human values and incorporating ethics in the design and use of automated decision systems that use machine learning. Published CAN
CIO Strategy Council CAN/CIOSC 100-2™ - Third-Party Access to Data and Privacy Specifies minimum requirements and a set of privacy controls for third-party access to data. This Standard applies to all organisations, including public and private companies, government entities, and not-for-profit organisations. Published CAN
CIO Strategy Council CAN/CIOSC 100-1™- Data Protection of Digital Assets Specifies minimum requirements for the data protection of all digital assets at-rest, in-motion, and in-use across platforms, facilitating secure sharing and collaboration across IT systems within and between organizations. Published CAN
IEEE IEEE P3652.1™ - IEEE Draft Standards Project for Guide for Architectural Framework and Application of Federated Machine Learning Provides a blueprint for data usage and model building across organizations while meeting applicable privacy, security and regulatory requirements. In Development Global
IEEE IEEE P3333.1.3 - Standard for the Deep Learning Based Assessment of Visual Experience Based on Human Factors This standard defines deep learning-based metrics of content analysis and quality of experience (QoE) assessment for visual contents. In Development Global
IEEE IEEE P2975™ - Standard for Industrial Artificial Intelligence (AI) Data Attributes Defines attributes related to industrial Artificial Intelligence (AI) data that facilitates the classification, association, and mapping towards value creation using data. The attributes include but are not limited to data source, type, ownership, sampling frequency, traceability, privacy attributes for modeling, sampling, shareability and its use in AI algorithms. In Development Global
IEEE IEEE P2945™ - Standard for Technical Requirements for Face Recognition Systems Specifies an architecture and technical requirements for face recognition systems. A general technical architecture is defined. Functional, performance, and security requirements are defined. This standard is applicable to the design and application of face recognition systems. In Development Global
IEEE IEEE P2941™ - Standard for Artificial Intelligence (AI) Model Representation, Compression, Distribution and Management Defines AI development interface, AI model interoperable representation, coding format, and model encapsulated format for efficient AI model inference, storage, distribution, and management. In Development Global
IEEE IEEE P2894 - Guide for an Architectural Framework for Explainable Artificial Intelligence This guide specifies an architectural framework that facilitates the adoption of explainable artificial intelligence (XAI). In Development Global
IEEE IEEE P2863 - Recommended Practice for Organizational Governance of Artificial Intelligence This recommended practice specifies governance criteria such as safety, transparency, accountability, responsibility and minimizing bias, and process steps for effective implementation, performance auditing, training and compliance. In Development Global
IEEE IEEE P2842 - Recommended Practice for Secure Multi-party Computation This standard provides a technical framework for Secure Multi-Party Computation In Development Global
IEEE IEEE P2841 - Framework and Process for Deep Learning Evaluation This document defines best practices for developing and implementing deep learning algorithms and defines a framework and criteria for evaluating algorithm reliability and quality of the resulting software systems In Development Global
IEEE IEEE P2840 - Standard for Responsible AI Licensing The standard describes specifications for the factors that shall be considered in the development of a Responsible Artificial Intelligence (AI) license. In Development Global
IEEE IEEE P2830 - Standard for Technical Framework and Requirements of Shared Machine Learning This standard defines a framework and architectures for machine learning in which a model is trained using encrypted data that has been aggregated from multiple sources and is processed by a third party trusted execution environment. In Development Global
IEEE IEEE P2817™ - IEEE Draft Standards Project Guide for Verification of Autonomous Systems Identifies existing best practices and provides instruction sets that define valid verification processes for a range of autonomous system configurations. In Development Global
IEEE IEEE P2807.4™ - Guide for Scientific Knowledge Graphs This standard defines guidelines for application of knowledge graphs for financial services. The standard specifies technical framework, workflows, implementation guidelines and application scenarios of financial knowledge graphs. Published Global
IEEE IEEE P2807.2™ - Guide for Application of Knowledge Graphs for Financial Services This standard defines guidelines for application of knowledge graphs for financial services. The standard specifies technical framework, workflows, implementation guidelines and application scenarios of financial knowledge graphs. Published Global
IEEE IEEE P2807.1 - Standard for Technical Requirements and Evaluation of Knowledge Graphs This standard defines technical requirements, performance metrics, evaluation criteria and test cases for knowledge graphs. In Development Global
IEEE IEEE P2807 - Framework of Knowledge Graphs This standard defines the framework of knowledge graphs (KGs). In Development Global
IEEE IEEE P2802™ - Standard for the Performance and Safety Evaluation of Artificial Intelligence Based Medical Device: Terminology The standard establishes terminology used in artificial intelligence medical device, including definitions of fundamental concepts and methodology that describe the safety, effectiveness, risks and quality management of artificial intelligence medical device. The standard provides definitions using the following forms, such as but not limited to literal description, equations, tables, figures and legends. The standard also establishes a vocabulary for the development of future standards for artificial intelligence medical device. Published Global
