Back to the database
Record STMT-W42A463Voluntary

ISO/IEC 23053:2022 Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML)

Standard International lawGlobalin force

ISO/IEC 23053:2022 provides a conceptual framework and shared terminology for describing artificial intelligence systems that use machine learning. It defines the components and functions of machine learning-based AI systems within the broader AI ecosystem to offer clarity on operations and interactions. The standard is designed for technical experts and non-specialists seeking to understand machine learning systems in a structured and consistent way.

Summary and content fields are drawn from the document text and are pending editorial review.

Who issued it

International Organization for StandardizationStandards body
Lead issuer
International Electrotechnical CommissionStandards body
Co-issuer
Legal forceVoluntary
Under whose authorityInternational law
Judged fromfull text

Who it governs

AI developers and providersCompaniesAI deployers and usersResearchers and academics

Organisations and technical or non-technical stakeholders designing, developing, deploying, or evaluating AI systems using machine learning.

Sectors
Cross-sector

What the document contains

What's covered

The document covers a unified vocabulary, conceptual framework, and system models for artificial intelligence systems utilizing machine learning. It details components, functions, and interactions within the machine learning ecosystem.

What's missing

The text does not provide specific enforcement mechanisms, binding legal obligations, or detailed risk management procedures.

Key takeaways
  • ISO/IEC 23053:2022 establishes a conceptual framework and shared terminology for AI systems using machine learning.
  • The standard defines components and functions of machine learning-based AI systems to reduce confusion and miscommunication.
  • It supports collaboration across teams and organizations by enhancing transparency and understanding of system components.
  • Deep learning is explicitly addressed as a subset of machine learning within the framework.
  • The standard lays the foundational terminology and models to facilitate more specific standards for risk management, governance, and conformity assessment.
IssuedJune 2022
Length684 words
FormatNot recorded
Scopeglobal

How it scores

Pending review

Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.

Accountability

0/5

Clear responsibility for AI outcomes

General information

screening score · 2026-10-23

Fairness

0/5

Non-discrimination and equitable treatment

General information

screening score · 2026-10-23

Human Dignity

0/5

Respect for the inherent worth of persons

General information

screening score · 2026-10-23

Human Oversight

1/5

Humans remain in control of consequential decisions

lay the groundwork for responsible design, implementation and oversight of AI technologies

Why is ISO/IEC 23053 important?

screening score · 2026-10-23

Privacy

0/5

Protection of personal data and private life

General information

screening score · 2026-10-23

Transparency

2/5

Openness about how AI systems work and are used

Enhances transparency and understanding of AI system components

Benefits

screening score · 2026-10-23

Enforcement

0/5

Consequences and compliance mechanisms with real force

General information

screening score · 2026-10-23

Impact Assessment

0/5

Required assessment of an AI system's risks/impacts before or during use

General information

screening score · 2026-10-23

Topics

artificial_intelligence machine_learning terminology technical_standard framework