Standardization · SIS/TK 421

Artificiell intelligens

AI-standardisering främjar svensk innovation, konkurrenskraft och tillit i den digitala ekonomin. Sverige deltar aktivt i det internationella arbetet hos ISO/IEC och det europeiska arbetet hos CEN/CENELEC. Tillsammans utvecklas gemensamma riktlinjer, principer och krav för AI-system och deras tillämpningar. Genom att följa dessa standarder kan svenska aktörer bidra till att skapa etiska, säkra och hållbara AI-lösningar som gynnar både människor och samhälle.

En utgångspunkt  för kommitténs arbete är standardiseringen kopplad till Europeiska Kommissionens AI-förordning (AI Act). Dessa harmoniserade standarder blir nyckelverktyg för att uppvisa efterlevnad av Kommissionens lagstiftning. Arbetet samordnas av den europeiska kommittén CEN-CLC/JTC 21 Artificial intelligence, där svenska experter kan delta genom SIS/TK 421.

Även den internationella AI-standardisering, som drivs genom ISO/IEC JTC 1/SC 42 Artificial intelligence, speglas i SIS/TK 421. Inom SC 42 pågår bland annat arbete med ledningssystem för AI, datakvalitet, tillförlitlighet, samt testning och validering av AI-system. Dessutom leder Sverige det internationella projekt som fokuserar på att ta fram riktlinjer för hantering av samhälleliga frågor och etiska överväganden vid hantering av AI-system.

SIS/TK 421 bevakar, påverkar och tillhandahåller möjliggörande standarder inom AI, för att främja harmonisering av horisontella standarder som är lägger grunden för sektorsspecifik standardisering av AI.

Kommittén ger vägledning till andra tekniska kommittéer inom SIS, samt andra organisationer som utvecklar standarder och applikationer baserat på AI.

Påverka på europeisk och internationell nivå

Den svenska kommittén arbetar mot både den europeiska (CEN/CENELEC) och internationella (ISO/IEC) kommittén som fokuserar på AI:

Vill du vara med i kommittén?

Genom att delta i arbetet kan du och din organisation påverka innehåll och inriktningen på de nationella, europeiska och internationella standarderna, och lyfta fram frågor som är till fördel för er verksamhet. Som deltagare får ni löpande förstahandsinformation som direkt eller indirekt kan användas till gagn för er egen verksamhets utveckling. Svenska spegelkommittéer utgör en utmärkt samlingspunkt där gränsöverskridande dialog mellan näringsliv, myndigheter, och forskare skapar en gemensam svensk linje i det europeiska och internationella arbetet. Vi behöver din hjälp och kompetens för att säkerställa att standarderna kommer att fungera under svenska förhållanden. Gör intresseanmälan uppe till höger.

More information about the committèes work:

Nyheter

 

EU AI Act

Vad är EU AI Act?

  • Den första omfattande lagstiftningen i världen som reglerar Artificiell Intelligens
  • Syftet är att säkerställa säker, etisk och tillförlitlig AI inom EU
  • Klassificerar AI-system efter risknivå (baserat på tänkt användningsområde): oacceptabel, hög, begränsad och minimal risk

Tidslinje

  • Trädde i kraft 1 augusti 2024 med en gradvis tillämpning
  • Krav på högrisksystem i december 2027
  • Förbud mot oacceptabel AI började gälla i februari 2025

Krav på högrisk-AI

  • Införande av kvalitetsledningssystem (QMS)
  • Riskhanteringssystem
  • Hög datakvalitet och dokumentation
  • Loggning och spårbarhet
  • Transparens och information till användare
  • Mänsklig övervakning
  • Noggrannhet, robusthet och cybersäkerhet

  • Bedömning av överensstämmelse (egen eller via tredje part)

Sanktioner vid överträdelser

  • Upp till €35 miljoner eller 7% av global omsättning för allvarliga brott (t.ex. förbjudna tillämpningar)
  • Lägre men kännbara böter för andra regelbrott (€15/3% och €7.5/1.5%)
  • Mikro-, små- och medelstora företag (enligt EU:s SME-definition) får lägre sanktionsbelopp, för att undvika oproportionerlig belastning

Rollen för harmoniserade standarder

  • Ger praktiska och tekniska lösningar för att uppfylla kraven i lagstiftningen
  • Följande av standarder ger presumtion om överensstämmelse med lagen
  • Underlättar utveckling, revision och certifiering
  • Utvecklas av CEN, CENELEC och ETSI på uppdrag av EU-kommissionen
  • Svenska aktörer kan delta i arbetet via SIS/TK 421 AI

Utforska lagstiftningen via denna hemsida.

