AI Policies, Orders, and Standards

While AI standards and policies are rapidly emerging, there are several that appear to be shaping the landscape.

Global AI Policies, Orders, and Standards

The standard provides a thorough approach to establishing, implementing, maintaining, and continually improving an Artificial Intelligence Management System. It offers a risk-based approach to AI design and management, which is helpful when assessing AI during procurement.

The guidance mostly refers to the use of machine learning. They provide a set of guiding principles on how to buy AI technology, as well as insights on tackling challenges that may arise during procurement. It is the first of such guidance, and is not exhaustive.

The guidelines provide fundamental considerations that a government should address before acquiring and deploying AI solutions and services. They apply once it has been determined that the solution needed for a problem could be AI-driven

The AIRC supports and operationalizes the NIST AI Risk Management Framework (AI RMF 1.0) and accompanying Playbook and will grow with enhancements to enable an interactive, role-based experience providing access to a wide-range of relevant AI resources.

7000-2021 - IEEE Standard Model Process for Addressing Ethical Concerns during System Design
7001-2021 - IEEE Standard for Transparency of Autonomous Systems
7002-2022 - IEEE Standard for Data Privacy Process
7003-2024 - IEEE Algorithmic Bias Considerations
7005-2021 - IEEE Standard for Transparent Employer Data Governance
7007-2021 - IEEE Ontological Standard for Ethically Driven Robotics and Automation Systems
7009-2023 - Fail-Safe Design of Autonomous and Semi-Autonomous Systems
7010-2020 - IEEE Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well-Being
7014-2024 - Emulated Empathy in Autonomous and Intelligent Systems
2089-2021 - IEEE Standard for an Age Appropriate Digital Services Framework Based on the 5Rights Principles for Children

The NAIAC consists of leaders with a broad and interdisciplinary range of AI-relevant expertise from across academia, non-profits, civil society, and the private sector. The procurement recommendations cover topics ranging from staff training and vendor interrogation to embedding AI into the procurement procedures to gain efficiencies.