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Record STMT-W77CE5BVoluntary

Information technology — Artificial intelligence — Overview of ethical and societal concerns

Report Institutional policyGlobalin force

ISO/IEC TR 24368:2022 is a technical report that provides an overview of ethical and societal concerns surrounding artificial intelligence. It outlines common sources of these concerns, highlights key principles and processes, and maps relevant international standards supporting responsible AI development. The report aims to promote awareness of risks like bias and transparency issues without prescribing any single value system.

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 authorityInstitutional policy
Judged fromfull text

Who it governs

Researchers and academicsGeneral publicRegulatorsCompaniesAI developers and providersAI deployers and users

Technologists, policymakers, standard-setters, researchers, and organisations involved in the design, deployment, or oversight of AI systems.

Sectors
Cross-sectorResearch and science · Information technology and artificial intelligence

What the document contains

What's covered

The document addresses ethical and societal concerns surrounding AI, common sources of these concerns, key principles and processes, and maps relevant international standards supporting responsible AI development and use.

What's missing

It does not prescribe specific ethical values or advocate for any single value system.

Key takeaways
  • The report provides a high-level overview of ethical and societal concerns related to artificial intelligence.
  • It outlines common sources of ethical concerns, key principles, and processes without advocating for any single value system.
  • It maps relevant international standards that support responsible AI development and use.
  • It promotes awareness of risks such as bias, lack of transparency, privacy violations, and diminishing human autonomy.
Outline
Not stated
Issued19 August 2022
Length586 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

3/5

Clear responsibility for AI outcomes

helping to build AI that is not only effective, but also fair, transparent and accountable.

Why is ISO/IEC TR 24368 important?

screening score · 2026-10-23

Fairness

3/5

Non-discrimination and equitable treatment

Concerns such as bias, lack of transparency, privacy violations and diminishing human autonomy must be addressed proactively.

Why is ISO/IEC TR 24368 important?

screening score · 2026-10-23

Human Dignity

0/5

Respect for the inherent worth of persons

Introduction

screening score · 2026-10-23

Human Oversight

3/5

Humans remain in control of consequential decisions

Concerns such as bias, lack of transparency, privacy violations and diminishing human autonomy must be addressed proactively.

Why is ISO/IEC TR 24368 important?

screening score · 2026-10-23

Privacy

3/5

Protection of personal data and private life

Concerns such as bias, lack of transparency, privacy violations and diminishing human autonomy must be addressed proactively.

Why is ISO/IEC TR 24368 important?

screening score · 2026-10-23

Transparency

3/5

Openness about how AI systems work and are used

Concerns such as bias, lack of transparency, privacy violations and diminishing human autonomy must be addressed proactively.

Why is ISO/IEC TR 24368 important?

screening score · 2026-10-23

Enforcement

0/5

Consequences and compliance mechanisms with real force

Introduction

screening score · 2026-10-23

Impact Assessment

3/5

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

Provides a foundation for ethical impact assessments and best practices

Benefits

screening score · 2026-10-23

Topics

ethics societal_impact standards bias transparency