Europeiska arbetsgrupper

CEN/CLC/JTC 21/WG 1 Strategic Advisory Group (SAG)

CEN/CLC/JTC 21/WG 2 Operational aspects

CEN/CLC/JTC 21/WG 3 Engineering aspects

CEN/CLC/JTC 21/WG 4 Foundational and societal aspects

CEN/CLC/JTC 21/WG 5 Joint standardization on Cybersecurity for AI systems

Internationella arbetsgrupper

ISO/IEC JTC 1/SC 42/WG 1 Foundational standards

ISO/IEC JTC 1/SC 42/WG 2 Data

ISO/IEC JTC 1/SC 42/WG 3 Trustworthiness

ISO/IEC JTC 1/SC 42/WG 4 Use cases and applications

ISO/IEC JTC 1/SC 42/WG 5 Computational approaches and computational characteristics of AI systems

ISO/IEC JTC 1/SC 42/JWG 2 Joint Working Group ISO/IEC JTC1/SC 42 - ISO/IEC JTC1/SC 7: Testing of AI-based systems

ISO/IEC JTC 1/SC 42/JWG 3 Joint Working Group ISO/IEC JTC1/SC42 - ISO/TC 215 WG: AI enabled health informatics

ISO/IEC JTC 1/SC 42/JWG 4 Joint Working Group ISO/IEC JTC1/SC42 - IEC TC65/SC65A: Functional safety and AI systems

ISO/IEC JTC 1/SC 42/JWG 5 Joint Working Group ISO/IEC JTC1/SC42 - ISO/TC 37 WG: Natural language processing

 

 