IEEE IEEE P2801™ - IEEE Draft Standards Recommended Practice for the Quality Management of Datasets for Medical Artificial Intelligence Identifies best practices for establishing a quality management system for datasets used for artificial intelligence medical device. In Development Global
IEEE IEEE P2751 - 3D Map Data Representation for Robotics and Automation This standard extends the IEEE 1873-2015 Standard for Robot Map Data Representation from two-dimensional (2D) maps to three-dimensional (3D) maps. In Development Global
IEEE IEEE P2672 - Guide for General Requirements of Mass Customization This guide provides the definitions, terminologies, operation procedures, system architectures, key technological requirements, data requirements and applications of and related to user-oriented mass customization. In Development Global
IEEE IEEE P2671 - Standard for General Requirements of Online Detection Based on Machine Vision in Intelligent Manufacturing This standard specifies through the general requirements of online detection based on machine vision. In Development Global
IEEE IEEE P2247.4™ - Recommended Practice for Ethically Aligned Design of Artificial Intelligence (AI) in Adaptive Instructional Systems This recommended practice describes ethical considerations and recommended best practices in the design of artificial intelligence as used by adaptive instructional systems. In Development Global
IEEE IEEE P2247.3 - Recommended Practices for Evaluation of Adaptive Instructional Systems This recommended practice defines and classifies methods of evaluating adaptive instructional systems (AIS) and establishes guidance for the use of these methods. In Development Global
IEEE IEEE P2247.2 - Interoperability Standards for Adaptive Instructional Systems (AISs) This standard defines interactions and exchanges among the components of adaptive instructional systems (AISs). In Development Global
IEEE IEEE P2247.1 - Standard for the Classification of Adaptive Instructional Systems This standard defines and classifies the components and functionality of adaptive instructional systems (AIS). This standard defines parameters used to describe AIS and establishes requirements and guidance for the use of these parameters. In Development Global
IEEE IEEE P2089™ - IEEE Draft Standards Project for Age Appropriate Digital Services Framework - Based on the 5Rights Principles for Children Provides a methodology to establish a framework for digital services when end users are children, and by doing so, tailors the services that are provided so that they are age appropriate. In Development Global
IEEE IEEE P2049.1™ - IEEE Draft Standards Project for Standard for Human Augmentation: Taxonomy and Definitions Specifies the taxonomy and definitions for human augmentation. Human augmentation, also known as human enhancement, is used to refer to technologies that add to the human body and enhance human productivity or capability. Recent advancements in many technical areas have led to a large variety of implants, wearables and otherre technologies that could be classified as human augmentation. In Development Global
IEEE IEEE P2049.2™ - IEEE Draft Standards Project for Human Augmentation: Privacy and Security Specifies requirements, systems, methods, testing and verification for human augmentation to preserve the privacy and security of both consumers and non-consumers of human augmentation. In Development Global
IEEE IEEE P2049.3™ - IEEE Draft Standards Project for Human Augmentation: Identity Specifies the requirements and methods for verifying the identity of a person equipped with human augmentation technologies. Human augmentation refers to technologies that add to the human body and enhance human productivity. In Development Global
IEEE IEEE P2049.4™ - IEEE Draft Standards Project for Human Augmentation: Methodologies and Processes for Ethical Considerations Specifies methodologies and processes to prioritize ethical considerations in the creation of human augmentation technologies. In Development Global
IEEE IEEE 1873™-2015 - IEEE Standard for Robot Map Data Representation for Navigation A map data representation of environments of a mobile robot performing a navigation task is specified in this standard. It provides data models and data formats for two-dimensional (2D) metric and topological maps. Published Global
IEEE IEEE P1872.2 - Standard for Autonomous Robotics (AuR) Ontology This standard is a logical extension to IEEE 1872-2015 Standard for Ontologies for Robotics and Automation. The standard extends the CORA ontology by defining additional ontologies appropriate for Autonomous Robotics (AuR). In Development Global
IEEE IEEE 1855™-2016 - IEEE Standard for Fuzzy Markup Language A new specification language, named Fuzzy Markup Language (FML), is presented in this standard, exploiting the benefits offered by eXtensible Markup Language (XML) specifications and related tools in order to model a fuzzy logic system in a human-readable and hardware independent way. Published Global
IEEE IEEE 1232.3™-2014 - IEEE Guide for the Use of Artificial Intelligence Exchange and Service Tie to All Test Environments (AI-ESTATE) IEEE Guide for the Use of Artificial Intelligence Exchange and Service Tie to All Test Environments (AI-ESTATE) Published Global
ISO/IEC ISO/IEC 20546:2019™ - Information technology - Big Data - Overview and Vocabulary Provides a set of terms and definitions needed to promote improved communication and understanding of this area. It provides a terminological foundation for big data-related standards, and a conceptual overview. Published Global
ISO/IEC ISO/IEC TR 20547-1:2020™ - Information technology — Big data reference architecture — Part 1: Framework and application process This document describes the framework of the big data reference architecture and the process for how a user of the document can apply it to their particular problem domain. Published Global
ISO/IEC ISO/IEC TR 20547-2:2018™ - Information technology --Big data reference architecture --Part 2: Use cases and derived requirements Provides examples of big data use cases with application domains and technical considerations derived from the contributed use cases. Published Global