Now working on 95 standards
ISO/IEC FDIS 24970, Artificial intelligence — AI system logging (50.20)
ISO/IEC DTS 22443, Information technology — Artificial intelligence — Guidance on addressing societal concerns and ethical considerations (50.20)
ISO/IEC FDIS 42105, Information technology — Artificial intelligence — Guidance for human oversight of AI systems (50.20)
FprEN ISO/IEC 24970, Artificial intelligence - AI system logging (ISO/IEC FDIS 24970:2026) (50.20)
ISO/IEC 22989:2022/FDAmd 1, Information technology — Artificial intelligence — Artificial intelligence concepts and terminology — Amendment 1: Generative AI (50.00)
ISO/IEC 23053:2022/FDAmd 1, Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML) — Amendment 1: Generative AI (50.00)
ISO/IEC FDIS 25059, Software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Quality models for AI systems (50.00)
ISO/IEC DTS 25568, Information technology — Artificial Intelligence — Guidance on addressing risks in generative AI systems (50.00)
ISO/IEC FDIS 24029-3, Artificial intelligence (AI) — Assessment of the robustness of neural networks — Part 3: Methodology for the use of statistical methods (50.00)
EN ISO/IEC 23053:2023/prA1:2025, Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML) - Amendment 1: Generative AI (ISO/IEC 23053:2022/DAmd1:2025) (45.99)
ISO/IEC/IEEE DIS 42703, Artificial intelligence — Standard for algorithmic bias considerations (40.99)
prEN ISO/IEC 42102, Information technology - Artificial intelligence - Framework for characterizing AI system methods and capabilities (ISO/IEC DIS 42102:2026) (40.60)
prEN ISO/IEC 25029, Artificial intelligence - AI-enhanced nudging (ISO/IEC DIS 25029:2026) (40.60)
prEN ISO/IEC 25059, Software engineering - Systems and software Quality Requirements and Evaluation (SQuaRE) - Quality models for AI systems (ISO/IEC DIS 25059:2025) (40.60)
prEN 18288, Artificial Intelligence - Taxonomy of AI tasks in computer vision (40.60)
prEN 18281, Artificial Intelligence - Evaluation methods for accurate computer vision systems (40.60)
prEN 18282, Artificial intelligence - Cybersecurity specifications for AI Systems (40.60)
prEN 18228, AI Risk Management (40.60)
prEN 18229-1, AI trustworthiness framework - Part 1: Logging (40.60)
ISO/IEC DIS 25029, Artificial intelligence — AI-enhanced nudging (40.60)
ISO/IEC DIS 42102, Information technology — Artificial intelligence — Framework for characterizing AI system methods and capabilities (40.60)
EN ISO/IEC 22989:2023/prA1:2025, Information technology - Artificial intelligence - Artificial intelligence concepts and terminology - Amendment 1: Generative AI (ISO/IEC 22989:2022/DAmd1:2025) (40.60)
ISO/IEC DIS 42007, Information technology — Artificial intelligence — High-level framework and guidance for the development of conformity assessment schemes for AI systems (40.20)
ISO/IEC DIS 4213, Information technology — Artificial Intelligence — Performance measurement for AI classification, regression, clustering and recommendation tasks (40.20)
ISO/IEC DIS 23282, Artificial Intelligence — Evaluation methods for accurate natural language processing systems (40.20)
prEN 18229-3, AI trustworthiness framework - Part 3: Human oversight (40.20)
prEN 18283, Artificial Intelligence — Concepts, measures and requirements for managing bias in AI systems (40.20)
prEN 18287, Artificial Intelligence - Requirements and guidance for the environmental impact evaluation of artificial intelligence systems and services (40.20)
prEN ISO/IEC 23282, Artificial Intelligence - Evaluation methods for accurate natural language processing systems (ISO/IEC DIS 23282:2026) (40.20)
prEN ISO/IEC 42006, Information technology - Artificial intelligence - Requirements for bodies providing audit and certification of artificial intelligence management systems (ISO/IEC 42006:2025) (40.20)
ISO/IEC CD TR 25523, Information technology — Artificial intelligence — Overview of data profiles for analytics and machine learning (ML) (30.99)
ISO/IEC CD TR 42109, Information technology — Artificial intelligence — Use cases of human-machine teaming (30.60)
ISO/IEC CD TS 22440-1, Artificial intelligence — Functional safety and AI systems — Part 1: Requirements (30.60)
ISO/IEC CD TS 22440-2, Artificial intelligence — Functional safety and AI systems — Part 2: Guidance (30.60)
ISO/IEC CD TS 22440-3, Artificial intelligence — Functional safety and AI systems — Part 3: Examples of application (30.60)
ISO/IEC CD TS 25258, Information technology — Artificial intelligence — Hybrid AI inference framework for AI systems (30.60)
ISO/IEC CD TS 25571, Artificial Intelligence — Example template for documenting ethical issues of an AI system (30.60)
ISO/IEC CD TS 42111, Information technology — Artificial intelligence — Guidance on lightweight AI systems (30.60)
ISO/IEC CD TR 23281, Artificial intelligence — Overview of AI tasks and functionalities related to natural language processing (30.60)
ISO/IEC CD 25589, Information technology — Artificial intelligence — Framework for human-machine teaming (30.60)
ISO/IEC 22989:2022/CD Amd 2, Information technology — Artificial intelligence — Artificial intelligence concepts and terminology — Amendment 2 (30.20)
ISO/IEC CD 25590, Information technology — Artificial intelligence — Guidance for output data quality of generative AI applications (30.20)
ISO/IEC CD 25704, Artificial intelligence — Process assessment — Process assessment model for AI system life cycle processes (30.20)
ISO/IEC CD 25870, Information technology — Artificial intelligence — Data elements for reporting AI system incidents (30.20)
ISO/IEC CD TR 24030, Information technology — Artificial intelligence (AI) — Use cases (30.20)
ISO/CD TR 26313, Information technology — Artificial intelligence — Classification and use cases of generative AI in healthcare (30.00)
ISO/IEC WD TS 25570, Information Technology — Artificial Intelligence — Reliability assessment of AI systems (20.60)
prEN 18229-2, AI trustworthiness framework - Part 2: Transparency (20.60)
ISO/IEC 23053:2022/AWI Amd 2, Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML) — Amendment 2 (20.00)
ISO/IEC AWI 22989-2, Artificial intelligence — Concepts and terminology — Part 2: Healthcare (20.00)
ISO/IEC AWI 25058, Systems and software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Measurement and guidance for quality evaluation of AI systems (20.00)
ISO/IEC AWI 25623, Artificial intelligence — Machine learning (ML) model description framework (20.00)
ISO/IEC AWI 25872-1, Artificial intelligence — Knowledge enhancement for pretrained machine learning models — Part 1: Framework (20.00)
ISO/IEC AWI 25880, Artificial intelligence — Requirements and guidance for the organizational implementation of human-machine teaming (20.00)
ISO/IEC AWI 26582, Artificial intelligence — Conformity assessment for the functional correctness of an AI system (20.00)
ISO/IEC AWI 26741, Information technology — Artificial intelligence — Framework for describing AI systems as object of conformity assessment (20.00)
ISO/IEC AWI 42003, Information technology — Artificial intelligence — Guidance on the implementation of ISO/IEC 42001 (20.00)
ISO/IEC AWI TS 25223, Information technology — Artificial intelligence — Guidance and requirements for uncertainty quantification in AI systems (20.00)
ISO/IEC AWI TS 25566, Terminology and concepts for domain engineering of AI systems (20.00)
ISO/IEC AWI TS 25569, Artificial Intelligence — Implementation guidance on de-identification of data used in Machine Learning (ML) (20.00)
ISO/IEC AWI TS 25864, Information technology — Artificial Intelligence (AI) — Resilience assessment of AI systems (20.00)
ISO/IEC AWI TS 26312, Information technology — Artificial intelligence — Identification and treatment of unwanted bias in AI by healthcare (20.00)
ISO/IEC AWI TS 26320, Artificial intelligence — Corpus development and maintenance for natural language processing systems (20.00)
ISO/IEC AWI TS 42119-7, Artificial intelligence — Testing of AI — Part 7: Red teaming (20.00)
ISO/IEC AWI TS 42119-8, Artificial intelligence — Testing of AI — Part 8: Quality assessment of prompt-based text-to-text systems that utilize generative AI (20.00)
prCEN/CLC ISO/IEC/TS 22440-1, Artificial Intelligence – Functional Safety and AI systems – Part 1: Requirements (10.99)
prCEN/CLC ISO/IEC/TS 22440-2, Artificial intelligence — Functional safety and AI systems — Part 2: Guidance (10.99)
prCEN/CLC ISO/IEC/TS 22440-3, Artificial intelligence — Functional safety and AI systems — Part 3: Examples of application (10.99)
prCEN/CLC/TR 18347, Overview and architecture of standards in support of the EU AI Act (10.99)
EN ISO/IEC 22989:2023/prA2, Information technology — Artificial intelligence — Artificial intelligence concepts and terminology — Amendment 2 (10.99)
ISO/AWI TR 24492, Standardization needs for the application of artificial intelligence in the financial services industry (10.99)
EN ISO/IEC 23053:2023/prA2, Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML) — Amendment 2 (10.99)
prEN 18284, Artificial Intelligence - Quality and governance of data sets in AI (10.99)
prEN 18285, AI Conformity assessment framework (10.99)
prEN 18229-4, AI trustworthiness framework – Part 4: Accuracy (10.99)
prEN 18229-5, AI trustworthiness framework – Part 5: Robustness (10.99)
prEN ISO/IEC TR 23281, Artificial Intelligence - Overview of Al tasks and functionalities related to natural language processing (10.99)
ISO/IEC NP 42104, Information technology — Artificial intelligence — Guidance on addressing societal concerns and ethical considerations (10.20)