ISO/IEC ISO/IEC 20547-3:2020™ - Information technology — Big data reference architecture — Part 3: Reference architecture This document specifies the big data reference architecture (BDRA). The reference architecture includes concepts and architectural views. Published Global
ISO/IEC ISO/IEC TR 20547-5:2018™ - Information technology --Big data reference architecture --Part 5: Standards roadmap Describes big data relevant standards, both in existence and under development, along with priorities for future big data standards development based on gap analysis. Published Global
ISO/IEC ISO/IEC 22989™ - Information technology — Artificial intelligence — Artificial intelligence concepts and terminology Foundational standard In Development Global
ISO/IEC ISO/IEC 23053™ - Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML) Foundational standard In Development Global
ISO/IEC ISO/IEC TR 24028:2020™ - Information technology — Artificial intelligence — Overview of trustworthiness in artificial intelligence This document surveys topics related to trustworthiness in AI systems. It briefly surveys the existing approaches that can support or improve trustworthiness in technical systems and discusses their potential application. Published Global
ISO/IEC ISO/IEC TR 24029-1:2021™ Artificial Intelligence (AI) — Assessment of the robustness of neural networks — Part 1: Overview This document provides background about existing methods to assess the robustness of neural networks. Published Global
BSI BS 8611:2016 Robots and robotic devices. Guide to the ethical design and application of robots and robotic systems This British Standard gives guidance on the identification of potential ethical harm and provides guidelines on safe design, protective measures and information for the design and application of robots. Published Regional
IEEE IC20-027 - Responsible Innovation of AI and the Life Sciences Nowhere is the potential of Artificial Intelligence (AI) and autonomous intelligent systems (AIS) more apparent than in human health and human biology, where increasingly sophisticated computational data modelling methods have led to dramatic improvements in our ability to precisely diagnose and treat disease, to estimate risks, and to deliver care. Genetic information is increasingly being used in AI algorithms to guide treatment selection and even whether treatment is provided at all. The transformative impact of these technologies and the commodification of our biological and genomic data will have a significant impact on the future biological continuum and geopolitical order. Global
IEEE IC20-016 - The IEEE Global Initiative on Ethics of Extended Reality The goal of this Industry Connections group is to continue and proliferate the existing efforts of The IEEE Standards Association focused on the ethical issues related to Extended Reality as outlined in the Extended Reality Chapter of Ethically Aligned Design while inviting Working Group members from the multiple Standards Working Groups focused on augmented and virtual reality and the spatial web and additional subject matter experts from industry and policy to create white papers, workshops, and PARs related to this work to ensure these technologies move from “perilous” to “purposeful.” Global
IEEE IC20-015 - The IEEE Earth Lab The goal of the IEEE Earth Lab is to develop a Green Guide to Artificial Intelligence Systems (AIS) that will serve as a pragmatic roadmap for engineers, corporate organizations and policy makers to leverage AIS innovation for an effective transition to a green economy. We will achieve this goal by developing and supporting a global network of Living Labs that deploy ecologically aligned AIS for efficient, livable cities, low-carbon, equitable and resilient infrastructures, and thriving ecosystems for and with communities most impacted by the effects of global warming. Global
IEEE IC20-012 - Roadmap for the Development and Implementation of Standard Oriented Knowledge Graphs This activity assists organizations or users who develop and apply standard-oriented knowledge graphs to have a basic picture of the framework and general construction method. In addition, it may assist the integrators of knowledge graphs to design a generic interface and follow clarified evaluation metrics. Furthermore, standard-oriented knowledge graphscan be integrated, implemented, and applied more simply and efficiently. Global
IEEE IC20-010 - Labeling Cybersecurity Data for AI Automation (Single- and-Multi-Modal) Cyber analysts are becoming a bottleneck in analyzing ever-increasing amounts of data. Automating cyber analysts actions using AI can help reduce amounts of work for analysts and thereby reduce time to outcome dramatically, record actions in knowledgebases for the training of new cyber analysts, and in general, open up the field for new opportunities. As a result, the state of cybersecurity will improve. It is envisioned that this group will bring together industry stakeholders to engage in building consensus on priority issues for standardization activities on these topics, and providing a platform for IEEE thought leadership to the industry. Global
IEC ISO/IEC TR 24029-1:2021 Artificial Intelligence (AI) — Assessment of the robustness of neural networks — Part 1: Overview This document provides background about existing methods to assess the robustness of neural networks. Published Gobal
IEC ISO/IEC TR 24028:2020 Information technology — Artificial intelligence — Overview of trustworthiness in artificial intelligence This document surveys topics related to trustworthiness in AI systems. It briefly surveys the existing approaches that can support or improve trustworthiness in technical systems and discusses their potential application. Published Gobal
IEC ISO/IEC 20547-3:2020 Information technology — Big data reference architecture — Part 3: Reference architecture This document specifies the big data reference architecture (BDRA). The reference architecture includes concepts and architectural views. Published Gobal
IEC ISO/IEC TR 20547-1:2020 Information technology — Big data reference architecture — Part 1: Framework and application process This document describes the framework of the big data reference architecture and the process for how a user of the document can apply it to their particular problem domain. Published Gobal