ISO/IEC NP 42117, Artificial intelligence — Trustworthiness Fact Labels — Part 1: Principles and general requirements on trustworthiness fact statements and programmes for AI systems and models (10.20)
ISO/IEC NP TS 25471, Information technology — Artificial Intelligence — Guidance on addressing risks in generative AI systems (10.00)
ISO/IEC PWI 42119-1, Artificial intelligence — Trustworthiness Fact Labels — Part 1: Principles and general requirements on trustworthiness fact statements and programmes for AI systems and models (10.00)
ISO/IEC PWI 26200, Standard Framework for Evaluation, Ethical Use, and Interoperability of Large Language Models (LLMs) in AI Systems (00.60)
-, Contributions towards ISO/IEC 27090 (00.60)
prCEN/CLC/TR XXX, AI Risks - Check List for AI Risks Management (00.60)
prCEN/CLC/TR XXX, Guidance on application of Risk Management in Critical Digital Infrastructure (00.60)
prCEN/CLC/TR XXX, Impact assessment in the context of the EU Fundamental Rights (00.60)
prCEN/TS, Guidance for upskilling organisations on AI ethics and social concerns (00.60)
prCEN/TS, Guidelines on tools for handling ethical issues in AI system life cycle (00.60)
ISO/IEC PWI 24029-5, Artificial intelligence (AI) — Assessment of the robustness of neural networks — Part 5: Applicability of the methodology to other artificial intelligence algorithms (00.00)
ISO/IEC PWI 25512, Information Technology — Artificial intelligence — Frontier Al risk management and impact assessment (00.00)
ISO/IEC PWI 25526, Information technology — Artificial intelligence — Taxonomy of computational methods specific to natural language processing (00.00)
ISO/IEC PWI 26750, Information technology — Artificial intelligence — Context for AI systems (00.00)
ISO/IEC PWI 26751, Information Technology — Artificial intelligence — Safety of AI models, systems and applications (00.00)
ISO/IEC PWI 42114, Information technology — Artificial intelligence — Guidelines for auditing of AI management system based on ISO/IEC 42001 (00.00)
ISO/PWI 26319, Information technology — Artificial intelligence — Evaluation framework for safety and reliability of generative AI in healthcare (00.00)
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Published 47 standards
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SIS-ISO/IEC TR 5259-6:2026
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 6: Visualization framework for data quality (ISO/IEC TR 5259-6:2026, IDT)
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SIS-ISO/IEC TS 42112:2026
Information technology — Artificial intelligence — Guidance on machine learning model training efficiency optimization (ISO/IEC TS 42112:2026, IDT)
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SIS-ISO/IEC TR 42106:2026
Information technology — Artificial intelligence (AI) — Overview of differentiated benchmarking of AI system quality characteristics (ISO/IEC TR 42106:2026, IDT)
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SS-EN 18274:2026
Competence requirements for professional AI ethicists
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SS-EN 18286:2026
Artificial intelligence — Quality management system for EU AI Act regulatory purposes
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SS-EN ISO/IEC 42001:2026
Information technology — Artificial intelligence — Management system (ISO/IEC 42001:2023, IDT)
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SIS-ISO/IEC TS 6254:2026
Information technology — Artificial intelligence — Objectives and approaches for explainability and interpretability of machine learning (ML) models and artificial intelligence (AI) systems (ISO/IEC TS 6254:2025, IDT)
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SS-ISO/IEC 38507:2026
Information technology — Governance of IT — Governance implications of the use of artificial intelligence by organizations (ISO/IEC 38507:2022, IDT)
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SIS-ISO/IEC TR 24372:2026
Information technology — Artificial intelligence (AI) — Overview of computational approaches for AI systems (ISO/IEC TR 24372:2021, IDT)
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SS-EN ISO/IEC 12792:2025
Information technology — Artificial intelligence — Transparency taxonomy of AI systems (ISO/IEC 12792:2025, IDT)
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SIS-ISO/IEC TS 42119-2:2025
Artificial intelligence — Testing of AI — Part 2: Overview of testing AI systems (ISO/IEC TS 42119-2:2025, IDT)
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SIS-ISO/IEC TR 20226:2025
Information technology — Artificial intelligence — Environmental sustainability aspects of AI systems (ISO/IEC TR 20226:2025, IDT)
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SIS-ISO/IEC TR 21221:2025
Information technology — Artificial intelligence — Beneficial AI systems (ISO/IEC TR 21221:2025, IDT)
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SS-ISO/IEC 42006:2025
Information technology — Artificial intelligence — Requirements for bodies providing audit and certification of artificial intelligence management systems (ISO/IEC 42006:2025, IDT)
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SS-ISO/IEC 42005:2025
Information technology — Artificial intelligence — AI system impact assessment (ISO/IEC 42005:2025, IDT)
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SS-EN ISO/IEC 5259-2:2025
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 2: Data quality measures (ISO/IEC 5259-2:2024, IDT)
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SS-EN ISO/IEC 5259-4:2025
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 4: Data quality process framework (ISO/IEC 5259-4:2024, IDT)
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SS-EN ISO/IEC 5259-1:2025
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 1: Overview, terminology, and examples (ISO/IEC 5259-1:2024, IDT)
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SS-EN ISO/IEC 5259-3:2025
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 3: Data quality management requirements and guidelines (ISO/IEC 5259-3:2024, IDT)
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SIS-CEN/TR 18145:2025
Environmentally sustainable Artificial Intelligence
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SS-ISO/IEC 5259-5:2025
Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 5: Data quality governance framework (ISO/IEC 5259-5:2025, IDT)
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SIS-CEN/CLC/TR 17894:2024
Artificial Intelligence — Artificial Intelligence Conformity Assessment
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SIS-CEN/CLC ISO/IEC/TS 12791:2024
Information technology - Artificial intelligence - Treatment of unwanted bias in classification and regression machine learning tasks (ISO/IEC TS 12791:2024, IDT)
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SIS-CEN/CLC/TR 18115:2024
Data governance and quality for AI within the European context
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SS-EN ISO/IEC 25059:2024
Software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Quality model for AI systems (ISO/IEC 25059:2023, IDT)
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SS-EN ISO/IEC 8183:2024
Information technology — Artificial intelligence — Data life cycle framework (ISO/IEC 8183:2023, IDT)
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SIS-ISO/IEC TR 5469:2024
Artificial intelligence — Functional safety and AI systems (ISO/IEC TR 5469:2024, IDT)
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SIS-ISO/IEC TR 17903:2024
Information technology — Artificial intelligence — Overview of machine learning computing devices (ISO/IEC TR 17903:2024, IDT)
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SS-ISO/IEC 5339:2024
Information technology — Artificial intelligence — Guidance for AI applications (ISO/IEC 5339:202, IDT)
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SS-ISO/IEC 24029-2:2024
Artificial intelligence (AI) — Assessment of the robustness of neural networks — Part 2: Methodology for the use of formal methods (ISO/IEC 24029-2:2023, IDT)
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SIS-ISO/IEC TS 8200:2024
Information technology — Artificial intelligence — Controllability of automated artificial intelligence systems (ISO/IEC TS 8200:2024, IDT)
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SS-ISO/IEC 5392:2024
Information technology — Artificial intelligence — Reference architecture of knowledge engineering (ISO/IEC 5392:2024, IDT)
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SIS-ISO/IEC TR 24030:2024
Information technology — Artificial intelligence (AI) — Use cases (ISO/IEC TR 24030:2024, IDT)
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SS-ISO/IEC 5338:2024
Information technology — Artificial intelligence — AI system life cycle processes (ISO/IEC 5338:2023, IDT)
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SS-EN ISO/IEC 23894:2024
Information technology — Artificial intelligence — Guidance on risk management (ISO/IEC 23894:2023, IDT)
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SIS-ISO/IEC TS 25058:2024
Systems and software engineering — Systems and software Quality Requirements and Evaluation (SQuaRE) — Guidance for quality evaluation of artificial intelligence (AI) systems (ISO/IEC TS 25058:2024, IDT)
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SIS-EN ISO/IEC TR 24027:2024
Information technology — Artificial intelligence (AI) — Bias in AI systems and AI aided decision making (ISO/IEC TR 24027:2021, IDT)
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SIS-EN ISO/IEC TR 24029-1:2024
Artificial Intelligence (AI) - Assessment of the robustness of neural networks - Part 1: Overview (ISO/IEC TR 24029-1:2021)
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SS-ISO/IEC 42001:2024
Information technology — Artificial intelligence — Management system (ISO/IEC 42001:2023, IDT)
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SS-ISO/IEC 23894:2023
Information technology - Artificial intelligence - Guidance on risk management (ISO/IEC 23894:2023, IDT)
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SIS-ISO/IEC TR 24028:2023
Information technology - Artificial intelligence - Overview of trustworthiness in artificial intelligence (ISO/IEC TR 24028:2020, IDT)
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SS-EN ISO/IEC 22989:2023
Information technology - Artificial intelligence - Artificial intelligence concepts and terminology (ISO/IEC 22989:2022)
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SS-EN ISO/IEC 23053:2023
Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML) (ISO/IEC 23053:2022)
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SIS-ISO/IEC TS 4213:2022
Information technology — Artificial Intelligence — Assessment of machine learning classification performance (ISO/IEC TS 4213:2022, IDT)
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SS-ISO/IEC 20546:2022
Information Technology - Big Data - Overview and vocabulary (ISO/IEC 20546:2019, IDT)
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SIS-ISO/IEC TR 24368:2022
Information technology — Artificial intelligence — Overview of ethical and societal concerns (ISO/IEC TR 24368:2022, IDT)
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SIS-ISO/IEC TR 24030:2022
Information technology — Artificial Intelligence (AI) — Use cases (ISO/IEC TR 24030:2021, IDT)
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Participants 22 companies and organizations
Antidiskrimineringsbyrån Väst, Göteborg
Arkatay Consulting AB, Malmö
Art25 Consulting AB, Sundbyberg
ASSA ABLOY AB, Stockholm
Bonde Advokater AB, Stockholm
Credo AI, Los Altos
DCFT Consulting AB, Täby
Digitalist Open Tech AB, Stockholm
Ericsson AB (EAB), Kista
Funktionsrätt Sverige, Sundbyberg
Knowit Insight Väst AB, Göteborg
Landsorganisationen i Sverige LO, Stockholm
Lunds universitet, Lund
RISE Research Institutes of Sweden AB, Borås
RISE Research Institutes of Sweden AB, Kista
SamCert AB, Göteborg
Scania CV AB, Södertälje
SciLifeLab Data Centre (Uppsala Universitet), Uppsala
Simovits Consulting AB, STOCKHOLM
Styrelsen för Ackreditering & Teknisk Kontroll SWEDAC, Borås
Västra Götalandsregionen, Göteborg
Volvo Technology AB, Göteborg
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International participation 19 international committees
ISO/IEC JTC 1/SC 42, Artificial intelligence
ISO/IEC JTC 1/SC 42/AHG 4, Liaison with SC 27
ISO/IEC JTC 1/SC 42/AHG 7, JTC1 joint development review
ISO/IEC JTC 1/SC 42/JAG, Joint Advisory Group on AI and sustainability with ISO/IEC JTC1/SC 39 and JTC1/SC 42
ISO/IEC JTC 1/SC 42/JWG 2, Joint Working Group ISO/IEC JTC1/SC 42 - ISO/IEC JTC1/SC 7
ISO/IEC JTC 1/SC 42/JWG 3, Joint Working Group ISO/IEC JTC1/SC42 - ISO/TC 215 WG : AI enabled health informatics
ISO/IEC JTC 1/SC 42/JWG 4, Joint Working Group ISO/IEC JTC1/SC42 - IEC TC65/SC65A: Functional safety and AI systems
ISO/IEC JTC 1/SC 42/JWG 5, Joint Working Group ISO/IEC JTC1/SC42 - ISO/TC 37 WG: Natural language processing
ISO/IEC JTC 1/SC 42/WG 1, Foundational standards
ISO/IEC JTC 1/SC 42/WG 2, Data
ISO/IEC JTC 1/SC 42/WG 3, Trustworthiness
ISO/IEC JTC 1/SC 42/WG 4, Use cases and applications
ISO/IEC JTC 1/SC 42/WG 5, Computational approaches and computational characteristics of AI systems
CEN/CLC/JTC 21, Artificial Intelligence
CEN/CLC/JTC 21/WG 1, Strategic Advisory Group (SAG)
CEN/CLC/JTC 21/WG 2, Operational aspects
CEN/CLC/JTC 21/WG 3, Engineering aspects
CEN/CLC/JTC 21/WG 4, Foundational and societal aspects
CEN/CLC/JTC 21/WG 5, Joint standardization on Cybersecurity for AI systems
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Intressentmöte 18 januari 2024

AI Act – EU:s lagstiftning för artificiell intelligens – och standarderna som hjälper er uppfylla kraven

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Webbinarium från den 27 november 2023

Webbinarium från den 27 november 2023: 

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Contact

If you have questions or want to know more about the SIS standardization activities? Please contact us.

Patric Ridell
Project manager
patric.ridell@sis.se

Maria Andersson
Project coordinator
maria.andersson@sis.se